CN113496781A - Urban internal infectious disease diffusion simulation method and system and electronic equipment - Google Patents
Urban internal infectious disease diffusion simulation method and system and electronic equipment Download PDFInfo
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Abstract
The invention relates to a method for simulating the spread of an urban internal infectious disease, which comprises the following steps: initializing all population inside a city according to dengue input case data; constructing an individual mobile network for all the population of the initialized city according to individual trip chain information constructed by the multi-source track data, and calculating the residence time of the individual in the place; calculating to obtain mosquito media space-time distribution according to meteorological data comprising daily average air temperature and daily rainfall; and according to the constructed individual mobile network, calculating the obtained residence time of the occupational region and the mosquito vector space-time distribution, constructing a spatial display individual transmission model, and simulating the transmission and diffusion process of the infectious diseases. The invention also relates to a system and electronic equipment for simulating the spread of the urban internal infectious diseases. The invention can reflect the moving mode and the trip place of the individuals in the city more truly and simulate the interaction between the individuals more accurately, thereby improving the accuracy of the spread simulation of the infectious disease in space.
Description
Technical Field
The invention relates to a method, a system and electronic equipment for simulating the spread of an urban internal infectious disease.
Background
In recent decades, along with the comprehensive effects of factors such as climate environment change, population mobility and urbanization progress, the incidence of infectious diseases such as dengue fever and the like is remarkably increased around the world, and the health of human beings is seriously threatened. Due to computer modeling and simulation, a key scientific support is provided for understanding the infectious disease spreading process, predicting the infectious disease spreading situation and scientifically making prevention and control measures, and an accurate spreading model is urgently needed to more effectively simulate the spreading process of infectious diseases such as dengue fever.
In the prior art, since large-scale individual movement data is very sparse, many scholars construct individual activity patterns by various methods. For example, by utilizing a small part of actual person-to-person contact survey data, an approximate model of the daily activities of the person is obtained, and then the activities of the person are subjected to simulation distribution according to two activity rules of orientation and semi-random; or a random method is adopted to simulate population movement, namely, the individual randomly selects a place to travel from the residence place in the daytime. Although the methods simulate the activities of the crowd in the city, the methods cannot accurately describe the real travel mode of the individual.
Overall, the disadvantages of the prior art are mainly:
firstly, population movement data in the existing infectious disease spreading model cannot accurately describe the real travel mode of an individual, and great spatial inaccuracy exists, so that great difficulty exists in extracting large-scale resident travel information in a city;
secondly, only the influence factor of the number of asymptomatic infected persons is considered in the existing dengue fever transmission model, the influence of the spatial position of the asymptomatic infected persons is ignored, and no research is carried out on the spatial position of the asymptomatic infected persons;
thirdly, most of the research on describing the movement of people by using mobile phone positioning data in the existing infectious disease transmission model is on a larger spatial scale of a country or an area, and at present, no research on a smaller scale based on an internal building of a city exists.
Disclosure of Invention
In view of the above, it is desirable to provide a method, a system and an electronic device for simulating the spread of an urban internal infectious disease.
The invention provides a method for simulating the spread of an urban internal infectious disease, which comprises the following steps: a. initializing all population inside a city according to dengue input case data; b. constructing an individual mobile network for all the population of the initialized city according to individual trip chain information constructed by the multi-source track data, and calculating the residence time of the individual in the place; c. calculating to obtain mosquito media space-time distribution according to meteorological data comprising daily average air temperature and daily rainfall; d. and according to the constructed individual mobile network, calculating the obtained residence time of the occupational region and the mosquito vector space-time distribution, constructing a spatial display individual transmission model, and simulating the transmission and diffusion process of the infectious diseases.
Wherein, the method also comprises the following steps before the step a:
acquiring source data; the source data comprises multi-source track data, dengue input case data and meteorological data; the multi-source trajectory data includes: census data, trip survey data, building data and mobile phone positioning data.
The method further comprises step e:
and analyzing the space-time distribution mode of the urban internal infectious diseases according to the simulation result of the spatial explicit individual transmission model.
The step a specifically comprises the following steps:
initializing symptomatic infectors according to dengue fever input case data provided by an infectious disease prevention and control center;
according to each case of symptomatic infectors, generating a corresponding number of asymptomatic infectors according to the proportion of dengue symptomatic infectors and asymptomatic infectors, and initializing the asymptomatic infectors;
selecting a corresponding number of people from the initial population according to the proportion of the immune people in the city or the age distribution characteristics of the immune people and setting the people in an immune state.
The step b specifically comprises the following steps:
carrying out large-scale individual movement modeling according to the multi-source track data and constructing individual trip chain information, wherein the individual trip chain information refers to trip location information of an individual for 24 hours a day;
identifying and obtaining the occupational places of the individuals according to the individual trip chain information, the census data and the building data, and constructing a network for the individuals to move among the occupational places and buildings;
and calculating the residence time of each individual in the place of employment through the obtained information of the place of employment and the individual trip chain.
The step c specifically comprises the following steps:
respectively calculating the daily average air temperature of the previous month and the accumulated rainfall of the previous month in each area in the infectious disease simulation period according to the daily average air temperature and rainfall meteorological factors of each area;
and calculating the daily mosquito vector space-time distribution condition of each area according to the calculated daily average air temperature of the previous month and the accumulated rainfall days of the previous month of each area and a relational expression of the mosquito vector quantity and the two meteorological factors.
The step d specifically comprises the following steps:
an independent building is used as a simulation unit, and a classical SEIR model is combined to model the spread of viruses in the crowd and the dynamic transfer among different states of individuals in the crowd;
the simulation of dengue transmission spread was performed using a spatial explicit individual model in day steps, starting from the first day that the first input case in the population was infected until the entire dengue transmission simulation process ended.
The step e specifically comprises the following steps:
when time distribution results are analyzed, the scene is simulated for N times respectively, the simulation results of each time are counted according to the day, and finally the mean value and 95% confidence interval of the N times of simulation are obtained;
when the spatial distribution result is analyzed, a 1km x 1km spatial grid is used as a basic spatial unit for spatial analysis, the spatial distribution result of the dengue epidemic under the grid scale is analyzed, the scene is simulated for N times respectively, the spatial distribution result of the dengue infectors simulated each time is counted according to the grid, the mean value of the number of cases simulated for N times by each grid is solved respectively, and finally, the mean value is compared with the spatial distribution result of an actual case, and the spatial distribution characteristics of the simulation result and the simulation effect of the model on the spatial distribution are analyzed.
