Scientists in the US have developed a statistical model that can accurately forecast dengue outbreaks in Thailand.
Dengue hemorrhagic fever (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.
In the present study, a team of researchers led by Associate Professor Stephen A. Lauer and colleagues at the University of Massachusetts Amherst, US, 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 percent of the province-years, and could rank 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.
The article can be found at: Lauer et al. (2018) Prospective Forecasts of Annual Dengue Hemorrhagic Fever Incidence in Thailand, 2010–2014.
Source: Proceedings of the National Academy of Sciences of the United States of America