JP7372495B1 - Infection control support system - Google Patents

Abstract

The present invention relates to a technique that can streamline infection control measures against infectious microorganisms. An infection control support system according to the present invention is an infection control support system that supports infection control measures against infectious microorganisms in a target area, and includes a control unit. The control unit acquires exposure risk-related information related to the exposure risk, and obtains a plurality of information for evaluating the exposure risk classified by at least one element selected from the position in the target area, time, and behavior of the subject. Evaluate the exposure risk for each of the evaluation items based on exposure risk-related information, and generate advice on infection control measures to reduce the evaluated exposure risk for at least one of the multiple evaluation items. , predicts the exposure risk for evaluation items after implementation of infection control measures, and outputs infection control support information including the exposure risk evaluation results, generated infection control advice, and exposure risk prediction results. . [Selection diagram] Figure 20

Description

The present invention relates to a technique for increasing the efficiency of measures to prevent infection by infectious microorganisms.

BACKGROUND ART From the perspective of taking appropriate measures against infectious microorganisms such as bacteria and viruses, techniques for evaluating the risk of exposure to infectious microorganisms and the risk of infection are known. For example, Patent Document 1 discloses that the user's virus exposure amount is calculated based on the virus concentration in a predetermined area and the user's presence time, and when it is determined that the calculation result is equal to or higher than a predetermined threshold, the user is notified. Disclosed is a leaving device capable of doing this. For example, Non-Patent Document 1 discloses a technique for simulating the amount of exposure to SARS-CoV-2 among spectators at an event and evaluating the risk of infection with COVID-19. For example, Non-Patent Document 2 discloses a model that can simulate the infection risk for each infection route for influenza viruses.

Japanese Patent Application Publication No. 2015-117950

M. Murakami et al., COVID-19 risk assessment at the opening ceremony of the Tokyo 2020 Olympic Games, Microbial Risk Analysis, Available online 21 March 2021, 100162. doi: 10.1016/j.mran.2021.100162, URL: https:/ /doi.org/10.1016/j.mran.2021.100162

Nicas, M., and Jones, R. M. (2009). Relative contributions of four exposure pathways to influenza infection risk. Risk Analysis: An International Journal, 29(9), 1292-130

On the other hand, there are a wide variety of situations in which there is a risk of exposure to infectious microorganisms in facilities that are subject to infection control measures. Therefore, from the viewpoint of reducing the burden of hygiene management on the above-mentioned facilities, there is a need to make infection control measures against infectious microorganisms more efficient.

The present invention relates to a technology that can streamline infection control measures against infectious microorganisms.

An infection control support system according to one embodiment of the present invention is an infection control support system that supports infection control measures against infectious microorganisms in a target area, and includes a control unit.
The control unit includes:
obtaining exposure risk related information related to the exposure risk;
The exposure risk in each of the plurality of evaluation items for evaluating the exposure risk, classified by at least one element selected from the position in the target area, time, and the behavior of the subject, is determined based on the exposure risk-related make an informed assessment,
generating advice regarding infection control measures to reduce the evaluated exposure risk for at least one evaluation item among the plurality of evaluation items;
Predicting the exposure risk for the evaluation item after implementing the infection control measures,
Infection control support information including the exposure risk evaluation result, the generated advice regarding the infection control measure, and the exposure risk prediction result is output.

Further, an infection control support method according to another embodiment of the present invention is an infection control support method that supports infection control measures against infectious microorganisms in a target area.
The infection control support method is
obtaining exposure risk related information related to the exposure risk;
The exposure risk in each of the plurality of evaluation items for evaluating the exposure risk, classified by at least one element selected from the position in the target area, time, and the behavior of the subject, is determined based on the exposure risk-related an informed evaluation step;
generating advice regarding infection control measures to reduce the evaluated exposure risk for at least one evaluation item among the plurality of evaluation items;
predicting the exposure risk for the evaluation item after implementing the infection control measures;
The method includes a step of outputting infection control support information including the exposure risk evaluation result, the generated advice regarding the infection control measure, and the exposure risk prediction result.

Further, a program for supporting infection control measures according to another embodiment of the present invention is a program for supporting infection control measures against infectious microorganisms in a target area, and is a program for supporting infection control measures against infectious microorganisms in a target area.
obtaining exposure risk related information related to the exposure risk;
The exposure risk in each of the plurality of evaluation items for evaluating the exposure risk, classified by at least one element selected from the position in the target area, time, and the behavior of the subject, is determined based on the exposure risk-related an informed evaluation step;
generating advice regarding infection control measures to reduce the evaluated exposure risk for at least one evaluation item among the plurality of evaluation items;
predicting the exposure risk for the evaluation item after implementing the infection control measures;
outputting infection control support information including the exposure risk evaluation result, the generated advice regarding the infection control, and the exposure risk prediction result;
Execute.

According to the present invention, it is possible to make infection control measures against infectious microorganisms more efficient.

1 is a diagram illustrating the configuration of an exposure risk assessment system according to a first embodiment of the present invention. (A) is a diagram showing the hardware configuration of a server included in the above system, and (B) is a diagram showing the hardware configuration of a terminal device included in the above system. A schematic map of a target area (restaurant store) that is a target of an operation example of the present embodiment is shown. FIG. 3 is a sequence diagram illustrating the processing flow of the system in the operation example. It is a figure which shows the example of the display screen of the 1st terminal device in ST11 of the said example of operation. It is a figure which shows the example of the display screen of the 1st terminal device in ST11 of the said example of operation. It is a figure which shows the example of the display screen of the 1st terminal device in ST11 of the said example of operation. It is a figure which shows the example of the display screen of the 1st terminal device in ST11 of the said example of operation. It is a figure which shows the example of the display screen of the 1st terminal device in ST11 of the said example of operation. It is a figure which shows the example of the display screen of the 1st terminal device in ST11 of the said example of operation. (A) is a diagram schematically showing an example of a contact scene assumed in the above operation example, and (B) is a diagram schematically showing an example of a contact event. It is a figure which shows the example of the display screen of the 2nd terminal device in ST42 of the said example of operation. 12 is a flowchart showing the flow of processing by the server according to a modification of the above operation example. It is a figure which shows the example of another display screen of the 2nd terminal device in ST42 of the said example of operation. It is a figure which shows the example of another display screen of the 2nd terminal device in ST42 of the said example of operation. It is a figure which shows the example of another display screen of the 2nd terminal device in ST42 of the said example of operation. It is a figure which shows the example of another display screen of the 2nd terminal device in ST42 of the said example of operation. It is a figure which shows the example of another display screen of the 2nd terminal device in ST42 of the said example of operation. FIG. 2 is a diagram illustrating an example of a simulation model for exposure risk assessment that can be adopted in the embodiment described above, and is a diagram illustrating state transitions in a long-distance infection route of an infectious virus. FIG. 7 is a sequence diagram illustrating the processing flow of the infection control support system in an operation example of the second embodiment of the present invention. It is a figure which shows the example of the display screen of the 2nd terminal device in ST44 of the said example of operation. 12 is a flowchart showing the flow of processing by the server according to a modification of the above operation example. It is a figure which shows the example of another display screen of the 2nd terminal device in ST44 of the said example of operation. It is a figure which shows the example of another display screen of the 2nd terminal device in ST44 of the said example of operation. It is a figure which shows the example of the display screen of the 2nd terminal device based on other embodiment of this invention.

Embodiments of the present invention will be described below with reference to the drawings. Note that in this specification, a "system" includes one or more information processing devices. For example, a single information processing device can constitute a system, and even when a plurality of information processing devices cooperate to perform functions such as a web server, these information processing devices can configure a system. Furthermore, as described in the embodiments below, the "system" may include an information processing device that functions as a web server, one or more terminal devices, and one or more inspection devices.

<First embodiment>
[System overview]
The system according to the first embodiment of the present invention configures a system via the Internet, for example. In this embodiment, the system functions as an exposure risk assessment system that assesses the risk of exposure to infectious microorganisms.

In the example shown in FIG. 1, the system according to the present embodiment includes a server 100 on the Internet N, a first terminal device 200A, a second terminal device 200B, a detection device 300, and a measurement device 400. The first terminal device 200A and the second terminal device 200B may have the same hardware configuration and are also referred to as the terminal device 200. Further, the detection device 300 and the measurement device 400 each function as an inspection device 500 used for an inspection to acquire exposure risk-related information, which will be described later. Note that although FIG. 1 shows an example in which the system includes two terminal devices 200, the system may include three or more terminal devices 200. Further, the system may include three or more inspection devices 500.

The server 100 can be, for example, a web server (information processing device) operated by an operator of an infection control support service that supports infection control measures against infectious microorganisms. The infection control support service may be, for example, a service that supports infection control in a target area for a manager or the like who performs hygiene management of the target area. In this embodiment, a person who manages the hygiene of a target area of a service provider is referred to as a "manager." The server 100 is connected to a plurality of terminal devices 200 and a plurality of inspection devices 500 via the Internet N, for example. The server 100 processes, for example, information input from the first terminal device 200A and the inspection device 500A (the detection device 300 and the measurement device 400), and performs management using the second terminal device 200B via an application, a website, etc. Infection prevention support services can be provided to those who are infected.

The terminal devices 200 (200A, 200B...) may be, for example, a smartphone, a desktop PC, a notebook PC, a tablet PC, a smart watch, etc., but are not limited thereto. For example, the terminal device 200 accesses the server 100, receives a web page generated by the server 100, and displays the received web page on a screen using a browser or the like.

In the present embodiment, the first terminal device 200A receives, for example, input of test results for the target area, behavior history of the target person staying in the target area, etc. (at least a part of exposure risk related information described below), This information can be sent to the server 100. The first terminal device 200A can be used by an inspector who performs an inspection to obtain exposure risk-related information, which will be described later, in the target area. The inspector may be, for example, the operator of the infection control support service or a person entrusted by the operator, or the administrator of the target area.

The second terminal device 200B can display information regarding infection control support generated by the server 100, for example. The terminal device 200B can be used by an administrator who registers with the infection control support service.

The detection device 300 is, for example, an inspection device that performs a detection test regarding infectious microorganisms using a sample collected from the environment of a target area. The detection device 300 is connected to the server 100 via the Internet N, and can transmit detection results to the server 100.

The measurement device 400 is, for example, an inspection device that measures an index related to exposure risk in the environment of the target area. In this embodiment, the measurement device 400 is, for example, a device that measures CO ₂ concentration in space. The measuring device 400 is connected to the server 100 via the Internet N, and can transmit measurement results to the server 100.

In this specification, the "target area" is an area targeted for sanitary treatment by the user (administrator) of the infection control support service, and may include facilities, outdoor areas, public transportation, residences, and the like.

Examples of facilities include commercial facilities, accommodation facilities, educational facilities, childcare facilities, medical facilities, nursing facilities, business facilities, eating and drinking facilities, health promotion facilities, event facilities, and complex facilities thereof. Examples of commercial facilities include shopping centers, supermarkets, cinema complexes, and amusement facilities. Examples of accommodation facilities include hotels, inns, private lodging facilities, and the like. Examples of educational facilities include various schools and cultural centers. Examples of childcare facilities include nursery schools and temporary childcare facilities for infants. Examples of medical facilities include hospitals and the like. Examples of business facilities include office buildings, factories, and the like. Examples of eating facilities include restaurants, coffee shops, fast food restaurants, and the like. Examples of health promotion facilities include fitness facilities, hot bath facilities, and the like.

