CN107277763B - Infectious disease prevention and control method and system - Google Patents
Infectious disease prevention and control method and system Download PDFInfo
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- 208000015181 infectious disease Diseases 0.000 title claims abstract description 125
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Abstract
the application relates to an infectious disease prevention and control method and system. The method comprises the following steps: identifying a high risk area of the infectious disease from the local risk of infection data; identifying a user accessing a high-risk area and the early leaving time, the late returning time, the home position, the position of a first destination after leaving the home and the position of a last destination before returning the home of the user according to the regular mobile phone data; and working out travel time prevention and control measures according to the active time of the disease infection source, and sending corresponding travel intervention information to the user by combining the local infection risk values of the early leaving time, the late returning time, the home position, the first destination position after leaving the home and the last destination position before returning the home of the user. According to the method and the device, the user is guided to adjust the travel time by sending the individually customized travel intervention information to the user, so that the input risk of a high-risk area is reduced.
Description
Technical Field
The application relates to the technical field of public health, in particular to an infectious disease prevention and control method and system.
Background
with the advance of urbanization in China, population density in urban areas is increased, the outgoing modes and the outgoing demands of residents in cities are increased, infectious diseases are easy to spread in the cities due to changes of urban environments, and timely, effective and targeted prevention and control measures are important in the cities. Since the concept of "precise medicine" was proposed in the beginning of the new year in 2015, the concept of "precise public health" was recently proposed, and the new concept provides a new direction for public health research and is greatly concerned by medical researchers and health practitioners. The accurate public health needs to be different from person to person, and differential and individual intervention measures are implemented at the correct time.
Because large-scale rule cell-phone data can provide higher spatial and temporal resolution to possess a large amount of user crowds, can be easier the analysis out user's trip time according to rule cell-phone data, combine the active level data of aedes mosquito further to analyze out the time and the region that the user is susceptible to infection, accomplish accurate prevention and control on the time dimension more easily. At present, the research of infectious disease prevention and control by using large-scale mobile phone data is still in the starting stage, and the existing research mainly considers the establishment of infectious disease prevention and control measures from the space perspective and hardly has infectious disease prevention and control measures from the time perspective. In the research, irregular call detailed record data is mainly adopted to analyze individual space-time characteristics, a city or a plurality of mobile phone base stations are used as prevention and control units to carry out travel control in a wide range of areas such as the world or the country, coarse-grained regulation and control are mainly carried out on certain crowds, and specific measures comprise reducing the number of flights of transportation means such as flights and trains among cities or spreading the safety level of infectious diseases in the city by means of influence of media so that individuals can spontaneously regulate and control their own travel routes to avoid the cities with high-level infection rates and the like.
in summary, the existing infectious disease prevention and control research has a large perfection space in the aspects of mobile phone data, research scale, prevention and control angle, prevention and control measures and the like, and the specific defects include:
Firstly, the used call detailed record mobile phone data is limited, complete individual space-time information is difficult to provide, and the irregular mobile phone data has randomness and short-term explosiveness and even can mislead the extraction of individual space-time characteristics.
secondly, the existing infectious disease prevention and control technology mainly aims at the prevention and control research of the national and regional level, and a prevention and control measure implementation unit generally aims at a certain city or a plurality of base stations and lacks a specific and effective prevention and control scheme aiming at the interior of the city.
third, most of the existing researches consider travel prevention and control measures from the space perspective, and lack the prevention and control measures for travel control from the time perspective.
Fourth, most of the existing prevention and control measures for infectious disease prevention and control research adopt methods of reducing the number of flights of transportation means such as flights and trains between cities or spreading the safety level of infectious diseases in cities by means of the influence of media, so that individuals can spontaneously regulate and control their own travel routes to avoid cities with high-level infection rates, and the like to perform travel control mainly aiming at the macro control of the population or the individuals can spontaneously avoid the infection, and customized travel control measures aiming at the individuals are lacked.