The invention provides a system for simulating the spread of an urban internal infectious disease, which comprises a population initialization module, a mobile network construction module, a mosquito medium space-time distribution module and a propagation simulation module, wherein the population initialization module comprises: the population initialization module is used for initializing all population inside a city according to dengue input case data; the mobile network construction module is used for constructing an individual mobile network for all the initialized population of the city according to individual trip chain information constructed by the multi-source track data and calculating the residence time of the individual in the place; the mosquito medium space-time distribution module is used for calculating to obtain mosquito medium space-time distribution according to meteorological data comprising daily average air temperature and daily rainfall; the propagation simulation module is used for calculating the residence time of the occupational region and the mosquito vector space-time distribution according to the constructed individual mobile network, constructing a spatial display individual propagation model and simulating the propagation and diffusion process of infectious diseases.
Wherein the system further comprises:
the acquisition module is used for acquiring source data; the source data comprises multi-source track data, dengue input case data and meteorological data; the multi-source trajectory data includes: census data, trip survey data, building data and mobile phone positioning data;
and the analysis module is used for analyzing the space-time distribution mode of the urban internal infectious diseases according to the simulation result of the spatial explicit individual transmission model.
The present invention also provides an electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the one processor to cause the at least one processor to perform the following operations of the method for simulating spread of infectious diseases in cities:
step a: initializing all population inside a city according to dengue input case data;
step b: constructing an individual mobile network for all the population of the initialized city according to individual trip chain information constructed by the multi-source track data, and calculating the residence time of the individual in the place;
step c: calculating to obtain mosquito media space-time distribution according to meteorological data comprising daily average air temperature and daily rainfall;
step d: and according to the constructed individual mobile network, calculating the obtained residence time of the occupational region and the mosquito vector space-time distribution, constructing a spatial display individual transmission model, and simulating the transmission and diffusion process of the infectious diseases.
According to the urban internal infectious disease spread simulation method, the urban internal infectious disease spread simulation system and the electronic equipment, disclosed by the invention, resident travel activities constructed based on multi-source track data can truly reflect the moving modes and the travel places of urban internal individuals, and can more accurately simulate interaction among the individuals, so that the accuracy of the dengue fever and other infectious disease spread and spread simulation on space is improved, and the method, the system and the electronic equipment can also be used for implementing simulation evaluation of more accurate intervention measures on time space; three allocation strategies are set for the spatial position of an asymptomatic infected person, the influence of the spatial position of a recessive input case on the spread of infectious diseases such as dengue fever is explored for the first time, and the most possible spatial distribution condition of the recessive input case can be preliminarily explored through the spatial-temporal distribution of a simulation result; the invention describes the movement of people among different buildings in the city by using the mobile phone positioning data, realizes important breakthrough of the current infectious disease research based on the smaller scale of the buildings in the city, and can provide scientific support for the precise prevention and control of infectious diseases.
Drawings
FIG. 1 is a flow chart of the simulation method for spreading the infectious diseases in the city according to the present invention;
FIG. 2 is a schematic diagram of activities between locations of an individual according to an embodiment of the present invention;
FIG. 3 is a flowchart of an infectious disease simulation performed in a day-to-day step according to an embodiment of the present invention;
FIG. 4 is a diagram of the hardware architecture of the simulation system for spreading the infectious diseases in the city;
FIGS. 5-7 are schematic time series diagrams of dengue fever transmission spread provided by embodiments of the present invention;
FIGS. 8-10 are schematic diagrams of the daily accumulation of dengue fever transmission spread provided by embodiments of the present invention;
FIGS. 11-13 are schematic diagrams of the results of the spatial distribution of dengue fever transmission spread provided by an embodiment of the present invention;
fig. 14 is a schematic diagram of a local case space distribution in the 2014 Shenzhen city provided in the embodiment of the present invention;
fig. 15 is a schematic structural diagram of a hardware device of a method for simulating spreading of an internal infectious disease in a city according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
This example illustrates dengue as an example of an infectious disease:
referring to fig. 1, a flow chart of the operation of the method for simulating the spread of infectious diseases in cities according to the preferred embodiment of the present invention is shown.
In step S0, source data is acquired. The source data includes multi-source trajectory data, dengue input case data, meteorological data, and other underlying data.
The multi-source track data comprise a large amount of mobile phone positioning data and travel survey data. In this embodiment, the cell phone location data refers to over 762 million anonymous user records of a certain day of 5 months in 2012, and the user records (as shown in table 1) include anonymous user ID, timestamp, longitude and latitude. The dengue input case data comprises 348 local case data of Shenzhen city in 2014 and 206 exceptional input cases (the input cases refer to all dengue infectors entering the Shenzhen city from a region outside the Shenzhen city), and the dengue input case data comprises information such as sex, age, family address, infection date and the like, and the case data is sourced from the Shenzhen city medical information center. The meteorological data refer to the daily average lowest air temperature, rainfall and average relative humidity of 22 meteorological sites in Shenzhen City in 2014, and the meteorological data are derived from the Shenzhen City weather bureau. The other basic data comprise the sixth census data in 2010, the Shenzhen City statistical yearbook and the Shenzhen City building data.
TABLE 1
And step S1, initializing all population inside the city according to the acquired dengue input case data. That is, the infection status is set for symptomatic infected persons; generating asymptomatic infected persons according to the proportion of the asymptomatic infected persons, and setting the infection state of the asymptomatic infected persons; a corresponding number of people were selected among the initial population and set to an immune state.
Specifically, the step S1 includes:
And 102, generating a corresponding number of asymptomatic infectors according to the proportion of dengue fever infected persons to asymptomatic infectors according to each symptomatic infector, and initializing the asymptomatic infectors. The home address allocation method for asymptomatic infected persons is divided into three strategies: one is based on the spatiotemporal distribution of symptomatic infected persons; secondly, according to the distribution of urban internal population; and thirdly, the distribution is random. The infection status of asymptomatic infected persons is set after the production.
And 103, selecting a corresponding number of people from the initial population according to the proportion of the immune people in the city or the age distribution characteristics of the immune people and setting the immune people to be in an immune state, wherein the immune people cannot be infected in the whole dengue fever spreading process and have life-long immunity. Wherein the initial population is the entire population of the city except for symptomatic and asymptomatic infected persons.
