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Spatial-temporal distribution of dengue and climate characteristics for two clusters in Sri Lanka from 2012 to 2016.
Dengue is a vector-borne disease causing high morbidity and mortality in tropical and subtropical countries. Urbanization, globalization, and lack of effective mosquito control have lead to dramatically increased frequency and magnitude of dengue epidemic in the past 40 years. The virus and the mosquito vectors keep expanding geographically in the tropical regions of the world. Using the hot spot analysis and the spatial-temporal clustering method, we investigated the spatial-temporal distribution of dengue in Sri Lanka from 2012 to 2016 to identify spatial-temporal clusters and elucidate the association of climatic factors with dengue incidence. We detected two important spatial-temporal clusters in Sri Lanka. Dengue incidences were predicted by combining historical dengue incidence data with climate data, and hot and cold spots were forecasted using the predicted dengue incidences to identify areas at high risks. Targeting the hot spots during outbreaks instead of all the regions can save resources and time for public health authorities. Our study helps better understand how climatic factors impact spatial and temporal spread of dengue virus. Hot spot prediction helps public health authorities forecast future high risk areas and direct control measures to minimize cost on health, time, and economy.
Harbin Engineering University, Department of Mathematics, Harbin, 150001, China.,
Harbin Engineering University, Department of Mathematics, Harbin, 150001, China. Ling.Xue@umanitoba.ca. University of Manitoba, Department of Mathematics, Winnipeg, R3T 2M8, Canada. Ling.Xue@umanitoba.ca.
Harbin Engineering University, Department of Mathematics, Harbin, 150001, China.
Pub Type(s)Journal Article