Outdoor areas include parks, garden areas, green spaces, construction sites, and the like. Examples of public transportation include railways, buses, taxis, ships, airplanes, and the like.

In this specification, a "target person" is a person staying in a target area, and includes an actual target person and a virtual stayer. Specifically, the target person may be a person actually observed in the target area, or a person assumed through a simulation or the like.

As used herein, "infectious microorganisms" are microorganisms that cause infectious diseases, and include, for example, at least one type selected from viruses, bacteria, parasites, fungi, and other infectious microorganisms. Among these, it is preferable that the infectious microorganism to be evaluated includes at least one selected from viruses, bacteria, protozoa, and fungi for which infection control measures are highly necessary from the viewpoint of public health. Specific examples of viruses include influenza virus, respiratory syncytial virus, coronavirus, adenovirus, enterovirus, mumps virus, rubella virus, human metapneumovirus, norovirus, rotavirus, dengue virus, and the like. Specific examples of bacteria include Staphylococcus aureus, hemolytic streptococcus, Streptococcus pneumoniae, Mycobacterium tuberculosis, pathogenic Escherichia coli, Salmonella enterica, Vibrio parahaemolyticus, Clostridium botulinum, Clostridium perfringens, Shigella, Vibrio cholerae, Legionella, etc. . Specific examples of fungi include Aspergillus and Cryptococcus. Protozoa refers to single-celled microorganisms among parasites, and examples thereof include malaria, pathogenic amoeba, Giardia, Cryptosporidium, and the like. The system of this embodiment can target one or more of the above infectious microorganisms.

As used herein, "exposure" typically means that infectious microorganisms attach to the skin or hair of a subject or invade the body, and "exposure risk" typically refers to This refers to the risk of infectious microorganisms attaching to the subject's skin or hair, or entering the body. Furthermore, "infection control" refers to measures to prevent the establishment of infection within the body of a subject, and includes, for example, measures to suppress exposure to infectious microorganisms, measures to reduce the amount of exposure, and the like.

[Hardware configuration of information processing device]
As shown in FIG. 2A, the server 100 includes, for example, a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, an input/output interface 15, and A connecting bus 14 is provided.

The CPU 11 accesses the RAM 13 and the like as necessary, and performs various arithmetic operations while controlling each block of the server 100 in an integrated manner. The ROM 12 is a nonvolatile memory in which firmware such as an OS, programs, and various parameters to be executed by the CPU 11 is permanently stored. The RAM 13 is used as a work area for the CPU 11, and temporarily stores the OS, various applications being executed, and various data being processed.

A display section 16, an operation reception section 17, a storage section 18, a communication section 19, etc. are connected to the input/output interface 15.

The display unit 16 is a display device using, for example, an LCD (Liquid Crystal Display), an OELD (Organic ElectroLuminescence Display), a CRT (Cathode Ray Tube), or the like.

The operation reception unit 17 is, for example, a pointing device such as a mouse, a keyboard, a touch panel, or other input device. When the operation receiving section 17 is a touch panel, the touch panel can be integrated with the display section 16.

The storage unit 18 is, for example, a nonvolatile memory such as an HDD (Hard Disk Drive), a flash memory (SSD; Solid State Drive), or other solid state memory. The storage unit 18 stores the OS, various applications, and various data.

In the present embodiment, the storage unit 18 may include programs necessary for exposure risk evaluation processing, which will be described later, as well as a target area database, which will be described later, and other databases used for processing. Databases such as the target area database are referenced as necessary during system processing. Note that these databases may be stored not in the storage unit 18 but in a storage device or server externally connected to the server 100.

The communication unit 19 is, for example, various modules for wireless communication such as an Ethernet NIC (Network Interface Card) or a wireless LAN, and is responsible for communication processing with the terminal device 200.

As shown in FIG. 2(B), like the server 100, the terminal device 200 also includes, for example, a CPU 21, a ROM 22, a RAM 23, a bus 24, an input/output interface 25, a display section 26, an operation reception section 27, a storage section 28, It has a communication section 29.

Furthermore, in addition to the same configuration as the server 100, the detection device 300 may further include a detection unit that detects an indicator related to infectious microorganisms. For example, in addition to the same configuration as the server 100, the measurement device 400 may further include a measurement unit that measures CO ₂ concentration.

[Database configuration example]
The target area database stores attribute information of target areas to be registered in the infection control support service for each target area. Attribute information of the target area is not particularly limited, but includes, for example, name, ID for identifying the target area, classification of the target area (facility classification, etc.), name and/or ID of the operator who operates the target area, In addition to general information such as address (region), the information may include area information divided in the target area, map information of the target area, attribute information of the target person staying in the target area, and the like. The attribute information preferably includes, for example, information about attributes related to exposure risk, risk of aggravation, and/or risk of onset, and such attributes include, for example, age group, role, occupation, etc., as well as information regarding these risks. These include the prevalence of related diseases, pre-existing disease rates, morbidity rates, etc. Note that the area information includes the name of the area, its position information, etc., and the position information may be stored in association with the position of the target area on the map.

In this embodiment, the target area database includes, in addition to the above attribute information, information on a plurality of evaluation items, which will be described later, and acquired exposure risk-related information for each target area. Further, the target area database may include, for example, information regarding infectious microorganisms to be evaluated in the target area (classification, infection route, risk of infection, risk of aggravation, etc.), and information used for other processing.

In the present embodiment, the plurality of evaluation items are items classified by at least one element selected from the position in the target area, time, and behavior of the target person, and are items for evaluating exposure risk. In this embodiment, the evaluation item becomes a processing unit of exposure risk evaluation processing. The plurality of evaluation items are determined based on, for example, the behavior of the subject in the target area, the infection route of infectious microorganisms, hygiene control items in the target area, and the like.

For example, the evaluation items may correspond to a plurality of scenes classified based on the subject's behavior related to exposure risk. Scenes corresponding to the evaluation items are scenes where the subject performs a predetermined action, such as scenes on the flow line of a typical subject in the target area (e.g., washing hands, eating, conversation, etc.), and scenes in the target area. Examples include scenes (for example, reception, entrance, exit, etc.) depending on the event being held. Further, each evaluation item corresponding to a scene may be associated with positional information (for example, area information, etc.) within the target area where the scene is performed.

Alternatively, the evaluation items may correspond to areas in the target region that are classified by exposure risk. The area corresponding to the evaluation item may be, for example, a section of the target area separated by a wall or partition (e.g., a conference room, staff room, kitchen, etc.), or it may be a section of the target area that is divided by walls or partitions (e.g., a conference room, a staff room, a kitchen, etc.), or it may be a section of the target area that is divided by walls or partitions, or it may be a section of the target area that is divided by walls or partitions. It may also be an area at risk (eg, eating area, disinfection area, etc.).

Alternatively, the evaluation items may correspond to time zones classified by exposure risk (for example, morning, noon, night, morning, afternoon, etc.).

Furthermore, the evaluation items may be items categorized by a plurality of factors selected from the position within the target area, time, and behavior of the subject. Examples of such evaluation items include evaluation items classified according to the elements of time and area, evaluation items classified according to the elements of time and scene, evaluation items classified according to area and scene, and the like.

In this embodiment, each evaluation item is preferably stored in association with at least one infection route by an infectious microorganism. This facilitates the selection of inspection items for acquiring exposure risk-related information, which will be described later.

Specifically, the infection route by the infectious microorganism is at least one selected from droplet infection, contact infection, airborne infection, oral infection, vector infection, and other infection routes depending on the type of infectious microorganism. include. The infection route corresponding to each evaluation item is selected from the infection routes by the target infectious microorganism, and includes, for example, the behavior of the subject corresponding to each evaluation item, the environment corresponding to each evaluation item (for example, environmental surfaces and spaces). etc.) etc.). The number of infection routes corresponding to each evaluation item may be one or more. For example, when the evaluation item corresponds to a scene, a scene in which a subject uses an article that is frequently contacted may be stored in association with contact infection, for example. Furthermore, scenes in which subjects may come into close contact with each other may be stored in association with, for example, droplet infection, contact infection due to droplets, and airborne infection.

The exposure risk related information is information related to exposure risk, and is information used in the exposure risk evaluation process by the server 100. In this embodiment, the exposure risk-related information is at least one piece of information selected from information input by the first terminal device 200A and transmitted to the server 100, and information about test results transmitted by the testing device 500. including.

In this embodiment, it is preferable that the exposure risk related information is information related to the exposure risk in each of the plurality of evaluation items. For example, the exposure risk related information preferably includes information related to the exposure risk due to at least one infection route corresponding to each of the plurality of evaluation items. For example, the exposure risk-related information preferably includes at least one piece of information selected from behavioral risk information and environmental risk information, which will be described later.

In the present embodiment, the behavioral risk information is information regarding a subject's behavior related to exposure risk in a situation corresponding to at least one evaluation item among a plurality of evaluation items. By including behavioral risk information in the exposure risk-related information, it becomes possible to evaluate a wide range of exposure risks such as contact infection, droplet infection, and airborne infection.

The behavioral risk information preferably includes at least one piece of information selected from, for example, information about the subject's behavior related to exposure risk, and information about situations that change the exposure risk caused by the subject's behavior. Behaviors associated with exposure risk include, for example, behaviors that may change the risk of exposure to infectious microorganisms. Such actions include, for example, droplet-generating actions such as talking with others, speaking, sneezing, and coughing, touching environmental surfaces, and infection control actions such as hand hygiene, cleaning, and wearing a mask. Examples of situations that change the exposure risk due to the subject's actions include the infection control situation described below.

For example, the behavioral risk information may include information regarding the exposure risk-related behavior of one or more sample subjects observed in a situation corresponding to the evaluation item. The sample subject may be a subject actually observed in the target area, or may be a virtual subject observed in a virtual space corresponding to the target area. Furthermore, examples of methods for observing an actual sample subject include a method of going to the target area and directly observing the target area, and a method of observing an image of the target area.

For example, it is preferable that the behavioral risk information includes information regarding a contact scene in which a plurality of sample subjects who are observed in a situation corresponding to an evaluation item come into contact. In this specification, "contact" between multiple (sample) subjects refers to actions that involve direct contact of the skin or clothing of these (sample) subjects, as well as actions that involve close-range interaction such as conversation. include. Furthermore, a "contact scene" is a scene that is observed in a situation corresponding to an evaluation item and includes contact behavior by a plurality of sample contacts, and is a different concept from a "scene" as an evaluation item.

Specifically, the behavioral risk information includes, for example, the length of stay of one or more sample subjects in the contact scene, the droplet-generating behavior of one or more sample subjects in the contact scene, the positional relationship of the sample subjects in the contact scene, It is preferable to include information on at least one selected from the infection control status in contact situations. Examples of the information about the stay time include information about the stay time when a plurality of sample subjects stayed close to each other. Information on the above-mentioned positional relationship includes information on the distance between the people in contact with the sample, the positional relationship of the seats of the people in contact with the sample (facing each other, diagonally, etc.), and the like. Examples of the droplet-generating behavior include conversation, vocalization, sneezing, coughing, etc., and information about the droplet-generating behavior includes, for example, information about the presence or absence, time, frequency, number of times, etc. of the droplet-generating behavior. Infection control status includes hand hygiene, cleaning, wearing masks, installing partitions, etc. Information on infection control status includes presence or absence of infection control status, and number of infection control actions (hand hygiene, cleaning, etc.) , the location and/or number of partitions, the material of the mask, etc.

