Abstract
BackgroundCases of dengue fever have increased in areas of Southeast Asia in recent years. Taiwan hit a record-high 42,856 cases in 2015, with the majority in southern Tainan and Kaohsiung Cities. Leveraging spatial statistics and geo-visualization techniques, we aim to design an online analytical tool for local public health workers to prospectively identify ongoing hot spots of dengue fever weekly at the village level.MethodsA total of 57,516 confirmed cases of dengue fever in 2014 and 2015 were obtained from the Taiwan Centers for Disease Control (TCDC). Incorporating demographic information as covariates with cumulative cases (365 days) in a discrete Poisson model, we iteratively applied space–time scan statistics by SaTScan software to detect the currently active cluster of dengue fever (reported as relative risk) in each village of Tainan and Kaohsiung every week. A village with a relative risk >1 and p value <0.05 was identified as a dengue-epidemic area. Assuming an ongoing transmission might continuously spread for two consecutive weeks, we estimated the sensitivity and specificity for detecting outbreaks by comparing the scan-based classification (dengue-epidemic vs. dengue-free village) with the true cumulative case numbers from the TCDC’s surveillance statistics.ResultsAmong the 1648 villages in Tainan and Kaohsiung, the overall sensitivity for detecting outbreaks increases as case numbers grow in a total of 92 weekly simulations. The specificity for detecting outbreaks behaves inversely, compared to the sensitivity. On average, the mean sensitivity and specificity of 2-week hot spot detection were 0.615 and 0.891 respectively (p value <0.001) for the covariate adjustment model, as the maximum spatial and temporal windows were specified as 50% of the total population at risk and 28 days. Dengue-epidemic villages were visualized and explored in an interactive map.ConclusionsWe designed an online analytical tool for front-line public health workers to prospectively detect ongoing dengue fever transmission on a weekly basis at the village level by using the routine surveillance data.
Highlights
Cases of dengue fever have increased in areas of Southeast Asia in recent years
Prospective scan statistics have been applied in detecting ongoing transmission of malaria [8], shigellosis [9, 10], and Campylobacter [5], what health workers might be interested in is the ability to relate existing hot spots to future infection [8, 11]
To evaluate the detection capability, different model specifications, percentages of the total population at risk, and lengths of the maximum temporal window were manipulated in SaTScan
Summary
Cases of dengue fever have increased in areas of Southeast Asia in recent years. Taiwan hit a recordhigh 42,856 cases in 2015, with the majority in southern Tainan and Kaohsiung Cities. Prospective scan statistics have been applied in detecting ongoing transmission of malaria [8], shigellosis [9, 10], and Campylobacter [5], what health workers might be interested in is the ability to relate existing hot spots to future infection [8, 11]. Taking DF as an example, since DF is an acute transmission disease, health workers might want to identify the hot spots in week t, and be interested in the duration of the identified hot spots, which is important for them to plan the insecticide spraying campaign for the coming 1 (weekt+1) or 2 (weekt+2) weeks. With the advance in online techniques and utilization of mobile phones, an online scan statistics tool might help public health workers detect ongoing transmission promptly, compared to the current desktop software
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
