Leveraging the Niche of Open Data for Disease Surveillance and Health Education

How to Cite

Chan, T.-C., Teng, Y.-C., Kuo, C.- ling, Yeh, Y.-H., & Lin, B.-C. (2017). Leveraging the Niche of Open Data for Disease Surveillance and Health Education. Online Journal of Public Health Informatics, 9(1). https://doi.org/10.5210/ojphi.v9i1.7621


ObjectiveTo visualize the incidence of notifiable infectious diseasesspatially and interactively, we aimed to provide a friendly interfaceto access local epidemic information based on open data for healthprofessionals and the public.IntroductionTransparency of information on infectious disease epidemicsis crucial for not only public health workers but also the residentsin the communities. Traditionally, disease control departmentscreated official websites for displaying disease maps or epi-curveswith the confirmed case counts. The websites were usually veryformal and static, without interaction, animation, or even the aid ofspatial statistics. Therefore, we tried to take advantage of open dataand use a lightweight programming language, JavaScript, to createan interactive website, named “Taiwan Infectious Disease Map(http://ide.geohealth.tw/)“. With the website, we expect to providereal-time incidence information and related epidemiological featuresusing interactive maps and charts.MethodsThis study used infectious-disease-related open data from Taiwan’sopen data platform (http://data.gov.tw) maintained by the TaiwanCDC. It covers 70 types of infectious diseases starting from 2004, andthe latest status is updated every day. We then automatically bridgethis data into our database and calculate the age-adjusted incidencerate by annual census data and 2000 WH0 standard population.The spatial resolution is mostly at the township level, except thatresolution for sexually-transmitted infectious diseases is at the citylevel. The temporal resolution is month and year, except for denguefever, which is by week.We used R software to automatically compute incidence everyday, and also used its package named “spdep” to compute the spatialclusters of the selected infectious diseases online. In addition, weused JavaScript language, PHP, OpenLayers 3 and Highcharts toimplement interactive maps and charts. All the data and graphicalfigures from the charts viewed in this website can be downloadedfreely. The temporal animation slider can be played and paused atany time point. The health education button can directly link to anintroduction to the selected infectious disease maintained by theTaiwan CDC.ResultsThe website of the Taiwan Infectious Disease Map is displayedin Figure 1. The users can select the temporal precision, types ofinfectious diseases, spatial precision and the gender at the beginning.In this case, the left map is the spatial distribution of the cumulativeincidence of tuberculosis (TB) in 2016. The darker red color representshigher incidence. The right top panel is the ranking of TB incidenceamong 368 townships. The right middle panel is the ranking of TBincidence among 22 cities or counties. The right bottom panel is theannual TB incidence from 2004 to the current date. The highest TBincidence was 67.47 per 100,000 in 2004, and this declined sharply to15.92 per 100,000 in 2015.ConclusionsWith this user-friendly web application, the public and localpublic health workers can easily understand the current risk for theirtownships. The application can provide relevant health education forthe public to understand diseases and how to protect themselves. Thespatial clusters, gender distribution, age distribution, epi-curve andtop ten infectious diseases are all practical and important informationprovided from this website to assist in preventing and mitigating nextepidemic.
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