Disclosure of Invention
the present application provides a method and a system for preventing and controlling infectious diseases, which aim to solve at least one of the above technical problems in the prior art to a certain extent.
in order to solve the above problems, the present application provides the following technical solutions:
An infectious disease prevention and control method comprises the following steps:
Step a: identifying a high risk area of the infectious disease from the local risk of infection data;
Step b: identifying early leaving time, late returning time, home position, position of a first destination after leaving home and position of a last destination before returning home of a user accessing the high risk area and the user accessing the high risk area according to regular mobile phone data;
Step c: and working out travel time prevention and control measures according to the active time of the disease infection source, and respectively sending corresponding travel intervention information to the users visiting the high risk area by combining the early leaving time and the late returning time of the users visiting the high risk area, and the local infection risk values of the home position, the first destination position after leaving the home and the last destination position before returning the home.
The technical scheme adopted by the embodiment of the application further comprises the following steps: in the step b, the regular mobile phone data is regular mobile phone positioning data in hours.
The technical scheme adopted by the embodiment of the application further comprises the following steps: the step c further comprises the following steps: and respectively acquiring local infection risk values of the home position of the user visiting the high-risk area, the position of the first destination after leaving the home and the position of the last destination before returning home from local infection risk data.
the technical scheme adopted by the embodiment of the application further comprises the following steps: in the step c, the disease infection source is aedes, and the step of making the travel time prevention and control measure according to the active time of the disease infection source specifically comprises the following steps: taking a strategy of avoiding staying in a high risk area in the early activity time period of the aedes as a prevention and control measure for early leaving home; and taking a strategy of avoiding staying in a high-risk area in the late active period of aedes as a late home time prevention and control measure.
The technical scheme adopted by the embodiment of the application further comprises the following steps: in step c, the sending of the corresponding trip intervention information to the user visiting the high risk area specifically includes: the local infection risk value of the home location is represented by HomeRL, the local infection risk value of the location of the first destination after leaving home is represented by FirstRL, the local infection risk value of the location of the last destination before returning home is represented by LastRL, and the HomeRL and firsttrl and the HomeRL and LastRL are compared, respectively:
if FirstRL > - [ HomeRL, and the user's early departure time is earlier than the end time of the aedes early activity period, then send travel intervention information: "please leave home after the end time of the aedes early activity period";
if FirstRL < HomeRL and the user's early departure time is later than the start time of the aedes early activity period, then send travel intervention information: "please leave home before the start time of the aedes early activity period";
if LastRL > - [ HomeRL, and the user's late time of returning home is later than the start time of the Aedes mosquito late active time period, then the travel intervention information is sent: "please go home before the start time of the aedes late active period";
If LastRL < HomeRL and the user's late time to home is earlier than the end time of the Aedes mosquito late activity time period, then send travel intervention information: "please aedes late active time period to come home after the end time".
another technical scheme adopted by the embodiment of the application is as follows: an infectious disease prevention and control system comprising:
an area identification module: identifying a high risk area for the infectious disease from the local risk of infection data;
A user identification module: the mobile phone is used for identifying the early leaving time, the late returning time, the home position, the position of the first destination after leaving the home and the position of the last destination before returning the home of the user accessing the high risk area according to the regular mobile phone data;
The trip prevention and control module: the system is used for making travel time prevention and control measures according to the active time of disease infection sources, and respectively sending corresponding travel intervention information to the users visiting the high-risk areas according to the local infection risk values of the early leaving time, the late returning time, the home position of the user, the first destination position after leaving the home and the last destination position before returning the home.
the technical scheme adopted by the embodiment of the application further comprises the following steps: the regular mobile phone data is regular mobile phone positioning data taking hours as units.
the technical scheme adopted by the embodiment of the application further comprises a risk value acquisition module: and the local infection risk value is used for respectively acquiring the position of the home of the user accessing the high-risk area, the position of the first destination after leaving the home and the position of the last destination before returning home from the local infection risk data.
the technical scheme adopted by the embodiment of the application further comprises the following steps: the disease infection source is aedes, and the travel prevention and control module is used for making travel time prevention and control measures according to the active time of the disease infection source, and the travel time prevention and control measures are as follows: taking a strategy of avoiding staying in a high risk area in the early activity time period of the aedes as a prevention and control measure for early leaving home; and taking a strategy of avoiding staying in a high-risk area in the late active period of aedes as a late home time prevention and control measure.
