WO2022261007A1

WO2022261007A1 - Disease management system

Info

Publication number: WO2022261007A1
Application number: PCT/US2022/032362
Authority: WO
Inventors: Kartik Raghavan; Jeffrey RAIKES; Patrick Arensdorf; Yvonne Maldonado; Lorene NELSON; Stephen R. Quake
Original assignee: Chan Zuckerberg Biohub, Inc.; The Board Of Trustees Of The Leland Stanford Junior University
Priority date: 2021-06-08
Filing date: 2022-06-06
Publication date: 2022-12-15

Abstract

Various methods, apparatuses, and systems are provided for managing resources related to a disease. Information related to the disease can be gathered from users and utilized for determining individuals to be tested and/or vaccinated for the disease based on infection probability for the disease. The information can further be utilized for determining efficient distribution of test kits and/or vaccines, as well as initiating targeted marketing for gathering information from additional users.

Description

DISEASE MANAGEMENT SYSTEM

CROSS-REFERENCES TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63/208,203, filed on June 8, 2021, the contents of which are incorporated herein by reference in its entirety for all purposes.

BACKGROUND

[0002] Recent events relating to the CO VID- 19 pandemic have shown that containing an epidemic or a pandemic can be difficult, and the risks for the failure of containment are very high. Diagnostic testing is usually part of containment, but it is costly and impractical to test all people every day. Accordingly, it is desirable for new techniques to contain future epidemics/pandemics in an efficient manner.

SUMMARY

[0003] Various embodiments use information related to a disease from users to determine whether users are to receive medical intervention for the disease. The information from users may be utilized to generate and adapt a symptomology model for determining which users are to receive medical intervention for the disease. The system may further utilize the information for distribution of test kits, vaccinations and/or medications for the disease and initiation of electronic communications to gather information from additional users.

[0004] Some embodiments are provided for a method performed by a computer system. The method may include retrieving, from one or more databases, symptom information for users of the computer system, and infection results of the disease for the users from the one or more databases, the infection results corresponding to the tests for the disease that were administered for the users. The method may further include generating a symptomology model for prediction of risk for a user being infected by the disease based on the symptom information for the users and the infection results for the users. Further, the method may include receiving symptom information for a first user and an infection result for the first user and adapting the symptomology model based on the symptom information for the first user and the infection result for the first user. Symptom information may be received for the second user, and an infection probability score for the disease for the second user may be determined based on the symptom information for the second user and the adapted symptomology model. The method may further include determining whether the second user is to receive medical intervention for the disease based on the infection probability score and providing an indication whether the second user should receive medical intervention based on the determination whether the second user is to receive medical intervention for the disease.

[0005] Some embodiments are provided for a method performed by a server. The method may include determining a symptomology model for prediction of risk for a user being infected by a disease based on collected symptom information for users of the server, collected infection results for the users, and collected environmental information associated with the users. The method may further include receiving user symptom information for the user and receiving user environmental information associated with the user; the user environmental information providing a measure of disease activity for a geographic region or a group within which the user belongs. An infection probability score may be determined based on the user symptom information for the user, the user environmental information for the user, and the symptomology model. The method may further include comparing the infection probability score with a score threshold, determining that the user is to receive a medical intervention for the disease based on the comparison, and providing an indication that the user is to receive the medical intervention.

[0006] These embodiments and other embodiments of the disclosure are described in detail below. For example, other embodiments are directed to systems, devices, and computer readable media associated with methods described herein.

[0007] A better understanding of the nature and advantages of embodiments of the present disclosure may be gained with reference to the following detailed description and the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0008] FIG. 1 A illustrates a first portion of an example system flow in accordance with some embodiments.

[0009] FIG. IB illustrates a second portion of the example system flow in accordance with some embodiments. [0010] FIG. 2A illustrates a first portion of an example system flow with contact tracing in accordance with some embodiments.

[0011] FIG. 2B illustrates a second portion of the example system flow in accordance with some embodiments.

[0012] FIG. 3 A illustrates a first portion of an example system flow with symptomatic grouping and expansion in accordance with some embodiments.

[0013] FIG. 3B illustrates a second portion of the example system flow in accordance with some embodiments.

[0014] FIG. 3C illustrates a third portion of the example system flow in accordance with some embodiments.

[0015] FIG. 4 illustrates an example system flow for grouping users in accordance with some embodiments.

[0016] FIG. 5 illustrates an example computer system arrangement in accordance with some embodiments.

[0017] FIG. 6 illustrates an example procedure for generating and/or adapting a symptomology model in accordance with some embodiments.

[0018] FIG. 7 illustrates an example procedure for analyzing users in accordance with some embodiments.

[0019] FIG. 8 illustrates an example procedure for distributing test kits and/or vaccines in accordance with some embodiments.

[0020] FIG. 9 illustrates an example procedure for initiating user recruiting in accordance with some embodiments.

[0021] FIG. 10 illustrates an example computer system in accordance with some embodiments.

TERMINOLOGY

[0022] The term “computer system” as used herein refers to any type interconnected electronic devices, computer devices, or components thereof. Additionally, the term “computer system” or “system” may refer to various components of a computer that are communicatively coupled with one another. Furthermore, the term “computer system” or “system” may refer to multiple computer devices or multiple computing systems that are communicatively coupled with one another and configured to share computing or networking resources.

[0023] The term “circuitry” as used herein refers to, is part of, or includes hardware components such as an electronic circuit, a logic circuit, a processor (shared, dedicated, or group) or memory (shared, dedicated, or group), an application specific integrated circuit (ASIC), a field-programmable device (FPD) (e.g., a field-programmable gate array (FPGA), a programmable logic device (PLD), a complex PLD (CPLD), a high-capacity PLD (HCPLD), a structured ASIC, or a programmable system-on-a-chip (SoC)), digital signal processors (DSPs), etc., that are configured to provide the described functionality. In some embodiments, the circuitry may execute one or more software or firmware programs to provide at least some of the described functionality. The term “circuitry” may also refer to a combination of one or more hardware elements (or a combination of circuits used in an electrical or electronic system) with the program code used to carry out the functionality of that program code. In these embodiments, the combination of hardware elements and program code may be referred to as a particular type of circuitry.

[0024] The term “medical intervention” as used herein may refer to testing, vaccination, pharmacological treatment, monitoring (such as further monitoring), informational/educational intervention, or some combination thereof. In some embodiments, the term “medical intervention” may further refer to any other procedure a medical professional may perform related to a disease. The term “resources for medical intervention” as used herein may refer to test kits, vaccines, self-vaccination kits, pharmaceuticals, monitoring devices, presenters for information/educational intervention, or some combination thereof. In some embodiments, the term “resources for medical intervention” may further refer to any resources that may be utilized for performance of a medical intervention.

[0025] The term “pharmacological treatment” as used herein may refer to treatment by pharmaceuticals. The term “further monitoring” as used herein may refer to monitoring in addition to the monitoring provided by the system. The term “informational/educational intervention” as used herein may refer to presentation of information and/or educational materials. [0026] The term “connected” may mean that two or more elements have an established signaling relationship with one another over a communication channel, link, interface, or reference point.

DETAILED DESCRIPTION

[0027] Herein disclosed are systems, computer readable media, and methods that may collect and manage information related to a disease and may effectively utilize the information to implement approaches for collecting additional information, identifying individuals to receive medical intervention for the disease and/or providing medical intervention for the disease. For example, the system may collect information of users related to the disease and generate or update one or more symptomology models based on the information of the users, where the symptomology models that can be utilized for identifying additional users that are at risk for the disease. The system may utilize the symptomology model to analyze information from a user to determine whether the user is to receive medical intervention for the disease. The system may also receive infection results of the tests for users, and train and/or update the symptomology models based on the infection results for the users and the information of the users. The system may further manage, or assist in management of, disease test delivery and disease test result analysis, as well as pharmacological or other therapies and treatment recommendations, based on the collected information. The system may operate as a healthcare management system that incorporates multiple elements related to disease management that provide for more efficient and more effective approaches to disease management.

I. DETERMINING MEDICAL INTERVENTION PROVISION

[0028] A system may determine which users are to medical intervention for a disease. For example, the system may collect information from users and determine which users are to be tested, vaccinated and/or treated based on the information from the users. The system can provide the users with test kits, vaccines, prescriptions, therapy and/or other treatment based on the determination.

A . General population system flow

[0029] In some embodiments, a system may determine whether target users and/or interested visitors are to receive medical intervention for a disease. For example, the system may implement an informational website that can be accessed by targeted users and interested visitors to provide information to the system. The system can utilize the provided information to determine whether each of the target users and/or interested visitors are to receive medical intervention for the disease, such as being tested for the disease, being vaccinated for the disease, receiving pharmacological treatment for the disease, receiving further monitoring for the disease, receiving information/educational interventions for the disease, or some combination thereof.

[0030] FIG. 1 A illustrates a first portion of an example system flow 100 in accordance with some embodiments. FIG. IB illustrates a second portion of the example system flow 100 in accordance with some embodiments. For example, the system flow 100 shows an operation flow that may be performed by the healthcare system in one or more of the embodiments described herein. A system may perform the system flow 100 to identify one or more users to receive medical intervention for the disease. The medical intervention may include being tested for the disease, being vaccinated for the disease, receiving pharmacological treatment for the disease, receiving further monitoring for the disease, receiving information/educational interventions for the disease, or some combination thereof. In some instances, the system may be configured to perform the system flow 100 when test kits, vaccines and/or treatment for the disease are limited or limited to certain geographic regions. It should be understood that the operations of the system flow 100 may be performed in a different order than illustrated, one or more of the operations may be omitted from the system flow 100 and/or the operations of the system flow 100 may be combined with one or more of the operations described throughout this disclosure.

[0031] In block 102, the system may present an informational website that may be accessed by one or more users of the system. The informational website may be operated by one or more computer systems that can present the informational website for access via a network, such as the internet. The computer systems may have instructions stored thereon that provide operations performed by the informational website, such as presentation of the informational website on a device of a user, interaction with users via the informational website, and/or collection of data via the informational website. Further, the computer systems (such as via the informational website) may interact with one or more other computer systems (such as servers) to retrieve data and utilize services provided by the other computer systems.

[0032] The informational website may be utilized for collecting information related to a disease. The information may be collected from users of the informational website. The users may include a targeted population 104 invited to provide their information via the informational website, interested visitors 106 that access the informational website without being targeted, and/or any other individuals that may access the informational website. In some embodiments, a portion of the targeted population 104 may have been issued a ticket as part of the invitation, where the ticket indicates that the user is to receive medical intervention for the disease. The portion of the targeted population 104 to which the tickets are issued may be at high risk for infection from the disease, where the portion of the targeted population 104 to which the tickets are issued may receive medical intervention for the disease regardless of symptoms. The informational website may be accessible by healthcare providers (such as hospitals, medical offices, doctors, and/or other healthcare providers) as well as by the general public, thereby allowing for information for users to be received from both the healthcare providers and the general public rather than just from healthcare providers. Therefore, the system may gather more information than systems that are only accessible by healthcare providers.

[0033] Tn some embodiments, the informational website presented may differ based on the user accessing the informational website. For example, a first version of the informational website may be presented to the healthcare provider, and a second version of the informational website may be presented to the general public. The different versions of the informational website may provide for input of information customized to the particular user. For example, a version of the informational website presented to a healthcare provider may provide technical prompts to elicit data in formats known to be produced by healthcare providers. In contrast, a version of the informational website presented to the general public may include more general prompts to elicit answers that can be expected to be known by individuals within the general public. In some embodiments, the informational website presented to the general public may include a prompt for an identifier and/or code that may be provided to the users within the targeted population along with the invitation to access the informational website. In response to receipt of the valid identifier and/or code, the informational website may present customized prompts based on the identifier and/or the code, and/or may store data related to a user with a particular importance, in a particular location, and/or with relation to a particular group based on the identifier and/or the code.

[0034] In 108, a consent form and survey module may be presented via the informational website. For example, the informational website may present a consent form prompting consent from the user to store the information of the user, utilize the information of the user, and/or analyze the information of the user. The consent form may include prompts identifying possible specific uses of the information of the user allowing the user to select to which specific uses of the information the user consents. The prompts to consent presented may conform to a specific standard, such as health insurance portability and accountability act (HIPAA) standards. In some embodiments, the prompts to consent may vary based on the user. For example, the prompts to consent may be different for a user that is a medical provider as compared to a user that is of the general public. The survey module, or portions thereof, may be presented based on the consent provided by the user. For example, the survey module may not be presented if the user does not provide consent, a portion of the survey module may be presented if the user consents to a portion of the uses of the information, and an entirety of the survey model may be presented if the user consents to all of the uses of the information.

[0035] The survey module may include fields for entry of information related to the user. For example, the information included in the survey module may include symptom information of the user, whether test results for a disease are available for the user, the test results for the user, vaccination status of the user, exposure of the user to individuals having the disease or other sources of the disease, or some combination thereof. The symptom information may correspond to symptoms identified related to the disease, such as symptoms that healthcare professionals identify as may indicate an individual has the disease. In some instances, the symptom information may allow the user to enter any symptoms they present which appear not normal for the individual, such as when the test results for the disease indicate that the user tested positive for the disease. The survey module may include prompts customized to the user (such as being customized based on a group to which the user belongs) and/or the disease to obtain desired symptom information for determining whether the user likely has the disease and/or identifying symptoms of the disease. Symptoms may include both signs and symptoms as well as commonly available home monitoring measurements, such as inputs like weight, body mass index, body fat, temperature, heart rate, respiratory rate, pulse oximetry (oxygen saturation), and physiological activity/exercise, as well as visual (photographic or imaging) or sound (recording, as of cough or other vocalizations) inputs from the user, all of which can commonly be provided or captured using smartphones or other commonly available consumer devices.

[0036] The survey module may further include fields for entry of demographic information for the user. The demographic information may include age, race, ethnicity, gender, marital status, income, education, employment, or some combination thereof. In some embodiments, the demographic information, or portions thereof, may be made optional for entry by the user, where the user can decide whether or not they would like to provide the demographic information.

[0037] The survey module may further include fields for entry of environmental information for the user. The environmental information may include location information for the user. The location information may include locations where the user lives, locations where the user has visited, locations where the user has travelled or where the user normally travels, locations to which the user is planning on travelling, or some combination thereof. In some instances, the location information may include information regarding the means of travel the user used to travel to the locations or plans to use to travel to the locations, such as subway, bus, airplane, ride share, or other means of travel. In some embodiments, the environmental information may include characteristics of the locations, such as water supply information, wastewater information, possible pollution source information, and/or other information related to the locations.

[0038] The computer systems that operate the informational website may store the information obtained in the consent form and the survey module. The information may be securely and/or anonymously stored, such as to accord with information privacy standards including HIPAA standards. The information stored may be tied to randomly-generated tags (such as randomly-generated identifier numbers) stored separately from the information, such that the information may not be traced back to the users if accessed by an unauthorized entity. In some embodiments, the information may be separated into multiple portions, where each of the portions are stored in different locations. For example, the system may store the portions of the information in separate tables and/or in separate databases.

[0039] It should be understood that while certain information is described as being obtained via the consent form and the survey module, the information to be obtained via the consent form and the survey module may be customized by an operator of the computer systems that implement the informational website, such as being customized based on the disease, marketing, or other reasons the operator may determine for customization. Further, while techniques for storing the information have been described, different techniques for storing the information may be implemented, such as in accordance with different information privacy standards or different digital information protection techniques. [0040] In 110, the information obtained in 108 via the consent form and the survey module may be analyzed to determine whether a user is to be tested for the disease and/or vaccinated for the disease. For example, the system may determine whether the user from which the information collected was a user of the targeted population 104 to which a ticket was issued to be tested for the disease and/or vaccinated for the disease. In the instance where it is determined that the user was issued a ticket, the system may determine that the user is to be tested for the disease and/or vaccinated for the disease.

[0041] In some embodiments, the system may determine if the user had been previously tested for the disease and an amount of time since the user had been previously tested for the disease. If the amount of time since the user had been previously tested for the disease is less than a threshold amount of time, the system may determine that the user is not to be tested for the disease. Providing the threshold amount of time between tests for the disease may prevent the same user from being repetitively tested for the disease when it is likely that the results of the test would not have changed since the previous test for the disease.

[0042] Further, the system may determine whether the user is to be tested for the disease and/or vaccinated for the disease based on a vaccination status of the user in some embodiments. If the information obtained from the user indicates that the user has been vaccinated for the disease, the system may determine that the user is not to be tested for the disease and/or vaccinated for the disease. In some embodiments, the vaccination status may include an indication of a variant of the vaccination administered to the user, a date the vaccination was administered to the user, an indication whether the vaccination is in a series of vaccinations and/or the vaccinations within the series that have been administered to the user, or some combination thereof.

