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Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania

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 hotspot...

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Autores principales: Hounmanou, Yaovi M. G., Mølbak, Kåre, Kähler, Jonas, Mdegela, Robinson H., Olsen, John E., Dalsgaard, Anders
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805412/
https://www.ncbi.nlm.nih.gov/pubmed/31639037
http://dx.doi.org/10.1186/s13104-019-4731-0
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author Hounmanou, Yaovi M. G.
Mølbak, Kåre
Kähler, Jonas
Mdegela, Robinson H.
Olsen, John E.
Dalsgaard, Anders
author_facet Hounmanou, Yaovi M. G.
Mølbak, Kåre
Kähler, Jonas
Mdegela, Robinson H.
Olsen, John E.
Dalsgaard, Anders
author_sort Hounmanou, Yaovi M. G.
collection PubMed
description 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.
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spelling pubmed-68054122019-10-24 Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania Hounmanou, Yaovi M. G. Mølbak, Kåre Kähler, Jonas Mdegela, Robinson H. Olsen, John E. Dalsgaard, Anders BMC Res Notes Research Note 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. BioMed Central 2019-10-21 /pmc/articles/PMC6805412/ /pubmed/31639037 http://dx.doi.org/10.1186/s13104-019-4731-0 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Note
Hounmanou, Yaovi M. G.
Mølbak, Kåre
Kähler, Jonas
Mdegela, Robinson H.
Olsen, John E.
Dalsgaard, Anders
Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania
title Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania
title_full Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania
title_fullStr Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania
title_full_unstemmed Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania
title_short Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania
title_sort cholera hotspots and surveillance constraints contributing to recurrent epidemics in tanzania
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805412/
https://www.ncbi.nlm.nih.gov/pubmed/31639037
http://dx.doi.org/10.1186/s13104-019-4731-0
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