Cargando…

Analysis of Effects of Meteorological Factors on Dengue Incidence in Sri Lanka Using Time Series Data

In tropical and subtropical regions of eastern and South-eastern Asia, dengue fever (DF) and dengue hemorrhagic fever (DHF) outbreaks occur frequently. Previous studies indicate an association between meteorological variables and dengue incidence using time series analyses. The impacts of meteorolog...

Descripción completa

Detalles Bibliográficos
Autores principales: Goto, Kensuke, Kumarendran, Balachandran, Mettananda, Sachith, Gunasekara, Deepa, Fujii, Yoshito, Kaneko, Satoshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3650072/
https://www.ncbi.nlm.nih.gov/pubmed/23671694
http://dx.doi.org/10.1371/journal.pone.0063717
_version_ 1782269071223422976
author Goto, Kensuke
Kumarendran, Balachandran
Mettananda, Sachith
Gunasekara, Deepa
Fujii, Yoshito
Kaneko, Satoshi
author_facet Goto, Kensuke
Kumarendran, Balachandran
Mettananda, Sachith
Gunasekara, Deepa
Fujii, Yoshito
Kaneko, Satoshi
author_sort Goto, Kensuke
collection PubMed
description In tropical and subtropical regions of eastern and South-eastern Asia, dengue fever (DF) and dengue hemorrhagic fever (DHF) outbreaks occur frequently. Previous studies indicate an association between meteorological variables and dengue incidence using time series analyses. The impacts of meteorological changes can affect dengue outbreak. However, difficulties in collecting detailed time series data in developing countries have led to common use of monthly data in most previous studies. In addition, time series analyses are often limited to one area because of the difficulty in collecting meteorological and dengue incidence data in multiple areas. To gain better understanding, we examined the effects of meteorological factors on dengue incidence in three geographically distinct areas (Ratnapura, Colombo, and Anuradhapura) of Sri Lanka by time series analysis of weekly data. The weekly average maximum temperature and total rainfall and the total number of dengue cases from 2005 to 2011 (7 years) were used as time series data in this study. Subsequently, time series analyses were performed on the basis of ordinary least squares regression analysis followed by the vector autoregressive model (VAR). In conclusion, weekly average maximum temperatures and the weekly total rainfall did not significantly affect dengue incidence in three geographically different areas of Sri Lanka. However, the weekly total rainfall slightly influenced dengue incidence in the cities of Colombo and Anuradhapura.
format Online
Article
Text
id pubmed-3650072
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-36500722013-05-13 Analysis of Effects of Meteorological Factors on Dengue Incidence in Sri Lanka Using Time Series Data Goto, Kensuke Kumarendran, Balachandran Mettananda, Sachith Gunasekara, Deepa Fujii, Yoshito Kaneko, Satoshi PLoS One Research Article In tropical and subtropical regions of eastern and South-eastern Asia, dengue fever (DF) and dengue hemorrhagic fever (DHF) outbreaks occur frequently. Previous studies indicate an association between meteorological variables and dengue incidence using time series analyses. The impacts of meteorological changes can affect dengue outbreak. However, difficulties in collecting detailed time series data in developing countries have led to common use of monthly data in most previous studies. In addition, time series analyses are often limited to one area because of the difficulty in collecting meteorological and dengue incidence data in multiple areas. To gain better understanding, we examined the effects of meteorological factors on dengue incidence in three geographically distinct areas (Ratnapura, Colombo, and Anuradhapura) of Sri Lanka by time series analysis of weekly data. The weekly average maximum temperature and total rainfall and the total number of dengue cases from 2005 to 2011 (7 years) were used as time series data in this study. Subsequently, time series analyses were performed on the basis of ordinary least squares regression analysis followed by the vector autoregressive model (VAR). In conclusion, weekly average maximum temperatures and the weekly total rainfall did not significantly affect dengue incidence in three geographically different areas of Sri Lanka. However, the weekly total rainfall slightly influenced dengue incidence in the cities of Colombo and Anuradhapura. Public Library of Science 2013-05-09 /pmc/articles/PMC3650072/ /pubmed/23671694 http://dx.doi.org/10.1371/journal.pone.0063717 Text en © 2013 Goto et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Goto, Kensuke
Kumarendran, Balachandran
Mettananda, Sachith
Gunasekara, Deepa
Fujii, Yoshito
Kaneko, Satoshi
Analysis of Effects of Meteorological Factors on Dengue Incidence in Sri Lanka Using Time Series Data
title Analysis of Effects of Meteorological Factors on Dengue Incidence in Sri Lanka Using Time Series Data
title_full Analysis of Effects of Meteorological Factors on Dengue Incidence in Sri Lanka Using Time Series Data
title_fullStr Analysis of Effects of Meteorological Factors on Dengue Incidence in Sri Lanka Using Time Series Data
title_full_unstemmed Analysis of Effects of Meteorological Factors on Dengue Incidence in Sri Lanka Using Time Series Data
title_short Analysis of Effects of Meteorological Factors on Dengue Incidence in Sri Lanka Using Time Series Data
title_sort analysis of effects of meteorological factors on dengue incidence in sri lanka using time series data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3650072/
https://www.ncbi.nlm.nih.gov/pubmed/23671694
http://dx.doi.org/10.1371/journal.pone.0063717
work_keys_str_mv AT gotokensuke analysisofeffectsofmeteorologicalfactorsondengueincidenceinsrilankausingtimeseriesdata
AT kumarendranbalachandran analysisofeffectsofmeteorologicalfactorsondengueincidenceinsrilankausingtimeseriesdata
AT mettanandasachith analysisofeffectsofmeteorologicalfactorsondengueincidenceinsrilankausingtimeseriesdata
AT gunasekaradeepa analysisofeffectsofmeteorologicalfactorsondengueincidenceinsrilankausingtimeseriesdata
AT fujiiyoshito analysisofeffectsofmeteorologicalfactorsondengueincidenceinsrilankausingtimeseriesdata
AT kanekosatoshi analysisofeffectsofmeteorologicalfactorsondengueincidenceinsrilankausingtimeseriesdata