In this embodiment, the environmental risk information is information related to an exposure risk caused by the environment corresponding to at least one evaluation item among a plurality of evaluation items. In this specification, the environment in the target area includes, for example, an environmental surface within the target area, a space within the target area, water used in the target area, and the like. In this specification, the environmental surface may include, for example, the surface of a building included in the target area (floor, wall, etc.), the surface of an article placed in the target area, and the like. The article may be a fixed article or an unfixed article. The material of the article is also not limited. Examples of the articles include furniture, electrical appliances, plumbing items, building materials, fittings, clothing, bedding, and the like.

In this embodiment, the environmental risk information preferably includes, for example, information about detection results regarding infectious microorganisms in the environment. The detection result regarding the infectious microorganism may include, for example, at least one of the detection result about the infectious microorganism or the detection result of an indicator related to the infectious microorganism. Detection results regarding infectious microorganisms include, for example, detection results of proteins or fragments thereof contained in infectious microorganisms, detection results of genes of infectious microorganisms, and the like. Examples of methods for detecting proteins or fragments thereof include methods using antigen-antibody reactions such as ELISA, immunochromatography, and biosensors. Examples of gene detection methods include methods using PCR, real-time PCR, LAMP, and the like. Detection results of indicators related to infectious microorganisms can be selected as appropriate depending on the type of infectious microorganism, but examples include detection results of saliva-containing components, ATP detection results, biosensor detection results, etc. It will be done.

The environmental risk information preferably includes, for example, information about detection results regarding infectious microorganisms in the environment, and preferably includes information about detection results regarding infectious microorganisms on environmental surfaces. Examples of methods for collecting detection samples from environmental surfaces include a method in which a suitable collection means (absorbent cotton, nonwoven fabric, sponge, cotton swab, swab, etc.) is brought into contact with the environmental surface. In this case, the collection means is preferably in a state where it is soaked with a suitable liquid (an aqueous solution containing a surfactant, physiological saline, a buffer solution, a liquid combination thereof, etc.). Furthermore, the environmental risk information may include information about detection results regarding infectious microorganisms in the environmental space. Examples of methods for collecting a detection sample from an environmental space include capture using a filter, capture in a liquid by bubbling, etc., capture by electrostatic adsorption, suction using a pump, and the like. Further, the collection method may be passive sampling without using a pump or capture using classification.

In this embodiment, the environmental risk information preferably includes, for example, detection results of saliva-containing components and/or fecal-containing components such as bile acids in the environment. It is preferable to include the detection results of saliva-containing components on the surface). Preferably, the saliva-containing component to be detected includes, for example, amylase. Amylase is an enzyme found in human saliva. By including the detection results of saliva-containing components such as amylase in the environmental risk information, it becomes possible to evaluate the state of contamination caused by saliva droplets in the environment. The detection result of the saliva-containing component may include, for example, information about the detected amount of the component, information about the detection frequency of the component, and the like.

In this embodiment, the environmental risk information preferably includes, for example, information about the detection results of ATP in the environment, and particularly preferably includes information about the detection results of ATP on the environmental surface. ATP can be detected by electrochemical methods, such as chemiluminescence. By including the ATP detection results in the environmental risk information, it is possible to evaluate not only the contamination by microorganisms themselves in the environment, but also the contamination by organic matter related to the growth of microorganisms, and it is possible to evaluate the risk of growth of infectious microorganisms in the environment. becomes possible. For example, ATP on environmental surfaces can be rapidly detected, such as by an ATP swab test.

In this embodiment, it is preferable that the environmental risk information includes, for example, information regarding the ventilation status of the space. Information on the ventilation status of the space includes information on the measurement results of the CO ₂ concentration in the space, information on the measurement results of the ventilation amount in the space, information on the capacity and power of ventilation equipment, information on the frequency of ventilation in the space, Examples include information on measurement results of the wind speed, air volume, and/or wind direction of the air current in the space.

In addition to the above-mentioned examples, the environmental risk information may include, for example, information about the risk of water-borne exposure via water in the area of interest. Information related to such water-mediated exposure risks includes wastewater discharged in the target area, water used in the target area (tap water, pool water, water in bathtubs, water in irrigation canals, river water). Examples include microbial test results and water quality test results for water such as lake water, etc.).

In this embodiment, the storage unit 18 may further include a user database. The user database stores attribute information of users who are registered with the infection control support service for each user. In this embodiment, the user is a user who can access the infection control support service, and includes, for example, an examiner who registers test results and an administrator. User attribute information is not particularly limited, but includes, for example, the user's name (nickname), ID for identifying the user, user classification (e.g., administrator, inspector, etc.), user's affiliation, and user's contact information. In addition to general information such as the destination, information on the target area for each user may be included.

[System operation example]
Next, an example of the operation of the system configured as described above will be described. The operations of the server 100 described below are executed by the cooperation of hardware such as the CPU 11 and the communication section 19, and software stored in the storage section 18. The operations of the first and second terminal devices 200A and 200B are similarly executed by cooperation between hardware such as the CPU 21 and the communication section 29, and software stored in the storage section 28. The same applies to each inspection device 500.

In this operation example, the target area is store A, which is a restaurant, and the target infectious microorganism is an enveloped virus (influenza virus, coronavirus, etc.) that causes infectious diseases through contact infection, droplet infection, airborne infection, etc. Give an example. In this operation example, an inspector using the first terminal device 200A performs a predetermined inspection in the target area, and inputs the inspection result or information related to the inspection result into the first terminal device 200A. Further, the inspection device 500 (for example, the detection device 300 and the measurement device 400) installed in the target area acquires the inspection result and transmits the inspection result to the server 100. The server 100 performs an exposure risk evaluation process based on the received information. The server 100 then transmits the processing results to the terminal device 200B used by a health manager (hereinafter referred to as "administrator") of the target area who is a user of the infection control support service. However, the operation of the system in this embodiment is not limited to the following operation example.

FIG. 3 shows an example of a map of a store 50, which is a restaurant serving as a target area of this operation example. This store 50 includes, for example, a common area 510 used by customers and staff, and a staff area 520 used by staff. Further, the common area 510 includes, for example, an entrance area 511 and a dining area 512. Entrance area 511 has an entrance/exit 513 and a waiting zone 514. The eating area 512 includes a passage zone 515, a plurality of tables 516A, 516B, . . . , and a restroom 517. The staff area 520 includes a kitchen zone 521 and a staff room 522. Information on these areas is stored, for example, in a target area database. Further, it is preferable that information on such a map is also stored in, for example, a target area database.

A typical person (customer) using the store 50 enters the store 50 through an entrance/exit 513, for example, and disinfects his/her hands with a disinfector 518 disposed near the entrance/exit 513. Then, the user waits in the waiting zone 514 and enters the eating area 512. The customer is seated at a predetermined table 516A, selects a menu, and orders the menu. Then, the staff serves the meal to table 516A. Thereafter, the customer eats and converses at the table 516A, uses the restroom 517 as needed, leaves his seat, and leaves the store.

In this operational example, the target area database stores, for example, evaluation items corresponding to each scene on the customer's flow line determined in advance as described above. In this operation example, the evaluation items include, for example, scenes such as alcohol disinfection, waiting, taking a seat, menu selection, ordering, serving, eating, conversation, restroom, leaving, and leaving the store. Table 1 shows examples of evaluation items in this operation example. Information on each of these evaluation items (scenes) is associated with, for example, information on infection routes that may pose an exposure risk (for example, contact infection, droplet infection, and airborne infection). Further, it is preferable that the information on each evaluation item is also associated with, for example, information on the target area.

The inspector conducts an inspection to obtain exposure risk-related information. Tests can be selected for each evaluation item based on information on infection routes, actual customer behavior, and the like. In this operational example, a behavior test is performed to observe the behavior of the sample subject in situations such as eating and conversation that may include contact situations. In addition, in situations where there is a risk of contamination of environmental surfaces, such as menu selection, meals, conversations, and restrooms, tests for saliva-containing components and ATP are performed on the environmental surfaces. Further, the inspector selects, for example, an area with a risk of spatial contamination (for example, the eating and drinking area 512, etc.) and installs the measuring device 400 that measures the CO ₂ concentration.

(Processing for acquiring exposure risk-related information)
First, referring to FIG. 4, the first terminal device 200A used by the inspector receives input of at least part of the exposure risk-related information (ST11), and transmits at least part of the exposure risk-related information to the server 100. (ST12). In this operation example, the exposure risk-related information that the first terminal device 200A accepts as input is, for example, information about the test results of the behavioral test included in the behavioral risk information, and the test results of the saliva droplet test included in the environmental risk information. Contains information about and. Regarding the ATP test and the CO ₂ test, the first terminal device 200A can input and transmit information related to the test results, such as position information of the test device 500.

First, an example of a behavioral test will be explained.
An inspector who performs a behavioral test may visit a store in the target area and observe the behavior, or may observe the behavior based on images stored by a camera or the like installed in the store, for example. For example, in each scene associated with droplet infection, the inspector selects a contact scene that includes the sample subject (the subject and his or her contacts) to be tested. For example, the examiner can perform a behavior test at predetermined intervals. In this case, if the same sample subject group is observed at different times, behavioral tests can be conducted for each group.

Next, in order to input the behavioral test results into the first terminal device 200A, the tester displays a screen for inputting the contact scene test results. First, when the tester using the first terminal device 200A performs a login operation to the infection control support service application, the display section 26 of the first terminal device 200A can display the target area selection screen 201. It is possible (Fig. 5(A)). The target area selection screen 201 includes, for example, information on a plurality of target areas registered in the infection control support service. The inspector selects the target area (for example, store A) to be inspected on the target area selection screen 201 by tapping or the like, and displays the inspection item selection screen 202 on the display unit 26 (FIG. 5(B)). .

The test item selection screen 202 illustrated in FIG. 5(B) includes information on a plurality of test items. The tester can select a test item (here, a behavioral test) to be tested on the test item selection screen 202. Next, the display unit 26 of the first terminal device 200A can display an evaluation item selection screen 203 that includes information on the scene to be subjected to the behavioral test (FIG. 6(A)). For example, the tester selects a scene to be tested (in this example, "conversation") on the evaluation item selection screen 203, and displays a sample subject (hereinafter also referred to as "test subject") to be tested on the display unit 26. ) is displayed (FIG. 6(B)).

For example, the examiner selects the measurement button 204a of the test subject to be tested on the sample subject selection screen 204, and displays the stay time measurement screen 205 on the display unit 26 (FIG. 6(C)). The stay time measurement screen 205 illustrated in FIG. 6(C) includes a behavior input field 205a for the test subject, a behavior input field 205b for contact person 1, a behavior input field 205c for contact person 2, and a comment input field. It includes a column 205i and an inspection completion button 205j. The behavior input field 205a for the test subject includes, for example, a stay time measurement button 205d and a mask presence/absence registration button 205e. For example, when the action input fields 205b and 205c for contact person 1 and contact person 2 are selected, for example, by tapping, similar stay time measurement buttons and mask presence/absence registration buttons are expanded.

In this operation example, the tester observes the behavior of the test subject in one contact scene, for example, a conversation scene. For example, when a contact scene between the test subject and the contact person starts, the tester selects the stay time measurement button 205d by tapping or the like. Thereby, the CPU 21 starts measuring the residence time of the test subject in the contact scene. Furthermore, the inspector registers whether or not the person to be inspected is wearing a mask in the contact scene by selecting the mask presence/absence registration button 205e. In addition, the tester similarly starts measuring the stay time of a contact person who has been in contact with the test subject, and also registers whether or not the contact person is wearing a mask. For example, when the contact between the test subject and the contact person ends, the tester selects the stay time measurement button 205d again to finish measuring the stay time.

