The role of socioeconomic status in longitudinal trends of cholera in Matlab, Bangladesh, 1993-2007.
There has been little evidence of a decline in the global burden of cholera in recent years as the number of cholera cases reported to WHO continues to rise. Cholera remains a global threat to public health and a key indicator of lack of socioeconomic development. Overall socioeconomic development i...
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Autores principales: | , , , |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2013
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Materias: | |
Acceso en línea: | https://doaj.org/article/8da2d5ca4fae42fc883d1e9176011c16 |
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Sumario: | There has been little evidence of a decline in the global burden of cholera in recent years as the number of cholera cases reported to WHO continues to rise. Cholera remains a global threat to public health and a key indicator of lack of socioeconomic development. Overall socioeconomic development is the ultimate solution for control of cholera as evidenced in developed countries. However, most research has focused on cross-county comparisons so that the role of individual- or small area-level socioeconomic status (SES) in cholera dynamics has not been carefully studied. Reported cases of cholera in Matlab, Bangladesh have fluctuated greatly over time and epidemic outbreaks of cholera continue, most recently with the introduction of a new serotype into the region. The wealth of longitudinal data on the population of Matlab provides a unique opportunity to explore the impact of socioeconomic status and other demographic characteristics on the long-term temporal dynamics of cholera in the region. In this population-based study we examine which factors impact the initial number of cholera cases in a bari at the beginning of the 0139 epidemic and the factors impacting the number of cases over time. Cholera data were derived from the ICDDR,B health records and linked to socioeconomic and geographic data collected as part of the Matlab Health and Demographic Surveillance System. Longitudinal zero-inflated Poisson (ZIP) multilevel regression models are used to examine the impact of environmental and socio-demographic factors on cholera counts across baris. Results indicate that baris with a high socioeconomic status had lower initial rates of cholera at the beginning of the 0139 epidemic (γ(01) = -0.147, p = 0.041) and a higher probability of reporting no cholera cases (α(01) = 0.156, p = 0.061). Populations in baris characterized by low SES are more likely to experience higher cholera morbidity at the beginning of an epidemic than populations in high SES baris. |
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