The technical scheme adopted by the embodiment of the application further comprises the following steps: the step of sending corresponding trip intervention information to the user visiting the high risk area by the trip prevention and control module is specifically as follows: the local infection risk value of the home location is represented by HomeRL, the local infection risk value of the location of the first destination after leaving home is represented by FirstRL, the local infection risk value of the location of the last destination before returning home is represented by LastRL, and the HomeRL and firsttrl and the HomeRL and LastRL are compared, respectively:
If FirstRL > - [ HomeRL, and the user's early departure time is earlier than the end time of the aedes early activity period, then send travel intervention information: "please leave home after the end time of the aedes early activity period";
If FirstRL < HomeRL and the user's early departure time is later than the start time of the aedes early activity period, then send travel intervention information: "please leave home before the start time of the aedes early activity period";
If LastRL > - [ HomeRL, and the user's late time of returning home is later than the start time of the Aedes mosquito late active time period, then the travel intervention information is sent: "please go home before the start time of the aedes late active period";
if LastRL < HomeRL and the user's late time to home is earlier than the end time of the Aedes mosquito late activity time period, then send travel intervention information: "please aedes late active time period to come home after the end time".
compared with the prior art, the embodiment of the application has the advantages that: according to the infectious disease prevention and control method and system, the user is guided to adjust the travel time by sending the individually customized travel intervention information aiming at the user in the city, so that the input risk of a high-risk area is reduced, and the purpose of accurately preventing and controlling infectious diseases in a time angle is achieved. Compared with the prior art, the method has the following advantages:
1. By adopting regular mobile phone positioning data taking hours as units, more complete and reliable individual space-time characteristics can be obtained, and the feasibility of implementing accurate time prevention and control on individuals is ensured.
2. The prevention and control research is carried out in the city, so that the vacancy of implementing prevention and control in the city is filled.
3. The travel time prevention and control measures made in the time angle utilize the mobile phone to send personalized travel intervention information to the user, change the early-leaving time and the late-returning time of the user in the high risk area, effectively reduce the input risk value of the high risk area, and have obvious prevention and control effects on the spread of control diseases.
Drawings
FIG. 1 is a flowchart of an infectious disease prevention and control method according to an embodiment of the present application;
Fig. 2 is a schematic structural diagram of an infectious disease prevention and control system according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
according to the infectious disease prevention and control method and system, accurate high space-time resolution in regular mobile phone data is fully utilized, the travel time of a user is analyzed by the regular mobile phone data, travel time prevention and control measures aiming at individual personalized time angles are made in a city, accurate intervention aiming at the individually customized time angles in the city is achieved more accurately, and scientific guidance and basis can be provided for prevention and control work of future infectious disease outbreaks in the city.
Specifically, please refer to fig. 1, which is a flowchart illustrating an infectious disease prevention and control method according to an embodiment of the present application. The infectious disease prevention and control method comprises the following steps:
step 100: identifying a high risk area of the infectious disease from the local risk of infection data;
In step 100, the high risk area refers to an area with a high local risk probability value, and the local risk data is a grid risk map which is obtained through a random forest model and is composed of case data and various environmental factors influencing the survival of aedes mosquitoes.
Step 200: identifying users accessing high risk areas according to the regular mobile phone data;
in step 200, the regular mobile phone data records the mobile phone location data of the user location once per hour.
step 300: identifying the early leaving time, the late returning time, the home position, the position of the first destination after leaving the home and the position of the last destination before returning the home of each user by accessing the mobile phone track data of the users in the high risk area;
In step 300, the location of the user's home, the location of the first destination after leaving the home, and the location of the last destination before returning home for accessing the high risk area may be obtained from the user's cell phone trajectory data.
Step 400: respectively acquiring local infection risk values of three positions, namely the position of the home of the user, the position of the first destination after leaving the home and the position of the last destination before returning home, from the local infection risk data;
in step 400, when identifying local infection risk values of the location of the user's home, the location of the first destination after leaving home, and the location of the last destination before returning home, since the local infection risk data is grid data of 100m, the mobile phone trajectory data is the location of a base station, and one base station usually covers multiple grids, the present application randomly selects 100 local infection risk values within the base station ranges of the location of the user's home, the location of the first destination after leaving home, and the location of the last destination before returning home, and then respectively selects the mean value of the random data as the local infection risk values of the location of the user's home, the location of the first destination after leaving home, and the location of the last destination before returning home.
step 500: and respectively making travel time prevention and control measures according to the active time of the disease infection source, and respectively sending corresponding travel intervention information to the users visiting the high-risk area according to the early leaving time, the late returning time, the home position of the user, the position of the first destination after leaving the home and the local infection risk value of the position of the last destination before returning the home.