Further, the specific implementation method of the embodiment includes:
firstly, initializing a symptomatic infected person, and specifically realizing the method as follows: finding out all individuals in the building according to the family addresses of the input cases, calculating the similarity of each individual and two attributes of the sex and the age of the input cases, then selecting the individual with the highest similarity to match the input cases, and if a plurality of individuals with the highest similarity are equal, randomly selecting one of the individuals to match the input cases.
Then, initialization was performed for asymptomatic infected persons: the ratio of symptomatic infectors to asymptomatic infectors in the process of the outbreak of dengue fever in Shenzhen is assumed to be 1: 2.2. the specific implementation method comprises the following steps: the assignment of home addresses to asymptomatic infected persons assumes 3 scenarios: firstly, selecting according to the home address of an input case, assuming that the spatial distribution of the input case is consistent with that of the input case, namely, for each symptomatic infected person, randomly generating N asymptomatic infected persons with the probability of 2.2:1, and randomly selecting N asymptomatic infected persons in the same area with the corresponding symptomatic infected person; selecting the family address of the asymptomatic infector according to population distribution, namely selecting according to the probability of the total population of 10 jurisdictions in Shenzhen city, namely the probability in the region with the larger total population is larger; and thirdly, selecting the home address of the asymptomatic infector according to random distribution, namely randomly selecting one region from 10 jurisdictions in Shenzhen city, and setting the incubation period, the infection period and the recovery period of the asymptomatic infector after determining the home address of the asymptomatic infector.
Finally, assuming that the proportion of the population initially immunized by the resident in Shenzhen city is 2.43%, after all input cases (including symptomatic infected persons and asymptomatic infected persons) are removed from the total population, the immune population is randomly selected from the rest of the population according to the immune proportion of the population, the state of the immune population is set to be a recovery state, and the individual is assumed to obtain the permanent immunity of the dengue virus.
And step S2, constructing an individual mobile network for all the initialized population of the city according to the individual trip chain information constructed by the multi-source track data, and calculating the residence time of the individual in the place.
The individual trip chain information constructed by the multi-source track data refers to trip place information of an individual for 24 hours a day, which is simulated according to general population survey data, building data, trip survey data and a large amount of mobile phone positioning data, the place of employment and the trip chain information of the population data are identified, a mobile network between the places of employment of the individual is constructed, and the residence time of each individual in the place of employment is calculated.
Specifically, the step S2 includes:
step 201: and carrying out large-scale individual movement modeling and constructing individual trip chain information according to multi-source track data comprising census data, trip survey data, building data and mobile phone positioning data. The individual trip chain information refers to trip location information of an individual 24 hours a day.
Step 202: according to the individual travel chain information, census data and building data, the places of employment of the individuals are identified and obtained, and a network (please refer to fig. 2) for the individuals to move among the buildings of the places of employment is constructed, wherein only the most main travel activities of the individuals are considered in the model, so that the main travel activity places of the individuals only consider the buildings of families, work places or schools.
Step 203: and calculating the residence time of each individual in the place of employment through the obtained information of the place of employment and the individual trip chain. The dwell time is used for the selection of newly infected persons in the course of infectious disease simulation, the longer the dwell time in the building in which the infected person is present, the greater the probability that the individual is infected.
And step S3, calculating the mosquito media space-time distribution according to the meteorological data including daily average air temperature and daily rainfall. That is, the average daily air temperature and the number of days of rainfall in the previous month in each area are calculated by using the weather factors such as the average daily air temperature and the amount of rainfall in the previous month, and the spatiotemporal dynamic distribution of the mosquito vectors in each area in the city is calculated.
Specifically, the step S3 includes:
step 301: and respectively calculating the daily average air temperature of the previous month and the accumulated rainfall of the previous month in each area in the infectious disease simulation period according to the daily average air temperature and rainfall meteorological factors of each area.
Step 302: and calculating the daily mosquito vector space-time distribution condition of each area according to the calculated daily average air temperature of the previous month and the accumulated rainfall days of the previous month of each area and a relational expression of the mosquito vector quantity and the two meteorological factors.
Further, the specific implementation method of the embodiment includes:
respectively calculating the daily average air temperature of the previous month and the accumulated rainfall days of the previous month of each day of each region according to the data of 22 meteorological sites in Shenzhen city, and calculating the mosquito medium space-time distribution condition of each day of each region according to a formula (1):
Mij＝0.05Pij-0.0081Tij 2+0.5289Tij-5.5461 (1)
wherein M isijRepresents the number of mosquito vectors, P, at day j of the i-th areaijRepresents the number of days of cumulative rainfall in the month immediately before the jth day of the ith area, TijRepresents the average temperature of the i-th zone on the j-th day in the previous month, and the value range of i is [1,10 ]]Respectively representing 10 jurisdictions in Shenzhen city, and the value range of j is [1,365 ]]It means 1/1 to 12/31/2014.
And step S4, calculating the residence time of the occupational region and the mosquito-media space-time distribution according to the constructed individual mobile network, constructing a spatial display individual transmission model, and simulating the transmission and diffusion process of the infectious diseases.
The spatial explicit individual propagation model is to use a building as a simulation unit and combine a classical SEIR model to model propagation of viruses in a crowd and dynamic transition between different states of individuals in the crowd. Each individual is an agent in the model, and the travel activities of the individual refer to movement between places of employment.
Specifically, the step S4 includes:
step 401: an independent building is taken as a simulation unit, and a classical SEIR model is combined to model the spread of viruses in the crowd and the dynamic transition between different states of individuals in the crowd. Each individual in the model is an agent, each agent has attributes of age, sex, home residence, place of work, and infection status, and the agent's travel activities include staying at home, going to work, or going to school. In addition, in the course of the simulation, the difference in the infection period between symptomatic and asymptomatic infected persons was differentiated.
Step 402: the simulation of dengue transmission spread was performed using a spatial explicit individual model in day steps, starting from the first day that the first input case in the population was infected until the entire dengue transmission simulation process ended. With reference to fig. 3, during the daily simulation, all buildings of the workplace are traversed to see if new infected persons are present. If a new infected person is generated in the building, the newly generated infected person in the building is selected according to the weight of the infected person, then the infection symptom of the infected person is determined according to the probability of the ratio of the symptomatic infected person and the asymptomatic infected person, and finally the incubation period, the infection period and the recovery period of the infected person are respectively set.
