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Local population and regional environmental drivers of cholera in Bangladesh

Creators: Emch, Michael, Yunus, Mohammad, Escamilla, Veronica, Feldacker, Caryl, Ali, Mohammad

File Type: pdf | Filesize: 575.7 KB | Date Added: 2012-08-23 | Date Created: 2010-01-14

Abstract Background Regional environmental factors have been shown to be related to cholera. Previous work in Bangladesh found that temporal patterns of cholera are positively related to satellite-derived environmental variables including ocean chlorophyll concentration (OCC). Methods This paper investigates whether local socio-economic status (SES) modifies the effect of regional environmental forces. The study area is Matlab, Bangladesh, an area of approximately 200,000 people with an active health and demographic surveillance system. Study data include (1) spatially-referenced demographic and socio-economic characteristics of the population; (2) satellite-derived variables for sea surface temperature (SST), sea surface height (SSH), and OCC; and (3) laboratory confirmed cholera case data for the entire population. Relationships between cholera, the environmental variables, and SES are measured using generalized estimating equations with a logit link function. Additionally two separate seasonal models are built because there are two annual cholera epidemics, one pre-monsoon, and one post-monsoon. Results SES has a significant impact on cholera occurrence: the higher the SES score, the lower the occurrence of cholera. There is a significant negative association between cholera incidence and SSH during the pre-monsoon period but not for the post-monsoon period. OCC is positively associated with cholera during the pre-monsoon period but not for the post-monsoon period. SST is not related to cholera incidence. Conclusions Overall, it appears cholera is influenced by regional environmental variables during the pre-monsoon period and by local-level variables (e.g., water and sanitation) during the post-monsoon period. In both pre- and post-monsoon seasons, SES significantly influences these patterns, likely because it is a proxy for poor water quality and sanitation in poorer households.