In this operation example, the tester can register information related to the exposure risk of the test subject and the contact, other than the above-mentioned stay time. For example, the examiner selects the three-dot reader 205f placed near the behavior input field 205a of the person to be tested, and displays the person to be tested registration screen 206 on the display unit 26 (FIG. 7(A)). The test subject registration screen 206 illustrated in FIG. 7A includes, for example, a test subject's age group registration field 206a, mask type registration field 206b, voice volume registration field 206c, and respiratory rate registration field. 206d, a hand hygiene registration field 206e, a cleaning action registration field 206f, a confirmation button 206g, and the like. The examiner registers the information of the person to be examined in these registration columns, for example, and selects the confirm button 206g. Thereby, detailed information of the person to be tested is input to the first terminal device 200A.

Similarly, the examiner selects the three-dot reader 205g (205h) placed near the contact person behavior input field 205b (205c) and displays the contact registration screen 207 on the display unit 26 (see FIG. 7). B)). The contact registration screen 207 illustrated in FIG. 7(B) includes, for example, an age group registration field 207a for the person to be tested, a registration field 207b for the type of mask, a registration field 207c for the distance to the person to be tested, and a field 207c for registering the presence or absence of a partition. It includes a registration field 207d, a confirmation button 207e, and the like. The examiner registers contact person information in these registration fields and selects the confirm button 207e. Thereby, detailed information on the contact person regarding the exposure risk is input to the first terminal device 200A.

When the test in the contact scene is completed, the tester selects the test completion button 205j on the stay time measurement screen 205 to display the test result display screen 208 on the display unit 26. The test result display screen 208 includes, for example, a display field 208a for test information (test date and time, name of examiner, etc.), a test subject information display field 208b, a contact information display field 208c, a comment display field 208d, a confirmation button 208e, etc. including. The examiner checks the display items on the test result display screen 208 and selects the confirm button 208e.

Thereby, the CPU 21 of the first terminal device 200A provides basic information about the behavioral test (information about the target area, evaluation items (scenes), test date and time, tester, etc.), behavioral risk information about the test subject (residence time, Information on age group, whether or not to wear a mask, volume of voice, respiratory rate, hand hygiene, cleaning contact situation, etc.), behavioral risk information on contacts (length of stay, age group, whether or not to wear a mask, people to be tested) It is possible to accept inputs such as information such as the distance from the server, the presence or absence of a partition, etc., and to correlate and transmit this information to the server 100.

Next, an example of a saliva droplet test will be explained.
In this operational example, the saliva droplet test is a test for detecting amylase. First, the examiner can select a site to be inspected that has a risk of contact infection among the evaluation items (for example, scenes) to be inspected in the target area. Then, the examiner can collect a test sample at the site to be examined. The test sample is collected, for example, by wiping the surface of the test target region with a predetermined collection tool. The examiner can extract and detect amylase using the collected sample. Extraction and detection of amylase can be performed using, for example, a commercially available kit. Detection of amylase is performed, for example, by a method using an antigen-antibody reaction and/or an enzyme reaction. The inspector can visually confirm the amylase detection results displayed on the kit or the like. Further, the examiner can take an image of the amylase detection result using, for example, the first terminal device 200A.

Next, as in the behavioral test example, the examiner logs into the infection support countermeasure application using, for example, the first terminal device 200A, selects store A on the target area selection screen 201, and selects the test item selection screen 202. Select the saliva droplet test to be tested (FIGS. 5(A) and (B)). Next, the display unit 26 of the first terminal device 200A displays, for example, an evaluation item selection screen for saliva droplet testing. The evaluation item selection screen may be configured similarly to the evaluation item selection screen in FIG. 6(A). The inspector selects a scene to be inspected on the evaluation item selection screen, and causes the display unit 26 to display an inspection object setting screen 209 (FIG. 8(A)).

The inspection object setting screen 209 illustrated in FIG. 8A includes, for example, an inspection object position information selection column 209a, an inspection information display column 209b for each inspection object, a map position registration button 209d, and the like. The test information display column 209b includes, for example, the name of the test object and measurement buttons 209c for each test target part of the test object. Information about the object to be inspected and its parts may be registered in advance in the target area database of the server 100, or the inspector may register the object to be inspected on the inspection object registration screen 210 (FIG. 8(B) ). Furthermore, if the map information of the target area is registered in the target area database in advance, the inspector selects the map position registration button 209d on the inspection target object setting screen 209, and selects the map position information of the inspection target object on the map. You can also register. The inspector selects the measurement button 209c for the part of the object to be inspected for which the inspection result has been obtained, and causes the display unit 26 to display the inspection result registration screen 211 (FIG. 8(C)).

The test result registration screen 211 illustrated in FIG. 8C includes, for example, a test information display field 211a, a test result image display field 211b, a test result registration field 211c, a comment input field 211d, a confirm button 211e, and the like. The examination information display column 211a includes information such as measurement date and time, name of the examiner, examination area, name and/or image of the object to be examined, name and/or image of the part to be examined. The test result image display field 211b includes image information of kits, reagents, etc., showing test results, uploaded by the tester. The test result registration field 211c is a field in which the tester registers information on test results determined visually (for example, positive/negative, colorimetric test results, etc.). The inspector uploads an image of the test result and registers the visually determined test result in the test result registration field 211c. After registering all test results, the tester selects the confirm button 211e.

As a result, the first terminal device 200A provides basic test information (measurement date and time, name of tester, test area, name and/or image of the test object, It is possible to accept inputs of information such as the name and/image of the part to be examined) and examination result information (image information of the examination result, registration information of the examination result), and to correlate and transmit these pieces of information to the server 100.

On the other hand, regarding the test results of the ATP test and _CO2 test included in the environmental risk information, the test device 500 (for example, the detection device 300 and the measurement device 400) acquires the test results (ST21) and uses the test results as exposure risk-related information. (ST22). Note that, as shown below, information regarding these tests can be acquired through cooperation between the testing device 500, the server 100, and the first terminal device 200A.

An example of an ATP test will be explained.
In this operation example, a detection example using an ATP wiping method using a detection device 300 capable of detecting ATP using a chemiluminescence method and reading the detection result will be given. In this operational example, the examiner can, for example, select a site to be tested that has a risk of contact infection in the target evaluation item, and collect a test sample from the site to be tested. The test sample is collected by wiping the surface of the test target region with a predetermined collection tool. The inspector sets the sampling tool on the detection device 300 and operates the detection device 300 to start the detection process. Thereby, the detection device 300 can acquire the detection result.

Next, the examiner logs into the infection support countermeasure application using the first terminal device 200A, selects store A on the target area selection screen 201, and selects the test item selection screen, as in the case of behavioral testing. In 202, an ATP test to be tested is selected (FIGS. 5(A) and (B)). Thereby, the display unit 26 of the first terminal device 200A displays, for example, an evaluation item selection screen to be subjected to the ATP test. The evaluation item selection screen may be configured similarly to the evaluation item selection screen in FIG. 6(A). For example, the examiner selects a scene to be inspected on the evaluation item selection screen, and causes the display unit 26 to display an inspection object setting screen 212 (FIG. 9(A)).

The inspection target setting screen 212 illustrated in FIG. 9A includes, for example, an area information selection field 212a where the inspection target is located, an inspection information display field 212b for each inspection target, a map position registration button 212c, and a detection device connection button. 212e etc. The inspection information display column 212b includes, for example, measurement buttons 212d for each inspection target part of the inspection object. Information about the object to be inspected and its parts may be registered in advance in the target area database of the server 100, or may be registered by the examiner on the inspection object registration screen. Furthermore, if the map information of the target area is registered in the target area database in advance, the inspector can select the map position registration button 212c to register the position information of the inspection target on the map. For example, the examiner selects the detection device connection button 212e to display the detection device connection screen 213 on the display unit 26 (FIG. 9(B)).

The inspector can select the detection device 300 that has obtained the detection result from among the detection devices 300 included in the detection device connection screen 213 illustrated in FIG. 9(B). Thereby, the selected detection device 300 can transmit information about the ATP detection result associated with the identification information of the detection device 300 to the server 100 via the Internet N. The first terminal device 200A can, for example, receive information about the ATP detection result from the server 100 and display the test result registration screen 214 on the display unit 26 (FIG. 9(C)).

The test result registration screen 214 illustrated in FIG. 9C includes, for example, a test information display field 214a, a test object selection field 214b, a test target region registration field 214c, a detection result information display field 214d, a comment input field 214e, and a confirmation field. It includes a button 214f and the like. The inspection information display field 214a includes information such as the date and time of measurement, the name of the inspector, and the area of the object to be inspected. The test result information display column 214d displays, for example, information on detection results obtained from the connected detection device 300 (for example, quantitative information (positive/negative, etc.) and/or qualitative information (detection values, etc.)) including. The examiner can register information on the test object and its part corresponding to the detection result using the test object selection field 214b and the test target region registration field 214c. After registering all test results, the examiner selects, for example, the confirm button 214f.

Thereby, the first terminal device 200A provides basic information of the examination (examination date and time, name of the examiner, examination area, name and/or image of the object to be examined, name of the part to be examined, and /images, etc.), and can transmit this information to the server 100 in association with test result information.

Next, CO ₂ inspection will be explained.
The inspector can install the measuring device 400 that measures the CO ₂ concentration in the air, for example, in an area (eg, eating area) corresponding to the evaluation item (eg, conversation scene) of the target area. The inspector can use the first terminal device 200A to perform an input operation for starting measurement with the measuring device 400, an input operation for associating the identification information of the measuring device 400 with information such as the installation position, and the like.

Next, as in the behavioral test example, the examiner logs into the infection support countermeasure application using, for example, the first terminal device 200A, selects store A on the target area selection screen 201, and selects the test item selection screen 202. Select the CO ₂ test to be tested (FIGS. 5(A) and (B)). Next, the display unit 26 of the first terminal device 200A displays, for example, an evaluation item selection screen for CO ₂ measurement. The evaluation item selection screen may be configured similarly to the evaluation item selection screen in FIG. 6(A). For example, the inspector selects a scene to be inspected on the evaluation item selection screen, and causes the display unit 26 to display the measurement device setting screen 215 (FIG. 10(A)).

The measuring device setting screen 215 illustrated in FIG. 10A includes, for example, an area information selection field 215a where the measuring device 400 is located, an identification information display field 215b of the measuring device 400, a measurement button 215c of each measuring device 400, a measuring device 400 additional buttons 215d and the like. When registering a new measuring device 400, the inspector selects the add button 215d to display the measuring device registration screen 216 on the display unit 26, and enters the identification information of the measuring device 400 ( (serial number, etc.) can be input.

Thereby, the first terminal device 200A can receive input of information such as position information and identification information of the measuring device 400, associate these pieces of information, and transmit the information to the server 100.

On the measurement device setting screen 215, the inspector selects, for example, the measurement button 215c corresponding to the measurement device 400 with which to start measurement. Thereby, the selected measurement device 400 acquires the measurement result of the CO ₂ concentration, and transmits information about the measurement result associated with the identification information of the measurement device 400 to the server 100 via the Internet N. be able to.