Further, the specific implementation method of the embodiment includes:
an independent building is taken as a simulation unit, and a classical SEIR model is combined to model the spread of viruses in the crowd and the dynamic transition between different states of individuals in the crowd. Each individual in the model is an agent, each agent has attributes of age, sex, home residence, place of work, and infection status, and the movement of agents between different buildings results in the spread of dengue virus. In addition, in the course of the simulation, the differences in the infection phase were differentiated between those with and without symptomatic infection. The whole population is divided into susceptible people HSLatent person HESymptomatic infected person HIsAsymptomatic infected person HIaAnd person recovering HR。
When an individual is in a susceptible state (H)S) After being bitten by a virus-carrying Aedes mosquito, it will probably be converted into a latent state (H)E) The probability depends on the susceptible individualProbability of acquiring infection (beta) by one bite of mosquito with virusH) And the number of aedes in the building where the current individual is located. Individuals in latent state (H)E) Passing through the latent period (. delta.)H) Then will be converted into an infectious state (H)IsOr HIa) Individuals in the latent state are not infectious, but if the aedes bites an individual in the infectious state, dengue fever virus will have a probability of betaVInfected to healthy aedes, virus-carrying aedes may bite susceptible individuals to spread the virus throughout their life. The probability of an individual in a susceptible state being infected is:
wherein M is k.M, M represents the number of the human aedes, k is a proportionality coefficient, and M represents the number of mosquito vectors in each analog unit.
The simulation of dengue transmission spread was then performed using a spatial explicit individual model in day steps, starting with the first day of infection of the first input case in the population until the entire dengue transmission simulation process was completed. In the simulation, all the occupational buildings are traversed to see if a new infected person is present. If a new infected person is generated in the building, the newly generated infected person in the building is selected according to the weight of the infected person, then the infection symptom of the infected person is determined according to the probability of the ratio of the symptomatic infected person and the asymptomatic infected person, and finally the incubation period, the infection period and the recovery period of the infected person are respectively set. Wherein the weight of each individual within the building that is infected is equal to the sum of the normalized individual incidence and the normalized residence time. The newly infected individuals eventually selected are selected as many as possible of those individuals with high morbidity (age related) and relatively long residence time (cumulative residence time in the building where the infected is present).
Step S5: and analyzing the space-time distribution mode of the urban internal infectious diseases according to the simulation result of the spatial explicit individual transmission model. That is, the effect of the model is analyzed from the time distribution and the space distribution according to the comparison between the actual local case data and the simulation result, and the space-time distribution of the infectious disease is analyzed.
Specifically, the step S5 includes:
step 501: when the time distribution result is analyzed, in order to solve the problem of uncertainty caused in the random parameter value taking process of one-time simulation, a plurality of scenes are simulated for N times respectively, the simulation result of each time is counted according to the day, and finally the mean value and 95% confidence interval of the N times of simulation are obtained. The time distribution results of the local case and the simulated symptomatic infected persons are respectively displayed through a time sequence diagram and a daily cumulative diagram, then the time distribution characteristics of the results and the simulation effect of the model on the time distribution are analyzed, and the most probable spatial distribution condition of the asymptomatic infected persons is explored through the time distribution results under different strategies.
Step 502: and when analyzing the spatial distribution result, taking a spatial grid of 1km x 1km as a basic spatial unit of spatial analysis, and analyzing the spatial distribution result of the dengue epidemic under the scale of the grid. Similarly, in order to solve the problem of uncertainty caused in the random parameter value taking process of one simulation, various scenes are simulated for N times respectively, the spatial distribution result of the dengue infectors simulated each time is counted according to grids, the mean value of the number of cases simulated for N times in each grid is solved respectively, finally, the mean value is compared with the spatial distribution result of an actual case, the spatial distribution characteristics of the simulation result and the simulation effect of the model on spatial distribution are analyzed, and the most possible spatial distribution condition of asymptomatic infectors is explored through the spatial distribution result under different strategies.
Further, the specific implementation method of the embodiment includes:
the three scenes are simulated for 100 times respectively, the simulation result of each time is counted according to the day, and finally the mean value of the 100 times of simulation and the 95% confidence interval are obtained. The time distribution results of the local cases and those of the simulated symptomatic infected persons are shown by time series graphs (fig. 5-7) and daily cumulative graphs (fig. 8-10), respectively. Wherein, the black curve in the graph represents the actual local case of Shenzhen city in 2014; the red curve represents the mean of the number of symptomatic infected persons for 100 simulations; the gray areas indicate 95% confidence intervals. As can be seen from the simulation results of FIGS. 5-7 and 8-10, the model can better simulate the spreading process of dengue fever in the time dimension. Although the number of days of peak and the size of peak were somewhat different from the local actual cases after the results of 100 simulations were averaged, the simulation was generally good. Meanwhile, the time sequence diagrams of the three scenes can show that when the home address of the asymptomatic infected person is distributed according to the spatial distribution (figure 5) of the input case, the simulation effect of the model is better, and the number of rush hour days and the size of the peak value are more consistent with those of the local actual case.
Similarly, when analyzing the spatial distribution result, the results of 100 times of simulation are counted by using the spatial grid of 1km x 1km as the basic spatial unit, then the average value of the number of cases simulated by 100 times per grid is obtained, and finally the results are compared with the spatial distribution result of the actual case, and the spatial distribution characteristics of the simulation result and the simulation effect of the model on the spatial distribution are analyzed. As can be seen from the spatial distribution of the simulation results in fig. 11-13, the symptomatic infectors mainly concentrated in the baean region (adjacent to the southern mountain region), the southern mountain region, fodo, lawy region and longhua region, which is generally consistent with the spatial distribution of actual local cases in shenzhen city 2014 (as shown in fig. 14). The simulation results of the home address distribution scenarios of the three asymptomatic input cases show that the simulation results of the home positions of the asymptomatic infectors distributed according to the spatial distribution of the input cases are relatively accurate (fig. 11), and most accord with the actual local cases, especially the simulation results of the areas such as the southern mountain area, the lake area, the Baoan area and the adjacent part of the southern mountain area accord with the actual local cases, and are all areas with more and dense dengue cases.
Referring to fig. 4, a diagram of the hardware architecture of the simulation system 10 for spreading the infectious diseases in the city is shown. The system comprises: the system comprises an acquisition module 100, a population initialization module 101, a mobile network construction module 102, a mosquito medium space-time distribution module 103, a propagation simulation module 104 and an analysis module 105.
