Real-time dengue forecast for outbreak alerts in southern Taiwan
Journal
PLoS neglected tropical diseases
Journal Volume
14
Journal Issue
7
Pages
1-18
Date Issued
2020
Author(s)
Cheng, Y.-C.
Lee, F.-J.
Hsu, Y.-T.
Slud, E.V.
Hsiung, C.A.
Chen, C.-H.
Liao, C.-L.
Wen, T.-H.
Chang, C.-W.
Chang, J.-H.
Wu, H.-Y.
Chang, T.-P.
Lin, P.-S.
Ho, H.-P.
Hung, W.-F.
Chou, J.-D.
Abstract
Dengue fever is a viral disease transmitted by mosquitoes. In recent decades, dengue fever has spread throughout the world. In 2014 and 2015, southern Taiwan experienced its most serious dengue outbreak in recent years. Some statistical models have been established in the past, however, these models may not be suitable for predicting huge outbreaks in 2014 and 2015. The control of dengue fever has become the primary task of local health agen-cies. This study attempts to predict the occurrence of dengue fever in order to achieve the purpose of timely warning. We applied a newly developed autoregressive model (AR model) to assess the association between daily weather variability and daily dengue case number in 2014 and 2015 in Kaohsiung, the largest city in southern Taiwan. This model also con-tained additional lagged weather predictors, and developed 5-day-ahead and 15-day-ahead predictive models. Our results indicate that numbers of dengue cases in Kaohsiung are associated with humidity and the biting rate (BR). Our model is simple, intuitive and easy to use. The developed model can be embedded in a "real-time" schedule, and the data (at present) can be updated daily or weekly based on the needs of public health workers. In this study, a simple model using only meteorological factors performed well. The proposed real-time forecast model can help health agencies take public health actions to mitigate the influ-ences of the epidemic. © 2020, Public Library of Science. All rights reserved.
Other Subjects
Article; bite; biting rate; climate change; dengue; Dengue virus; disease transmission; environmental temperature; epidemic; forecasting; human; humidity; mathematical model; public health; rainy season; risk factor; sensitivity analysis; Taiwan; virus transmission; dengue; forecasting; statistical model; temperature; weather; Dengue; Disease Outbreaks; Forecasting; Humans; Humidity; Models, Statistical; Taiwan; Temperature; Weather
Type
journal article