As shown in FIG. 4, the CPU 11 of the server 100 receives (obtains) exposure risk-related information transmitted from, for example, the first terminal device 200A and the inspection device 500 (the detection device 300 and the measurement device 400) (ST31). For example, this information is stored in the target area database of the storage unit 18.

(Exposure risk evaluation process)
As shown in FIG. 4, the CPU 11 evaluates the exposure risk for each of the plurality of evaluation items based on the exposure risk related information (ST32). In this operation example, the CPU 11 can evaluate each scene, which is an evaluation item, using exposure risk related information associated with the evaluation item. In the evaluation of each evaluation item, the CPU 11 may, for example, evaluate the exposure risk based on each test result, and derive the evaluation result of each evaluation item based on these evaluation results. Alternatively, the CPU 11 can apply all test results corresponding to an evaluation item to a machine learning model or the like to derive an evaluation result for the evaluation item. In this operational example, the exposure risk evaluation result may be derived as an exposure risk index that is an index of exposure risk, for example. The exposure risk index may be expressed as a numerical value (score) or as a rank other than a numerical value.

The CPU 11 may evaluate the exposure risk using, for example, a machine learning model for deriving the evaluation result from the exposure risk related information. Alternatively, the CPU 11 may evaluate the exposure risk using a table stored in the storage unit 18 that associates test results with evaluation results corresponding thereto. Further, as described later, the CPU 11 may evaluate the exposure risk using a simulation model that simulates the exposure risk from information included in the exposure risk related information. From the viewpoint of increasing the speed of information processing for deriving evaluation results, it is more preferable to use a table, a simulation model, or a combination thereof.

In this operation example, the CPU 11 can evaluate the exposure risk of each evaluation item based on at least one exposure risk related information selected from the behavioral risk information and environmental risk information corresponding to each evaluation item. For example, the CPU 11 may calculate an exposure risk index from each test result acquired as exposure risk related information for each evaluation item. Alternatively, the CPU 11 may calculate at least one selected from the total value, average value, maximum value, median value, etc. of the exposure risk index calculated from each test result. Further, the CPU 11 may calculate an exposure risk index for each infection route for each evaluation item from the test results corresponding to each infection route. In addition, when adding up the exposure risk index derived from different test results, the CPU 11 multiplies the exposure risk index derived from each test result by a coefficient according to the degree of importance (for example, degree of contribution, etc.) to the exposure risk. The calculated value can be calculated and the calculated value can be added.

An example of evaluation processing using behavioral risk information will be explained.
In this operational example, the CPU 11 can evaluate the exposure risk based on the behavioral risk information acquired through the behavioral test. Specifically, in this operation example, the CPU 11 evaluates the exposure risk of one or more sample contacts (test subjects and/or contacts) based on information regarding the contact scene corresponding to each evaluation item. I can do it. In this operation example, the behavioral risk information regarding the contact scene includes, for example, basic information about the behavioral test (information about the target area, evaluation item (scene), test date and time, tester, etc.), behavioral risk information about the test subject ( Information on age groups, whether masks are worn, volume of voice, breathing volume, hand hygiene, cleaning, length of stay in contact situations, etc.), behavioral risk information about contacts (age groups, whether masks are worn, test targets, etc.) information such as the distance to the person, presence or absence of a partition, etc.).

Specifically, for example, the CPU 11 assumes that at least one of the sample subjects is a carrier subject who carries an infectious microorganism, and based on the behavioral risk information and the infection route of the infectious microorganism, By simulating the exposure risk of non-carrying subjects, who are other sample subjects, it is possible to evaluate the exposure risk in contact situations. In this operation example, assuming that the person to be tested is a carrier and the contact person is a non-carrier, the amount of virus transferred from the person to be tested and/or the environment to the contact is simulated. The risk of exposure to the virus can be assessed.

Further, when the contact scene includes three or more sample subjects, the CPU 11 divides the contact scene into a plurality of contact events including one sample subject and one non- sample subject, and for each contact event, It is possible to calculate the exposure risk index, which is an index of the exposure risk of the subject. Then, the CPU 11 can evaluate the exposure risk in the contact scene based on the calculated exposure risk index for the plurality of contact events. Specifically, the CPU 11 calculates the exposure risk in the contact scene by calculating at least one selected from the total value, average value, maximum value, median value, etc. of the exposure risk index for a plurality of contact events. can be evaluated.

As used herein, a contact event is an event in which all sample subjects making up a contact scene come into one-on-one contact with one other sample contact person. As used herein, the exposure risk index is an index of exposure risk, and may be, for example, at least one index selected from an estimated exposure amount of infectious microorganisms, an estimated exposure rate, an estimated positive rate, and the like.

An example of a contact event will be described using FIG. 11. FIG. 11A shows an example of the arrangement of three sample subjects observed on table 516A of store A. It is assumed that sample subjects H1, H2, and H3 are seated at table 516A in the store, and a conversation scene is in progress. In this example, one contact scene is a conversation scene in which sample subjects H1, H2, and H3 surround the table 516A during a certain time period. In addition, when test results regarding multiple contact situations are obtained for the same sample subject group, the CPU 11 evaluates the exposure risk based on the test results (behavioral risk information) regarding the contact situations in each time period. be able to. This makes it possible to accurately evaluate the risk of exposure in long-term contact situations.

As illustrated in FIG. 11(B), this contact scene includes a contact event V1 including sample subjects H1 and H2, a contact event V2 including sample subjects H1 and H3, and a contact event including sample subjects H2 and H3. It is classified as V3. In each of the contact events V1, V2, and V3, the CPU 11 calculates the exposure risk index of the non-carrying subject using a simulation model, with one sample subject as the carrying subject and the other sample subject as the non-carrying subject. Then, the CPU 11 calculates at least one selected from the total value, average value, maximum value, median value, etc. of the exposure risk index calculated for the contact events V1, V2, and V3, so that the It is possible to calculate an exposure risk index in a contact scene involving sample subjects H1, H2, and H3.

Furthermore, when behavioral risk information corresponding to multiple contact scenes is acquired for one evaluation item, the CPU 11 selects from the total value, average value, maximum value, median value, etc. of the exposure risk index for the multiple contact scenes. By calculating at least one of the following, it is possible to evaluate the exposure risk based on the behavioral risk information for the entire evaluation item.

In this embodiment, an appropriate simulation model can be selected based on the infection route of the infectious microorganism and the like. For example, the simulation model may be a probabilistic model or a deterministic model, or may be a combination of these models. Note that a specific example of the simulation model used in this operation example will be described later.

Next, an example of evaluation processing using environmental risk information will be explained.
In this operational example, the CPU 11 can evaluate the exposure risk due to the environment for each evaluation item, for example, based on the acquired environmental risk information.

For example, the CPU 11 can evaluate the exposure risk based on information about the detection results of infectious microorganisms in the environment. This makes it possible to assess the risk of exposure to infectious microorganisms from the environment. The evaluation result of exposure risk can be, for example, the detection result itself, or can be expressed as an exposure risk index that is an index of exposure risk. The CPU 11 may calculate the exposure risk index using, for example, a machine learning model for calculating the exposure risk index from the detection result. Alternatively, the CPU 11 may calculate the exposure risk index using, for example, a table stored in the storage unit 18 that associates detection results with corresponding exposure risk indexes. Further, the CPU 11 may calculate the exposure risk index using a simulation model that calculates the exposure risk index from the detection results.

In this operational example, the environmental risk information may include a plurality of detection results for one inspection target site. For example, in the above example, two types of detection results, amylase and ATP, can be obtained for the inspection target site "table surface". In this case, for example, the CPU 11 calculates each exposure risk index based on each detection result, and calculates at least one selected from the total value, average value, maximum value, median value, etc. It is possible to calculate the exposure risk index at the site to be inspected. In addition, if the importance (for example, reliability, contribution, etc.) of each of the plurality of detection results to the exposure risk is different, the CPU 11 may, for example, assign the exposure risk index calculated from each detection result according to the importance, etc. By calculating the value multiplied by a predetermined coefficient, and calculating at least one selected from the total value, average value, maximum value, median value, etc., the exposure risk index for one inspection target site is calculated. can do.

In this operational example, the environmental risk information may include, for example, information about detection results at a plurality of inspection target sites for each evaluation item. For example, in the above example, for the evaluation item "conversation", it is possible to obtain detection results for two inspection target parts, the "surface" and "edge" of the "table". In this case, the CPU 11 calculates an exposure risk index from each of the test results of a plurality of test target parts corresponding to the evaluation item, and calculates at least one of the total value, average value, maximum value, median value, etc. By calculating these, it is possible to calculate the exposure risk index for the inspection target site corresponding to the evaluation item. Note that if the risks of contact between the plurality of test target parts are different, the CPU 11 may, for example, apply a predetermined coefficient according to the contact risk to the index value calculated from the test results of each test target part. By calculating the multiplied value and calculating at least one selected from the total value, average value, maximum value, median value, etc., it is possible to calculate the exposure risk index for a plurality of inspection target sites.

In this operation example, the CPU 11 can evaluate the exposure risk, for example, based on information regarding the ventilation status of the space associated with each evaluation item. The CPU 11 can evaluate the exposure risk, for example, based on space-related indicators (for example, CO ₂ concentration, ventilation volume, air volume, wind speed, etc.) that indicate the ventilation status of the space.

For example, the CPU 11 may evaluate the exposure risk using a machine learning model for deriving the exposure risk index from the space-related index included in the environmental risk information. Alternatively, the CPU 11 may evaluate the exposure risk using, for example, a table stored in the storage unit 18 that associates space-related indicators with corresponding exposure risk indicators. Further, the CPU 11 may evaluate the exposure risk using a simulation model that derives the exposure risk index from the space-related index.

In this embodiment, when the environmental risk information includes location information corresponding to a space-related index, the CPU 11 can use the space-related index to evaluate the exposure risk in the evaluation item corresponding to the location information. In this operation example, for example, when the measuring device 400 that measures CO ₂ concentration is installed in the eating and drinking area, the CPU 11 uses the measurement results by the measuring device 400 to evaluate the exposure risk of each scene performed in the eating and drinking area. be able to. Further, the CPU 11 may evaluate the exposure risk due to the ventilation status for the evaluation item based on the correspondence between the position of the measuring device 400 and the area corresponding to the evaluation item.

(Priority determination process)
Subsequently, as shown in FIG. 4, the CPU 11 determines the priority of infection control measures against infectious microorganisms in the plurality of evaluation items based on the evaluation results of the exposure risk for each of the plurality of evaluation items (ST33). The priority may be expressed by a rank or by the priority order of evaluation items. For example, the CPU 11 can determine the priority of the evaluation items according to the exposure risk score. In this case, the CPU 11 may determine the priority order in descending order of the scores, or may determine the rank corresponding to the range of scores.

Table 2 shows the evaluation results of exposure risks for each situation and examples of their priorities. In this example, the exposure risk evaluation is expressed, for example, as a score for each scene (number in parentheses), and the priority is expressed as a five-level priority rank of A, B, C, D, and E. ing. Furthermore, as shown in Table 3, each priority rank is associated with a range of exposure risk scores.