The obtaining module 100 is configured to obtain source data. The source data includes multi-source trajectory data, dengue input case data, meteorological data, and other underlying data.
The multi-source track data comprise a large amount of mobile phone positioning data and travel survey data. In this embodiment, the cell phone location data refers to over 762 million anonymous user records of a certain day of 5 months in 2012, and the user records (as shown in table 1) include anonymous user ID, timestamp, longitude and latitude. The dengue input case data comprises 348 local case data of Shenzhen city in 2014 and 206 exceptional input cases (the input cases refer to all dengue infectors entering the Shenzhen city from a region outside the Shenzhen city), and the dengue input case data comprises information such as sex, age, family address, infection date and the like, and the case data is sourced from the Shenzhen city medical information center. The meteorological data refer to the daily average lowest air temperature, rainfall and average relative humidity of 22 meteorological sites in Shenzhen City in 2014, and the meteorological data are derived from the Shenzhen City weather bureau. The other basic data comprise the sixth census data in 2010, the Shenzhen City statistical yearbook and the Shenzhen City building data.
TABLE 1
The population initialization module 101 is used for initializing all population inside the city according to the acquired dengue input case data. That is, the infection status is set for symptomatic infected persons; generating asymptomatic infected persons according to the proportion of the asymptomatic infected persons, and setting the infection state of the asymptomatic infected persons; a corresponding number of people were selected among the initial population and set to an immune state.
Specifically, the method comprises the following steps:
first, the population initialization module 101 performs initialization of symptomatic infected persons based on dengue input case data provided by the center for prevention and control of infectious diseases: in other words, in the whole population data in the simulated city, similarity matching is carried out on all individuals in the population data according to attribute information such as age, sex, family address and the like of each input case, the most relevant individual is found out and set as the input case, and the infection state of the most relevant individual is set.
Then, the population initialization module 101 generates a corresponding number of asymptomatic infectors according to the proportion of dengue fever infected persons to asymptomatic infectors for each case of symptomatic infectors, and performs asymptomatic infector initialization. The home address allocation method for asymptomatic infected persons is divided into three strategies: one is based on the spatiotemporal distribution of symptomatic infected persons; secondly, according to the distribution of urban internal population; and thirdly, the distribution is random. The infection status of asymptomatic infected persons is set after the production.
Finally, the population initialization module 101 selects a corresponding number of people from the initial population according to the proportion of the immune people in the city or the age distribution characteristics of the immune people, and sets the selected people in an immune state, so that the immune people are not infected in the whole dengue fever transmission process and have life-long immunity. Wherein the initial population is the entire population of the city except for symptomatic and asymptomatic infected persons.
Further, in this embodiment, the population initialization module 101 is specifically implemented as:
first, the population initialization module 101 initializes a symptomatic infected person, specifically: finding out all individuals in the building according to the family addresses of the input cases, calculating the similarity of each individual and two attributes of the sex and the age of the input cases, then selecting the individual with the highest similarity to match the input cases, and if a plurality of individuals with the highest similarity are equal, randomly selecting one of the individuals to match the input cases.
The population initialization module 101 then initializes the asymptomatic infected person: the ratio of symptomatic infectors to asymptomatic infectors in the process of the outbreak of dengue fever in Shenzhen is assumed to be 1: 2.2. the specific implementation method comprises the following steps: the assignment of home addresses to asymptomatic infected persons assumes 3 scenarios: firstly, selecting according to the home address of an input case, assuming that the spatial distribution of the input case is consistent with that of the input case, namely, for each symptomatic infected person, randomly generating N asymptomatic infected persons with the probability of 2.2:1, and randomly selecting N asymptomatic infected persons in the same area with the corresponding symptomatic infected person; selecting the family address of the asymptomatic infector according to population distribution, namely selecting according to the probability of the total population of 10 jurisdictions in Shenzhen city, namely the probability in the region with the larger total population is larger; and thirdly, selecting the home address of the asymptomatic infector according to random distribution, namely randomly selecting one region from 10 jurisdictions in Shenzhen city, and setting the incubation period, the infection period and the recovery period of the asymptomatic infector after determining the home address of the asymptomatic infector.
Finally, assuming that the proportion of the population initially immunized by the resident in Shenzhen city is 2.43%, after all input cases (including symptomatic infected persons and asymptomatic infected persons) are removed from the total population, the immune population is randomly selected from the rest of the population according to the immune proportion of the population, the state of the immune population is set to be a recovery state, and the individual is assumed to obtain the permanent immunity of the dengue virus.
The mobile network construction module 102 is configured to construct an individual mobile network for all the initialized population of the city according to individual trip chain information constructed from the multi-source trajectory data, and calculate the residence time of the individual in the place of work.
The individual trip chain information constructed by the multi-source track data refers to trip place information of an individual for 24 hours a day, which is simulated according to general population survey data, building data, trip survey data and a large amount of mobile phone positioning data, the place of employment and the trip chain information of the population data are identified, a mobile network between the places of employment of the individual is constructed, and the residence time of each individual in the place of employment is calculated.
Specifically, the method comprises the following steps:
the mobile network construction module 102 performs large-scale individual movement modeling and constructs individual trip chain information according to multi-source trajectory data including census data, trip survey data, building data and mobile phone positioning data. The individual trip chain information refers to trip location information of an individual 24 hours a day.
The mobile network construction module 102 identifies and obtains the places of employment of individuals according to the individual trip chain information, census data and building data, and constructs a network (see fig. 2) in which the individuals move among the buildings of the places of employment, wherein only the most important trip activities of the individuals are considered in the model, so that the main trip activity places of the individuals only consider buildings where families, work places or schools are located.
The mobile network construction module 102 calculates and obtains the residence time of each individual in the place of employment through the obtained information of the place of employment and the individual trip chain. The dwell time is used for the selection of newly infected persons in the course of infectious disease simulation, the longer the dwell time in the building in which the infected person is present, the greater the probability that the individual is infected.
The mosquito medium space-time distribution module 103 is used for calculating mosquito medium space-time distribution according to meteorological data including daily average air temperature and daily rainfall. That is, the average daily air temperature and the number of days of rainfall in the previous month in each area are calculated by using the weather factors such as the average daily air temperature and the amount of rainfall in the previous month, and the spatiotemporal dynamic distribution of the mosquito vectors in each area in the city is calculated.
