Evaluation of Possible Dengue Outbreak Detection Methodologies for Thailand, which one should be implemented?
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Date
2017-06-26
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Johns Hopkins University
Abstract
Dengue has become a more impact vector-borne disease than malaria globally in both morbidity distribution and economic resources. The burdens of Dengue in Thailand seem to be one of the highest in the South-East Asia Region of the World Health Organization (WHO). Current WHO’s Dengue Strategic Plan is to improve the countries’ capacity for early detection to allow timely outbreak prevention and control. However, there are only few published research papers that address the use, implementation and evaluation of novel early detection methodologies. This is a first national operational research project with objectives to study the feasibility of implementing modern dengue outbreak detection methodologies and to evaluate these methods at better alternatives to the current outbreak detection method (median-5-years) in Thailand. We conducted a descriptive Ecological study from a complete Dengue dataset retrieved from the Department of Epidemiology, Ministry of Public Health, Thailand. During 2003-2015, there were 1,014,201 visits and 13 outbreaks of Dengue virus with the largest attack in 2013. While each of the studied detection methods displayed unique characteristics, we observed similar values of the averages and medians, upper Confidence Intervals (CI)and percentiles across three methods. Same period media-5-years might be good for alert threshold. EARS methods were able to detect every outbreak but they did not provide information on outbreak long-term trend or magnitude. Moving percentiles or upper CI could provide information for long-term trends and epidemic thresholds. Off-seasonal median or average might be suitable for seasonal thresholds. Each detection method has its own strengths and weaknesses, thus implementing these methodologies could be of great epidemiological assistance local public health surveillance systems and for early Dengue outbreak detection.
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Keywords
Dengue, Public Health Informatics, early disease detection, Surveillance systems, Disease Notification, Thailand