[0043] In instances where it has not been determined based on other factors (such as the ticket, time since last test, and vaccination status) whether the user is to be tested and/or vaccinated, the information obtained from the user may be analyzed to determine whether the user should be tested for the disease and/or vaccinated for the disease. For example, the system may utilize a symptomology model to analyze the information provided by the user to determine whether the user should be tested for the disease and/or vaccinated for the disease.

In some embodiments, the symptomology model may have inputs corresponding to symptoms of the disease, where the symptomology model may include weightings for each of the symptoms. The weightings for each of the symptoms may correspond to a likelihood that the symptom, or combination of symptoms, indicates that the user is likely to have the disease. For example, if a symptom of respiratory issues corresponds to a high likelihood of a user having the disease (e.g., 40% of subjects with a respiratory issue having the disease), the symptom of respiratory issues may be assigned a higher weighting than a symptom of a headache that corresponds to a lower likelihood of a user having the disease (e.g., 5% of subjects with a headache having the disease) . The symptomology model may generate an infection probability score based on the information provided by the user that indicates how likely the user is to have the disease.

[0044] The system may compare the infection probability score produced by the symptomology model to a threshold infection probability score to determine whether the user is to receive medical intervention for the disease. The threshold infection probability score may be set by an operator of the system or may be dynamically determined by the system based on one or more factors. For example, the system may determine the threshold infection probability score based on a total number of users of the informational website, an expected number of users of the informational website based on invitations provided to the targeted population 104 or marketing campaigns, a number of tests for the disease available, costs of each of the tests, a number of vaccinations for the disease available, costs of each of the vaccinations, costs of the medical intervention, available budget for providing the tests, vaccinations and/or other medical intervention, or some combination thereof. In some embodiments, the system may determine that the user is to receive medical intervention based on the infection probability score for the user being greater than or equal to the threshold infection probability score and may determine that the user is not to receive medical intervention based on the infection probability score for the user being less than the threshold infection probability. In this manner, only specific users may receive medical intervention, thereby maximizing the medical interventions to where and when they are most needed.

[0045] In some embodiments, the system may maintain multiple symptomology models. Each of the symptomology models may correspond to a certain population. For example, a first symptomology model may correspond to a first geographic region while a second symptomology model may correspond to a second geographic region. The population to which the symptomology models correspond may be based on locations, demographics, possible exposure to the disease, or some combination thereof. A symptomology model to be utilized for a user to determine whether the user is to receive medical intervention for the disease may be selected from the plurality of symptomology models based at least on a portion of the information for the user. For example, the system may compare the locations for the user, the demographics for the user, and/or the possible exposure to the disease for the user to factors corresponding to each of the symptomology models to determine which symptomology model is to be utilized for the user.

[0046] In some embodiments, the system may maintain multiple threshold infection probability scores. Each of the threshold infection probability scores may correspond to a certain population. For example, a first threshold infection probability score may correspond to a first geographic region while a second symptomology model may correspond to a second geographic region. The population to which the threshold infection probability scores correspond may be based on locations, demographics, possible exposure to the disease, or some combination thereof. A threshold infection probability score to be utilized for a user to determine whether the user is to receive medical intervention for the disease may be selected from the plurality of symptomology models based at least on a portion of the information for the user. For example, the system may compare the locations for the user, the demographics for the user, and/or the possible exposure to the disease for the user to factors corresponding to each of the threshold infection probability scores to determine which threshold infection probability score is to be utilized for the user.

[0047] In 112, if the user is determined not to receive medical intervention in 110 based on the information from the user, the user and corresponding information may be stored as part of a lottery. In some embodiments, an identifier of the user (such as a name of the user or another identifier assigned to the user), the information, or portions thereof may be stored in separate locations, such as in separate tables and/or separate databases. The lottery may include users who were not selected initially for medical intervention for the disease based on the infection probability scores for the users. The users in the lottery may be randomly selected to receive medical intervention based on a quota. The quota may indicate a certain amount of users desired to receive medical intervention. In some instances, the quota may correspond to a particular population, where the quota indicates an amount of the users desired to receive medical intervention within the population. The quota may be a certain number of the population, a certain percentage of the population, a certain number of users within the population, or a certain percentage of users within the population to receive medical intervention. [0048] In 114, the system may randomly select users from the lottery to receive medical intervention for the disease. For example, the system may randomly select a number of users from the lottery of 112 to fulfill the quota. In some embodiments, the system may separate the users in the lottery into different groups based on the information for the users and may select the users as desired from the different groups to fulfill the quota. In some of these embodiments, one or more of the different groups may have different quotas corresponding to each of the different groups, where the users may be selected from the different groups to fulfill each of the quotas. The users not selected to receive medical intervention in the current lottery selection may be put back into the lottery 112 for future lottery selections. The users randomly selected from the lottery to receive medical intervention may provide additional symptom information and infection results that can be utilized in generating a symptomatic model and/or adapting a symptomatic model as described further in relation to 718 (FIG. 7).

[0049] In 116, users included in the lottery 112 may update their information collected in the consent form and/or the survey module of 108. For example, a user who previously accessed the informational website and was placed into the lottery of 112 may access the informational website and update the symptom information, demographic information, exposure information, and/or vaccination status information previously provided by the user. If user updates the information, the user may be considered again in 110 with the updated information to determine whether the user is to receive medical intervention for the disease.

If the user does not update the information for the user when again accessing the informational website, the user may remain in the lottery of 112.

[0050] System flow 100 proceeds from 110 or 114 in FIG. 1 A to 118 in FIG. IB.

[0051] In 118, if a user is determined to be tested based on the analysis in 110 or based on being randomly selected from the lottery in 114, the user may be offered a test kit for testing for the disease in 118, or a message (e.g., including authorization) can be provided to a user device indicating that the user is to be tested. The indication may comprise a push notification in some embodiments. For example, the system may provide the push notification via a web interface, email, short message service (SMS), or other means of providing a push notification. In some embodiments, the system may further indicate options for the user to obtain a test kit, such as via a push notification. For example, the system may provide the option to have a test kit delivered to the user for taking the test for the disease. This option may be available for self-test kits, where the user can perform the test for the disease. In some embodiments, the system may allow the user to input delivery instructions for delivery of the test kit. The test kit being delivered may be assigned a unique identifier (such as a kit identifier or quick response (QR) code) allowing the system to track delivery of the test kit. The system may maintain a correspondence between the unique identifier for the test kit and tracking code for a carrier such that the system can track the delivery of the test kit via a website or server of the carrier.

[0052] In some embodiments, the indication of the options for the user to obtain a test kit may include an indication of merchant locations within a certain proximity of the user that have test kits available. This option may be available for self-test kits, where the user can perform the test for the disease. The system may access the websites and/or servers of the merchant locations to determine a stock of test kits that each of the merchant locations have available. The indication provided to the user may include indications of one or more merchant locations within the certain proximity of the user that have tests available. The indication of the merchant locations may include a name of the merchant, an address of the merchant location, contact information for the merchant location, or some combination thereof. In some embodiments, the user may indicate which merchant location from which they intend to obtain a test kit and the system may take the indication of the merchant location from the user into account when providing indications to other users of where to obtain test kits.

[0053] In some embodiments, the indication of the options for the user to obtain a test kit may include an indication of locations that the user may go to be tested for the disease. This option may be available for test kits that can be administered by a test administrator (such as a medical professional). The system may access the websites and/or servers of locations administering the tests for the disease to determine the availability of testing services at the location. For example, the system may determine whether the location has tests available, times that the location is administering the tests, available times within a schedule for the locations, or some combination thereof. In instances where a location schedules times for administering the test, the system may allow the user to select an available time to have the test administered and may schedule the time with the location to have the user tested.

[0054] In some embodiments, the indication that the user is to be tested may include an option for the user to indicate that the user has a test kit. For example, the user may have previously obtained a test kit via a merchant location, the test kit previously being delivered to the user, or another way by which the user obtained the kit. In some embodiments, the option to have the test kit delivered, the indication of merchant locations, and/or the indication of locations that the user may go to be tested for the disease may be omitted based on the user indicating that the user has a test kit. The indication that the user is to be tested may include an indication to the user to use the test kit to test themselves in instances where the user indicated that the user has a test kit.

[0055] The test kits may be utilized for performing one or more different types of tests. For example, the test kits may be for a polymerase chain reaction (PCR) test for deoxyribonucleic acid (DNA) or ribonucleic acid (RNA), an antigen test, or some combination thereof. The type of test for which the test kits are being provided may be based on the disease for which testing is being performed, a stage of the testing for the disease, or some combination thereof.

[0056] If a user is determined to be vaccinated based on the analysis in 110 or based on being randomly selected from the lottery in 114, the user may be offered a vaccine for the disease in 118. In particular, the system may present an indication to the user that the user is to be vaccinated for the disease. The indication may comprise a push notification in some embodiments. For example, the system may provide the push notification via a web interface, email, short message service (SMS), or other means of providing a push notification. The indication may include an indication of locations that the user may go to be vaccinated for the disease. The system may access the websites and/or servers of locations administering vaccines for the disease to determine the availability of vaccination services at the location. For example, the system may determine whether the location has vaccines available, times that the location is administering the vaccines, available times within a schedule for the locations, or some combination thereof. In instances where a location schedules times for administering the vaccines, the system may allow the user to select an available time to have the vaccine administered and may schedule the time with the location to have the user vaccinated. In some embodiments, once the user has been vaccinated or scheduled for vaccination, the user may be removed from consideration for being tested and/or vaccinated.

[0057] In some instance, the vaccination may allow for self-vaccination, such as via a self- vaccination kit. In these instances, the system may offer the user a self- vaccination kit or provide options for obtaining a self-vaccination kit based on the user being determined to be vaccinated. For example, a message (e.g., including authorization) can be provided to a user device indicating that the user is to be tested. The indication may comprise a push notification in some embodiments. For example, the system may provide the push notification via a web interface, email, short message service (SMS), or other means of providing a push notification. In some embodiments, the system may further indicate options for the user to obtain a self- vaccination kit, such as via a push notification. For example, the system may provide the option to have a self- vaccination kit delivered to the user for vaccinating for the disease. This option may be available for self-vaccination kits, where the user can perform the vaccination for the disease. In some embodiments, the system may allow the user to input delivery instructions for delivery of the self-vaccination kit. The self-vaccination kit being delivered may be assigned a unique identifier (such as a kit identifier or quick response (QR) code) allowing the system to track delivery of the test kit. The system may maintain a correspondence between the unique identifier for the self- vaccination kit and tracking code for a carrier such that the system can track the delivery of the self-vaccination kit via a website or server of the carrier.

[0058] Tn some embodiments, the indication of the options for the user to obtain a self- vaccination kit may include an indication of merchant locations within a certain proximity of the user that have self-vaccination kits available. This option may be available for self- vaccination kits, where the user can perform the vaccination for the disease. The system may access the websites and/or servers of the merchant locations to determine a stock of self- vaccination kits that each of the merchant locations have available. The indication provided to the user may include indications of one or more merchant locations within the certain proximity of the user that have self-vaccination kits available. The indication of the merchant locations may include a name of the merchant, an address of the merchant location, contact information for the merchant location, or some combination thereof. In some embodiments, the user may indicate which merchant location from which they intend to obtain a self- vaccination kit and the system may take the indication of the merchant location from the user into account when providing indications to other users of where to obtain self- vaccination kits.

[0059] In some embodiments, the indication that the user is to be vaccinated may include an option for the user to indicate that the user has a self-vaccination kit. For example, the user may have previously obtained a self- vaccination kit via a merchant location, the self- vaccination kit previously being delivered to the user, or another way by which the user obtained the kit. In some embodiments, the option to have the self-vaccination kit delivered, the indication of merchant locations, and/or the indication of locations that the user may go to be vaccinated for the disease may be omitted based on the user indicating that the user has a self-vaccination kit. The indication that the user is to be vaccinated may include an indication to the user to use the self-vaccination kit to vaccinate themselves in instances where the user indicated that the user has a self- vaccination kit.

[0060] If a user is determined to receive another medical intervention based on the analysis in 110 or based on being randomly selected from the lottery in 114, the user may be offered the other medical intervention and/or be provided with a location where the user can obtain the other medical intervention. The other medical interventions may include providing treatment for the disease, providing medication for the disease, providing therapy for the disease, providing pharmacological treatment for the disease, provide further monitoring for the disease, providing informational/educational interventions informing the user and/or changing the behavior of the user, or some combination thereof. The other medical interventions may be self-administered or provided by a medical administrator (such as a medical professional).

[0061] In the instances where the medical interventions may be self-administered, delivery of the medical interventions may be offered, indication of options for the user to obtain the medical interventions may be provided and/or allowing indication from the user that the user has the elements for the medical interventions may available. Procedures for offering delivery of the medical interventions, providing options for the user to obtain the medical interventions and/or allowing the indication from the user that the user has elements for the medical interventions may include one or more of the features for the procedures of offering delivery of the test kits/self-vaccination kits, providing options for obtaining the test kits/self- vaccination kits and/or allowing the indication from the user that the user has the test kits/self-vaccination kits as described above. In some instances where the medical intervention comprises providing informational/educational interventions, the informational/educational interventions may be provide via the internet (such as the informational website of block 102) in some embodiments. In instances where the medical interventions may be provided by a medical administrator, an indication of locations that the user may go to have the medical interventions administered may be provided. The procedure for indicating of locations that the user may go to have the medical interventions administered may include one or more of the features for the procedures of indicating locations that the user may go to be tested/receive the vaccine as described as above. [0062] In 120, the system may receive an indication that the user has utilized the test kit to produce a sample, completed the test to produce a sample, or has been tested by a test administrator. For example, the user may indicate that the user has completed the test in the case of self-test kits or test kits administered by a test administrator, and/or the test administrator may provide an indication that a user has been tested and/or the infection results from the test. In instances where the self-test kits provide infection results without having to take the test kit or sample to a lab, the user may provide the infection results of the test to the system in addition to indicating that the test has been completed by the user. The system may set a flag (such as a flag within a register of the system) corresponding to the user that indicates the user has provided the infection results in response to the user providing the infection results.

[0063] In 122, the system may schedule pickup of a sample produced by the test kit indicated by a user in 120. For example, the system may schedule a carrier to pick up any self-test kits indicated by users as being completed. The system may interact with the website and/or server to schedule pick up of the test kit from the user and delivery of the test kit to a lab that can produce the infection results from the test. In some embodiments, the system may provide an indication to an operator of the computer systems to schedule the pickup and delivery of the self-test kits. The system may schedule for delivery of the test kit to a nearest lab with testing availability to produce infection results from the test kit. The scheduling of the pickup in 122 may be omitted in instances where the self-test kits provide infection results from the test without having to be delivered to the lab, or the test kit is administered by a test administrator that can produce the infection results from the test or provide the test to a lab for testing.

[0064] In 124, the system may receive infection results from the test. In particular, the system may receive the infection results from the lab. The lab may provide the unique identifier corresponding to the test along with the infection results, where the system may utilize the unique identifier to associate the infection results with the user. The receipt of the infection results from the lab in 124 may be omitted when the infection results had been previously provided by the users and/or the test administrator.

[0065] In 126, the system may determine whether and/or how to indicate the infection results of a test are available to a user. For example, the system may determine whether to provide the infection results of the test based on whether the infection results were already available to the user, such as when the self-test kit provides the infection results without having to be provided to a lab. In particular, the system may detect a flag related to the user has been set based on the user having provided the infection results to the system. The system may determine that the infections results were already available to the user based on the user providing the infection results from the test kit, such as described in relation to 120. If the system determines that the indication of the infection results being available are to be provided to the user, the system may determine how to indicate the availability of the infection results to the user. The indication of the availability of the infection results may be provided to the user by phone call, text, email, mail, a portal (such as a secure portal), a push notification, or another form of providing the indication. In some embodiments, the format of how the indication of the availability of the infection results is provided to the user may depend on the infection results.