In step 500, the disease infection source is aedes or other virus transmission media, and since the user's trip causes input risk and the disease has strong infectivity in a high risk area, the final purpose of the trip time prevention and control measures in the present application is to utilize the mobile phone to send trip intervention information customized for the individual to the user visiting the high risk area to guide the user to adjust the time of leaving or returning home in the morning and evening, so that the residence time of the part of people in the high risk area during the period of the disease infection source activity can be reduced, thereby reducing the input risk in the high risk area. Wherein, the input risk data is obtained by calculating the individual infection probability at different moments by using the local infection risk value and the mosquito media activity intensity and accumulating and summing the probabilities, and the calculation formula of the input risk data is as follows:
In formula (1) and formula (2), Pri represents the probability value of the infection of the user i who visits the polygon, rl (t) is the local risk value of the infection of the user at the position of t hours, and a (t) represents the activity intensity of the infection source of the disease at the time period.
Taking aedes as an example, through research, the active time of biting of the aedes is mainly concentrated in two peak periods of the morning and the evening, and the specific active time periods are respectively 5: 00 to 8: 00 and 18 in the evening: 00 to 20: 00. In the daily travel activities of most users, the time period of leaving home in the morning and returning home in the evening is just similar to the morning and evening active time period of aedes mosquito. Therefore, the travel time prevention and control measures are divided into two types according to two active time periods of the aedes, the travel intervention information is sent to the user by combining the local infection risk value and the travel time of the user, the time of leaving or/and returning the user is changed by taking hours as a time unit, the input risk caused by travel is reduced, and accurate prevention and control in a time angle is achieved.
Specifically, the method comprises the following steps: the first category is to avoid the situation in the morning 5: 00 to 8: the strategy that the early active period of aedes mosquito of 00 stays in a high risk area is taken as a prevention and control measure for early leaving home time: for morning 5: 00 to 8: 00, sending early departure intervention message of 'please leave home before/after morning a' informing the user to change the time of leaving home in the morning, thereby reducing the user staying in the high risk area during the period of aedes mosquito activity. Sending information to regulate the user to have morning according to the daily travel activity rule of the user 5: 00, the difficulty of leaving home is great, therefore, the application selects 5: 00 as the starting time for the preventive measure. The local infection risk value of the home position is represented by HomeRL, the local infection risk value of the first destination position after leaving home is represented by FirstRL, the HomeRL and the FirstRL are compared with the leaving home time of the user, and the sent early leaving home intervention information is as follows:
if FirstRL > ═ HomeRL and the user's early departure time is earlier than the end time of the aedes early active period (i.e., 8: 00 a.m.), then trip intervention information is sent: "please leave home after the end time of the aedes early activity period (i.e., after 8: 00 a.m.);
if FirstRL < HomeRL and the user's early departure time is later than the beginning time of the aedes early activity period (i.e. 5: 00 a morning), then send a trip intervention message: "please leave home before the start time of the aedes early activity period" (i.e., 5: 00 a.m.).
The second category is that the night 18: 00 to 20: the strategy that the mosquito of 00 stays in a high risk area in the late active time period is taken as a late home time prevention and control measure: for night 18: 00 to 20: 00, and sending a night-to-home intervention message of 'please go home before/after night Tmax', informing the user to change the time to go home at night, thereby reducing the user staying in the high risk area during the period of the mosquito activity. The local infection risk value of the position of the last destination before returning home is expressed by LastRL, HomeRL and LastRL are compared with the time of returning home of the user, and the transmitted late-returning-home intervention information is as follows:
if LastRL > -, HomeRL and the user's late time to home is later than the beginning time of the aedes mosquito late active period (i.e., 18: 00 pm), then trip intervention information is sent: "please return home before the start time of the aedes late active period (i.e., 18: 00 pm);
if LastRL < HomeRL and the user's late time to home is earlier than the end of the Aedes mosquito late active period (i.e., 20: 00 pm), then travel intervention information is sent: "please aedes late active time period to end time (i.e. after 20: 00 pm) to come home".
