Spatial-temporal distribution of dengue and climate characteristics for two clusters in Sri Lanka from 2012 to 2016

Abstract 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...

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Main Authors: Wei Sun, Ling Xue, Xiaoxue Xie
Format: Article
Language:English
Published: Nature Publishing Group 2017-10-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-017-13163-z
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spelling doaj-94c7dede302a48f89bda3f65d5f0e08f2020-12-08T03:17:51ZengNature Publishing GroupScientific Reports2045-23222017-10-017111210.1038/s41598-017-13163-zSpatial-temporal distribution of dengue and climate characteristics for two clusters in Sri Lanka from 2012 to 2016Wei Sun0Ling Xue1Xiaoxue Xie2Harbin Engineering University, Department of MathematicsHarbin Engineering University, Department of MathematicsHarbin Engineering University, Department of MathematicsAbstract 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.https://doi.org/10.1038/s41598-017-13163-z
collection DOAJ
language English
format Article
sources DOAJ
author Wei Sun
Ling Xue
Xiaoxue Xie
spellingShingle Wei Sun
Ling Xue
Xiaoxue Xie
Spatial-temporal distribution of dengue and climate characteristics for two clusters in Sri Lanka from 2012 to 2016
Scientific Reports
author_facet Wei Sun
Ling Xue
Xiaoxue Xie
author_sort Wei Sun
title Spatial-temporal distribution of dengue and climate characteristics for two clusters in Sri Lanka from 2012 to 2016
title_short Spatial-temporal distribution of dengue and climate characteristics for two clusters in Sri Lanka from 2012 to 2016
title_full Spatial-temporal distribution of dengue and climate characteristics for two clusters in Sri Lanka from 2012 to 2016
title_fullStr Spatial-temporal distribution of dengue and climate characteristics for two clusters in Sri Lanka from 2012 to 2016
title_full_unstemmed Spatial-temporal distribution of dengue and climate characteristics for two clusters in Sri Lanka from 2012 to 2016
title_sort spatial-temporal distribution of dengue and climate characteristics for two clusters in sri lanka from 2012 to 2016
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2017-10-01
description Abstract 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.
url https://doi.org/10.1038/s41598-017-13163-z
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AT lingxue spatialtemporaldistributionofdengueandclimatecharacteristicsfortwoclustersinsrilankafrom2012to2016
AT xiaoxuexie spatialtemporaldistributionofdengueandclimatecharacteristicsfortwoclustersinsrilankafrom2012to2016
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