[0066] The system may provide the indication that the infection results are available and/or whether the infection results indicate that the user is infected with the disease in accordance with the form for providing the indication determined in 126. For example, the system may provide the availability indication and whether the infection results indicate that the user is infected with the disease via phone in 128 when the infection results are positive or inclusive for the user in the illustrated embodiment. Further, the system provides the indication and whether the infection results indicate that the user is infected with the disease via a secure portal in 130 when the infection results are negative for the user in the illustrated embodiment. For example, the system may provide an indication that the infection results are available (such as via phone or email) with a link to a secure portal or a passcode for the secure portal that provides the infection results for the user. The data provided by secure portal may be stored with an encryption, where the link or the passcode provided to user operates as a key for decrypted the data for presentation to the user. In some instances, providing the indication that the infection results are available and/or whether the infection results indicate that the user is infected with the disease may be omitted, such as when the system determines that the infection results have been previously provided to the user.

B. Multi test and prioritized system flow

[0067] In some embodiments, a system may have the option of multiple different medical interventions for users and/or studies in which to enroll users. For example, the system may select among multiple different medical interventions and/or studies for a user based on the system determining that a user is receive medical intervention. Further, the system may determine a priority for providing medical interventions to the users in some embodiments, such as by issuing tickets to the users having different priorities.

[0068] FIG. 2A illustrates a first portion of another example system flow 200 with contact tracing in accordance with some embodiments. FIG. 2B illustrates a second portion of the example system flow 200 in accordance with some embodiments. For example, the system flow 200 shows an operation flow that may be performed by the healthcare system in one or more of the embodiments described herein. A system may perform the system flow 200 to identify one or more users to receive medical intervention for the disease. In some instances, the system may be configured to perform the system flow 200 when medical interventions for the disease are limited or limited to certain geographic regions. It should be understood that the operations of the system flow 200 may be performed in a different order than illustrated, one or more of the operations may be omitted from the system flow 200, and/or the operations of the system flow 200 may be combined with one or more of the operations described throughout this disclosure.

[0069] In 202, the system may present an informational website that may be accessed by one or more users of the system. The informational website may include one or more of the features of the informational website of block 102 (FIG. 1A). The informational website may be utilized for collecting information related to a disease. The information may be collected from users of the informational website. The users may include a targeted population 204 invited to provide their information via the informational website, interested visitors 206 that access the informational website without being targeted, contacts 208 within a certain level of an individual who tested positive for the disease (such as being within a same household with an individual who tested positive for the disease), health response individuals 210 (such as healthcare providers, lab staff, and/or others that support identification and/or treatment of the disease), and/or any other individuals that may access the informational website.

[0070] In some embodiments, a portion of the targeted population 204, the contacts 208, and/or the health response individuals 210 may have been issued a ticket as part of an invitation to the informational website, where the ticket indicates that the user is to receive medical intervention for the disease. The system may issue the tickets to the portion of the targeted population 204, the contacts 208 and/or the health response individuals 210 based on the groups being at high risk for the disease. In some of these embodiments, the different groups may be issued different levels of tickets, where the different levels of tickets can indicate a priority of the user for reception of medical intervention for the disease. For example, the targeted population 204 is issued a first level ticket, the contacts 208 are issued a second level ticket with a priority below the first level ticket, and the health response individuals 210 are issued a third level ticket with a priority below the second level ticket in the illustrated embodiment. In some embodiments, a targeted screening program (such as targeted screening program 212) may be implemented to indicate a portion of the targeted population 204, the contacts 208, and/or the health response individuals that are to receive the tickets. For example, the targeted screening program 212 may be implemented in the illustrated embodiment to determine which portion of the health response individuals 210 are to receive a ticket.

[0071] In 214, a consent form and survey module may be presented via the informational website. The consent form and survey module may include one or more of the features of the consent form and survey model of 108 (FIG. 1 A). For example, the consent form and survey module may collect information from users and store the information obtained in the consent form and survey module as described in relation to the consent form and survey model of 108.

[0072] In 216, the information obtained in 214 via the consent form and the survey module may be analyzed to determine whether a user is to receive medical intervention for the disease. The analysis of the information in 216 may include one or more of the features of the analysis of information in 110 (FIG. 1 A). For example, the system may analyze the information obtained in 214 to determine whether a user is to receive medical intervention for the disease as described in relation to the analysis of information in 110. The system may determine whether the user is to receive medical intervention based on whether the user has been issued a ticket, whether the user had been previously tested for the disease, a vaccination status of the user, an infection probability score for the user produced by a symptomology model, or some combination thereof, as described in relation to the analysis of information in 110.

[0073] In some embodiments, the system may determine whether the user from which the information collected was a user to which a ticket was issued to receive medical intervention for the disease. In the instance where it is determined that the user was issued a ticket, the system may determine that the user is to receive medical intervention for the disease. In some instances (such as when there is limited medical intervention available), the priority level of the tickets may be taken in consideration when determining whether the user is to receive medical intervention for the disease. For example, the users issued tickets with the highest priority may be determined to receive medical intervention for the disease first and the system will continue to work down the priority levels of the tickets until medical interventions are no longer available. In other instances, the system may consider users with a certain priority level of ticket for medical intervention once all, or a certain portion, of the users issued higher priority level tickets have at least been offered medical intervention.

[0074] The system may compare the infection probability score produced by the symptomology model to a threshold infection probability score to determine whether the user is to receive medical intervention for the disease. The threshold infection probability score may be set by an operator of the system or may be dynamically determined by the system based on one or more factors. For example, the system may determine the threshold infection probability score based on a total number of users of the informational website, an expected number of users of the informational website based on invitations provided to the targeted population 104 or marketing campaigns, a number of tests for the disease available, costs of each of the tests, a number of vaccinations for the disease available, costs of each of the vaccinations, costs of medical intervention, available budget for providing the tests, vaccinations and/or other medical intervention, or some combination thereof. In some embodiments, the system may determine that the user is to receive medical intervention based on the infection probability score for the user being greater than or equal to the threshold infection probability score and may determine that the user is not to receive medical intervention based on the infection probability score for the user being less than the threshold infection probability. In this manner, only specific users are tested, thereby maximizing the medical interventions to where and when they are most needed.

[0075] In some embodiments, the system may implement a second threshold infection probability score in addition to the threshold infection probability score utilized for determining whether a user is to receive medical intervention. The second threshold infection probability score may correspond to a higher score produced by the symptomology table than the threshold infection probability score utilized for determining whether the user is to receive medical intervention. The system may utilize the second threshold infection probability score to determine whether a response to the information of a user is to exceed the response of indicating that the user is to receive medical intervention. For example, based on the system determining that the infection probability score for the user is equal to or greater than the second threshold infection probability score, the system may determine to escalate the response for the user, such as dispatching emergency medical services to the user in 218 or taking another defined escalated action. The system may communicate with the website and/or the server of an entity utilized for escalation (such as the emergency medical services) to provide the escalated response to the user.

[0076] In 220, if the user is determined not to receive medical intervention in 216 based on the information from the user, the user and corresponding information may be stored as part of a lottery. For example, the lottery and corresponding operations of 220 may include one or more of the features of the lottery and corresponding operations of 112 (FIG. 1 A).

[0077] In 222, the system may randomly select users from the lottery to receive medical intervention for the disease. For example, the system may randomly select a number of users from the lottery of 220 to fulfill the quota. The random selection of users of 222 may include one or more of the features of the random selection of users of 114 (FIG. 1 A). For example, the users may be randomly selected to fulfill a quota as described in relation to 114.

[0078] For users in the lottery of 220, the system may provide follow-up inquiries to the users in 224. For example, the system may provide follow-up inquiries at set intervals, or when triggered by an event (such updates to one or more of the symptomology models), to a user inquiring about any updates to the information of the user. In some embodiments, a follow-up inquiry may include a link to the informational website, which the user may utilize the informational website to update the information of the user.

[0079] In 226, users included in the lottery 220 may update their information collected in the consent form and/or the survey module of 214. For example, the updating of the information of 226 may include one or more of the features of updating of the information described in relation to 116.

[0080] In 228, if the system determines that a user is to be tested based on the analysis in 216 or based on being randomly selected from the lottery in 222, the system may select a medical intervention and/or study to be offered to the user. For example, the system may select a medical intervention and/or study from a plurality of medical interventions and/or studies when there are multiple medical interventions and/or studies for the disease. In the case where there is a single medical intervention and/or study for the disease, the system may select the single medical intervention and/or study. In some instances, the system may select the medical intervention and/or study based at least in part on the efficacy of the medical intervention and/or study, a desired amount of users to utilize the medical intervention and/or study, an availability of the medical intervention and/or study, or some combination thereof.

[0081] System flow 200 proceeds from 228 in FIG. 2A to 230 in FIG. 2B.

[0082] In 230, the system may offer a test kit to a user that is determined to be tested for the disease. In particular, the system may present an indication to the user that the user is to be tested for the disease. The offering of the test kit and/or the presentation of the indication to the user of 230 may include one or more of the features of the offering of the test kit and/or the presentation of indication of the user of 118 (FIG. IB). For example, the system may provide options to have the test delivered, options for the user to obtain a test kit, options of locations where the user may go to be tested for the disease, or some combination thereof as described in relation to 118.

[0083] If a user is determined to be vaccinated based on the analysis in 216 or based on being randomly selected from the lottery in 220, the user may be offered a vaccine for the disease in 230. The offering of the vaccine of 230 may include one or more of the features of the offering of the vaccine of 118. For example, the system may present the indication to the user that the user is to vaccinated, the indication of the locations to be vaccinated, or some combination thereof as described in relation to 118.

[0084] If a user is determined to receive another medical intervention based on the analysis in 216 or based on being randomly selected from the lottery in 220, the user may be offered the other medical intervention and/or be provided with a location where the user can obtain the other medical intervention. The offering of the other medical intervention and/or being provided with the location where the user can obtain the other medical intervention may include one or more of the features of the offering of the other medical intervention and/or being provided with the location where the user can obtain the other medical intervention of 118. For example, the system may present the indication to the user that the user is to receive medical intervention, the indication of locations to receive medical intervention, or some combination thereof as described in relation to 118.

[0085] In some embodiments, the system may request insurance information from the user in 232. For example, the system may present the user with one or more fields to input the insurance information of the user. The system may utilize the insurance information to verify that the user has insurance and/or determine whether the insurance of the user covers the medical intervention. The system may utilize a website and/or server of an indicated insurer to verify that the user has insurance and/or determine whether the insurance of the user covers the medical intervention or may present an indication including the insurance information to an operator of the system indicating that the operator is to verify that the user has insurance and/or determine whether the insurance of the user covers the medical intervention. If the system determines that the user has insurance and/or the insurance of the user covers the medical intervention, the system may provide cost and/or billing information for the medical intervention to the insurer to facilitate payment for the medical intervention by the insurer. In some of these embodiments, the system may utilize the insurance and/or insurance coverage of the user in the determination in 228 to determine the medical intervention to be offered to the user. Further, the system may determine whether to offer medical intervention to the user in 230 based on the insurance and/or insurance coverage of the user in some of these embodiments.

[0086] In 234, the system may receive an indication that the user has utilized the test kit to produce a sample, completed the test to produce a sample, or has been tested by a test administrator. The receipt of the indication of 234 may include one or more of the features of the receipt of the indication of 120 (FIG. IB).

[0087] In 236, the system may schedule pickup of a completed test indicated by a user in 234. The scheduling of the pickup of the completed test of 236 may include one or more of the features of the scheduling of the pickup of the completed test of 122 (FIG. IB). For example, the system may schedule the pickup of the test kit as described in relation to 122.

[0088] In 238, the system may receive infection results from the test. The reception of the infection results of 238 may include one or more of the features of the reception of the infection results of 124 (FIG. IB). For example, the system may receive the infection results from the lab as described in relation to 124.

[0089] In 240, the system may determine whether and/or how to indicate the infection results of a test are available to a user. The determination whether and/or how to indicate the infection results of 240 may include one or more of the features of the determination whether and/or how to indicate the infection results of 126 (FIG. IB).

[0090] The system may provide the indication that the infection results are available and/or whether the infection results indicate that the user is infected with the disease in accordance with the form for providing the indication determined in 240. For example, the system provides the indication and whether the infection results indicate that the user is infected with the disease via phone in 242 when the infection results are positive or inclusive for the user in the illustrated embodiment. Further, the system provides the indication and whether the infection results indicate that the user is infected with the disease via a secure portal in 244 when the infection results are negative for the user in the illustrated embodiment. In some instances, providing the indication that the infection results are available and/or whether the infection results indicate that the user is infected with the disease may be omitted, such as when the system determines that the infection results have been previously provided to the user.

[0091] In some embodiments, when the system determines that the infection results for a user are inconclusive (such as when the infection results produced by a test kit are indicated as being inconclusive in 238), the system may offer the user another test kit. For example, the system may return to 230 and offer the user corresponding to the infection results that were determined to be inconclusive another test kit. The system may then repeat 234, 236, 238, 240, 242, and/or 244 for the new test kit offered to the user.

[0092] In some embodiments, when the system determines that the infection results for a user are negative, the system may offer the user involvement in one or more engagement programs in 246. For example, the system may provide an indication to the user of one or more engagement programs (such as community social engagement programs) that a user may join. In some of these embodiments, the indication of the engagement programs may be provided based on the test kit being negative. The indication may be provided via a push notification in some embodiments. For example, the system may provide the push notification via a web interface, email, short message service (SMS), or other means of providing a push notification. In some instances, the engagement programs may allow the user to interact with other users who have tested negative for the disease.

[0093] In some embodiments, when the system determines that the infection results for a user are negative, the system may share the infection results for the disease with one or more healthcare providers associated with the user in 248. For example, the system may interact with websites and/or servers of the healthcare providers associated with the user to provide the infection results of the user to the healthcare providers associated with the user. The healthcare providers may utilize provided infection results to update health records associated with the user. The system may proceed to 224 for the user providing follow-up inquiries to the user and/or storing the user in the lottery of 220.

[0094] In some embodiments, when the system determines that the infection results for a user are positive, the system may provide social distancing and re-testing support to the user in 250. For example, the system may offer to schedule the user for one or more additional tests after the test that resulted in the positive diagnosis for the disease, where the additional tests can indicate when the user has recovered from the disease. If the user elects to allow the system to schedule the one or more additional tests, the system may perform 230, 234, 236, 238, 240, 242, and/or 244 for each of the additional tests in accordance with a defined schedule for re-testing.

[0095] In some embodiments, when the system determines that the infection results for a user are positive, the system may offer contact tracing in 252. The contact tracing may be optional where a user can select whether the user is to be enrolled in a contact tracing program at any stage after initial access of the informational website by the user. By selecting to be part of the contact tracing program, the user may submit locations where the user has visited to the system, enable the system to receive locations tracked by a wearable device (or other device that can be used for determining a location of the user or the device) of the user, or some combination thereof. In response to the system determining that the infection results for the user are positive, the system may identify other users (from the users that selected to be part of the contact tracing program) that have been within a defined proximity of the user within a certain period of time of the completion of the test kit that produced the positive infection results and provide an indication to the identified other users that they have been within the proximity of a user that tested positive for the disease. The indication may comprise a push notification in some embodiments. For example, the system may provide the push notification via a web interface, email, short message service (SMS), or other means of providing a push notification. In some embodiments, the system may present an offer to the user corresponding to the positive infection result to select whether to allow the system to identify other users that have been within the defined proximity prior to identifying, or not identifying the other users based on the selection of the user, the other users.

[0096] In some embodiments, when the system determines that the infection results for a user are positive, the system may offer medical intervention to household contacts in 254. In particular, the system may utilize the information for the user corresponding to the positive infection result and/or information associated with one or more other users to identify users that live within a same household as the user corresponding to the positive infection result. The system may issue tickets to those users identified as living within the same household as the user corresponding to the positive infection result, which can result in the users issued the ticket being included in the contacts of 208. Accordingly, the users issued tickets may be determined to receive medical intervention in 216 based on the ticket. In some of these embodiments, the system may present an offer to the user corresponding to the positive infection result to select whether to identify and/or issue tickets to the users living within the same household as the user corresponding to the positive infection result prior to the system identifying and/or issuing the tickets, or not identifying and/or issuing the tickets to, to the users living within the same household. c. Targeted recruiting system flow

[0097] In some embodiments, a system may target individuals to recruit for providing information to the system. For example, the system may identify individuals to target and provide targeted media to recruit the individuals, such as mailings and/or other targeted advertisements. In some embodiments, the system may initiate other types of media to recruit users. The system may identify the individuals to target based on users having the same or similar characteristics (such as the same or similar geographic location, demographics, social determinants, symptoms, or some combination thereof) as the individuals being under underrepresented, users having the same or similar characteristics as the individuals presenting an above average rate of infection for the disease (such as high risk geographic location hot spots), users having a high risk level for being infected with the disease, or some combination thereof.