In the above, because the activities of leaving home in the morning and returning home at night are performed in different time periods of a day, and there is no conflict between the two travel time prevention and control measures, some users may receive the early leaving intervention information and the late returning intervention information at the same time, and the late returning intervention information may also interfere with the user going out again after returning home at night, thereby reducing other input risks caused by returning home at night.
the above embodiment is only specifically described by taking aedes as an example, and if the disease infection source is other infectious agents, the information content and the time threshold in the travel intervention information can be adjusted according to the types and the active time of the other infectious agents.
please refer to fig. 2, which is a schematic structural diagram of an infectious disease prevention and control system according to an embodiment of the present application. The infectious disease prevention and control system comprises an area identification module, a user identification module, a risk value acquisition module and a trip prevention and control module; specifically, the method comprises the following steps:
an area identification module: identifying a high risk area for the infectious disease from the local risk of infection data; the high risk area refers to an area with a large local infection risk probability value, and the local infection risk data is a grid risk graph which is obtained through a random forest model and consists of case data and various environmental factors influencing the survival of aedes mosquitoes.
a user identification module: the mobile phone is used for identifying users visiting the high-risk area and the early leaving time, the late returning time, the home position, the position of the first destination after leaving the home and the position of the last destination before returning the home of each user according to the regular mobile phone data; the regular mobile phone data is mobile phone positioning data of the user position recorded once per hour.
a risk value acquisition module: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for respectively acquiring local infection risk values of three positions, namely a position of a user home, a position of a first destination after leaving home and a position of a last destination before returning home, from local infection risk data; when identifying local infection risk values of the position of a user home, the position of a first destination after leaving home and the position of a last destination before returning home, the local infection risk data is grid data of 100m, the mobile phone track data is the position of a base station, and one base station usually covers a plurality of grids, so that 100 times of local infection risk values are randomly selected in the base station ranges of the position of the user home, the position of the first destination after leaving home and the position of the last destination before returning home respectively, and then the average value of the random data is selected as the local infection risk values of the position of the user home, the position of the first destination after leaving home and the position of the last destination before returning home respectively.
the trip prevention and control module: the system is used for respectively making travel time prevention and control measures according to the active time of disease infection sources, and respectively sending corresponding travel intervention information to users visiting the high-risk area according to the early leaving time and the late returning time of the users, and the local infection risk values of the home position, the first destination position after leaving the home and the last destination position before returning the home. Because the user's trip causes the input risk, the disease has stronger infectivity in the high risk area, therefore the final purpose of the trip time prevention and control measure in this application is to utilize the cell-phone to send the trip intervention information customized for the individual to the user who visits the high risk area to guide the user to adjust the time of leaving home or returning home in the morning and evening, make this part of crowd can reduce the dwell time in the high risk area during the active period of the disease infection source, thus reduce the input risk in the high risk area. Wherein, the input risk data is obtained by calculating the individual infection probability at different moments by using the local infection risk value and the mosquito media activity intensity and accumulating and summing the probabilities, and the calculation formula of the input risk data is as follows:
In formula (1) and formula (2), Pri represents the probability value of the infection of the user i who visits the polygon, rl (t) is the local risk value of the infection of the user at the position of t hours, and a (t) represents the activity intensity of the infection source of the disease at the time period.
taking aedes as an example, through research, the active time of biting of the aedes is mainly concentrated in two peak periods of the morning and the evening, and the specific active time periods are respectively 5: 00 to 8: 00 and 18 in the evening: 00 to 20: 00. In the daily travel activities of most users, the time period of leaving home in the morning and returning home in the evening is just similar to the morning and evening active time period of aedes mosquito. Therefore, the travel time prevention and control measures are divided into two types according to two active time periods of the aedes, the travel intervention information is sent to the user by combining the local infection risk value and the travel time of the user, the time of leaving or/and returning the user is changed by taking hours as a time unit, the input risk caused by travel is reduced, and accurate prevention and control in a time angle is achieved.