As another example, the CPU 11 may determine the priority based on an evaluation result of exposure risk derived from exposure risk related information of high importance. The exposure risk-related information with high importance may be, for example, exposure risk-related information corresponding to a predetermined infection route, or may be exposure risk-related information corresponding to test results of a predetermined test. Specifically, the importance of exposure risk-related information can be set based on, for example, reliability of data, relevance to exposure risk and/or infection risk, ease of infection control, and the like. Exposure risk-related information with high importance used for priority processing may be set for each evaluation item, or may be the same for all evaluation items. Furthermore, exposure risk-related information with high importance may be stored in the target area database through setting registration by a user such as an administrator, for example. Alternatively, the CPU 11 may determine exposure risk-related information with high importance based on the infection route associated with the evaluation item. This makes it possible to determine the priority of infection control measures that are more useful. Furthermore, for example, when the administrator sets and registers the degree of importance, it becomes possible to determine the priority according to the needs of the administrator.

(Output processing of evaluation result related information)
Subsequently, the CPU 11 outputs evaluation result related information including information about the determined priority (ST34). In this operation example, the CPU 11 can transmit the evaluation result related information to the second terminal device 200B. The information related to the evaluation results may be transmitted using, for example, a notification function on an application or website that provides the above-mentioned infection control support service, or may be transmitted using e-mail or various messenger applications. good. The CPU 11 may output the output information to an external device such as a printer. Thereby, it is also possible to provide evaluation result related information to the administrator of the target area via paper media such as direct mail.

Further, the evaluation result related information may include information about the evaluation results of exposure risk for each of the plurality of evaluation items. Such information includes the exposure risk score and/or rank for each evaluation item, and the exposure risk score and rank derived from each test result related to each evaluation item.

In addition, the evaluation result related information may include analysis information on the exposure risk in the target area and/or evaluation item. The analysis information may include, for example, information such as a graph generated using the obtained test results and the derived exposure risk index data. Graphs include, but are not particularly limited to, graphs such as bar graphs, line graphs, bubble diagrams, Pareto diagrams, pie graphs, and radar charts. Furthermore, the analysis information may include information such as comments and explanations regarding the evaluation results.

The second terminal device 200B receives the evaluation result related information (ST41) and displays the received evaluation result related information on the display section 26 (ST42). In this operational example, the display section 26 of the second terminal device 200B functions as a "display section that displays evaluation result related information output from the control section."

As illustrated in FIG. 12, the display unit 26 may display, for example, a screen showing the evaluation result of exposure risk for each evaluation item (for example, scene) and the priority of infection control for each scene. Furthermore, the screen may include comments regarding the evaluation results. Further, the display unit 26 may display the priorities in different colors. Thereby, the user using the second terminal device 200B can intuitively understand the priority.

[Actions and effects of this embodiment]
According to the exposure risk assessment system of this embodiment, by outputting information regarding the priority of infection control measures for multiple evaluation items, it is possible to inform managers in charge of hygiene management of target areas that they should focus on infection control measures. Evaluation items (location, scene, time of day, etc.) can be clearly indicated. Although there are often a wide variety of items for infection control in a target area, the above configuration can reduce the effort of an administrator who performs hygiene management of a target area to determine which items to prioritize for infection control. Moreover, this makes it possible to reduce the processing load of data analysis and the like by the second terminal device 200B used by the administrator. Therefore, according to the system of this embodiment, it is possible to streamline infection control measures in the target area.

In addition, the behavioral risk information of the exposure risk-related information includes, for example, information about contact situations where multiple observed sample contacts come into contact, so that highly reliable information about high exposure risk behaviors can be used. exposure risk can be assessed. Thereby, it is possible to accurately evaluate exposure risk based on behavioral risk information. In addition, it is assumed that at least one of the sample subjects is a carrier subject who carries infectious microorganisms, and based on the behavioral risk information and the infection route of infectious microorganisms, it is assumed that at least one sample subject is a sample subject other than the carrier subject. By simulating the exposure risk of non-carrying subjects, it is possible to more accurately evaluate the exposure risk based on behavioral risk information.

Furthermore, when the plurality of sample subjects in the contact scene includes three or more sample subjects, the CPU 11 (control unit) converts the contact scene into a plurality of contact events including one possessing subject and one non-holding subject. By classifying the exposure risk index for non-carrying subjects for each contact event and summing the exposure risk index for multiple contact events, it is possible to accurately evaluate the exposure risk in the entire contact scene. . As a result, even in contact situations where there are three or more sample subjects, for each contact event where the sample subjects come into contact one-on-one, one person with the sample will transition from one person with the sample to one who does not have the sample. Infectious microorganisms can be quantitatively evaluated. This makes it possible to perform simulations that match actual infection situations, and to evaluate exposure risk more accurately.

[Modified example]
As shown in FIG. 13, the CPU 11 may determine the overall evaluation of the exposure risk in the target area based on the exposure risk information (ST35). The evaluation result relationship including at least information about and may be output (ST34).

For example, the CPU 11 may determine the overall evaluation of the exposure risk based on the evaluation results of the exposure risk derived for each of the plurality of evaluation items. For example, the CPU 11 determines the overall evaluation of the exposure risk by calculating at least one selected from the total value, average value, maximum value, median value, etc. of the exposure risk index calculated for each of the plurality of evaluation items. You may. In this case, the information about the comprehensive evaluation may include information about the calculated numerical value and/or rank of the exposure risk index. Furthermore, if information about the importance of each evaluation item is stored, the CPU 11 may determine the overall evaluation by referring to the information about the importance of each evaluation item. For example, the CPU 11 may calculate a value by multiplying the exposure risk index of each evaluation item by a coefficient determined based on the degree of importance, and use this value to determine the overall evaluation.

Alternatively, the CPU 11 may determine a comprehensive evaluation of the exposure risk in the target area based on the exposure risk related information, separately from the exposure risk evaluation process for each of the plurality of evaluation items. For example, the CPU 11 can determine a comprehensive evaluation of the exposure risk in the target area using exposure risk related information corresponding to one or more test results obtained in association with the target area. This comprehensive evaluation may be determined based on a plurality of test results, or may be derived based on each test result.

Thereby, referring to FIG. 4, the second terminal device 200B can receive evaluation result related information including information about the comprehensive evaluation (ST41) and display the received information on the display unit 26 (ST42). .

Further, the screen displayed on the display unit 26 is not limited to the example shown in FIG. 12, and may take various forms. Modified examples of the display screen will be described below.
As illustrated in FIG. 14, for example, the display unit 26 may display analysis information obtained by analyzing the exposure risk evaluation results in detail. The screen shown in the same figure includes behavioral risk information of a certain evaluation item (area A) and evaluation results and/or analysis results regarding the exposure risk when the evaluation items are divided into areas. This screen displays information about conversation time in a certain area A, information about the risk of exposure due to droplet infection based on behavior including conversation ("droplet risk"), and information about the risk of exposure due to contact infection based on the behavior ("contact risk"). ), and bubble diagrams showing examples of changes in droplet risk and contact risk depending on conversation duration. Thereby, the administrator using the second terminal device 200B can grasp the exposure risk due to the subject's actions in more detail.

As another display example of the exposure risk evaluation results, the display unit 26 illustrated in FIG. 15 displays a screen that displays the evaluation results and/or analysis results for the exposure risk due to the corresponding infection route for each evaluation item. It's okay. The screen shown in FIG. 15 includes information on amylase detection results for each evaluation item (here, area) and information on the amount of virus exposure derived based on the information. Furthermore, the screen may include a bar graph of the amount of virus exposure for each evaluation item as analysis information. Thereby, the administrator using the second terminal device 200B can intuitively understand evaluation items that have a high risk of exposure due to a predetermined infection route (for example, contact infection).

As another display example of the exposure risk evaluation results, as shown in FIG. 16, the display unit 26 may display a screen containing analysis information obtained by analyzing environmental risk information and/or the exposure risk evaluation results based on the environmental risk information. good. The screen shown in Figure 16 shows a radar chart showing the evaluation results of the ATP test and saliva droplet test for each test object corresponding to area A when the evaluation items are divided into areas, and a radar chart showing the evaluation results of the ATP test and saliva droplet test for each test object corresponding to area A, and A bar graph showing the evaluation results for each part.

Alternatively, as shown in FIG. 17, the display unit 26 may include a Pareto chart showing the evaluation results of the ATP test and saliva droplet test for each test object in a certain evaluation item (area B) as analysis information. good. By displaying the analysis results as shown in FIGS. 16 and 17, the administrator using the second terminal device 200B can clearly grasp the areas with high exposure risk on the environmental surface.

Further, the display unit 26 may display detailed information regarding the comprehensive evaluation. For example, the screen illustrated in FIG. 18 displays comprehensive evaluation information based on all test results for the target area (here, facility B), and the results of each of the behavioral tests, CO ₂ tests, ATP tests, and saliva droplet tests. Contains comprehensive evaluation information based on the. This makes it possible to evaluate the exposure risk of the target area from multiple perspectives, and more effectively support the administrator's infection control measures.

[Specific example of simulation model]
A specific example of a simulation model for simulating exposure risk based on behavioral risk information that can be used in this embodiment will be described. However, the simulation model used in this embodiment is not limited to the following example.

When a contact scene includes three or more sample subjects, this simulation model divides the contact scene into multiple contact events containing one sample subject and one non- sample subject, and for each contact event, This is a model that can calculate the exposure risk index of the person who holds it. Specifically, in this simulation model, in each contact event, the estimated amount of exposure to infectious microorganisms from a carrier target to a non-carrier target is calculated for each infection route. By summing up the estimated exposure amount calculated for each infection route, it is possible to calculate the estimated exposure amount to non-carrying subjects for each contact event.

In the following description, examples of infectious microorganisms such as viruses that are transferred via saliva droplets and the like will be given. Examples of such viruses include SARS-CoV-2. In this example, the infection route includes, for example, a long-distance infection route and a short-distance infection route. Long-distance infection routes include, for example, airborne infection and contact infection. The short-distance infection route includes, for example, droplet infection.

With reference to FIG. 19, a method for calculating the amount of exposure based on a long-distance infection route will be described.
As shown in the figure, in order to accurately estimate the amount of exposure due to long-distance infection routes, this simulation model divides the change in the virus over time into multiple states, and the transition between each state is expressed as a first-order reaction. Create a model and calculate the amount of virus transferred to non-carrying subjects as the exposure amount. The plurality of states include, for example, "Room Air", "Textile Surfaces", "Nontextile Surfaces", "Hands", and "Facial Membranes". ``Loss of Viability (inactivated virus)'' and ``Exhausted from Room.''

The state transition model shown in FIG. 19 can be described using ordinary differential equations shown in equations (1) to (8) below. In addition, the specific numerical values of the parameters in each of the following formulas may be set as appropriate with reference to known exposure risk simulation models, such as those disclosed in Non-Patent Document 1 and Non-Patent Document 2. I can do it.

In these equations, λ _ij is a transition rate constant when transitioning from state i to state j. Moreover, Q ₁ , Q ₂ , and Q ₃ are the amount of virus distributed to each state due to droplet generation events (coughing, sneezing, conversation, etc.) (the dimension is the amount of virus per unit [PFU/s]). In this simulation model, the virus distribution amounts Q ₁ , Q ₂ , and Q ₃ were determined as shown in equations (9) to (11) with reference to the model described in Non-Patent Document 1. In the following formula, Q _large and Q _small represent the volumes of large droplets and small droplets generated per unit time due to coughing, talking, sneezing, etc., respectively. C _saliva is the virus concentration ([PFU/mL]) contained in saliva. Furthermore, f _textile and f _nontextile are the ratios of fiber surfaces and hard surfaces in the environmental surface. By solving equations (1) to (11) under the initial conditions (initial viral load), changes over time in the viral load in each state can be obtained.