[0098] FIG. 3A illustrates a first portion of another example system flow 300 with symptomatic grouping and expansion in accordance with some embodiments. FIG. 3B illustrates a second portion of the example system flow 300 in accordance with some embodiments. FIG. 3C illustrates a third portion of the example system flow 300 in accordance with some embodiments. For example, the system flow 300 shows an operation flow that may be performed by the healthcare system in one or more of the embodiments described herein. It should be understood that the operations of the system flow 300 may be performed in a different order than illustrated, one or more of the operations may be omitted from the system flow 300, and/or the operations of the system flow 300 may be combined with one or more of the operations described throughout this disclosure.

[0099] In 302, the system may prepare informational media. For example, the system may determine to initiate an informational media campaign for gathering information from users based on information already gathered from other users. The system may analyze previously gathered information from users to determine whether information is desired from further users. In some embodiments, a threshold amount of users from which information is to be gathered may be defined for the disease, and the system may determine that information is desired from further users based on a current amount of users from which information has been gathered being less than the threshold amount of users. For example, the threshold amount of users for which information is to be gathered may be defined by an operator of the system, based on a target population, based on information related to the characteristics of the disease, or some combination thereof. In some embodiments, the system may define the threshold amount of users as being a certain percentage of a target population, where the target population may be an entirety of the public or individuals having common characteristics (such as common geographic location, common demographics, common social determinants, common symptoms, or some combination thereof). In some embodiments, the threshold amount of users may be based on the severity of the disease, level of transmission (such as the reproductive ratio or R value) of the disease, modes of transmission of the disease, or some combination thereof. For example, the system may retrieve indications of severity, level of transmission, and/or modes of transmission of a disease from a website and/or a server of health authority (such as the World Health Organization, the Department of Health and Human Services, the Center for Disease Control, or other health authorities) and determine the threshold amount of users based on the severity, level of transmission, and/or modes of transmission of the disease. In some instances, the system may determine that diseases with higher severity, higher levels of transmission, and/or easier modes of transmission are to have a higher threshold amount of users than diseases with lower severity, lower levels of transmission, and/or harder modes of transmission. In other embodiments, the system may analyze the previously gathered information from users to determine a response rate (for example, a number of users who have responded versus a population being targeted for response), a risk level for the disease for a population, environmental factors contributing to infection by the disease, or some combination thereof, to produce the threshold amount of users from which information is to be gathered. [0100] The system may determine whether to initiate the informational media campaign based on a particular population. For example, the system may analyze the information previously gathered from users for a particular population, where the population may be defined based on geographic information, demographic information, and/or social determinants for the users. The system may identify users within a same geographic region, a same demographic, and/or a same social determinant and determine the response rate, risk level, and/or environmental factors contributing to infection by the disease for the users within the same geographic region, the same demographic, and/or the same social determinant. The system may compare the number of users within the same geographic region, the same demographic, and/or the same social determinant with a defined threshold amount of users or a determined threshold amount of users to determine whether information is desired from further users. In some embodiments, the defined threshold amount of users or the determined threshold amount of users may be specific to the population, where different populations defined by different geographic regions, different demographics, and/or different social determinants may have different threshold amounts of users. Further, the threshold amount of users for the different populations may be determined based on the risk level, where a population with a high risk level (which may be referred to as a high risk hot spot) may have a higher threshold amount than populations with lower risk levels.

[0101] Based on the system determining that an informational media campaign is to be initiated to gather information from further users, the system may initiate an informative media propaganda to inform the population of the informational media campaign. For example, the system may cause advertisements to be displayed in various mediums informing the targeted population of the desire for additional information and/or the method of which the additional information may be provided by individuals within the population. For example, the system may cause internet advertisements to be displayed, television advertisements to be displayed, sound advertisements to be played, print advertisements to be provided, or other mediums of advertisement to be initiated informing the population of the desire for additional information. The advertisements initiated by the system may provide the informational website (such as the informational website of block 102 (FIG. 1A) and/or the informational website 202 (FIG. 2A)) by which the information may be provided by the individuals of the population. In other instances, the advertisements may inform the population of other procedures for providing the information, such as informing the population to monitor their mail for mailings providing a procedure for submitting information by the individuals of the population.

[0102] In 304, the system may determine particular individuals within the population to provide the procedure for submitting information. For example, the system may determine that particular individuals within the population are to be provided a mailing providing the individual with access to the informational website and/or another procedure for submission of information to the system. The system may identify addresses (such as street addresses and/or electronic mail addresses) for the particular individuals to which the mailing may be provided. The particular individuals may be determined based on a likelihood that the individual will respond (which may be based on previous responses to information requests from the individual), any particularized risk factors for the disease associated with the individual, a geographic region in which the individual is located, a demographic that includes the individual, a social determinant that includes the individual, or some combination thereof. Tn some embodiments, the system may predict an amount of the individuals likely to respond (which may be based on previous response to information requests from the individual) and may determine a number of individuals to which the mailing is to be provided to meet the threshold amount of users from which information is to be gathered.

[0103] In 306, the system may provide the procedure to submit information to the particular individuals. For example, the system may cause the mailing to be sent to the particular individuals determined in 304. In particular, the system may cause the electronic mail to be sent to the particular individuals and/or cause physical mailings to be sent to the particular individuals (such as by providing an indication to an operator of the system to send out the physical mailings and/or causing an automated mailing system to send out the physical mailings).

[0104] In some embodiments, a portion of the mailings may include a ticket (such as the tickets issued to the targeted population 104 (FIG. 1A), the tickets issued to the targeted population 204 (FIG. 2A), the tickets issued to the contacts 208 (FIG. 2A), and/or the tickets issued to the health response individuals 210 (FIG. 2A). The system may determine the portion to receive the ticket based on a particularized reason for gathering the information from the individual, such as users within a same geographic region, demographic, and/or social determinant as the individual having a high rate of infection for the disease, a geographic region, demographic, and/or social determinant of the individual having a high chance of infection for the disease, the individual having a relationship with users infected with the disease, or some combination thereof. The system may be able to determine the relationship of the individual to users based on information that the system can collect from the internet (such as from social media websites) in some embodiments. In some embodiments, operation 304 and operation 306 may be omitted, such as where the informative media propaganda of 302 provides the procedure for the individuals to provide the information to the system.

[0105] In embodiments where a portion of the mailings include a ticket, the system may have particular operations that are performed with individuals that were issued a ticket as compared to those individuals that did not receive a ticket. For example, the system may initiate a telephone follow-up for individual that were issued a ticket in 308. The system may cause an automated call to be placed to the individual and/or provide an indication to an operator of the system to place a call to the individual to remind the individual of the request for information. In some embodiments, the system may monitor for responses from the individuals that were issued a ticket and may determine whether the individual has responded. If the system determines that the individual has responded, the system may forgo the telephone follow-up of 308. If the system determines that the individual has not responded, the system may initiate the telephone follow-up of 308. In some instances, the system may continue to initiate the telephone follow-up at set intervals until the information is received from the individual, or the individual indicates that they do not want to receive the telephone follow-up or do not wish to provide information.

[0106] In further embodiments where a portion of the mailings include a ticket, the system may initiate a mailing follow-up with individuals that were issued a ticket in 310. For example, the system may cause an electronic mailing to be sent to the individuals and/or cause physical mailings to be sent to the individuals (such as by providing an indication to an operator of the system to send out the physical mailings and/or causing an automated mailing system to send out the physical mailings) to follow-up the initial mailing. In some embodiments, the system may monitor for responses from the individuals that were issued a ticket and may determine whether the individual has responded. If the system determines that the individual has responded, the system may forgo the mailing follow-up of 310. If the system determines that the individual has not responded, the system may initiate the mailing follow-up of 310. In some instances, the system may continue to initiate the mailing follow- up at set intervals until the information is received from the individual, or the individual indicates that they do not want to receive the telephone follow-up or do not wish to provide information. In some embodiments, operation 308 and operation 310 maybe omitted, such as in embodiments where tickets are not issued in 306.

[0107] In 312, the system may present an informational website that may be accessed by the individuals, where the individuals may become users of the system. The informational website may be operated by one or more computer systems that can present the informational website for access via a network, such as the internet. The computer systems may have instructions stored thereon that provide operations performed by the informational website, such as presentation of the informational website on a device of the user, interaction with users via the informational website, and/or collection of data via the informational website. Further, the computer systems (such as via the informational website) may interact with one or more other computer systems (such as servers) to retrieve data and utilize services provided by the other computer systems.

[0108] The informational website may be utilized for collecting information related to a disease. The information may be collected from users of the informational website. The users may include the individuals to which the informational media campaign of 302 was directed and/or the individuals to which the procedure to submit information was provided in 306, among other users (such as users that previously accessed the informational website, the targeted population (such as the targeted population 104 (FIG. 1 A) and the targeted population 204 (FIG. 2A)), interested visitors (such as the interested visitors 106 (FIG. 1 A) and the interested visitors 206 (FIG. 2A)), and/or contacts (such as the contacts 208 (FIG. 2A), and/or health response individuals 210 (FIG. 2A))). The informational website may be accessible by healthcare providers (such as hospitals, medical offices, doctors, and/or other healthcare providers) as well as by the general public, thereby allowing for information to be received from both sources rather than just from healthcare providers. Therefore, the system may gather more information than systems that are only accessible by healthcare providers.

[0109] In some embodiments, the informational website presented may differ based on the user accessing the informational website. For example, a first version of the informational website may be presented to the healthcare provider and a second version of the informational website may be presented to the general public. The different versions of the informational website may provide for input of information customized to the particular user. For example, a version of the informational website presented to a healthcare provider may provide technical prompts to elicit data in formats known to be produced by healthcare providers. In contrast, a version of the informational website presented to the general public may include more general prompts to elicit answers that can be expected to be known by individuals within the general public. In some embodiments, the informational website presented to the general public may include a prompt for an identifier and/or code that may be provided to the users within the targeted population along with the invitation to access the informational website. In response to receipt of the valid identifier and/or code, the informational website may present customized prompts based on the identifier and/or the code, and/or may store data related to a user with a particular importance, in a particular location, and/or with relation to a particular group based on the identifier and/or the code.

[0110] In 314, the system may select a portion of the users who accessed the informational website in 312 for testing for the disease. The system may select the portion of the users based on the tickets issued to a portion of the users, information provided to the system via the informational website in 312, or some combination thereof, or may randomly select the portion of the users. The system may provide the portion of the users with a test kit (such as with offering of the test kit in 118 (FIG. IB) and/or 230 (FIG. 2B)), and/or picking up the test kit in 122 (FIG. IB) and/or 236 (FIG. 2B)) and may receive the infection results for the users (such as the reception of the infection results in 124 (FIG. IB) and/or 238 (FIG. 2B)).

[0111] The system may provide an alternative route to testing and submitting information to the system for individuals that were not selected for the targeted mailing of operations 302, 304, and 306. For example, the system may initiate a social media and public relations campaign in 316. The social media and public relations campaign may include running advertisements via one or more different mediums (such as via television, sound, internet, print, or other commonly utilized advertisement mediums) for the informational website for submitting information to the system. The social media and public relations campaign may be directed to an entirety of the public, certain geographic regions, certain demographics, certain social determinants, or some combination thereof.

[0112] In 318, the system may present an informational website that may be accessed by the individuals, where the individuals may become users of the system. The informational website may be a same informational website as the informational website of 312 or a different informational website. For example, individuals selected via the informational media campaign of 302, 304, and 306 may be directed to a different informational website or may be presented a different version of the informational website than a individuals responding to the social media and public relations campaign of 316. In these embodiments, the system may determine which informational website or version of the informational website to present to the individual based on identifier of the individual (such as a name of the individual and/or identifier assigned to the individual via the mailing in 306) and/or an access code to a certain informational website or version of the informational website provided via the mailing in 306. In other embodiments, the system may direct the individuals selected via the informational media campaign of 302, 304, and 306 and the individuals accessing the informational website via the social media and public relations campaign to the same informational website or the same version of the informational website.

[0113] The informational website may be operated by one or more computer systems that can present the informational website for access via a network, such as the internet. The computer systems may have instructions stored thereon that provide operations performed by the informational website, such as presentation of the informational website on a device of the user, interaction with users via the informational website, and/or collection of data via the informational website. Further, the computer systems (such as via the informational website) may interact with one or more other computer systems (such as servers) to retrieve data and utilize services provided by the other computer systems.

[0114] The informational website may be utilized for collecting information related to a disease. The information may be collected from users of the informational website. The users may include the individuals that accessed the informational website based on the social media and public relations campaign, among other users (such as users that previously accessed the informational website, the targeted population (such as the targeted population 104 (FIG. 1A) and the targeted population 204 (FIG. 2A)), interested visitors (such as the interested visitors 106 (FIG. 1A) and the interested visitors 206 (FIG. 2 A)), contacts (such as the contacts 208 (FIG. 2A), and/or health response individuals 210 (FIG. 2A))). The informational website may be accessible by healthcare providers (such as hospitals, medical offices, doctors, and/or other healthcare providers) as well as by the general public, thereby allowing for information to be received from both sources rather than just from healthcare providers. Therefore, the system may gather more information than systems that are only accessible by healthcare providers. 1. Symptomatic and Asymptomatic Grouping

[0115] In some embodiments, a system may group users based on symptoms of the users. For example, the system may group users into symptomatic and asymptomatic groups based on the symptoms presented by the user. In some embodiments, the system may receive definitions for the symptomatic and asymptomatic groups from a health authority and utilize the definitions for separating the users into symptomatic and asymptomatic groups. In some embodiments, the system may utilize different symptomology models to determine whether users in the symptomatic group and the asymptomatic groups are to be tested and/or vaccinated.

[0116] In 318, the system may separate the users into symptomatic users and asymptomatic users based on the information provided to the system by the users via the informational website. For example, the system may compare the information provided by the users to known symptoms of the disease to determine which users present the symptoms of the disease and which users do not. The system may assign users that present symptoms to the symptomatic user group 320 and users that do not present symptoms to the asymptomatic user group 322. In some embodiments, the system may apply a symptomology model (such as the symptomology model utilized in 110 (FIG. 1) and/or the symptomology model utilized in 216 (FIG. 2)) to the information provided by each of the users and determine whether each of the users is symptomatic or asymptomatic based on an infection probability score produced by the symptomology model. The system may utilize a predefined threshold infection probability score or a threshold infection probability score determined by the system on previously collected information from users to determine whether a user is symptomatic or asymptomatic. For example, the system may assign users with infection probability scores that are equal or greater than the threshold infection probability score to the symptomatic user group 320 and may assign users with infection probability scores that are less than the threshold infection probability score to the asymptomatic user group 322.

[0117] In other embodiments, the definition of symptomatic may be defined based on an external source. For example, the system may retrieve a definition from symptomatic from an external source, such as the Center for Disease Control and Prevention, the World Health Organization, or other sources that provide a definition of symptomatic. The system may retrieve the definition from a website and/or server for the external source. In other embodiments, an operator of the system may input the definition of symptomatic. The system may compare the information provided by the users to the provided definition of symptomatic to determine which users are symptomatic and which users are asymptomatic. The system may assign users that meet the symptomatic definition to the symptomatic user group 320 and users that do not meet the symptomatic definition to the asymptomatic user group 322.

[0118] The system may select users from the symptomatic user group 320 and/or the asymptomatic user group 322 for which to provide a test kit (such as with offering of the test kit in 118 (FIG. IB) and/or 230 (FIG. 2B)), and/or picking up the test kit in 122 (FIG. IB) and/or 236 (FIG. 2B)) and may receive the infection results for the users (such as the reception of the infection results in 124 (FIG. IB) and/or 238 (FIG. 2B)). The amount of users selected from the symptomatic user group 320 may be equal to or different than the amount of users selected from the asymptomatic user group 322. The system may select the users for testing from the symptomatic user group 320 and/or the asymptomatic user group 322 based on the information received from each of the users, or may randomly select users for testing from the symptomatic user group 320 and/or the asymptomatic user group 322. The system may cause test kits to be provided to the users selected from the symptomatic user group 320 and/or the asymptomatic group.

[0119] The system may perform different operations based on whether the infection results from the test kit indicated that the user is infected with the disease. Further, the system may perform different operations based on whether the user submitted information based on the informational media campaign of 302, 304, and 306 or based on the social media and public relations campaign of 316. For example, the system may perform further operations with users who tested negative for the disease from the informational media campaign users, while the system may not perform further operations with users who tested negative for the disease from the social media and public relations campaign in some embodiments. In other embodiments, the system may perform the same operations for the users based on the infection results from the test kit regardless of whether the user submitted the information based on the informational media campaign or the social media and public relations campaign.

