A framework for assessing location-based personalized exposure risk of infectious disease transmission

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A framework for assessing location-based personalized exposure risk of infectious disease transmission
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Seoul, South Korea

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Human mobility is an important risk factor affecting disease transmission. Therefore, understanding detailed spatial behaviors and interactions among individuals is a fundamental issue. Past studies using high-resolution human contacts data from smart phones with GPS logs have captured spatial-temporal heterogeneity and daily contact patterns among individuals. However, measuring personalized exposed risk of infectious disease transmission is still under development. The purpose of the study is to establish a location-based framework for assessing personalized exposed risk of infectious disease transmission. The framework consists of three components: the first is client-side smart phone-based risk assessment module. We developed Android application for collecting real-time location data and displaying the personalized exposed risk score. The second component is the server-side epidemic simulation model. The simulation model calculated the personalized exposed risk score based on real-time GPS logs and individual mobility data from the client-side Android application. The last component is the disease alarm device for triggering the service-side epidemic simulation model. We installed infrared sensors in people-gathering areas as the alarm device to monitor human body temperature for detecting fever syndrome. We used NTU main campus as a pilot study to demonstrate the feasibility of the framework. We analyzed the records of students’ taking course and modeled the spatial interaction relationships among classroom buildings due to students’ mobility around the campus. Someone who got a fever is detected by the sensor and the server-side epidemic simulation is triggered. Each student who installed the client-side risk assessment module in his/her smart phone receives the real-time personalized exposed risk score when an epidemic outbreak on the NTU campus. The study proposed a location-based framework for measuring real-time personalized exposed risk. Each student at the campus could understand the spatial diffusion of disease transmission and make better spatial decisions based on personalized exposed risk scores.
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the i glad to know ladies and gentlemen my
name is cheating shouldn't come from National Taiwan University the topic of my presentation today is a framework for assessing location-based personalized is false risk of infectious disease transmissions when we try to understand the
relationship between our health outcome and environmental portion small and most studies focus on present always pressure assessment because prayer and defend people spend their time from start the fire from the individual to individual it is important tool a sense is for the risk based on their behavior painter instead of of instead of clearly meanwhile we so that the regiment of GPS somewhere biosensors or personal monitoring device we can come personal we can to that person the opposite number but he states that in that environment daytime all occurrence and that into grad we use GIS to estimated not personalities portion of a state of risk sounds that the use of a body's issues are talking about things the sorry the at the time of that the some start about policy issues are talking about air pollution is or a pesticide use brochure and so on and in the analogy
most of us start these reason reasoners in human body tape that try to understand collective behavior is and the special diffusion of infectious disease for example how does the disease a break between the are hot easily in impact of borrow mobility retains IdeaFisher's disease dynamic they seldom folks on perspective on personal explores risk of infectious disease however there are some distinctive features between infectious disease and environmental pollution effects simple you know race car will be affected by the peoples around with you the mole people's at most think people around with you from all risk you are that is the source of infection crew could fester learning environment or Perugian on the other hand the impact of that the small years and quickly FIL some my introduction but with GPS or positioning function in the with both device we can collect high-resolution individuals space time data based on these state we have a boat to understand that was on moment of erosion is portion but other in it the knowledge that perspective on personal use progerin assessment of infectious disease is still on unclear so our performance of Li's study that the prose of this study is to establish a framework for assessing personalized response risk assessment of of tool to of sensing present noise was risk of infectious disease transmission that
framework consists of tool components of 1st he's kind sided smartphone applications we develop enjoy application for connecting present to be as look state hot and the providing users personalities pose risk some assessments of each the 2nd is the cited it then makes simulation model another similar to the spatial diffusion of the and integrated with the personal liberty he died hot calculated the personal risks In this model we analyze students course taking makers to understand how those students but walked on sorry we use score composer Praat study to demonstrate a facility of this framework are how we analyze students course taking records tool to understand how students walk on the components and the 2 model laws they show interactions between Kasteren buildings and the wizard is relationship we can model of spatial of diffusion of the disease on the campus to that is
my study area mission what our university Mencken those there are 75 classroom buildings that is still the ceremony database outweighs greedy function weekend and all last students course taking makers from individual to individual of for example which cause he texts and of and if it'll go to a class for example these still there is no goal tool Gymnasien I'm on this morning and then go to building a and a from doing and 2 butene B and so on so always this information we can analyze he's rout routes on campus and we divide these rules in tool tool time slice morning and afternoon then we I could get all of the students through summer campers to tool instead of a schlub buildings network it is already origin-destination they trees for each time slice so we can understand the spatial even our social interactions between classroom buildings peer and we integrate that their relationship we use meant operation approach and SII are still model to simulate last spatial diffusion of the season the candidates with the model we can all learn dynamic efficient patents by buildings pierheads state and are based on a lot the nation in the analogy the force of infection in the country at this index of of a risk score for each doing so far we can understand the dynamic of disease diffusion and can answer some questions fall example with Praat he then the curve of release of break we we can realize around the we have to friend disease control strategy but by legalizing the risk score of each building is weekend all rich buildings is the most serious 1 at a specific date and I have to point out the other buildings that have crossed relationship we close relation issues means are there are a lot of students coming to go between 2 buildings he for 1 buildings outbreak and I'll let easiest would spread tool the other 1 because and based on this information we can turn the strategy more precisely last we are going to
look at the function of most smartphone applications thank you is
that is the rat being and environment which consist of 3 functions including re progesterone a call collecting personal GPS lock state hot and the creating present risk of infectious disease transmission 1st sorry just a relation is to create an account to and in database and the provide users whose risk assessment and that the other information so we why
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simulating spread of loss of the season we can understand the spatial patterns of each of the sparse risk and all the like an old ladies patents Willie's present our rules on the campus the based on is idea we developed indicator to measure how dangerous the user's ease as personally sponsored risks for finally
at that greedy you saying the vast media site to type of creating the 1st 1 is kind has created fat environment risk think about disease outbreak of us you do as a student you may want to know how dangerous is that buildings he's going to and we see that Query users can understand the spatial patterns of real risk on the candidates on the other side but you personal clearly provide their risks got information to each user low risks got you space on their own would be that the payments layout a ball to model the risk that have been encountered or are going to fax release of we suppose information can help users make better spatial decision such as those of wallet tool of all be staying high risk price tool reveals that probability of dating sink Our if he doesn't feel we'll and what he found that he has disposed to high risk and it is is better for him tools I see about pattern over where send 3 paramedic but but but so in
conclusion we've of loss of a framework for personal use the risk of infectious disease transmission which consists of smartphone at and that it did make simulation models we use information about the environment at risk or personal risk we may make better decisions in a disease outbreak thank you any
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my thanks thank you thank you very much