Researchers test statistical models for forecasting outbreaks of dengue hemorrhagic fever (DHF) in Thailand. DHF affects between 15,000 and 105,000 people annually in Thailand. However, the distribution of DHF cases varies each year, complicating prevention and treatment strategies. Stephen A. Lauer and colleagues used demographic, weather, and dengue incidence data to develop models for predicting DHF outbreaks in Thailand. The authors compared observed DHF data and baseline forecasts with two model types--one based on weather, incidence, and population (WIP) data and another incorporating only incidence data. The models were tested in each of Thailand's 76 provinces from 2010 to 2014, equivalent to 380 province-years. In 217 of the 380 province-years, the authors found that the incidence-only model better reflected the observed DHF incidence data than did the WIP model. Additionally, the incidence-only model outperformed baseline forecasts in 65% of the province-years, and ordered provinces by outbreak risk. In Thailand's 13 health regions as defined by the Thailand Ministry of Public Health, the incidence-only and WIP models performed best in 10 of 13 and 2 of 13 health regions, respectively. Relative to baseline forecasts, the WIP model performed better in regions with colder and rainier low-dengue seasons. The findings carry implications for public health strategies aimed at curbing the spread of infectious disease, according to the authors.
Article #17-14457: "Prospective forecasts of annual dengue hemorrhagic fever incidence in Thailand, 2010-2014," by Stephen A. Lauer et al.
MEDIA CONTACT: Stephen A. Lauer, University of Massachusetts Amherst, MA; tel: 978-460-4797; e-mail: <slauer@schoolph.umass.edu>
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