2. Infection Result Expansion

[0120] In some embodiments, a system may utilize an infection result for a user to determine other users to receive medical intervention. For example, the system may identify users within a same household as, or that come into contact with, a user for which the system has an infection result. The system may utilize the relationship with the user in determining whether the other users are to receive medical intervention. For example, a symptomology model to be utilized by the system for determining whether a user is to receive medical intervention may include a factor related to relationships between users. Due to the symptomology model including the factor related to relationships between users, the symptomology model may be more or less likely to indicate a user is to receive medical intervention for the disease based on the user’s relationships with other users.

[0121] System flow 300 proceeds from 314 in FIG. 3 A to 324 in FIG. 3B.

[0122] In 324, if the infection result for a user indicates that the user is not infected with the disease, the system may add the user to a stored user population that were indicated as having negative infection results. The system may utilize the infection results for the users within the stored user population indicated as having negative infection results to expand information for other related users. For example, the system may identify household members of the users with negative infection results in 326 and 328. The system may determine that the household members are less likely to be infected with the disease based on sharing a household with the user with the negative infection result and accordingly may make the household members less likely to be tested for the disease and/or place a lower priority on testing the household member than other individuals. For example, the system may apply a symptomology model (such as the symptomology model utilized in 110 (FIG. 1) and/or the symptomology model utilized in 216 (FIG. 2)) for the household member that takes into account that the household member lives in a household with the user that tested negative and produces a lower infection probability score based on living in the household with the user than if living in the household with the user was not taken into account. The symptomology model may include a factor for relationships between users, where the factor may cause the probability score to be higher and lower based on whether certain relationships (such as being household members) exist between the users. The training of the symptomology model may determine an amount of weight given to the factor for the relationships between users.

[0123] In some embodiments, the system may further offer a serology test to the user that was indicated as not being infected by the disease in 330. For example, the system may initiate serology testing for the user to determine whether the user has developed antibodies to the disease. The system may update the information for the user based on whether the serology test indicates that the user has developed antibodies for the disease. Further, the system may take into account whether the user has developed antibodies for the disease for determining whether to offer medical intervention to the user and/or the household members in the future. For example, the system may utilize a symptomology model that takes into account whether the user has developed antibodies for the disease when determining whether to offer medical intervention to the user and/or the household members. The symptomology model may produce a lower infection probability score for the user and/or household members when the serology testing indicated that the user has developed antibodies for the disease than if the symptomology model did not take into account whether the user has developed antibodies for the disease.

[0124] System flow 300 proceeds from 314, 320, or 322 in FIG. 1A to 332 in FIG. IB.

[0125] If the infection result for a user indicates that the user is infected with the disease, the system may add the user to a stored user population that were indicated as having positive infection results in 332. The system may utilize the infection results for the users within the stored user population indicated as having positive infection results to expand information for other related users. For example, the system may identify household members of the users with positive infection results in 334 and 336. The system may determine that the household members are more likely to be infected with the disease based on sharing a household with the user with the positive infection result and accordingly may make the household members more likely to receive medical intervention for the disease and/or place a higher priority on medical intervention for the household member than other individuals. For example, the system may apply a symptomology model (such as the symptomology model utilized in 110 (FIG. 1) and/or the symptomology model utilized in 216 (FIG. 2)) for the household member that takes into account that the household member lives in a household with the user that tested positive and produces a higher infection probability score based on living in the household with the user than if living in the household with the user was not taken into account.

[0126] In some embodiments, the system may further provide contact tracing for the user that was indicated as infected with the disease. For example, the system may utilize geographic information provided by the user with the positive test results and identify other users that have been within a certain proximity of the user in 338 and 340. The system may determine that the other users identified within the certain proximity of the user are more likely to be infected with the disease and may take into account the other users being within the certain proximity of the user when determining whether to offer the other users medical intervention for the disease. For example, the system may utilize a symptomology model that takes into account whether the user has been within a certain proximity of a user that is infected with the disease. The symptomology model may produce a higher infection probability score for the user when the user was within the certain proximity of the user infected with the disease than when the proximity to the user infected with the disease is not taken into account.

[0127] In some embodiments, the system may issue tickets to household members identified in 334 and 336, and/or the users identified in 338 and 340. The tickets may indicate that the household members and/or the users are to receive medical intervention for the disease. For example, the tickets may indicate that the household members and/or the users are to receive a reverse transcription polymerase chain reaction (RT-PCR) test, a serology dried blood spot (DBS) test, or both to test for the disease. The system may utilize the infection results of the tests administered to the household members identified in 334 and 336 and the users identified in 338 and 340 to determine possible transmission levels of the disease and/or immunity development for the disease. For example, if a high amount of household members identified in 334 and 336 and/or users identified in 338 and 340 test positive for the disease, the system may determine that the disease presents a high level of transmission and individuals within households of users testing positive for the disease and/or individuals who came into contact with users testing positive for the disease are more likely to be infected. Based the system determining that the individuals within the households and/or that came into contact with the users are more likely to be infected, the system may increase the chances that the system selects the individuals for medical intervention, such as by issuing the individuals tickets indicating that the individuals are to receive medical intervention or adapting a symptomology model to have the individuals within the households and/or that came into contact with the users more likely to be chosen to receive medical intervention by the system than other individuals outside the household and that did not come into contact with the users that tested positive for the disease. The system may determine that the amount of household members identified in 334 and 336 and/or users identified in 338 and 340 is high based on a threshold amount, where the threshold amount may be predefined. [0128] The system may further elicit additional information from the user that was infected with the disease as the disease progresses and as the user recovers from the disease in 342. For example, the system may provide follow-up inquiries at set intervals after the user has tested positive for disease to the user inquiring about any updates to the information of the user. Based on the information provided by the user in response to the follow-up inquiries, the system may determine whether the user is still infected with the disease, whether the user has recovered from the disease, whether to provide the user with another test kit to determine whether the user is still infected with the disease or the user has recovered from the disease

(such as when the system is unable to determine whether the user is still infected with the disease), or some combination thereof.

[0129] The system may associate the information received from the user with a stage of the disease, and/or a time relative to the positive test result for the disease or the recovery from the disease. For example, the system may determine that the user is still infected with the disease and/or an amount of time from which the reception of the indication of the initial positive test result for the user occurred to a time the information was provided to the system based on the information, and may associate the information received with the user still being infected with the disease and/or the amount of time. Based on the information received for the user while the user is still infected, the system may analyze the information and determine how symptoms change and/or progress as the disease progresses. In some embodiments, the system may utilize how the symptoms change and/or progress as the disease progresses to determine how far along in the infection period a user is and/or whether treatment of the user needs to be elevated (such as contacting emergency services for the individual and/or providing instruction for the user to visit a healthcare facility).

[0130] The system may determine that a user is no longer infected with a disease, an amount of time from which the reception of the indication of the initial positive test result for the user occurred to a time the information was provided to the system, and/or an amount of time from which the system determined that the user was no longer infected with the disease to the time the information was provided to the system. The system may associate the information received with the user having recovered from the disease and/or the amount of time. Based on the information received for the user once the user has recovered, the system may identity any symptoms that may extend after recovery from the disease. In some embodiments, the system may cause one or more serology tests to be performed on the user once the user has recovered from the disease to determine whether antibodies for the disease remain after the user has recovered and/or how long the antibodies for the disease remain with the user after the user recovers. The system may utilize the information provided by the user after recovery from the disease and/or the results of the serology tests to analyze other users that are recovering from the disease to make sure that the users are progressing properly, or as expected, in their recovery from the disease.

II. USER GROUPING

[0131] In some embodiments, a system may group users into different groups for analysis. For example, the system may separate users into symptomatic, asymptomatic, and community reserve groups. The system may perform different analysis and/or procedures for each of the groups. For example, the system may determine to provide medical intervention to the users in the symptomatic group and/or the asymptomatic group for the disease in some embodiments, whereas the system may determine that the users in the community reserve group are not to receive medical intervention. In some embodiments, the system may utilize different symptomology models for the symptomatic group, the asymptomatic group, and/or the community reserve group to determine whether the users within the groups are to receive medical intervention for the disease. Examples are provided below. Further, the system may request updates more frequently from some groups (such as the symptomatic group) than from other groups (such as the asymptomatic group and/or the community reserve group) in order for the system to more closely monitor individuals that may be at higher risk of complications or health issues from the disease.

[0132] FIG. 4 illustrates an example system flow 400 for grouping users in accordance with some embodiments. In particular, the system flow 400 illustrates example operations for grouping users of the system. The system may group users into a symptomatic group, an asymptomatic group, and a community reserve group in some embodiments.

[0133] In 402, the system may obtain information for users via an application. For example, the system may include a mobile application, a web application, an informational website, or some combination thereof that the system utilizes to obtain information for users. The system may obtain the information from a mobile device of the user (such as via as mobile application on the mobile device of the user), a wearable device of the user, a web application, and/or an informational website in 404. The system may further access social media (such as via one or more social media platforms) associated with a user in 406 and extract information for the user from the social media related to the disease, symptoms of the user, geographic information for the user, demographic information for the user, social determinants for the user, or some combination thereof. The system may further obtain information for users from one or more partner sites in 408. In some embodiments, the partner sites may include sites of healthcare providers, where the system may access information stored by the healthcare providers via the partner sites. The system may store the information associated with the users.

[0134] In 410, the system may determine whether the users have symptoms. For example, the system may analyze the information obtained via the application in 402 and determine whether users symptomatic for the disease based on the information. In some embodiments, the system may apply a symptomology model (such as the symptomology model utilized in 110 (FIG. 1) and/or the symptomology model utilized in 216 (FIG. 2)) to determine whether a user is symptomatic. For example, the system may have a predefined threshold infection probability score or may have determined a threshold infection probability score based on previously captured information. The system may compare an infection probability score for a user produced by the symptomology model with the threshold infection probability score to determine whether the user is symptomatic. The system may determine that the user is symptomatic based on the infection probability score for the user being greater than or equal to the threshold infection probability score. Further, the system may determine that the user is not symptomatic based on the infection probability score for the user being less than the threshold infection probability score. In other embodiments, the system may determine the user to be symptomatic based on the user displaying certain symptoms related to the disease, a certain number of symptoms related to the disease, or some combination thereof. If the system determines that the user is symptomatic, the system may assign the user to a symptomatic group 412.

[0135] In 414, if the system determines that the user is not presenting symptoms, the system may determine whether to assign the user to an asymptomatic group 416 or a community reserve group 418. In some embodiments, the system causes medical intervention to be provided to users within the asymptomatic group 416, whereas the system does not cause medical intervention to be provided to users within the community reserve group 418. The system may randomly select users from the users not presenting symptoms to assign to each of the asymptomatic group 416 and the community reserve group 418. In other embodiments, the system may assign the users to the asymptomatic group 416 and the community reserve group 418 based on the information associated with the users. For example, the system may apply a symptomology model (or use the infection probability score from the symptomology model in 410) to produce an infection probability score for the user. The system may compare the infection probability score with a threshold infection probability score to determine whether the user is to be assigned to the asymptomatic group 416 or the community reserve group 418. The threshold infection probability score may be lower than the threshold infection probability score used in 410. The threshold infection probability score may be predefined or determined by the system based on information previously obtained by the system. The system may assign the users with infection probability scores that are greater than or equal to the threshold infection probability score to the asymptomatic group 416, whereas the system may assign the users with infection probability scores less than the threshold infection probability score to the community reserve group 418. In some embodiments, the system may adapt the threshold infection probability score and/or the symptomology model to have the asymptomatic group 416 include a maximum number of users. The maximum number of users may be predefined or the system may determine the maximum number of users based on an amount of available test kits and/or vaccines for users within the asymptomatic group 416.

III. INFORMATION SOURCE ARRANGEMENT

[0136] A system may gather information from one or more sources for users to determine whether each of the users is to receive medical intervention for a disease. For example, the system may be coupled to a plurality of sources, where the system may receive information from one or more of the sources. The system may store the received information in a database of the system.

[0137] FIG. 5 illustrates an example computer system arrangement 500 in accordance with some embodiments. For example, the computer system arrangement 500 may include a computer system 502 that may perform one more of the operations described herein. For example, the computer system 502 may perform the system flow 100 (FIGs. 1A and IB), the system flow 200 (FIGs. 2A and 2B), the system flow 300 (FIGs. 3 A, 3B, and 3C), the system flow 400 (FIG. 4), the procedure 700 (FIG. 7), the procedure 800 (FIG. 8), the procedure 900 (FIG. 9), or some combination thereof.

[0138] The computer system 502 may implement one or more websites and/or may be coupled to one or more other systems (such as computer systems, servers, wearable devices, mobile devices, or other computer devices) for gathering information regarding users of the computer system 502. For example, the computer system 502 implements an information website 506 in the illustrated embodiment. The informational website 506 may include one or more of the features of the informational website of block 102 (FIG. 1A), the informational website 202 (FIG. 2A), and/or the informational website 312 (FIG. 3 A). Individuals may access the informational website 506 and sign up to be users of the computer system 502. The computer system 502 may present queries to the users via the informational website 506 to gather information from the users. The information may include any of the information of users described throughout this disclosure (such symptom information, infection results, environmental information, demographic information, exposure information, testing information, vaccination status, social determinants, weight, body mass index, body fat, temperature, heart rate, respiratory rate, pulse oximetry (oxygen saturation), physiological activity/ exercise, visual inputs and/or sound inputs). The computer system 502 may store the information in one or more databases 504 of the computer system 502. The databases 504 may be located within the computer system 502, remote to the computer system 502, or some combination thereof.

[0139] The computer system 502 is coupled to one or more partner servers 508 and one or more medical provider servers 510 in the illustrated embodiment. For example, the partner servers 508 may correspond to partner sites that may gather information for users and the medical provider servers 510 may correspond to medical providers that store information for users. The partner servers 508 and the medical provider servers 510 each may include one or more databases that stores the information for the users. The computer system 502 may retrieve information for one or more users from the partner servers 508 and/or the medical provider servers 510. For example, the computer system 502 may query the partner servers 508 and/or the medical provider servers 510 for information of a user based on the user signing up with the computer system 502 via the informational website 506. In some embodiments, the informational website 506 may present an authorization inquiry to the user to obtain authorization from the user to retrieve information of the user from the partner servers 508 and/or the medical provider servers 510. The computer system 502 may store the information retrieved from the partner servers 508 and/or medical provider servers 510 in the databases 504 of the computer system 502.

[0140] Further, the computer system 502 is coupled to one or more wearable devices 512 and mobile devices 514 in the illustrated embodiments. In particular, the computer system 502 may be coupled to wearable devices 512 and/or mobile devices 514 associated with the users and may retrieve information from the wearable devices 512 and/or mobile devices 514. In some embodiments, the informational website 506 may present an enrollment inquiry to the user such that the user can enroll the wearable devices 512 and/or mobile devices 514 with the computer system 502, thereby allowing the computer system 502 to couple to and receive information from the wearable devices 512 and/or the mobile devices 514. The computer system 502 may store the information received from the wearable devices 512 and/or the mobile devices 514 in the database 504.

IV. SYMPTOMOLOGY MODEL GENERATION

[0141] The system may generate a symptomology model for determining whether users are to receive medical intervention. For example, the system may utilize machine learning to produce a symptomology model. The machine learning may utilize infection results and information for users to produce the symptomology model.

[0142] FIG. 6 illustrates an example machine learning model 600 in accordance with some embodiments. In particular, a computer system (such as the computer system 502 (FIG. 5)) may utilize the machine learning model 600 for generating and/or adapting one or more symptomology models as described throughout the disclosure.

[0143] The machine learning model 600 may include a training set 602. The training set 602 may include information for one or more users and infection results for the one or more users. In some embodiments, the system may have previously collected the information and the infection results from one or more sources (such as the informational website 506 (FIG. 5), the partner servers 508 (FIG. 5), the medical provider servers 510 (FIG. 5), the wearable devices 512 (FIG. 5), and/or the mobile devices 514 (FIG. 5)) and stored the information the infection results within a database (such as the database 504 (FIG. 5)). The system may retrieve the information and the infection results from the database and generate the training set 602 from the information and the infection results. In particular, the training set 602 may include information and corresponding training results retrieved from the database. The system may generate the training set 602 once the system has information and corresponding infection results for a predefined number of users. The system may store the generated training set 602 in the database. In other embodiments, an operator of the system may provide the training set 602 to the system and the system may store the training set 602 provided by the operator in the database. [0144] The machine learning model 600 may further include a learning module 604 and a symptomology model 606. The learning module 604 may utilize the training set 602 to perform training of the symptomology model 606. For example, the system may execute the learning module 604 to optimize parameters of the symptomology model 606 such that a quality metric (for example, accuracy of the symptomology model 606) is achieved with one or more criteria (such as a number of users that can receive medical intervention based on budget, stock of resources (such as tests, vaccines and/or drugs) for medical intervention, or other factors that can define a number of users that can receive medical intervention). The parameters of the symptomology model 606 may be iteratively varied to increase the accuracy.

