Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Oct 10;7(1):12884.
doi: 10.1038/s41598-017-13163-z.

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

Wei Sun  1 , Ling Xue  2   3 , Xiaoxue Xie  1
Affiliations

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

Wei Sun et al. Sci Rep. .

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.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
Annual dengue incidences for 25 districts of Sri Lanka from 2012 to 2016. We predicted dengue incidences for 2016 with dengue incidence data from 2012 to 2015 and meteorological data for 2016. The ∙ represents incidence data, the red lines represent the predicted data, and the dotted lines represent the confidence interval.
Figure 2
Figure 2
Dengue incidences and monthly climatic factors between 2012 and 2016 for the first cluster. The clustering period is highlighted in blue from May 2014 to September 2016..
Figure 3
Figure 3
Dengue incidences and monthly climatic factors between 2012 and 2016 for the second cluster. The clustering period is highlighted in blue from June 2013 to November 2015.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Massad E, Coutinho FAB. The cost of dengue control. The Lancet. 2011;377:1630–1631. doi: 10.1016/S0140-6736(11)60470-4. - DOI - PubMed
    1. Global strategy for dengue prevention and control, 2012–2020. Tech. Rep., World Health Organization, Geneva, Switzerland (2012).
    1. Gubler D. The global pandemic of dengue/dengue haemorrhagic fever: current status and prospects for the future. Ann Acad Med Singapore. 1998;27:227–234. - PubMed
    1. Gubler D. Epidemic dengue/dengue hemorrhagic fever as a public health, social and economic problem in the 21st century. Ann Acad Med Singapore. 2002;10:100–103. - PubMed
    1. Guzman M, et al. Dengue: a continuing global threat. Nature Reviews Microbiology. 2010;8:S7–S16. doi: 10.1038/nrmicro2460. - DOI - PMC - PubMed

Publication types