Specifically, the method comprises the following steps: the first category is to avoid the situation in the morning 5: 00 to 8: the strategy that the early active period of aedes mosquito of 00 stays in a high risk area is taken as a prevention and control measure for early leaving home time: for morning 5: 00 to 8: 00, sending a trip intervention message of 'please leave home before/after morning fold', informing the user to change the time of leaving home in the morning, thereby reducing the user staying in the high risk area during the period of aedes mosquito activity. Sending information to regulate the user to have morning according to the daily travel activity rule of the user 5: 00, the difficulty of leaving home is great, therefore, the application selects 5: 00 as the starting time for the preventive measure. The local infection risk value of the home position is represented by HomeRL, the local infection risk value of the first destination position after leaving home is represented by FirstRL, the HomeRL and the FirstRL are compared with the leaving home time of the user, and the sent early leaving home intervention information is as follows:
if FirstRL > ═ HomeRL and the user's early departure time is earlier than the end time of the aedes early active period (i.e., 8: 00 a.m.), then trip intervention information is sent: "please leave home after the end time of the aedes early activity period (i.e., after 8: 00 a.m.);
if FirstRL < HomeRL and the user's early departure time is later than the beginning time of the aedes early activity period (i.e. 5: 00 a morning), then send a trip intervention message: "please leave home before the start time of the aedes early activity period" (i.e., 5: 00 a.m.).
The second category is that the night 18: 00 to 20: the strategy that the mosquito of 00 stays in a high risk area in the late active time period is taken as a late home time prevention and control measure: for night 18: 00 to 20: 00, and sending trip intervention information of 'please go home before/after night Tmax', informing the user to change the time of going home at night, thereby reducing the user staying in the high risk area during the period of the mosquito activity. The local infection risk value of the position of the last destination before returning home is expressed by LastRL, HomeRL and LastRL are compared with the time of returning home of the user, and the transmitted late-returning-home intervention information is as follows:
If LastRL > -, HomeRL and the user's late time to home is later than the beginning time of the aedes mosquito late active period (i.e., 18: 00 pm), then trip intervention information is sent: "please return home before the start time of the aedes late active period (i.e., 18: 00 pm);
If LastRL < HomeRL and the user's late time to home is earlier than the end of the Aedes mosquito late active period (i.e., 20: 00 pm), then travel intervention information is sent: "please aedes late active time period to end time (i.e. after 20: 00 pm) to come home".
in the above, because the activities of leaving home in the morning and returning home at night are performed in different time periods of a day, and there is no conflict between the two travel time prevention and control measures, some users may receive the early leaving intervention information and the late returning intervention information at the same time, and the late returning intervention information may also interfere with the user going out again after returning home at night, thereby reducing other input risks caused by returning home at night.
according to the method and the device, travel time prevention and control measures are made for the users in the high-risk area, travel time of leaving home in the morning and returning home in the evening in the mobile phone track data of the users is changed, and a plurality of sets of new mobile phone data are obtained through simulation. In the simulated mobile phone data, after the random simulation user receives the trip intervention information, 30% and 80% of people respectively obey the information notification to change the trip time. Simulation results show that the early departure intervention information and the late departure intervention information are sent at the same time, and the measures for adjusting the morning departure time and the evening departure time are obeyed, so that the input risk reduction rate of the high risk area is increased to a certain extent, and the input risk reduction rate of the high risk area under the compliance degree of 80% reaches 8.28%, which is 2.68 times of that under the compliance degree of 30%. A large amount of mobile phone simulation data prove that the travel time prevention and control measures are feasible and effective.
According to the infectious disease prevention and control method and system, the user is guided to adjust the travel time by sending the individually customized travel intervention information aiming at the user in the city, so that the input risk of a high-risk area is reduced, and the purpose of accurately preventing and controlling infectious diseases in a time angle is achieved. Compared with the prior art, the method has the following advantages:
1. By adopting regular mobile phone positioning data taking hours as units, more complete and reliable individual space-time characteristics can be obtained, and the feasibility of implementing accurate time prevention and control on individuals is ensured.
2. the prevention and control research is carried out in the city, so that the vacancy of implementing prevention and control in the city is filled.