[0145] In some embodiments of training, a gradient may be determined for how varying the parameters affects an amount of tests and/or vaccines to be provided, which can provide a measure of how accurate the current state of the machine learning model is. The gradient can be used in conjunction with a learning step (e.g., a measure of how much the parameters of the model should be updated for a given time step of the optimization process). The parameters (which can include weights, matrix transformations, and probability distributions) can thus be optimized to provide a set number of tests and/or vaccines to be provided. In other embodiments, training can be implemented with methods that do not require a hessian or gradient calculation, such as dynamic programming or evolutionary algorithms.

[0146] The machine learning model 600 may further receive user information 608 for another user. For example, the system operating the machine learning model 600 may receive the user information 608 from one of the sources and store the user information 608 in the database. The system may apply the trained symptomology model 606 to the user information 608 to produce a user classification 610 for the other user. The user classification 610 may indicate whether the other user is to receive medical intervention for a disease.

[0147] In instances where the user classification 610 indicates that a user is to be tested, a test may be provided to the user in accordance with the approaches described throughout this disclosure. The user may provide user infection results 612 to the system. The system may execute the learning module 604 with the user information 608 and the user infection results 612 to adapt the symptomology model 606. In particular, the system may adapt the previously generated symptomology model 606 based on the user information 608 and the user infection results 612. For example, the system may adapt the previously generated symptomology model 606 by comparing the user classification 610 with the user infection results 612 to determine whether the user classification 610 and the user infection results 612 match. Depending on whether the user classification 610 and the user infection results 612 match, the system may adapt the symptomology model 606 to improve the user classification 610 produced by the symptomology model 606 and/or increment the training set 602 in a iterative and continuously improving approach. The system may adapt the symptomology model 606 with each newly received user infection result, at set time intervals, at set intervals of newly received user infection results, or some combination thereof.

[0148] Examples of machine learning models include deep learning models, neural networks (e.g., deep learning neural networks), kernel-based regressions, adaptive basis regression or classification, Bayesian methods, ensemble methods, logistic regression and extensions, Gaussian processes, support vector machines (SVMs), a probabilistic model, and a probabilistic graphical model. Embodiments using neural networks can employ using wide and tensorized deep architectures, convolutional layers, dropout, various neural activations, and regularization steps. One or more of the symptomology models described throughout may be produced via the machine learning model 600.

V. SYMPTOMOLOGY MODEL ADAPTATION

[0149] The system may utilize a symptomology model for determination of which users are to receive medical intervention for the disease. As additional information is provided by users, the system may adapt the symptomology model based on the additional information. The additional information can be from updates of current users of the system or new users of the system.

[0150] FIG. 7 illustrates an example procedure 700 for analyzing users in accordance with some embodiments. For example, the system may perform the procedure 700 to produce a symptomology model for determining whether a user is to receive medical intervention for the disease. The procedure 700 may be performed in combination with the system flow 100 (Figs. 1 A and IB), the system flow 200 (Figs. 2A and 2B), the system flow 300 (Figs. 3 A and 3B), and/or the system flow 4 (FIG. 4). For example, the procedure 700, or portions thereof, may be utilized for generating the symptomology models utilized in the system flows, determining the users to receive medical intervention in the system flows, updating symptomology models utilized in the system flows, or some combination thereof.

[0151] At block 702, information can be retrieved for one or more users. For example, the system may retrieve information for one or more users via an informational website (such as the informational website of block 102 (FIG. 1A), the informational website of 202 (FIG. 2A), and/or the informational website of 312 (FIG. 3 A)), via an application (such as the application of 402 (FIG. 4)), from partner sites, from social media, from a mobile device of the user, a wearable of the user, from a web application, from a server associated with a healthcare provider or healthcare information storage service, from a memory of the system, or some combination thereof. The retrieved information may be stored in one or more databases (such as the database 504 (FIG. 5)) and may be retrieved from the databases for use. The information retrieved by the system may include symptom information of the users, infection results of the disease for the users, environmental information of the users, demographic information of the users, exposure information of the users, testing information of the users, vaccination status of the users, social determinants (such as familial relationships, social relationships, and/or other physical contact relationships) of the users, weight information of the users, body mass index information of the users, body fat information of the users, temperature information of the users, heart rate information of the users, respiratory rate information of the users, pulse oximetry (oxygen saturation) information of the users, physiological activity/exercise information of the users, visual information for the users, sound information for the users, or some combination thereof.

[0152] At block 704, one or more symptomology models may be generated. In particular, the system may analyze the information retrieved in 702 to identify trends in information for users with positive infection results for the disease and trends in information for users with negative infection results for the disease, and may generate the one or more symptomology models based on the trends. For example, the system may identify users with positive infection results for the disease and users with negative infection results for the disease based on the retrieved infection results from 702. The users may determine which symptoms are presented and which symptoms are not presented by the users with positive infection results and the users with negative infection results. The system may identify differences in the symptoms presented by the users with positive infection results and the users with negative infection results and may generate one or more symptomology models based on the differences in the symptoms. For example, the system may generate symptomology model that assigns weights to one or more symptoms displayed by the users, where the symptomology model produces an infection probability score for a user based at least in part on symptoms presented by the user. The system may assign larger weighting values for symptoms that are presented by the users with positive infection results and that are not presented by the users with negative infection results, whereas the system may assign smaller weighting values for symptoms that are presented by both or neither of the users with positive infection results and the users with negative infection results. In some embodiments, the symptomology model may comprise an algorithm where the weightings for each of the symptoms provide weighting to the corresponding symptom in the algorithm.

[0153] Generating the one or more symptomology models may include determining a threshold infection probability score. In some embodiments, the threshold infection probability score may be predefined and determining the threshold infection probability score may comprise identifying, by the system, the predefined threshold infection probability score. In other embodiments, the system may generate the threshold infection probability score based at least in part on the symptom information for the users for determining the threshold infection probability score. The system may further generate the threshold infection probability score based on an amount of users that are intended to be tested and/or vaccinated. For example, the system may determine a number of resources for medical intervention available and generate the threshold infection probability score to be a value that is predicted to cause the system to determine a number of users to be tested to be equal to or less than the number of resources available.

[0154] In some embodiments, the system may further take into consideration the environmental information of the users, the demographic information of the users, the exposure information of the users, the vaccination status of the users, the social determinants of the users, weight information of the users, body mass index information of the users, body fat information of the users, temperature information of the users, heart rate information of the users, respiratory rate information of the users, pulse oximetry (oxygen saturation) information of the users, physiological activity/exercise information of the users, visual information for the users, sound information for the users, or some combination thereof. For example, the system may define different groups of users (such as different groups based on locations of the users, demographics of the users, exposure information of the users, vaccination status of the users, the social determinants of the users, weight information of the users, body mass index information of the users, body fat information of the users, temperature information of the users, heart rate information of the users, respiratory rate information of the users, pulse oximetry (oxygen saturation) information of the users, physiological activity/exercise information of the users, visual information for the users and/or sound information for the users) and may generate different symptomology models for the different groups based on the symptoms of the users within each of the groups. In other instances, the system may generate different threshold infection probability scores for different groups of users based on the locations of the user, the demographics of the users, exposure information of the users, vaccination status of the users, the social determinants of the users, weight information of the users, body mass index information of the users, body fat information of the users, temperature information of the users, heart rate information of the users, respiratory rate information of the users, pulse oximetry (oxygen saturation) information of the users, physiological activity/exercise information of the users, visual information for the users and/or sound information for the users. In some embodiments, the system may include the locations of the users, demographics of the users, exposure information of the users, vaccination status of the users, the social determinants of the users, weight information of the users, body mass index information of the users, body fat information of the users, temperature information of the users, heart rate information of the users, respiratory rate information of the users, pulse oximetry (oxygen saturation) information of the users, physiological activity/exercise information of the users, visual information for the users and/or sound information for the users as part of the symptomology model with corresponding weightings for the factors determined based on the differences between the users with positive infection results and the users with negative infection results.

[0155] At block 706, information for another user may be received. In particular, the system may receive information for a new user to the system, or updated information for another user that has previously provided information to the system. The system may receive the information via the informational website, from the partner sites, from social media, from a mobile device of the user, a wearable of the user, from the web application, from a server associated with a healthcare provider or healthcare information storage service, or some combination thereof. In some instances, the system may receive the information from one or more databases associated with the informational website, the partner sites, social media, the mobile device of the user, the wearable device of the user, the web application, and/or the server associated with the healthcare provider or healthcare information storage service. The information may include symptom information of the user, environmental information of the user, demographic information of the user, exposure information of the user, testing information of the user, vaccination status of the user, social determinants of the user, weight information of the user, body mass index information of the user, body fat information of the user, temperature information of the user, heart rate information of the user, respiratory rate information of the user, pulse oximetry (oxygen saturation) information of the user, physiological activity/exercise information of the user, visual information for the user, sound information for the user, or some combination thereof.

[0156] At block 708, an infection probability score for the user may be determined. In particular, the system may determine an infection probability score for the user based on the information retrieved in 702. The system may apply a symptomology model, from the one or more symptomology models generated in 704, to the information for the user to produce an infection probability score for the user. For example, the system may apply the weightings included in the symptomology model to whichever of the symptom information of the user, the environmental information of the user, the demographic information of the user, the exposure information of the user, the demographic information of the user, the exposure information of the user, the vaccination status of the user, the social determinant of the user, weight information of the user, body mass index information of the user, body fat information of the user, temperature information of the user, heart rate information of the user, respiratory rate information of the user, pulse oximetry (oxygen saturation) information of the user, physiological activity/exercise information of the user, visual information for the user, and/or sound information for the user are included in the symptomology model to produce the infection probability score.

[0157] At block 710, whether the user is to receive medical intervention for the disease may be determined. In particular, the system may determine whether the user is to receive medical intervention for the disease based on the infection probability score for the user determined in 708. The system may compare the infection probability score for the user with a threshold infection probability score, from the one or more threshold infection probability scores determined in 704, to determine whether the user is to receive medical intervention. The system may determine that the user is to be receive medical intervention based on the infection probability score for the user being greater than or equal to the threshold infection probability score, and may determine that the user is not to receive medical intervention based on the infection probability score for the user being less than the threshold infection probability score. [0158] At block 712, an indication to the user whether the user is to receive medical intervention for the disease may be provided. In particular, the system may provide an indication to the user whether the user is to receive medical intervention for the disease based on the determination whether the user is to receive medical intervention for the disease in

710. In some embodiments, the indication may comprise a push notification. For example, the system may provide the push notification via a web interface, email, short message service (SMS), or other means of providing a push notification. The system may cause the indication to be displayed via the informational website, via the mobile device of the user, via the wearable of the user, via the web application, or some combination thereof to provide the indication to the user. The system may further cause a phone call (either via an automated phone call or providing an indication to an operator of the system) to be placed to the user to indicate whether the user is to receive medical intervention, cause mail (either via automated electronic mail, automated physical mail, or providing an indication to an operator of the system) to be sent to the user to indicate whether the user is to receive medical intervention, or some combination thereof.

[0159] Based on the system determining that the user is not to receive medical intervention in 710, the procedure 700 may proceed from 712 to 714. At block 714, the information for user may be stored. In particular, the system may store the information with association to the user. In some embodiments, the information may be separated into multiple portions, where each of the portions are stored in different locations. For example, the system may store the portions of the information in separate tables and/or in separate databases. In some embodiments, the user may be placed into a lottery (such as the lottery 112 (FIG. 1A) and/or the lottery 220 (FIG. 2A)), where the user may be selected from the lottery at a later time to receive medical intervention for the disease. In some of these embodiments, the system may allow the user to update the information for the user stored by the system. The information for the user may be retrieved at a later time for use in operations associated with the user, such as determining whether the user is to receive medical intervention for the disease at a later time and/or adapting the symptomology model based on the user.

[0160] Based on the system determining that the user is to be tested in 710, the procedure 700 may proceed from 712 to 716. At block 716, a test kit may be provided to the user may. For example, the system may cause a test kit to be provided to the user, and/or may indicate where the user may obtain a test kit and/or be tested. The system may perform the operations 118 (FIG. IB), 120 (FIG. IB), and 122 (FIG. IB), or the operations 230 (FIG. 2B), 234 (FIG. 2B), and 236 (FIG. 2B) to cause the test kit to be provided to the user in some embodiments.

[0161] In embodiments where the system indicates where the user may obtain a test kit, the system may access websites and/or servers of merchant locations within a certain proximity of the user to determine a stock of test kits that each of the merchant locations have available. The system may provide an indication of one or more merchant locations within the certain proximity of the user that have tests available. The indication may comprise a push notification in some embodiments. For example, the system may provide the push notification via a web interface, email, short message service (SMS), or other means of providing a push notification. The indication of the merchant locations may include a name of the merchant, an address of the merchant location, contact information for the merchant location, or some combination thereof. In some embodiments, the user may indicate which merchant location from which they intend to obtain a test kit and the system may take the indication of the merchant location from the user into account when providing indications to other users of where to obtain test kits.

[0162] In embodiments where the system indicates where the user may be tested, the system may access websites and/or servers of locations administering the tests for the disease to determine the availability of testing services at the location. For example, the system may determine whether the location has tests available, times that the location is administering the tests, available times within a schedule for the location, or some combination thereof. In instances where a location schedules times for administering the test, the system may allow the user to select an available time to have the test administered and may schedule the time with the location to have the user tested.

[0163] If a user is determined to be vaccinated based on the analysis in 710, the user may be offered a vaccine for the disease at block 716. In particular, the system may present an indication to the user that the user is to be vaccinated for the disease. The indication may comprise a push notification in some embodiments. For example, the system may provide the push notification via a web interface, email, short message service (SMS), or other means of providing a push notification. The indication may include an indication of locations that the user may go to be vaccinated for the disease and/or locations that the user may go to obtain a self- vaccination kit. The system may access the websites and/or servers of locations administering vaccines for the disease to determine the availability of vaccination services at the location, and/or may access the websites and/or servers of locations that stock the selfvaccination kits to determine the availability of self-vaccination kits at the location. For example, the system may determine whether the location has vaccines available, times that the location is administering the vaccines, available times within a schedule for the locations, whether the location has self-vaccination kits available, or some combination thereof. In instances where a location schedules times for administering the vaccines, the system may allow the user to select an available time to have the vaccine administered and may schedule the time with the location to have the user vaccinated. In some embodiments, once the user has been vaccinated or scheduled for vaccination, the user may be removed from consideration for being tested and/or vaccinated.

[0164] If a user is determined to receive another medical intervention in 710, the user may be offered the medical intervention for the disease at 716. In particular, the system may present an indication to the user that the user is to receive the medical intervention for the disease. The indication may comprise a push notification in some embodiments. For example, the system may provide the push notification via a web interface, email, short message service (SMS), or other means of providing a push notification. The indication may include an indication of locations that the user may go to receive the medical intervention for the disease. The system may access the websites and/or servers of locations administering the medical intervention for the disease to determine the availability of the medical intervention services at the location. For example, the system may determine whether the location has resources for the medical intervention available, times that the medical intervention is being administering, available times within a schedule for the locations, or some combination thereof. In instances where a location schedules times for administering the medical intervention, the system may allow the user to select an available time to have the medical intervention administered and may schedule the time with the location to have the user receive the medical intervention.

[0165] In some instances, 716 may be omitted. For example, a test kit or selfvaccination kit may have been previously provided to the user or the user may have previously obtained a test kit or self-vaccination kit. In these instances, the system may receive an indication from the user in response to 712 that indicates that the user has a test kit or self-vaccination kit. As the user already has a test kit or self-vaccination kit in these instances, the system may determine that a test kit or self- vaccination kit does not need to be provided to the user and may omit providing the test kit or self-vaccination kit to the user in 716.

