The role of climate variability in the spread of malaria in Bangladeshi highlands.

<h4>Background</h4>Malaria is a major public health problem in Bangladesh, frequently occurring as epidemics since the 1990s. Many factors affect increases in malaria cases, including changes in land use, drug resistance, malaria control programs, socioeconomic issues, and climatic facto...

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Main Authors: Ubydul Haque, Masahiro Hashizume, Gregory E Glass, Ashraf M Dewan, Hans J Overgaard, Taro Yamamoto
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2010-12-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21179555/?tool=EBI
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spelling doaj-70b5548310ac428dadb9e9051b01274d2021-03-04T02:11:31ZengPublic Library of Science (PLoS)PLoS ONE1932-62032010-12-01512e1434110.1371/journal.pone.0014341The role of climate variability in the spread of malaria in Bangladeshi highlands.Ubydul HaqueMasahiro HashizumeGregory E GlassAshraf M DewanHans J OvergaardTaro Yamamoto<h4>Background</h4>Malaria is a major public health problem in Bangladesh, frequently occurring as epidemics since the 1990s. Many factors affect increases in malaria cases, including changes in land use, drug resistance, malaria control programs, socioeconomic issues, and climatic factors. No study has examined the relationship between malaria epidemics and climatic factors in Bangladesh. Here, we investigate the relationship between climatic parameters [rainfall, temperature, humidity, sea surface temperature (SST), El Niño-Southern Oscillation (ENSO), the normalized difference vegetation index (NDVI)], and malaria cases over the last 20 years in the malaria endemic district of Chittagong Hill Tracts (CHT).<h4>Methods and principal findings</h4>Monthly malaria case data from January 1989 to December 2008, monthly rainfall, temperature, humidity sea surface temperature in the Bay of Bengal and ENSO index at the Niño Region 3 (NIÑO3) were used. A generalized linear negative binomial regression model was developed using the number of monthly malaria cases and each of the climatic parameters. After adjusting for potential mutual confounding between climatic factors there was no evidence for any association between the number of malaria cases and temperature, rainfall and humidity. Only a low NDVI was associated with an increase in the number of malaria cases. There was no evidence of an association between malaria cases and SST in the Bay of Bengal and NIÑO3.<h4>Conclusion and significance</h4>It seems counterintuitive that a low NDVI, an indicator of low vegetation greenness, is associated with increases in malaria cases, since the primary vectors in Bangladesh, such as An. dirus, are associated with forests. This relationship can be explained by the drying up of rivers and streams creating suitable breeding sites for the vector fauna. Bangladesh has very high vector species diversity and vectors suited to these habitats may be responsible for the observed results.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21179555/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Ubydul Haque
Masahiro Hashizume
Gregory E Glass
Ashraf M Dewan
Hans J Overgaard
Taro Yamamoto
spellingShingle Ubydul Haque
Masahiro Hashizume
Gregory E Glass
Ashraf M Dewan
Hans J Overgaard
Taro Yamamoto
The role of climate variability in the spread of malaria in Bangladeshi highlands.
PLoS ONE
author_facet Ubydul Haque
Masahiro Hashizume
Gregory E Glass
Ashraf M Dewan
Hans J Overgaard
Taro Yamamoto
author_sort Ubydul Haque
title The role of climate variability in the spread of malaria in Bangladeshi highlands.
title_short The role of climate variability in the spread of malaria in Bangladeshi highlands.
title_full The role of climate variability in the spread of malaria in Bangladeshi highlands.
title_fullStr The role of climate variability in the spread of malaria in Bangladeshi highlands.
title_full_unstemmed The role of climate variability in the spread of malaria in Bangladeshi highlands.
title_sort role of climate variability in the spread of malaria in bangladeshi highlands.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2010-12-01
description <h4>Background</h4>Malaria is a major public health problem in Bangladesh, frequently occurring as epidemics since the 1990s. Many factors affect increases in malaria cases, including changes in land use, drug resistance, malaria control programs, socioeconomic issues, and climatic factors. No study has examined the relationship between malaria epidemics and climatic factors in Bangladesh. Here, we investigate the relationship between climatic parameters [rainfall, temperature, humidity, sea surface temperature (SST), El Niño-Southern Oscillation (ENSO), the normalized difference vegetation index (NDVI)], and malaria cases over the last 20 years in the malaria endemic district of Chittagong Hill Tracts (CHT).<h4>Methods and principal findings</h4>Monthly malaria case data from January 1989 to December 2008, monthly rainfall, temperature, humidity sea surface temperature in the Bay of Bengal and ENSO index at the Niño Region 3 (NIÑO3) were used. A generalized linear negative binomial regression model was developed using the number of monthly malaria cases and each of the climatic parameters. After adjusting for potential mutual confounding between climatic factors there was no evidence for any association between the number of malaria cases and temperature, rainfall and humidity. Only a low NDVI was associated with an increase in the number of malaria cases. There was no evidence of an association between malaria cases and SST in the Bay of Bengal and NIÑO3.<h4>Conclusion and significance</h4>It seems counterintuitive that a low NDVI, an indicator of low vegetation greenness, is associated with increases in malaria cases, since the primary vectors in Bangladesh, such as An. dirus, are associated with forests. This relationship can be explained by the drying up of rivers and streams creating suitable breeding sites for the vector fauna. Bangladesh has very high vector species diversity and vectors suited to these habitats may be responsible for the observed results.
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21179555/?tool=EBI
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