3. the travel time prevention and control measures in a time-based system utilize a mobile phone to send personalized travel intervention information to a user, change the early-leaving time and the late-returning time of the user in a high risk area, effectively reduce the input risk value of the high risk area, and have obvious prevention and control effects on controlling the spread of diseases.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. an infectious disease prevention and control method is characterized by comprising the following steps:
Step a: identifying a high risk area of the infectious disease from the local risk of infection data;
Step b: identifying early leaving time, late returning time, home position, first destination position after leaving home and last destination position before returning home of a user accessing the high risk area according to regular mobile phone data, wherein the regular mobile phone data are regular mobile phone positioning data taking hours as a unit;
step c: and working out travel time prevention and control measures according to the active time of the disease infection source, and respectively sending corresponding travel intervention information to the users visiting the high risk area by combining the early leaving time and the late returning time of the users visiting the high risk area, and the local infection risk values of the home position, the first destination position after leaving the home and the last destination position before returning the home.
2. an infectious disease control method according to claim 1, wherein the step c further comprises: and respectively acquiring local infection risk values of the home position of the user visiting the high-risk area, the position of the first destination after leaving the home and the position of the last destination before returning home from local infection risk data.
3. an infectious disease control method according to claim 2, wherein in the step c, the disease infection source is aedes mosquito, and the step of determining the course time control measure according to the activity time of the disease infection source comprises: taking a strategy of avoiding staying in a high risk area in the early activity time period of the aedes as a prevention and control measure for early leaving home; and taking a strategy of avoiding staying in a high-risk area in the late active period of aedes as a late home time prevention and control measure.
4. An infectious disease prevention and control method according to claim 3, wherein in the step c, the sending of the corresponding trip intervention information to the user visiting the high risk area is specifically: the local infection risk value of the home location is represented by HomeRL, the local infection risk value of the location of the first destination after leaving home is represented by FirstRL, the local infection risk value of the location of the last destination before returning home is represented by LastRL, and the HomeRL and firsttrl and the HomeRL and LastRL are compared, respectively:
if FirstRL > -HomeRL and the user's early departure time is earlier than the end time of the aedes early active period, then send out intervention information: "please leave home after the end time of the aedes early activity period";
If FirstRL < HomeRL and the user's early departure time is later than the start time of the aedes early activity period, then send travel intervention information: "please leave home before the start time of the aedes early activity period";
If LastRL > -HomeRL and the user's late time of returning home is later than the start time of the Aedes mosquito late active time period, then send travel intervention information: "please go home before the start time of the aedes late active period";
If LastRL < HomeRL and the user's late time to home is earlier than the end time of the Aedes mosquito late active time period, then send travel intervention information: "please aedes late active time period to come home after the end time".
5. an infectious disease prevention and control system, comprising:
An area identification module: identifying a high risk area for the infectious disease from the local risk of infection data;
A user identification module: the mobile phone system is used for identifying the time of the user visiting the high-risk area and the time of the user visiting the high-risk area to leave home, the time of the user to go home, the position of the user, the position of the first destination after leaving home and the position of the last destination before going home according to regular mobile phone data, wherein the regular mobile phone data are regular mobile phone positioning data taking hours as units;
the trip prevention and control module: the system is used for making travel time prevention and control measures according to the active time of disease infection sources, and respectively sending corresponding travel intervention information to the users visiting the high-risk areas according to the local infection risk values of the early leaving time, the late returning time, the home position of the user, the first destination position after leaving the home and the last destination position before returning the home.
6. An infectious disease prevention and control system according to claim 5, further comprising a risk value acquisition module: and the local infection risk value is used for respectively acquiring the position of the home of the user accessing the high-risk area, the position of the first destination after leaving the home and the position of the last destination before returning home from the local infection risk data.
7. An infectious disease prevention and control system according to claim 6, wherein the disease infection source is aedes, and the travel prevention and control module is configured to take the following steps of: taking a strategy of avoiding staying in a high risk area in the early activity time period of the aedes as a prevention and control measure for early leaving home; and taking a strategy of avoiding staying in a high-risk area in the late active period of aedes as a late home time prevention and control measure.