[0166] At block 718, an infection result from the user may be received. In particular, the system may receive an indication of an infection result that indicates whether the user tested positive for the disease from the user. The system may receive the indication of the infection result via the informational website, from the partner sites, from a mobile device of the user, the wearable of the user, from the web application, from a server associated with a healthcare provider or healthcare information storage service, or some combination thereof. The infection result may indicate that the user tested positive for the disease, the user tested negative for the disease, or the testing was inconclusive. In the instance when the testing provided inconclusive results, the system may determine whether to provide the user with another test kit in accordance with 716 and/or indicate to the user that the user is to be tested in accordance with 712. The system may determine whether to provide another test kit to the user and/or provide the indication to be tested to the user based on an infection probability score for the user and/or a number of test kits available.

[0167] At block 720, the symptomology model may be adapted. For example, the system may adapt the symptomology model applied in 710 based on the information of the user and the infection result for the user. In some embodiments, the system may increase or decrease one or more of the weightings of the symptomology model. For example, if the user tests positive for the disease, the weightings of the factors (such as symptoms, environmental factors, demographic factors, exposure factors, vaccination status, social determinant factors, weight information, body mass index information, body fat information, temperature information, heart rate information, respiratory rate information, pulse oximetry (oxygen saturation) information, physiological activity/ exercise information, visual information, and/or sound information) of the symptomology model that correspond to the factors presented by the user may be increased, and the weightings of the factors corresponding to factors not presented by the user may be decreased in some instances. If the user tests negative for the disease, the weightings of the factors of the symptomology models that correspond to the factors presented by the user may be decreased. The adapted symptomology model may be utilized for determining whether further users are to be tested for the disease. In other embodiments, the symptomology model may be adapted at defined time intervals, once a certain number of users have provided infection results since the symptomology model was generated or last adapted, or some combination thereof. VI. RESOURCES FOR MEDICAL INTERVENTION DISTRIBUTION

[0168] In order to provide medical intervention to users for the disease, it is important that the resources for the medical intervention are provided to the proper locations for providing medical intervention to the users. Often providing resources to the locations can be inefficient and expensive. The system may utilize information for users to determine efficient and/or cost-effective approaches for distribution of the resources.

[0169] FIG. 8 illustrates an example procedure 800 for distributing resources for medical intervention in accordance with some embodiments. In particular, the system may perform the procedure 800 to distribute resources for the medical intervention. The system performing the procedure 800 to distribute resources may allow for resources to be distributed to certain locations prior to the need for the resources within geographic regions of the locations, thereby allowing to avoid rush delivery of the resources which can save money.

[0170] At block 802, information for one or more users may be retrieved. For example, the system may retrieve information for one or more users via an informational website (such as the informational website of block 102 (FIG. 1A), the informational website of 202 (FIG. 2A), and/or the informational website of 312 (FIG. 3 A)), via an application (such as the application of 402 (FIG. 4)), from partner sites, from social media, from a mobile device of the user, from a wearable of the user, from a web application, from a server associated with a healthcare provider or healthcare information storage service, from a memory of the system, or some combination thereof. In some instances, the system may retrieve the information from one or more databases associated with the informational website, the application, the partner sites, social media, the mobile device of the user, the wearable of the user, the web application, and/or the server associated with the healthcare provider or healthcare information storage service. The information retrieved by the system may include symptom information of the users, infection results of the disease for the users, environmental information of the users, demographic information of the users, exposure information of the users, testing information of the users, vaccination status of the users, social determinants of the users, weight information of the users, body mass index information of the users, body fat information of the users, temperature information of the users, heart rate information of the users, respiratory rate information of the users, pulse oximetry (oxygen saturation) information of the users, physiological activity/exercise information of the users, visual (photographic or imaging) information for the users, sound (recording, as of cough or other vocalizations) inputs from the users, or some combination thereof.

[0171] At block 804, geographic regions with high infection probability may be determined. In particular, the system may analyze the information retrieved in 802 and determine geographic regions that present high infection probability. The system may identify geographic regions associated with each of the users for which the information was retrieved in 802 and assign the users to different geographic regions. The geographic regions into which the users are assigned may be predefined by an operator of the system, or may be determined by the system based on locations to which the resources can be distributed, a number of people in each of the geographic regions, a number of users in each of the geographic regions, locations of distribution centers for the resources, distribution logistics for each of the geographic regions, or some combination thereof.

[0172] The system may determine an infection probability for each of the geographic regions. For example, the system may analyze the information associated with the users in each of the geographic regions and determine, based on the information, an infection probability score for the region. In some embodiments, the system may determine when each of the users that tested positive within a geographic region and determine trends in the number of users testing positive versus time. If the system determines that the number of users testing positive within the geographic region is trending toward an increase in the number of users testing positive, the system may determine that the geographic region presents a high infection probability. The system may determine that the geographic region presents a high infection probability if the increase in the number of users exceeds a certain rate, where the certain rate may be predefined or may be determined by the system based on a population within the geographic region, a number of users within the geographic region that have not tested positive for the disease, a number of users within the geographic region that have not been tested within a certain period of time, or some combination thereof.

[0173] In some embodiments, the system may analyze a portion of the information related to the users that tested positive in the geographic region to determine whether the users that tested positive presented a high infection probability to users that tested negative or have not been tested in the geographic region. For example, the system may analyze the information of a user that tested positive to determine how many individuals that the user that tested positive came into contact with. The system may base the determination of how many individuals the user that tested positive came into contact with on an employment situation of the user, transportation utilized by the user, contact tracing (if the user and/or individuals have consented to contact tracing), locations where the user has visited, a living situation of the user (for example, does the user live alone, live with other individuals, live in a single family home or an apartment complex, and/or other living situations), relationships between the user and the individuals, or some combination thereof. The system may determine that the geographic region presents a high infection probability if the system determines that the users that have tested positive came into contact with a high number of users. In some embodiments, the number of users that constitute the high number of users may be predefined or may be determined by the system based on a population within the geographic region, a number of users within the geographic region that have not tested positive for the disease, a number of users within the geographic region that have not been tested within a certain period of time, or some combination thereof.

[0174] Tn some embodiments, the system may determine based on a symptomology model (such as the symptomology model utilized in 110 (FIG. 1), the symptomology model utilized in 216 (FIG. 2), and/or the symptomology models of the procedure 700 (FIG. 7)). For example, the system may analyze the information for users within the geographic region and determine how many of the users that have not tested positive or have not been tested within a certain period of time have infection probability scores above a threshold infection probability score. The threshold infection probability score may be a same threshold infection probability score for determining whether a user is to receive medical intervention within the geographic region or may have a lower value than the threshold infection probability score for determining whether a user is to receive medical intervention. The system may determine whether the number of users that have infection probability scores above the threshold infection probability score exceeds a certain number of users, where the system may determine that the geographic region presents a high infection probability based on the number of users with the probability infection scores exceeding the certain number of user. The certain number of users may be predefined or may be defined by the system based on a population within the geographic region, a number of users within the geographic region that have not tested positive for the disease, a number of users within the geographic region that have not been tested within a certain period of time, or some combination thereof.

[0175] In some embodiments, the geographic regions may be dynamically defined by the system. For example, the system may analyze the infection probability for the users and then define a geographic region of a defined size, that includes a defined population size, or some combination thereof, based on the infection probability for a group of users within the geographic region. The system may define a geographic region based on a number of users within the geographic region having infection probability scores that exceed a threshold infection probability score being greater than a certain number of users. The certain number of users may be predefined or may be determined by the system based on information associated with one or more geographic regions.

[0176] In some embodiments, the geographic regions may be defined based on census tracks. For example, the system may determine census tracks (such as by accessing a site or a server to retrieve indications of the census tracks) and set the geographic regions to the census tracks. The census tracks may be geographic areas defined to be utilized for performing censuses of a certain area or population.

[0177] At block 806, a number of available resources for distribution may be determined. For example, the system may retrieve information regarding a number of available resources and determine a number of resources that are available for distribution based on the information. Retrieving the information regarding the number of available resources may include accessing websites and/or servers of distribution centers of the resources to determine how many resources the distribution centers have in stock. In some embodiments, the system may access websites and/or servers of resource manufacturers, as part of the retrieving information, to determine a number of resources that the manufacturers have in stock and/or the number of resources that the manufacturer is expected to produce in a period of time, where the system may determine when the resources from the manufacturers are expected to be delivered to the distribution centers for distribution. Further, the system may identify resources that were previously distributed that may be redistributed to other locations, as part of the retrieving information, in some embodiments, such as where the resources were distributed to a geographic region that currently presents a small infection probability and/or the number of resources within a geographic region exceeds a number of individuals expected to receive medical intervention within the geographic region within a certain period of time. The system may determine the number of available resources to be the total number of resources determined from the information.

[0178] At block 808, a number of resources to be distributed to the geographic regions may be determined. In particular, the system may determine numbers of resources to be distributed to each of the geographic regions with high infection probability determined in 804. The system may determine the number of resources to be distributed to each of the geographic regions based on the number of available resources for distribution determined in 806. For example, the system may determine a desired number of resources to be distributed to each of the geographic region. The desired number of resources may be equal to a number of individuals within the geographic region that have not provided information to the system of being tested for the disease within a certain period of time, a number of users of the system within the geographic region that have not been provided a test kit within a certain period of time, a population of the geographic region, a percentage of the population of the geographic region, a percentage of individuals within the geographic region that have not provided information to the system of being tested for the disease within a certain period of time, a percentage of users within the geographic region that have not been provided a test kit with a certain period of time, or some combination thereof. The system may compare the number of available resources for distribution with the desired number of resources for the geographic regions. If the system determines that the number of available resources for distribution is greater than or equal to the desired number of resources for the geographic regions, the system may determine that the desired number of resources are to be distributed to the each of the geographic regions.

[0179] If the system determines that the number of available resources for distribution is less than the desired number of resources for the geographic regions, the system may apportion the available resources for distribution between the geographic regions. In some instances, the system may determine that the available resources are to be distributed to the geographic regions with the highest infection probabilities and may determine to put off distributing resources to the geographic regions with the lower infection probabilities until additional resources are available for distribution. In other instances, the system may determine that the resources are to be equally distributed between the geographic regions, where the system may determine to distribute the same number of resources to each of the geographic regions. In other instances, the system may determine the number of resources to be distributed to each of the geographic regions based on the number of available resources, a number of individuals within each of the geographic regions that have not provided information to the system of being tested for the disease within a certain period of time, a number of users of the system within each of the geographic region that have not been provided a test kit within a certain period of time, a population of each of the geographic regions, a percentage of the population of each of the geographic regions, a percentage of individuals within each of the geographic regions that have not provided information to the system of being tested for the disease within a certain period of time, a percentage of users within each of the geographic regions that have not been provided a test kit with a certain period of time, infection probabilities for each of the geographic regions, or some combination thereof.

[0180] In some embodiments, the system may determine the number of available resources for distribution and/or the number of resources to be distributed to each of the geographic regions based on a location of the available resources and locations of the geographic regions. For example, if the available resources for distribution are located within a different country or continent than the geographic region, the system may determine that the available resources for distribution with the different country or continent are not available for the geographic region. The system may take into account the distance between the locations of the available resources and the locations of the geographic regions in determining to which geographic regions to distribute the resources. For example, the system may provide a weighting to the geographic regions located closer to the location of the resources than other geographic regions located further away, where the weighting may result in the closer geographic regions being provided more resources than if the locations were not taken into account. The system may further take into account the cost of distributing the resources to the geographic regions (which may be a cost based on a time that the resources are desired to arrive at the geographic regions) and provide a weighting to the geographic regions that cost less to distribute the resources.

[0181] At block 810, locations to deliver the resources within the geographic regions may be determined. For example, the system may determine locations within the geographic regions to which the resources are to be distributed. The system may identify merchants that carry the resources, healthcare providers that carry the resources, healthcare providers that administer the medical interventions with the resources, healthcare providers that administer the medical interventions, resource distribution locations that distribute the resources to individuals, other locations that may temporarily or permanently distribute the resources and/or administer the medical interventions, or some combination thereof as locations within each of the geographic regions. The system may access websites and/or servers of the locations to determine the current stock of the locations. Further, the system may access websites and/or servers of carriers to determine the cost of delivery of resources to each of the locations. The system may determine how many resources are to be delivered to each of the locations within the geographic regions based on the stock of the resources at each of the locations, the cost of delivery of the resources to each of the locations, or some combination thereof. In some embodiments, the system may take into account relationships and/or agreements with the particular locations in determining which locations to distribute the resources, where the distribution of the resources may be distributed to meet any relationships and/or agreements with the particular locations.

[0182] In some embodiments, an operator of the system may provide goals and/or parameters to the system for determining which locations to distribute the resources. For example, the operator may indicate that the system is to distribute the resources in a most cost effective manner. Based on the indication that the system is to distribute the resources in a most cost effective manner, the system may select locations that will cost the least for distribution of the resources. In other instances, the operator may indicate that the resources must be distributed to the locations by a particular date. Based on the indication that the resources must be distributed to the locations by the particular date, the system may select locations where it is possible to deliver the resources by the particular date.

[0183] At block 812, a delivery method for the resources may be determined. In particular, the system may determine carriers and/or delivery options for the resources to the locations determined in 810. The system may access websites and/or servers for one or more carriers and/or the locations to retrieve information about possible delivery methods for delivery of the resources to the locations. The system may utilize the information about the possible delivery methods to select delivery methods for the resources to each of the locations. The delivery method may include a carrier to deliver the resources, a delivery option (such as rushed delivery, ground delivery, air delivery, and/or transmit time for the delivery), a delivery service for the location (such as the location owning transports for transporting goods the location), or some combination thereof. The system may select the carriers and/or delivery options to achieve a goal and/or parameter, such as minimizing the cost of delivery of the resources, achieving a quickest delivery of the resources, meeting a delivery date for the resources, or some combination thereof.

[0184] At block 814, the resources may be distributed to the locations. In particular, the system may cause the resources to be distributed to the locations. For example, the system may utilize the websites and/or servers for the one or more carriers and/or the locations to schedule the delivery of the resources to the locations in accordance with the delivery methods determined in 812. In other instances, the system may display an indication to an operator of the system to schedule delivery of the resources to the locations. The indication provided by the system may include an indication of the delivery methods to be utilized for delivery of the resources to the locations. The system may further track the delivery of the resources via the websites and/or servers for the one or more carriers and/or the locations in some embodiments to verify that the resource have been delivered.

[0185] The system performing the procedure 800 may efficiently distribute the resources to geographic regions where having additional resources could be beneficial. Determining geographic regions to which resources are to be distributed and efficiently distributing the resources to the geographic regions have been a challenge that often ends up in inefficient, costly distribution of resources. The system performing the procedure 800 may address this challenge allowing for efficient distribution of the resources and/or less cost for distribution of the resources.

VII. USER RECRUITING

[0186] A challenge with every new product is getting users to use the product.

Further, the system may determine that additional information may useful for certain groups of the population. The system may initiate user recruiting for engaging the public and gathering additional information from certain groups of the population.

[0187] FIG. 9 illustrates an example procedure 900 for initiating user recruiting in accordance with some embodiments. In particular, a system may perform the procedure 900 for initiating user recruiting to elicit information related to a disease from individuals. The user recruiting may direct individuals to a means for providing the information to the system, such as an informational website for providing information to the system. The system may direct the user recruiting to particular individuals and/or particular groups of individual.

[0188] At block 902, information may be retrieved. In particular, the system may retrieve information for one or more users previously collected via an informational website (such as the informational website of block 102 (FIG. 1 A), the informational website of 202 (FIG. 2 A), and/or the informational website of 312 (FIG. 3 A)), via an application (such as the application of 402 (FIG. 4)), from partner sites, from social media, from a mobile device of the user, from a wearable device of the user, from a web application, from a server associated with a healthcare provider or healthcare information storage service, or some combination thereof. In some instances, the system may retrieve the information from one or more databases associated with the informational website, the application, the partner sites, social media, the mobile device of the user, the wearable device of the user, the web application, and/or the server associated with the healthcare provider or healthcare information storage service. The information may be stored in a memory of the system and the system may retrieve the information from the memory. In some embodiments, the information may be separated into multiple portions, where each of the portions are stored in different locations in the memory. For example, the system may store the portions of the information in separate tables and/or in separate databases in the memory. The information retrieved by the system may include symptom information of the users, infection results of the disease for the users, environmental information of the users, demographic information of the users, exposure information of the users, testing information of the users, vaccination status of the users, social determinants of the users, weight information of the users, body mass index information of the users, body fat information of the users, temperature information of the users, heart rate information of the users, respiratory rate information of the users, pulse oximetry (oxygen saturation) information of the users, physiological activity/exercise information of the users, visual (photographic or imaging) information for the users, sound (recording, as of cough or other vocalizations) information for the users, or some combination thereof.