Specifically, the method comprises the following steps:
the mosquito medium space-time distribution module 103 respectively calculates the daily average air temperature of the previous month and the number of days of cumulative rainfall of the previous month in each area during the infectious disease simulation period according to the daily average air temperature and rainfall meteorological factors of each area.
The mosquito medium space-time distribution module 103 calculates the mosquito medium space-time distribution condition of each area every day through a relational expression of the mosquito medium quantity and the two meteorological factors according to the calculated daily average air temperature of each area in the previous month and the accumulated rainfall in the previous month.
Further, in this embodiment, the mosquito medium temporal-spatial distribution module 103 is specifically implemented as:
respectively calculating the daily average air temperature of the previous month and the accumulated rainfall days of the previous month of each day of each region according to the data of 22 meteorological sites in Shenzhen city, and calculating the mosquito medium space-time distribution condition of each day of each region according to a formula (1):
Mij＝0.05Pij-0.0081Tij 2+0.5289Tij-5.5461 (1)
wherein M isijRepresents the number of mosquito vectors, P, at day j of the i-th areaijRepresents the number of days of cumulative rainfall in the month immediately before the jth day of the ith area, TijRepresents the average temperature of the i-th zone on the j-th day in the previous month, and the value range of i is [1,10 ]]Respectively representing 10 jurisdictions in Shenzhen city, and the value range of j is [1,365 ]]It means 1/1 to 12/31/2014.
The propagation simulation module 104 is configured to calculate the residence time of the occupational region and the mosquito-vector space-time distribution according to the constructed individual mobile network, construct a spatial explicit individual propagation model, and simulate the propagation and diffusion process of infectious diseases.
The spatial explicit individual propagation model is to use a building as a simulation unit and combine a classical SEIR model to model propagation of viruses in a crowd and dynamic transition between different states of individuals in the crowd. Each individual is an agent in the model, and the travel activities of the individual refer to movement between places of employment.
Specifically, the method comprises the following steps:
the propagation simulation module 104 takes an independent building as a simulation unit, and combines a classical SEIR model to model the propagation of the virus in the crowd and the dynamic transition between different states of individuals in the crowd. Each individual in the model is an agent, each agent has attributes of age, sex, home residence, place of work, and infection status, and the agent's travel activities include staying at home, going to work, or going to school. In addition, in the course of the simulation, the difference in the infection period between symptomatic and asymptomatic infected persons was differentiated.
The spread simulation module 104 performs a simulation of dengue spread using spatial explicit individual models in day steps, starting from the first day that the first input case in the population is infected until the entire dengue spread simulation process is complete. With reference to fig. 3, during the daily simulation, all buildings of the workplace are traversed to see if new infected persons are present. If a new infected person is generated in the building, the newly generated infected person in the building is selected according to the weight of the infected person, then the infection symptom of the infected person is determined according to the probability of the ratio of the symptomatic infected person and the asymptomatic infected person, and finally the incubation period, the infection period and the recovery period of the infected person are respectively set.
Further, in this embodiment, the propagation simulation module 104 is specifically implemented as:
the propagation simulation module 104 takes an independent building as a simulation unit, and combines a classical SEIR model to model the propagation of the virus in the crowd and the dynamic transition between different states of individuals in the crowd. Each individual in the model is an agent, each agent has attributes of age, sex, home residence, place of work, and infection status, and the movement of agents between different buildings results in the spread of dengue virus. In addition, in the course of the simulation, the differences in the infection phase were differentiated between those with and without symptomatic infection. The whole population is divided into susceptible people HSLatent person HESymptomatic infected person HIsAsymptomatic infected person HIaAnd person recovering HR。
When an individual is in a susceptible state (H)S) After being bitten by a virus-carrying Aedes mosquito, it will probably be converted into a latent state (H)E) The probability depends on the probability (beta) that a susceptible individual is bitten by a virus-bearing mosquito once to acquire an infectionH) And the number of aedes in the building where the current individual is located. Individuals in latent state (H)E) Passing through the latent period (. delta.)H) Then will be converted into an infectious state (H)IsOr HIa) Individuals in the latent state are not infectious, but if the aedes bites an individual in the infectious state, dengue fever virus will have a probability of betaVInfected to healthy aedes, virus-carrying aedes may bite susceptible individuals to spread the virus throughout their life. The probability of an individual in a susceptible state being infected is:
wherein M is k.M, M represents the number of the human aedes, k is a proportionality coefficient, and M represents the number of mosquito vectors in each analog unit.
The transmission simulation module 104 then performs a simulation of dengue transmission spread using spatial explicit individual models in day steps, starting with the first day of infection of the first input case in the population until the entire dengue transmission simulation process is complete. In the simulation, all the occupational buildings are traversed to see if a new infected person is present. If a new infected person is generated in the building, the newly generated infected person in the building is selected according to the weight of the infected person, then the infection symptom of the infected person is determined according to the probability of the ratio of the symptomatic infected person and the asymptomatic infected person, and finally the incubation period, the infection period and the recovery period of the infected person are respectively set. Wherein the weight of each individual within the building that is infected is equal to the sum of the normalized individual incidence and the normalized residence time. The newly infected individuals eventually selected are selected as many as possible of those individuals with high morbidity (age related) and relatively long residence time (cumulative residence time in the building where the infected is present).
The analysis module 105 is used for analyzing the space-time distribution mode of the infectious diseases in the city according to the simulation result of the spatial explicit individual transmission model. That is, the effect of the model is analyzed from the time distribution and the space distribution according to the comparison between the actual local case data and the simulation result, and the space-time distribution of the infectious disease is analyzed.
Specifically, the method comprises the following steps:
when the analysis module 105 analyzes the time distribution result, in order to solve the uncertainty problem caused in the random parameter value taking process of one simulation, a plurality of scenes are simulated for N times respectively, the simulation result of each time is counted according to the day, and finally the mean value and 95% confidence interval of the N times of simulation are obtained. The time distribution results of the local case and the simulated symptomatic infected persons are respectively displayed through a time sequence diagram and a daily cumulative diagram, then the time distribution characteristics of the results and the simulation effect of the model on the time distribution are analyzed, and the most probable spatial distribution condition of the asymptomatic infected persons is explored through the time distribution results under different strategies.
