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BMC Res Notes. 2019 Oct 21;12(1):664. doi: 10.1186/s13104-019-4731-0.

Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania.

Author information

1
Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg C, Copenhagen, Denmark. gil@sund.ku.dk.
2
Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg C, Copenhagen, Denmark.
3
Division of Infectious Disease Preparedness, Statens Serum Institut, Artillerivej 5, 2300, Copenhagen, Denmark.
4
Department of Veterinary Medicine and Public Health, College of Veterinary and Biomedical Sciences, Sokoine University of Agriculture, PO Box: 3021, Morogoro, Tanzania.
5
School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore, Singapore.

Abstract

OBJECTIVE:

We described the dynamics of cholera in Tanzania between 2007 and 2017 and assessed the weaknesses of the current surveillance system in providing necessary data in achieving the global roadmap to 2030 for cholera control.

RESULTS:

The Poisson-based spatial scan identified cholera hotspots in mainland Tanzania. A zero-inflated Poisson regression investigated the relationship between the incidence of cholera and available demographic, socio-economic and climatic exposure variables. Four cholera hotspots were detected covering 17 regions, home to 28 million people, including the central regions and those surrounding the Lakes Victoria, Tanganyika and Nyaza. The risk of experiencing cholera in these regions was up to 2.9 times higher than elsewhere in the country. Regression analyses revealed that every 100 km of water perimeter in a region increased the cholera incidence by 1.5%. Due to the compilation of surveillance data at regional level rather than at district, we were unable to reliably identify any other significant risk factors and specific hotspots. Cholera high-risk populations in Tanzania include those living near lakes and central regions. Successful surveillance require disaggregated data available weekly and at district levels in order to serve as data for action to support the roadmap for cholera control.

KEYWORDS:

Cholera; Cholera dynamics; Great Lakes; Spatial–temporal analysis; Tanzania

PMID:
31639037
PMCID:
PMC6805412
DOI:
10.1186/s13104-019-4731-0
[Indexed for MEDLINE]
Free PMC Article

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