[0189] At block 904, a target of the user recruiting may be determined. In particular, the system may analyze the information retrieved in 902 to determine a target for the user recruiting. For example, the system may analyze the information to determine any characteristics (such as geographic regions, demographics, social determinants, weight information, body mass index information, body fat information, temperature information, heart rate information, respiratory rate information, pulse oximetry (oxygen saturation) information, physiological activity/exercise information, visual information, sound information) for which information from additional users having the characteristics may be determined to be beneficial by the system. The system may determine that information from additional users may be beneficial based on the users having the characteristics being underrepresented in the current information, the users having the characteristics being determined to have a high probability of infection from the disease, or some combination thereof. The system may determine that the characteristic is underrepresented in the current information based on an amount of the users having the characteristic being below a threshold amount of users having the characteristic, an amount of the users having the characteristic not being representative of a portion of the population having the characteristic, an amount of users having the characteristic being less than the amounts of users having other comparable characteristics, or some combination thereof. The system may determine that individuals having the characteristic to be at a high probability of infection from the disease based on users having the characteristic for which information has already been collected presenting above average infection rates for the disease. The system may target individuals having the characteristic that is underrepresented or have a high probability of infection with the user recruiting.

[0190] At block 906, the media to be utilized for the user recruiting may be determined. For example, the system may select a media to be utilized for targeting the target determined in 904. The system may have a plurality of options of media that can be utilized for user recruiting to select from, where certain options may be better suited to individuals having certain characteristics. The options of media may include a means by which the media is delivered (such as via physical mail, electronic mail, video advertisements, print advertisements, sound advertisements, phone advertisements, and/or internet advertisements), what content is to be displayed, a language of the content to be displayed, a geographic area for which the media is to be displayed, or some combination thereof. The system may select media that is suited to the particular characteristic being targeted. For example, if the target is individuals that speak a certain language, the system may select the media to be of the specific language. Further, if the target is individuals residing within a certain geographic area, the system may select to have the media provided to the certain geographic area.

[0191] At block 908, the user recruiting may be initiated. In particular, the system may cause the media determined in 906 to be initiated. For example, the system may cause the media to be distributed in accordance with the determined media from 906. In some instances, the distribution of the media may be automated and the system may distribute the media. For example, the media may comprise pre-recorded advertisements and/or pre-defined mailings where the system may cause the pre-recorded advertisements to be displayed and/or cause the pre-defined mailings to be delivered. In other instances, the system may provide a notification to an operator to initiate the user recruiting. The notification may include an indication of the media that is to be displayed and/or delivered. The media being directed to the target determined in 904 may make it more likely that individuals targeted will respond than user recruiting that are not target to the individuals. Based on the user recruiting, the individuals may become users of the system and provide information related to the disease to the system.

VIII. COMPUTER SYSTEM

[0192] Any of the computer systems mentioned herein may utilize any suitable number of subsystems. Examples of such subsystems are shown in FIG. 10 in computer system 10. For example, the computer system 10 may perform one or more of the flows and/or procedures described throughout this disclosure, such as the system flow 100 (Figs. 1A and IB), the system flow 200 (Figs. 2A and 2B), the system flow 300 (Figs. 3A and 3B), the system flow 400 (FIG. 4), the procedure 700 (FIG. 7), the procedure 800 (FIG. 8), the procedure 900 (FIG. 9), or some combination thereof. In some embodiments, a computer system includes a single computer apparatus, where the subsystems can be the components of the computer apparatus. In other embodiments, a computer system can include multiple computer apparatuses, each being a subsystem, with internal components. A computer system can include desktop and laptop computers, distributed computer systems, servers, tablets, mobile phones and other mobile devices.

[0193] The subsystems shown in FIG. 10 are interconnected via a system bus 75. Additional subsystems such as a printer 74, keyboard 78, storage device(s) 79, monitor 76 (e.g., a display screen, such as an LED), which is coupled to display adapter 82, and others are shown. Peripherals and input/output (I/O) devices, which couple to I/O controller 71, can be connected to the computer system by any number of means known in the art such as input/output (I/O) port 77 (e.g., USB, FireWire®). For example, I/O port 77 or external interface 81 (e.g. Ethernet, Wi-Fi, etc.) can be used to connect computer system 10 to a wide area network such as the Internet, a mouse input device, or a scanner. The interconnection via system bus 75 allows the central processor 73 to communicate with each subsystem and to control the execution of a plurality of instructions from system memory 72 or the storage device(s) 79 (e.g., a fixed disk, such as a hard drive, or optical disk), as well as the exchange of information between subsystems. The system memory 72 and/or the storage device(s) 79 may embody a computer readable medium. Another subsystem is a data collection device 85, such as a camera, microphone, accelerometer, and the like. Any of the data mentioned herein can be output from one component to another component and can be output to the user.

[0194] A computer system can include a plurality of the same components or subsystems, e.g., connected together by external interface 81, by an internal interface, or via removable storage devices that can be connected and removed from one component to another component. In some embodiments, computer systems, subsystem, or apparatuses can communicate over a network. In such instances, one computer can be considered a client and another computer a server, where each can be part of a same computer system. A client and a server can each include multiple systems, subsystems, or components.

[0195] Aspects of embodiments can be implemented in the form of control logic using hardware circuitry (e.g. an application specific integrated circuit or field programmable gate array) and/or using computer software stored in a memory with a generally programmable processor in a modular or integrated manner, and thus a processor can include memory storing software instructions that configure hardware circuitry, as well as an FPGA with configuration instructions or an ASIC. As used herein, a processor can include a singlecore processor, multi-core processor on a same integrated chip, or multiple processing units on a single circuit board or networked, as well as dedicated hardware. Based on the disclosure and teachings provided herein, a person of ordinary skill in the art will know and appreciate other ways and/or methods to implement embodiments of the present disclosure using hardware and a combination of hardware and software.

[0196] Any of the software components or functions described in this application may be implemented as software code to be executed by a processor using any suitable computer language such as, for example, Java, C, C++, C#, Objective-C, Swift, or scripting language such as Perl or Python using, for example, conventional or object-oriented techniques. The software code may be stored as a series of instructions or commands on a computer readable medium for storage and/or transmission. A suitable non-transitory computer readable medium can include random access memory (RAM), a read only memory (ROM), a magnetic medium such as a hard-drive or a floppy disk, or an optical medium such as a compact disk (CD) or DVD (digital versatile disk) or Blu-ray disk, flash memory, and the like. The computer readable medium may be any combination of such devices. In addition, the order of operations may be re-arranged. A process can be terminated when its operations are completed, but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination may correspond to a return of the function to the calling function or the main function [0197] Such programs may also be encoded and transmitted using carrier signals adapted for transmission via wired, optical, and/or wireless networks conforming to a variety of protocols, including the Internet. As such, a computer readable medium may be created using a data signal encoded with such programs. Computer readable media encoded with the program code may be packaged with a compatible device or provided separately from other devices (e.g., via Internet download). Any such computer readable medium may reside on or within a single computer product (e.g. a hard drive, a CD, or an entire computer system), and may be present on or within different computer products within a system or network. A computer system may include a monitor, printer, or other suitable display for providing any of the results mentioned herein to a user.

[0198] Any of the methods described herein may be totally or partially performed with a computer system including one or more processors, which can be configured to perform the steps. Thus, embodiments can be directed to computer systems configured to perform the steps of any of the methods described herein, potentially with different components performing a respective step or a respective group of steps. Although presented as numbered steps, steps of methods herein can be performed at a same time or at different times or in a different order. Additionally, portions of these steps may be used with portions of other steps from other methods. Also, all or portions of a step may be optional.

Additionally, any of the steps of any of the methods can be performed with modules, units, circuits, or other means of a system for performing these steps.

[0199] The specific details of particular embodiments may be combined in any suitable manner without departing from the spirit and scope of embodiments of the invention. However, other embodiments of the invention may be directed to specific embodiments relating to each individual aspect, or specific combinations of these individual aspects.

[0200] The above description of example embodiments of the present disclosure has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the disclosure to the precise form described, and many modifications and variations are possible in light of the teaching above.

[0201] A recitation of "a", "an" or "the" is intended to mean "one or more" unless specifically indicated to the contrary. The use of “or” is intended to mean an “inclusive or,” and not an “exclusive or” unless specifically indicated to the contrary. Reference to a “first” component does not necessarily require that a second component be provided. Moreover, reference to a “first” or a “second” component does not limit the referenced component to a particular location unless expressly stated. The term “based on” is intended to mean “based at least in part on.”

[0202] All patents, patent applications, publications, and descriptions mentioned herein are incorporated by reference in their entirety for all purposes. None is admitted to be prior art.

Claims

WHAT IS CLAIMED IS:

1. A method performed by a computer system, the method comprising: retrieving, from one or more databases, symptom information for users of the computer system, the symptom information corresponding to times that tests for a disease were administered for the users; retrieving, from the one or more databases, infection results of the disease for the users from the one or more databases, the infection results corresponding to the tests for the disease that were administered for the users; generating, by the computer system, a symptomology model for prediction of risk for a user being infected by the disease based on the symptom information for the users and the infection results for the users; receiving, from a first user device associated with a first user of the computer system, symptom information for the first user and an infection result for the first user; adapting, by the computer system, the symptomology model based on the symptom information for the first user and the infection result for the first user; receiving, from a second user device associated with a second user of the computer system, symptom information for the second user; determining, by the computer system, an infection probability score for the disease for the second user based on the symptom information for the second user and the adapted symptomology model; determining, by the computer system, whether the second user is to receive a medical intervention for the disease based on the infection probability score; and providing, to the second user device, an indication whether the second user is to receive the medical intervention based on the determination whether the second user is to be tested for the disease.

2. The method of claim 1, wherein adapting the symptomology model includes updating weightings within the symptomology model related to symptoms of the disease based on the symptom information for the first user and the infection result for the first user.

3. The method of claim 1 , wherein determining whether the second user is to receive the medical intervention includes: comparing the infection probability score to a threshold infection probability score; and determining whether the second user is to receive the medical intervention based on whether the infection probability score exceeds the threshold infection probability score.

4. The method of claim 3, wherein determining whether the second user is to receive the medical intervention further includes: presenting, on the second user device, an inquiry based on the infection probability score exceeding the threshold infection probability score; and determining whether the second user is to receive the medical intervention based further on a response to the inquiry.

5. The method of claim 1, further comprising: retrieving, from the one or more databases, geographic information for the users; generating a plurality of symptomology models for different geographic regions based on the geographic information for the users, the symptom information for the users, and the infection results of the disease for the users, wherein the plurality of symptomology models includes the symptomology model and the symptomology model corresponds to a particular geographic region; receiving geographic information for the first user; and determining that the first user corresponds to the particular geographic region based on the geographic information for the first user, wherein the symptomology model is adapted based on the determining that the first user corresponds to the particular geographic region.

6. The method of claim 5, further comprising: receiving geographic information for the second user; and determining that the second user corresponds to the particular geographic region based on the geographic information for the second user, wherein the adapted symptomology model is utilized for determining the infection probability score for the disease for the second user based on the determining that the second user corresponds to the particular geographic region.

7. The method of claim 1, wherein the one or more databases are associated with one or more websites that allowed the users to provide the symptom information for the users and the infection results of the disease for the users.

8. The method of claim 1, further comprising: retrieving, from the one or more databases, geographic information for the users; identifying a geographic region of interest based on the geographic information for the users and the infection results of the disease for the users; and initiating an information-gathering campaign for the geographic region of interest.

9. The method of claim 8, wherein initiating the information-gathering campaign includes initiating digital marketing within the geographic region of interest requesting symptom information for users within the geographic region of interest.

10. The method of claim 8, further comprising: determining a response rate to the information-gathering campaign for the geographic region of interest; determining whether the response rate is below a threshold response rate; and adapting the symptomology model based on a determination that the response rate is below the threshold response rate.

11. The method of claim 1, wherein the second user device includes a wearable device worn by the second user, and wherein receiving the symptom information for the second user includes receiving the symptom information from the wearable device.

12. The method of claim 1, wherein the medical intervention includes testing of the second user for the disease.

13. The method of claim 1, wherein the medical intervention includes vaccination of the second user for the disease.

14. The method of claim 1, wherein the medical intervention includes pharmacological treatment of the second user for the disease.

15. The method of claim 1, wherein the medical intervention includes further monitoring of the second user for the disease.

16. The method of claim 1, wherein the medical intervention includes informational/educational intervention for the second user for the disease.

17. A method performed by a server, comprising: determining a symptomology model for prediction of risk for a user being infected by a disease based on collected symptom information for users of the server, collected infection results for the users, and collected environmental information associated with the users; receiving, from a user device of a user, user symptom information for the user; obtaining user environmental information associated with the user, the user environmental information providing a measure of disease activity for a geographic region or a group within which the user belongs; determining an infection probability score based on the user symptom information for the user, the user environmental information for the user, and the symptomology model; comparing the infection probability score with a score threshold; determining that the user is to receive a medical intervention for the disease based on the comparison; and providing, to the user device, an indication that the user is to receive the medical intervention.

18. The method of claim 17, further comprising collecting the collected symptom information and the collected infection results via one or more websites designed to receive input from the users, wherein the users include symptomatic individuals and asymptomatic individuals.

19. The method of claim 17, further comprising: identifying symptomatic users and asymptomatic users from the users based on the collected symptom information for the users; determining a first symptomology model for the symptomatic users based on collected symptom information for the symptomatic users and collected infection results for the symptomatic users, wherein the first symptomology model is to be utilized for determining whether users that present symptoms are receive the medical intervention; determining a second symptomology model for the asymptomatic users based on collected symptom information for the asymptomatic users and collected infection results for the asymptomatic users, wherein the second symptomology model is to be utilized for determining whether users that do not present symptoms are to receive the medical intervention; and selecting the symptomology model for prediction of risk for the user from the first symptomology model and the second symptomology model based on the user symptom information for the user.

20. The method of claim 17, further comprising: checking stocks of resources for the medical intervention for the disease from locations within a geographic range of the user; and determining a portion of the locations that have resources available for the user based on the stocks of resources, wherein the indication that the user is to receive the medical intervention includes an indication of the portion of the locations that have resources available for the user.

21. The method of claim 17, further comprising receiving social determinant information for the user, wherein the infection probability score is determined based further on the social determinant information for the user.

22. The method of claim 17, wherein the collected environmental information associated with the users includes geographic information for the users, and wherein the method further comprises: determining a number of resources for the disease to be utilized for the geographic region based on the geographic information for the users, the collected symptom information for the users, and the collected infection results for the users; determine a number of resources for the disease available within the geographic region; compare the number of resources for the disease available within the geographic region with the number of resources for the disease to be utilized for the geographic region; and initiate transit of additional resources for the disease to the geographic region based on the number of resources for the disease available within the geographic region being less than the number of resources for the disease to be utilized for the geographic region.

23. The method of claim 17, further comprising providing, based on the determination that the user is to receive medical intervention for the disease, an indication to receive medical intervention for the disease to one or more family members of the user, one or more coworkers of the user, or one or more people that have been within a certain proximity of the user.

24. The method of claim 17, wherein the users of the server comprise a subset of all users of the server, the users having similar characteristics.

25. The method of claim 17, wherein the collected environmental information associated with the users includes geolocation information associated with the users, wherein the user environmental information for the user includes geolocation information for the user, wherein determining the symptomology model is further based on collected demographic information associated with the users, exposure information of the users, testing information of the users, vaccination status of the users, or social determinants of the users, where the method further comprises receiving, from the user device, the demographic information associated with the user, the exposure information of the user, the testing information of the user, and the vaccination status of the user.

26. The method of claim 17, wherein the medical intervention includes testing of the user for the disease.

27. The method of claim 17, wherein the medical intervention includes vaccination of the user for the disease.

28. The method of claim 17, wherein the medical intervention includes pharmacological treatment of the user for the disease.

29. The method of claim 17, wherein the medical intervention includes further monitoring of the user for the disease.

30. The method of claim 17, wherein the medical intervention includes informational/educational intervention for the user for the disease.

31. A computer product comprising a non-transitory computer readable medium storing a plurality of instructions that when executed cause a computer system to perform the method of any one of the preceding claims.

32. A system comprising: the computer product of claim 31 ; and one or more processors for executing instructions stored on the computer readable medium.

33. A system comprising means for performing any of the above methods.

34. A system comprising one or more processors configured to perform any of the above methods.