When the analysis module 105 analyzes the spatial distribution result, the spatial grid of 1km x 1km is used as a basic spatial unit of spatial analysis, and the spatial distribution result of the dengue epidemic under the grid scale is analyzed. Similarly, in order to solve the problem of uncertainty caused in the random parameter value taking process of one simulation, various scenes are simulated for N times respectively, the spatial distribution result of the dengue infectors simulated each time is counted according to grids, the mean value of the number of cases simulated for N times in each grid is solved respectively, finally, the mean value is compared with the spatial distribution result of an actual case, the spatial distribution characteristics of the simulation result and the simulation effect of the model on spatial distribution are analyzed, and the most possible spatial distribution condition of asymptomatic infectors is explored through the spatial distribution result under different strategies.
Further, in this embodiment, the analysis module 105 is specifically implemented as:
the analysis module 105 simulates the three scenes 100 times respectively, the simulation result of each time is counted according to the day, and finally the mean value of the 100 times of simulation and the 95% confidence interval are obtained. The time distribution results of the local cases and those of the simulated symptomatic infected persons are shown by time series graphs (fig. 5-7) and daily cumulative graphs (fig. 8-10), respectively. Wherein, the black curve in the graph represents the actual local case of Shenzhen city in 2014; the red curve represents the mean of the number of symptomatic infected persons for 100 simulations; the gray areas indicate 95% confidence intervals. As can be seen from the simulation results of FIGS. 5-7 and 8-10, the model can better simulate the spreading process of dengue fever in the time dimension. Although the number of days of peak and the size of peak were somewhat different from the local actual cases after the results of 100 simulations were averaged, the simulation was generally good. Meanwhile, the time sequence diagrams of the three scenes can show that when the home address of the asymptomatic infected person is distributed according to the spatial distribution (figure 5) of the input case, the simulation effect of the model is better, and the number of rush hour days and the size of the peak value are more consistent with those of the local actual case.
Similarly, when the analysis module 105 analyzes the spatial distribution result, the results of 100 simulations are counted according to the spatial grid of 1km × 1km as the basic spatial unit, then the average of the number of cases simulated for 100 times per grid is obtained, and finally the average is compared with the spatial distribution result of the actual case, so as to analyze the spatial distribution characteristics of the simulation result and the simulation effect of the model on the spatial distribution. As can be seen from the spatial distribution of the simulation results in fig. 11-13, the symptomatic infectors mainly concentrated in the baean region (adjacent to the southern mountain region), the southern mountain region, fodo, lawy region and longhua region, which is generally consistent with the spatial distribution of actual local cases in shenzhen city 2014 (as shown in fig. 14). The simulation results of the home address distribution scenarios of the three asymptomatic input cases show that the simulation results of the home positions of the asymptomatic infectors distributed according to the spatial distribution of the input cases are relatively accurate (fig. 11), and most accord with the actual local cases, especially the simulation results of the areas such as the southern mountain area, the lake area, the Baoan area and the adjacent part of the southern mountain area accord with the actual local cases, and are all areas with more and dense dengue cases.
Fig. 15 is a schematic structural diagram of a hardware device of a method for simulating spreading of an internal infectious disease in a city according to an embodiment of the present application. As shown in fig. 15, the device includes one or more processors and memory. Taking a processor as an example, the apparatus may further include: an input system and an output system.
The processor, memory, input system, and output system may be connected by a bus or other means, as exemplified by the bus connection in fig. 15.
The memory, as a non-transitory computer-readable electronic device, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules. The processor executes various functional applications and data processing of the electronic device, i.e., implements the processing method of the above-described method embodiment, by executing the non-transitory software program, instructions and modules stored in the memory.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data and the like. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and these remote memories may be connected to the processing system over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input system may receive input numeric or character information and generate a signal input. The output system may include a display device such as a display screen.
The one or more modules are stored in the memory and, when executed by the one or more processors, perform the following for any of the above method embodiments:
step a: initializing all population inside a city according to dengue input case data;
step b: constructing an individual mobile network for all the population of the initialized city according to individual trip chain information constructed by the multi-source track data, and calculating the residence time of the individual in the place;
step c: calculating to obtain mosquito media space-time distribution according to meteorological data comprising daily average air temperature and daily rainfall;
step d: and according to the constructed individual mobile network, calculating the obtained residence time of the occupational region and the mosquito vector space-time distribution, constructing a spatial display individual transmission model, and simulating the transmission and diffusion process of the infectious diseases.
The product can execute the method provided by the embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details that are not described in detail in this embodiment, reference may be made to the methods provided in the embodiments of the present application.
Embodiments of the present application provide a non-transitory (non-volatile) computer electronic device having stored thereon computer-executable instructions that are operable to:
step a: initializing all population inside a city according to dengue input case data;
step b: constructing an individual mobile network for all the population of the initialized city according to individual trip chain information constructed by the multi-source track data, and calculating the residence time of the individual in the place;
step c: calculating to obtain mosquito media space-time distribution according to meteorological data comprising daily average air temperature and daily rainfall;
step d: and according to the constructed individual mobile network, calculating the obtained residence time of the occupational region and the mosquito vector space-time distribution, constructing a spatial display individual transmission model, and simulating the transmission and diffusion process of the infectious diseases.
Embodiments of the present application provide a computer program product comprising a computer program stored on a non-transitory computer readable electronic device, the computer program comprising program instructions that, when executed by a computer, cause the computer to perform the following:
step a: initializing all population inside a city according to dengue input case data;
step b: constructing an individual mobile network for all the population of the initialized city according to individual trip chain information constructed by the multi-source track data, and calculating the residence time of the individual in the place;
step c: calculating to obtain mosquito media space-time distribution according to meteorological data comprising daily average air temperature and daily rainfall;
step d: and according to the constructed individual mobile network, calculating the obtained residence time of the occupational region and the mosquito vector space-time distribution, constructing a spatial display individual transmission model, and simulating the transmission and diffusion process of the infectious diseases. According to the invention, the resident travel activities constructed based on the multi-source track data can truly reflect the movement modes and travel places of individuals in cities, and can simulate the interaction among the individuals more accurately, so that the accuracy of spreading simulation of infectious diseases such as dengue fever on space is improved, and the method can also be used for implementing simulation evaluation of more accurate intervention measures on time space. The spatial explicit individual model based on the multi-source trajectory data provides a framework for simulating the spread of infectious diseases such as dengue fever in cities, and provides scientific support for accurate simulation of infectious diseases and formulation of prevention and control strategies.