In this simulation model, the route of infection by inhaling droplet nuclei floating in the air is called "Respirable." The virus uptake amount D _respirable corresponds to N ₆ in FIG. 19.

Furthermore, in this simulation model, the route of infection caused by touching a contaminated environmental surface with one's fingers and touching the facial mucous membrane with the fingers is called "Hand Contact." The amount of virus uptake D _hand by Hand Contact corresponds to N ₅ in FIG. 19 .

Next, a method for calculating the amount of exposure due to short-distance infection routes will be explained. In this simulation model, two short-distance routes, for example, "Spray" and "Inspirable" are considered. Spray is ``a route of infection through large droplets generated by coughing, sneezing, and talking that land on mucous membranes.'' Inspirable is ``a route of infection through inhalation of small droplets generated by coughing, sneezing, and talking.''

In this simulation model, the amount of exposure due to spray can be estimated using the following concept.
(1) Droplets are ejected in a conical shape.
(2) Large particles contributing to the spray pass uniformly over the base area of the cone.
(3) The probability that a generated droplet will land on the mucous membrane can be expressed as the ratio of the "surface area of the mucous membrane" and the "base area of the cone."
(4) The infected person is close to the infected person at a certain frequency.
(5) The concentration of virus contained in saliva is constant regardless of the droplet diameter.

Based on this idea, the time change in the exposure amount D _spray due to spray is expressed by the following equations (14) and (15).

Here, Q _large is the total volume of large droplets generated per unit time by coughing, talking, and sneezing. In this example, only large droplets contribute to the spray. p _proximity is the frequency at which an infected person is near an infected person, and can be set to, for example, 0.05, with reference to Non-Patent Document 2.

In this simulation model, the exposure amount for Inspirable was estimated based on a cone, similar to Spray. The difference from Spray is that the small particles that contribute to Inspirable are uniformly suspended within the volume of the cone, and the probability of inhaling the generated droplets is determined by the ratio of "breathing frequency" and "breathing flow rate". There are two points that can be expressed. Based on this idea, the time change of the exposure amount D _spray due to Inspirable is expressed by the following equations (16) and (17). Note that 0.5 is the proportion of the liquid droplet sucked out of the suction volume.

Furthermore, in this simulation model, the infection risk can be calculated from the calculated estimated exposure amount.

For example, a dose-response model is known as a model that represents the probability of infection caused by a certain microorganism or virus. This model can be used when there is no threshold for infection establishment. In this simulation model, the infection risk (probability) can be estimated from the amount of virus exposure using, for example, an "exponential model" among dose-response models. In the exponential model, the relationship between virus exposure D _i and infection risk R _i is expressed as follows.

Here, the subscript i corresponds to route (Respirable, Hand Contact, Spray, Inspirable). Further, α _i is a parameter expressing the ease of infection. In this simulation model, since infection occurs in the lower respiratory tract in Respirable, the parameter α _i can be calculated separately from other infection routes (Hand Contact, Spray, Inspirable).

The total risk R _total , which takes into account the exposure amounts of all routes, can be determined by the inclusion-exclusion principle. By using the inclusion/exclusion principle, it is possible to calculate the infection risk in accordance with the reality that ``infection only occurs once'' without duplicating the infection risk from each route.

The contribution rate Φ _i of each route is defined, for example, by the following equation (22).

Thereby, the infection risk of each infection route can be calculated using equation (23) adjusted so that the sum of the infection risks of each route is equal to the total infection risk.

As described above, this simulation model uses a deterministic model with relatively fast calculation speed, and also calculates the estimated exposure amount for each infection route, so it can evaluate exposure risk with a fast processing speed. , and can be calculated with high accuracy.

<Second embodiment>
A second embodiment of this embodiment will be described below. Regarding this embodiment, descriptions of configurations similar to those of the first embodiment will be omitted as appropriate.

[System overview]
The system according to the second embodiment of the present invention can function as an infection control support system that supports infection control measures against infectious microorganisms in a target area. Similar to the first embodiment, the system includes a server 100 on the Internet N, a first terminal device 200A, and a second terminal device 200B, and further includes a detection device 300 and a measurement device as an inspection device 500. 400 (see FIG. 1).

In this embodiment, similar to the first embodiment, the server 100 acquires exposure risk related information related to the exposure risk in each of the plurality of evaluation items, and based on the exposure risk related information, Assess exposure risk. The difference from the first embodiment is that the server 100 generates advice regarding infection control measures to reduce the risk of exposure for at least one of the plurality of evaluation items, and generates advice regarding infection control measures to reduce the risk of exposure when the infection control measures are implemented. Anticipate risk. Thereby, the server 100 can output infection control support information including the exposure risk evaluation result, the generated infection control advice, and the exposure risk prediction result.

The hardware configuration of each device is, for example, configured similarly to the first embodiment (see FIGS. 2A and 2B). Furthermore, the storage unit 18 of the server 100 includes the same countermeasure area information database as in the first embodiment.

[System operation example]
Next, an example of the operation of the system configured as described above will be described using the sequence diagram of FIG. 20. The operations of the server 100 described below are executed by the cooperation of hardware such as the CPU 11 and the communication section 19, and software stored in the storage section 18. The same applies to other devices.

Also, in this operation example, as in the first embodiment, the target area is store A, which is a restaurant, and the infectious microorganism is a virus that causes an infectious disease through contact infection, droplet infection, airborne infection, etc. List. Further, in this operation example, the first terminal device 200A receives input of at least part of the exposure risk-related information (ST11), transmits at least part of the exposure risk-related information to the server 100 (ST12), A step in which the inspection device 500 acquires the test result (ST21), a step in which information about the measurement result is transmitted as part of the exposure risk-related information to the server 100 (ST22), and the server 100 acquires the exposure risk-related information (ST31) and the step (ST32) in which the CPU 11 evaluates the exposure risk for each of the plurality of evaluation items based on the exposure risk-related information are the same as in the first embodiment, so detailed explanation thereof will be omitted. do. This operation example differs from the first embodiment mainly in that the exposure risk evaluation results are used to generate advice regarding infection control, and furthermore, the exposure risk after infection control is predicted.

(Advice generation process)
In this operation example, after the priority determination step (ST33), the CPU 11 generates advice regarding infection control measures to reduce the evaluated exposure risk for at least one evaluation item among the plurality of evaluation items. (ST35).

For example, the CPU 11 may generate advice regarding infection control for each of all evaluation items for which exposure risk was evaluated. Alternatively, the CPU 11 may generate advice regarding infection control for at least one evaluation item selected based on the evaluation result of exposure risk. Alternatively, the CPU 11 may generate advice regarding evaluation items that have been evaluated as having a high exposure risk. For example, if the target area database stores information about the importance of evaluation items, the CPU 11 may generate advice regarding infection control for evaluation items with high importance.

Further, as described in the first embodiment, for example, when the CPU 11 determines the priorities of multiple evaluation items (see ST33 in FIG. 4), advice regarding infection control for the evaluation item with the higher priority is provided. May be generated. This makes it possible to present specific improvement measures for evaluation items with high priority.

In this step, the CPU 11 can select an infection countermeasure in the evaluation item for which advice is to be generated. For example, the CPU 11 may select infection control measures stored in association with evaluation items for which advice is to be generated. Alternatively, if information on the infection route for each evaluation item and information on infection control measures associated with the infection route are stored, the CPU 11 uses the infection control measures corresponding to the infection route of the evaluation item for which advice is to be generated. may be selected. In this case, the CPU 11 can select, for example, an infection route corresponding to an infection route evaluated to have a high exposure risk.

Furthermore, if the target area database stores the importance of evaluation items and/or infection routes, the CPU 11 can select infection countermeasures for evaluation items and/or infection routes with high importance. Furthermore, if information about the effort and/or cost for each infection control measure is stored, the CPU 11 selects an infection control measure that falls within the range of allowable effort and/or cost registered by the administrator, etc. It's okay.

Infection control measures against contact infection include, for example, implementation of infection control actions, and specific examples include cleaning, wearing a mask (for example, wearing a non-woven mask), and hand hygiene. Infection prevention measures against droplet infection include, for example, wearing a mask (e.g., wearing a non-woven mask), refraining from talking, installing partitions, improving ventilation efficiency, and means of indicating the location of each other (posters, marks indicating the location, etc.) ), etc.

As another example, the CPU 11 can select infection control measures related to the subject's behavior and/or infection control status included in the behavioral risk information. Examples of the target person's behavior included in the behavioral risk information include whether or not the person has a conversation or not, the duration of the conversation, whether the person wears a mask, the type of mask, the volume of the voice, the amount of breathing, hand hygiene, cleaning behavior, and the like. In addition, examples of the infection control status include installation of partitions, ventilation status (ventilation amount, number of ventilation, etc.). For example, the CPU 11 can select an infection control measure to improve at least one of the above behavior and/or infection control situation.

Subsequently, the CPU 11 can generate advice for each selected infection control measure. For example, the CPU 11 may generate advice using a fixed phrase stored in association with the selected infection control measure. Preferably, the fixed phrase is prepared for each infection control measure, for example. Alternatively, the CPU 11 may generate advice using keywords stored in association with the selected infection control measures. In this case, the CPU 11 can generate advice using, for example, a known text generation technique that automatically creates texts based on keywords.

(Exposure risk prediction processing)
The CPU 11 predicts the exposure risk for the evaluation item after implementing infection control measures (ST36). For example, the CPU 11 changes the value of at least one parameter corresponding to the selected infection control measure included in the exposure risk related information, and evaluates the exposure risk using the changed parameter value in the same manner as in step ST32. By doing so, the risk of exposure can be predicted. The value of the parameter here is not limited to an actual numerical value, but includes indicators that can be quantified, such as "present" and "absent", "high" and "low".

For example, parameters included in the behavioral risk information include parameters regarding the subject's behavior and/or infection control status. Parameters regarding the subject's behavior include, for example, whether or not the subject had a conversation or not, the duration of the conversation, whether or not the person wore a mask, the type of mask, the volume of his/her voice, the amount of breathing, whether or not he/she performed hand hygiene, and whether or not he/she performed cleaning activities. Parameters regarding the infection control status include, for example, whether partitions are installed or not, ventilation status (ventilation amount, number of ventilation, etc.). The parameter to be changed may be one or more of these. For example, when "wearing a mask" is selected as an infection control measure, the CPU 11 changes the parameter "whether or not to wear a mask" from the current "no mask" to "with mask" and performs the same process as in the evaluation step (ST32). Exposure risk can be assessed.

Parameters included in the environmental risk information include, for example, detection indicators for detection of infectious microorganisms, and specifically include detection indicators for saliva-containing components, ATP detection indicators, and the like. The parameter to be changed may be one or more of these. If the selected infection control measures include infection control measures related to these detection results (cleaning, hand hygiene, etc.), the CPU 11 changes the detection index regarding infectious microorganisms to a more preferable value, for example, and performs the evaluation step (ST32). Exposure risk can be assessed similarly.

Other parameters included in the environmental risk information include indicators related to ventilation status, specifically, ventilation volume, ventilation frequency, etc. When the selected infection control measures include infection control measures for ventilation conditions, the CPU 11 can, for example, change the index regarding the ventilation conditions to a more preferable value and evaluate the exposure risk in the same manner as in the evaluation step (ST32).