8. An infectious disease prevention and control system according to claim 7, wherein the trip prevention and control module sends corresponding trip intervention information to the user visiting the high risk area, specifically: the local infection risk value of the home location is represented by HomeRL, the local infection risk value of the location of the first destination after leaving home is represented by FirstRL, the local infection risk value of the location of the last destination before returning home is represented by LastRL, and the HomeRL and firsttrl and the HomeRL and LastRL are compared, respectively:
If FirstRL > -HomeRL and the user's early departure time is earlier than the end time of the aedes early active period, then send out intervention information: "please leave home after the end time of the aedes early activity period";
If FirstRL < HomeRL and the user's early departure time is later than the start time of the aedes early activity period, then send travel intervention information: "please leave home before the start time of the aedes early activity period";
If LastRL > -HomeRL and the user's late time of returning home is later than the start time of the Aedes mosquito late active time period, then send travel intervention information: "please go home before the start time of the aedes late active period";
If LastRL < HomeRL and the user's late time to home is earlier than the end time of the Aedes mosquito late active time period, then send travel intervention information: "please aedes late active time period to come home after the end time".
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110926655A (en) * | 2020-02-17 | 2020-03-27 | 深圳市刷新智能电子有限公司 | Epidemic situation monitoring method and system based on wearable body temperature sensor |
| CN111429324A (en) * | 2020-03-25 | 2020-07-17 | 淮阴工学院 | Electronic traffic state management method for multi-source information fusion |
| CN111405488A (en) * | 2020-03-31 | 2020-07-10 | 中科星图(深圳)数字技术产业研发中心有限公司 | Vehicle management method for multi-track cooperative tracking |
| CN113496781A (en) * | 2020-04-01 | 2021-10-12 | 中国科学院深圳先进技术研究院 | Urban internal infectious disease diffusion simulation method and system and electronic equipment |
| CN111611336B (en) * | 2020-05-11 | 2022-06-24 | 每日互动股份有限公司 | Terminal data processing system |
| CN111916215B (en) * | 2020-06-17 | 2022-04-29 | 扬州大学附属医院 | Cluster/chronic disease early automatic alarm, preliminary feature analysis and risk assessment system |
| CN111477343B (en) * | 2020-06-25 | 2020-09-11 | 中航信移动科技有限公司 | Manned aircraft infects early warning system |
| CN113539512B (en) * | 2021-07-21 | 2023-06-16 | 医渡云（北京）技术有限公司 | Method and device for predicting infectious disease transmission trend, storage medium and electronic equipment |
| CN116866842B (en) * | 2023-09-05 | 2023-11-21 | 成都健康医联信息产业有限公司 | Infectious disease cross-space-time target tracking and early warning method, system, terminal and medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20100018229A (en) * | 2008-08-06 | 2010-02-17 | 박정용 | Method of preventing communicable diseases by communicable diseases prevention system |
| CN102043893A (en) * | 2009-10-13 | 2011-05-04 | 北京大学 | Disease pre-warning method and system |
| CN102971755A (en) * | 2010-01-21 | 2013-03-13 | 阿斯玛西格诺斯公司 | Early warning method and system for chronic disease management |
| CN106209595A (en) * | 2016-07-19 | 2016-12-07 | 北京小米移动软件有限公司 | Information prompting method and device |
-
2017
- 2017-05-05 CN CN201710315294.0A patent/CN107277763B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20100018229A (en) * | 2008-08-06 | 2010-02-17 | 박정용 | Method of preventing communicable diseases by communicable diseases prevention system |
| CN102043893A (en) * | 2009-10-13 | 2011-05-04 | 北京大学 | Disease pre-warning method and system |
| CN102971755A (en) * | 2010-01-21 | 2013-03-13 | 阿斯玛西格诺斯公司 | Early warning method and system for chronic disease management |
| CN106209595A (en) * | 2016-07-19 | 2016-12-07 | 北京小米移动软件有限公司 | Information prompting method and device |
Non-Patent Citations (1)
| Title |
|---|
| Mapping intra-urban transmission risk of dengue fever with big hourly cellphone data;Liang Mao,Ling Yin,Xiaoqing Song,Shujiang Mei;《Acta Tropica》;20161031;全文 * |
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