It should be noted that the present invention is capable of diffusion simulation for the transmission of a variety of infectious diseases using mosquito vectors as transmission routes, such as: infectious diseases such as dengue fever and malaria.
Although the present invention has been described with reference to the presently preferred embodiments, it will be understood by those skilled in the art that the foregoing description is illustrative only and is not intended to limit the scope of the invention, as claimed.
Claims (11)
1. A method for simulating the spread of an infectious disease in a city is characterized by comprising the following steps:
a. initializing all population inside a city according to dengue input case data;
b. constructing an individual mobile network for all the population of the initialized city according to individual trip chain information constructed by the multi-source track data, and calculating the residence time of the individual in the place;
c. calculating to obtain mosquito media space-time distribution according to meteorological data comprising daily average air temperature and daily rainfall;
d. and according to the constructed individual mobile network, calculating the obtained residence time of the occupational region and the mosquito vector space-time distribution, constructing a spatial display individual transmission model, and simulating the transmission and diffusion process of the infectious diseases.
2. The method of claim 1, wherein the method further comprises, before step a, the steps of:
acquiring source data; the source data comprises multi-source track data, dengue input case data and meteorological data; the multi-source trajectory data includes: census data, trip survey data, building data and mobile phone positioning data.
3. A method according to claim 1 or 2, characterized in that the method further comprises the step e:
and analyzing the space-time distribution mode of the urban internal infectious diseases according to the simulation result of the spatial explicit individual transmission model.
4. The method according to claim 3, wherein said step a specifically comprises:
initializing symptomatic infectors according to dengue fever input case data provided by an infectious disease prevention and control center;
according to each case of symptomatic infectors, generating a corresponding number of asymptomatic infectors according to the proportion of dengue symptomatic infectors and asymptomatic infectors, and initializing the asymptomatic infectors;
selecting a corresponding number of people from the initial population according to the proportion of the immune people in the city or the age distribution characteristics of the immune people and setting the people in an immune state.
5. The method according to claim 4, wherein said step b specifically comprises:
carrying out large-scale individual movement modeling according to the multi-source track data and constructing individual trip chain information, wherein the individual trip chain information refers to trip location information of an individual for 24 hours a day;
identifying and obtaining the occupational places of the individuals according to the individual trip chain information, the census data and the building data, and constructing a network for the individuals to move among the occupational places and buildings;
and calculating the residence time of each individual in the place of employment through the obtained information of the place of employment and the individual trip chain.
6. The method according to claim 5, wherein said step c specifically comprises:
respectively calculating the daily average air temperature of the previous month and the accumulated rainfall of the previous month in each area in the infectious disease simulation period according to the daily average air temperature and rainfall meteorological factors of each area;
and calculating the daily mosquito vector space-time distribution condition of each area according to the calculated daily average air temperature of the previous month and the accumulated rainfall days of the previous month of each area and a relational expression of the mosquito vector quantity and the two meteorological factors.
7. The method according to claim 6, wherein said step d specifically comprises:
an independent building is used as a simulation unit, and a classical SEIR model is combined to model the spread of viruses in the crowd and the dynamic transfer among different states of individuals in the crowd;
the simulation of dengue transmission spread was performed using a spatial explicit individual model in day steps, starting from the first day that the first input case in the population was infected until the entire dengue transmission simulation process ended.
8. The method according to claim 7, wherein said step e specifically comprises:
when time distribution results are analyzed, the scene is simulated for N times respectively, the simulation results of each time are counted according to the day, and finally the mean value and 95% confidence interval of the N times of simulation are obtained;
when the spatial distribution result is analyzed, a 1km x 1km spatial grid is used as a basic spatial unit for spatial analysis, the spatial distribution result of the dengue epidemic under the grid scale is analyzed, the scene is simulated for N times respectively, the spatial distribution result of the dengue infectors simulated each time is counted according to the grid, the mean value of the number of cases simulated for N times by each grid is solved respectively, and finally, the mean value is compared with the spatial distribution result of an actual case, and the spatial distribution characteristics of the simulation result and the simulation effect of the model on the spatial distribution are analyzed.
9. The system for simulating the spread of the infectious diseases in the city is characterized by comprising a population initialization module, a mobile network construction module, a mosquito medium space-time distribution module and a transmission simulation module, wherein:
the population initialization module is used for initializing all population inside a city according to dengue input case data;
the mobile network construction module is used for constructing an individual mobile network for all the initialized population of the city according to individual trip chain information constructed by the multi-source track data and calculating the residence time of the individual in the place;
the mosquito medium space-time distribution module is used for calculating to obtain mosquito medium space-time distribution according to meteorological data comprising daily average air temperature and daily rainfall;
the propagation simulation module is used for calculating the residence time of the occupational region and the mosquito vector space-time distribution according to the constructed individual mobile network, constructing a spatial display individual propagation model and simulating the propagation and diffusion process of infectious diseases.
10. The system of claim 9, wherein the system further comprises:
the acquisition module is used for acquiring source data; the source data comprises multi-source track data, dengue input case data and meteorological data; the multi-source trajectory data includes: census data, trip survey data, building data and mobile phone positioning data;
and the analysis module is used for analyzing the space-time distribution mode of the urban internal infectious diseases according to the simulation result of the spatial explicit individual transmission model.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the following operations of the method for simulating urban internal infectious disease spread according to any one of the above 1 to 8:
step a: initializing all population inside a city according to dengue input case data;
step b: constructing an individual mobile network for all the population of the initialized city according to individual trip chain information constructed by the multi-source track data, and calculating the residence time of the individual in the place;
step c: calculating to obtain mosquito media space-time distribution according to meteorological data comprising daily average air temperature and daily rainfall;
step d: and according to the constructed individual mobile network, calculating the obtained residence time of the occupational region and the mosquito vector space-time distribution, constructing a spatial display individual transmission model, and simulating the transmission and diffusion process of the infectious diseases.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114582522A (en) * | 2022-03-04 | 2022-06-03 | 中国人民解放军军事科学院军事医学研究院 | Infectious disease aerosol propagation modeling simulation method and system based on Gaussian diffusion |
| CN115831388A (en) * | 2023-02-17 | 2023-03-21 | 南京市疾病预防控制中心 | Infectious disease simulation early warning method and system based on big data |
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