(Output processing of infection control support information)
Subsequently, the CPU 11 outputs infection control support information including an evaluation result of exposure risk, advice regarding infection control, and a prediction result of exposure risk (ST37). Note that the infection control support information may include analysis information obtained by analyzing exposure risk evaluation results and/or prediction results. In this operation example, the CPU 11 can transmit the infection control support information to the second terminal device 200B. Examples of the method for outputting the infection control support information include the same method as for the evaluation result related information according to the first embodiment.

Further, the infection control support information may include a comprehensive evaluation of exposure risk in the target area, which was described as a modification of the first embodiment.

Thereby, the second terminal device 200B can receive the infection control support information (ST43) and display the received information on the display section 26 (ST44). In this operational example, the display section 26 of the second terminal device 200B functions as a "display section that displays infection control support information output from the control section."

As shown in FIG. 21, the display unit 26 can display a screen including, for example, the evaluation results of exposure risk for each evaluation item (for example, scene), the prediction results of exposure risk, and advice regarding infection control. I can do it. This makes it possible to clearly show changes in exposure risk before and after infection control measures for each evaluation item, making it possible to provide persuasive advice. The screen may also include a comprehensive assessment of exposure risk. Further, the screen may include the infection control priorities for each scene (for example, A, B, C, D, E), and the display unit 26 may display the priorities in different colors.

[Actions and effects of this embodiment]
According to the infection control support system in this embodiment, it is possible to generate exposure risk evaluation results and advice regarding infection control for each of a plurality of evaluation items, and further predict and output the exposure risk after implementation of infection control measures. This can increase the persuasiveness of the necessity of infection control measures. In addition, by presenting advice on infection control measures, infection control measures can be clearly recommended. Furthermore, with the above configuration, it is possible to reduce the effort required by the administrator to determine specific infection control measures, such as analysis of exposure risk before and after infection control measures, and processing such as analysis processing by the second terminal device 200B. The burden can be reduced. Therefore, according to the system of the present embodiment, infection control measures in the target area can be made more efficient, and the burden of infection control measures on administrators and the like can be reduced.

[Modified example]
As illustrated in FIG. 22, the advice generation step (ST35) may be performed after the exposure risk prediction step (ST36). In this case, the CPU 11 selects an infection control measure to reduce the evaluated exposure risk for at least one evaluation item among the plurality of evaluation items, and selects an infection control measure to reduce the evaluated exposure risk after implementing the infection control measure. can be predicted (ST36). Thereafter, the CPU 11 can generate advice regarding infection control (ST35). This also allows the CPU 11 to output similar infection control support information.

Further, the screen displayed on the display unit 26 is not limited to the example shown in FIG. 21, and may take various forms. Modified examples of the display screen will be described below.
For example, as shown in FIG. 23, the display unit 26 displays analysis information including a graph showing the relationship between the presence or absence of infection control measures (for example, wearing a mask) and the risk of exposure for each evaluation item (for example, scene), and A screen including advice recommending countermeasures (for example, wearing a mask) may be displayed. This makes it possible to provide persuasive advice on infection control while presenting the results of exposure risk analysis.

For example, as shown in FIG. 24, the display unit 26 can display analysis information of evaluation results and analysis information of prediction results for a certain evaluation item. The screen shown in FIG. 24 includes, for example, analysis results (for example, a bubble diagram) regarding the risk of exposure to contact infection before and after infection control measures for a certain evaluation item (reduction in conversation time, reduction in residence time, reduction in droplet-generating behavior). This makes it possible to more clearly demonstrate the risk of exposure before and after infection control measures. Note that in this case, the display unit 26 can display advice on another display screen.

<Other embodiments>
Although the embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments, and various changes can be made without departing from the gist of the present invention. For example, the contents described in each embodiment may be implemented in combination as much as possible.

In the operation example in the above embodiment, four tests, namely a behavior test, a saliva droplet test, an ATP test, and a CO ₂ concentration measurement test, were illustrated as tests for acquiring exposure risk related information, but the present invention is not limited to these. . Furthermore, the number of tests for acquiring exposure risk-related information is not limited to multiple types, and may be one type.

Further, when the behavioral risk information includes information about the attributes of the sample subjects observed in the contact scene, the CPU 11 controls the behavior of the sample subjects classified based on the attributes. Exposure risk may be assessed and/or predicted based on Attributes of the sample subjects include attributes related to exposure risk, risk of aggravation, and/or risk of onset, such as age group, role, occupation, and diseases related to risk of exposure, risk of severity, and/or risk of onset. The prevalence, pre-existing disease rate, morbidity rate, etc.

The screen illustrated in FIG. 25 includes, for example, a bubble diagram that analyzes the exposure risk results of droplet infection at a chorus event at facility B. The screen classifies the sample subjects into, for example, chorus members, audience members, and staff members, and includes evaluation results of the risk of exposure to droplet infection for each of them. Furthermore, the screen includes prediction results of exposure risks, etc., such as when any one group wears masks 100% of the time, when the audience is separated from each other, etc. As a result, evaluation results can be obtained for each group of sample subjects with different risks of exposure and risk of worsening, and infection control can be made more efficient.

The exposure risk evaluation and/or prediction process by the CPU 11 may use information regarding the infectivity and/or danger of infectious microorganisms in addition to the exposure risk related information. Such information includes, for example, information on infectious diseases caused by infectious microorganisms (symptoms of infectious diseases, risk grades, etc.), correspondence tables between test results and risk grades, exposure risk simulations using dose-response functions, etc. Information on the titer of infectious microorganisms as a parameter used for (50% infectious dose, infectious dose, etc.), information on the prevalence of infectious microorganisms (community infection rate, number of infected people, etc.), infectious microorganisms Information on the status of immunity acquisition (antibody possession rate, vaccination rate, etc.), etc. This information is stored, for example, in the storage unit 18, and can be appropriately referenced in the exposure risk evaluation and/or prediction process performed by the server 100.

Furthermore, the configuration of the system is not limited to the above example. For example, in a case where the administrator himself inspects the target area, one terminal device may have the functions of the input reception section and the display section. Furthermore, the inspection device 500 that constitutes the system is not limited to the above-mentioned example. Alternatively, the system may not have an inspection device.

11, 21...CPU
18, 28...Storage unit 100...Server (information processing device)
200A, 200B...terminal device 300...detection device 400...measuring device 500...inspection device

Claims (20)

An infection control support system that supports infection control measures against infectious microorganisms in a target area,
obtaining exposure risk related information related to the exposure risk of the infectious microorganism ;
The exposure risk in each of the plurality of evaluation items for evaluating the exposure risk classified by at least one element selected from the position in the target area, time, and behavior of the subject staying in the target area. , evaluate based on the exposure risk related information,
generating advice regarding infection control measures to reduce the evaluated exposure risk for at least one evaluation item among the plurality of evaluation items;
Predicting the exposure risk for the evaluation item after implementing the infection control measures,
An infection control support system comprising: a control unit that outputs infection control support information including an evaluation result of the exposure risk, the generated advice regarding the infection control, and a prediction result of the exposure risk. The evaluation item is associated with at least one infection route by the infectious microorganism,
The infection control support system according to claim 1, wherein the exposure risk related information includes information related to the exposure risk due to the infection route corresponding to each of the plurality of evaluation items. The exposure risk related information is
The infection control support system according to claim 1, further comprising behavioral risk information regarding behavior related to the exposure risk of the subject in a situation corresponding to at least one evaluation item among the plurality of evaluation items. The behavioral risk information is
The infection control support system according to claim 3, further comprising information regarding contact scenes in which a plurality of sample subjects as the subjects come into contact, which are observed in situations corresponding to the evaluation items. The behavioral risk information is
At least one selected from the sample subject's stay time in the contact scene, the droplet generation behavior of the sample subject in the contact scene, the positional relationship between the sample subjects in the contact scene, and the infection control situation in the contact scene. The infection control support system according to claim 4, wherein the infection control support system includes information about one. The control unit includes:
Assuming that at least one of the sample subjects is a carrier subject who carries the infectious microorganism, and based on the behavioral risk information and the infection route of the infectious microorganism, the sample other than the sample subject is The infection control support system according to claim 5, wherein the exposure risk in the contact scene is evaluated by simulating the exposure risk of the non-carrying subject who is the subject. The control unit includes:
When the plurality of sample subjects in the contact scene include three or more sample subjects,
The contact scene is divided into a plurality of contact events including one person who is the subject of the disease and one person who is not the subject of the disease, and for each of the plurality of contact events, an exposure that is an index of the exposure risk of the subject who is not the subject of the disease is determined Calculate risk indicators,
The infection control support system according to claim 6, wherein the exposure risk in the contact scene is evaluated based on the calculated exposure risk index for the plurality of contact events. The exposure risk related information is
The infection control support system according to claim 1, further comprising environmental risk information related to the exposure risk caused by the environment corresponding to at least one evaluation item among the plurality of evaluation items. The infection control support system according to claim 8, wherein the environmental risk information includes information about detection results regarding the infectious microorganism in the environment. The infection control support system according to claim 9, wherein the environmental risk information includes information about detection results of saliva-containing components in the environment. The infection control support system according to claim 9 or 10, wherein the environmental risk information includes information about the detection result of ATP in the environment. The infection control support system according to claim 8, wherein the environmental risk information includes information regarding the ventilation status of the space within the target area . The infection control support system according to claim 1, wherein the plurality of evaluation items correspond to a plurality of scenes classified based on the behavior of the subject regarding the exposure risk. The infection control support system according to claim 1, wherein the plurality of evaluation items correspond to a plurality of areas divided in the target area, respectively. The infection control support information further includes:
Includes information about at least one selected from the comprehensive evaluation of the exposure risk in the target area determined based on the evaluation results of the exposure risk in each of the plurality of evaluation items and the exposure risk related information. The infection control support system described in Section 1. The infection control support system further includes:
The infection control support system according to claim 1, further comprising a display unit that displays the infection control support information output from the control unit. The infection control support system further includes:
The infection control support system according to claim 1, further comprising an input reception unit that receives input of at least part of the exposure risk related information. The infection control support system according to claim 1, wherein the infectious microorganism includes at least one selected from viruses, bacteria, protozoa, and fungi. An infection control support method for supporting infection control measures against infectious microorganisms in a target area, the method comprising:
The control unit of the information processing device
obtaining exposure risk related information related to the exposure risk of the infectious microorganism ;
The exposure risk in each of the plurality of evaluation items for evaluating the exposure risk classified by at least one element selected from the position in the target area, time, and behavior of the subject staying in the target area. , evaluate based on the exposure risk related information,
generating advice regarding infection control measures to reduce the evaluated exposure risk for at least one evaluation item among the plurality of evaluation items;
Predicting the exposure risk for the evaluation item after implementing the infection control measures,
An infection control support method that outputs infection control support information including the evaluation result of the exposure risk, the generated advice regarding the infection control, and the prediction result of the exposure risk. This is a program to support infection control measures against infectious microorganisms in the target area.
obtaining exposure risk related information related to the exposure risk of the infectious microorganism ;
The exposure risk in each of the plurality of evaluation items for evaluating the exposure risk classified by at least one element selected from the position in the target area, time, and behavior of the subject staying in the target area. , evaluating based on the exposure risk related information;
generating advice regarding infection control measures to reduce the evaluated exposure risk for at least one evaluation item among the plurality of evaluation items;
predicting the exposure risk for the evaluation item after implementing the infection control measures;
outputting infection control support information including the exposure risk evaluation result, the generated advice regarding the infection control, and the exposure risk prediction result;
A program to run.

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