The Role of Climate Variability in the Spread of Malaria in Bangladeshi Highlands

被引:57
作者
Haque, Ubydul [1 ,2 ]
Hashizume, Masahiro [1 ,2 ]
Glass, Gregory E. [3 ]
Dewan, Ashraf M. [4 ,5 ]
Overgaard, Hans J. [6 ]
Yamamoto, Taro [1 ,2 ]
机构
[1] Nagasaki Univ, NEKKEN, Inst Trop Med, Dept Int Hlth, Nagasaki 852, Japan
[2] Nagasaki Univ, Global Ctr Excellence Program, Nagasaki 852, Japan
[3] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Mol Microbiol & Immunol, Baltimore, MD USA
[4] Univ Dhaka, Dept Geog & Environm, Dhaka 1000, Bangladesh
[5] Curtin Univ Technol, Dept Spatial Sci, Perth, WA, Australia
[6] Norwegian Univ Life Sci, Dept Math Sci & Technol, As, Norway
关键词
SEA-SURFACE TEMPERATURE; EL-NINO; REGRESSION-MODELS; RAINFALL; EPIDEMICS; ERITREA; DIPOLE;
D O I
10.1371/journal.pone.0014341
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: 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 Nino-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). Methods and Principal Findings: 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 Nino Region 3 (NINO3) 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 NINO3. Conclusion and Significance: 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.
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页数:9
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