Simulating Interventions On Intra-urban Dengue Outbreaks Using Large-scale Mobile Phone Tracking Data

With the rapid development of information and communication technology and social media network,it is possible to get massive individual trajectory data which contains time and space information of individual mobility or activity on different spatiotemporal.Recently,it becomes a hot research topic in the field of Human science,sociology and geography etc that studying human mobility patterns or urban dynamic with mobile phone data,GPS data and social media data et al.Due to the mobile phone tracking data can reflect the trajectory of mobile phone users,when this kind of data combined the infectious disease prevalence map can reveal the existing or potential risk of disease,to identify the infectious disease epidemic area and the main sources of traffic,to provide quantitative guidance for the intervention of infectious disease.It provides a new thought for the study of infectious disease that mapping epidemical transmission risk and simulating interventions on infectious disease outbreaks using large-scale mobile phone tracking data.However,such research is still in its infancy,there are a lot of challenges in the research scale,mobile phone tracking data’s type and intervention strategies.In view of the above challenges,this paper makes a simulation study on the intervention strategies of Shenzhen city’s dengue fever with large-scale and regular sampled mobile phone tracking data.The main research content includes the following three aspects:①We make a local infection risk map of dengue fever with random forest algorithm to identify the high local infection risk areas quickly.②Then,this paper uses the large-scale and regular sampled mobile phone tracking data to assess the importation risk value of dengue fever in Shenzhen city.③The assessment results show us the major local infection risk areas and major importation risk areas.Based on these results of the above assessment,we make some intervention strategies,simulate these intervention strategies.On one hand,we simulate a strategy that we eliminate aedes albopictus in high local infection risk areas.On the other hand,we simulate another strategy that we intervene the travel of mobile phone users’ with high infection probability from spatial,time dimension’s and space-time’s perspective.In the end,we analysis the results and evaluate these intervention strategies.The contributions of this paper are as follows:(1)Build a framework for the intervention study of mosquito-borne infectious diseases with big hourly cellphone tracking data.There is no mobile phone trajectory data in the study of mosquito-borne diseases.Millions of cellphone tracking records,when combined with disease incidence or parasite prevalence data,can reveal existing and potential disease risks.This paper construct the framework for mosquito-borne infectious diseases’intervention with big hourly cellphone tracking data.This framework is based on big hourly cellphone tracking data,which can better reflect the residents travel trajectory.It improved the reliability of the result,filled the vacancy in the research of mosquito-borne infectious diseases in the past.This framework can be improved for other regions and other infectious diseases’ study in the future,improve the scientific guidance.(2)Present a method for risk assessment of dengue fever with high spatial and temporal resolution on inner-urban scale.Recently,most infectious diseases’ studies have been focused on mapping disease risk at national and regional scales.Few efforts have been devoted to an urban-scale risk mapping with cellphone tracking data,in which intra-urban travels are explicitly represented.The spatial and temporal resolution of the existing mosquito-borne infectious diseases’ risk assessment were low,which taken the ’day’as the unit of time,the ’state’ or ’city’ as the unit of space.The risk assessment with low spatial and temporal resolution was difficult to get efficient intervention.This paper present a method for risk assessment of dengue fever with high spatial and temporal resolution on inner-urban scale.It bases on dengue fever data and assess risk with high temporal-spatial resolution,which take the ’hour’ as the unit of time,the’cell tower’ as the unit of space.The assessment results have high temporal-spatial resolution and can help to improve the reliability of risk assessment and simulation results.It filled the vacancy in the research of infectious disease on inner-urban scale.(3)Design and simulate a series of intervention strategies with high space-time resolution on intra-urban scale from spatial,time dimension’s and space-time’s perspectives.In the current literature,however,few of these intervention programs could be labelled ’precision’,even though precision tools and big data were heavily utilized.First of all,few of these intervention programs are precise in time.A majority of studies have used massive mobile phone tracking data to map spatial distribution of sources and sinks of people and disease agents.The intervention strategies being suggested are therefore spatial targeting programs.None of them have explored the time dimension.Second,A major reason is these studies were conducted at a national level,and the detailed mobile phone records needed to be aggregated to coarser spatial and temporal scales(e.g.,by prefecture and by week)to ease the analysis.This paper bases on space-time trajectory of resident designs a list of intervention strategies with high space-time resolution on intra-urban dengue outbreaks from spatial,time dimension’s and space-time’s perspectives,to reduce the importation risk.The results indicated that intervening the travel of mobile phone users’ with high infection probability is also very important in dengue’s interventions.It improve the space-time resolution and efficiency of the deployment of intervention.This paper proposes a new research framework with guiding significance for intra-urban disease control and prevention.