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

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.

SUBMITTER: Hounmanou YMG

PROVIDER: S-EPMC6805412 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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

Hounmanou Yaovi M G YMG Mølbak Kåre K Kähler Jonas J Mdegela Robinson H RH Olsen John E JE Dalsgaard Anders A

BMC research notes 20191021 1

<h4>Objective</h4>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.<h4>Results</h4>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 v ...[more]

PMID: 31639037

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Project description:Despite advance in science and technology for prevention, detection and treatment of cholera, this infectious disease remains a major public health problem in many countries in sub-Saharan Africa, Uganda inclusive. The aim of this study was to identify cholera hotspots in Uganda to guide the development of a roadmap for prevention, control and elimination of cholera in the country.We obtained district level confirmed cholera outbreak data from 2011 to 2016 from the Ministry of Health, Uganda. Population and rainfall data were obtained from the Uganda Bureau of Statistics, and water, sanitation and hygiene data from the Ministry of Water and Environment. A spatial scan test was performed to identify the significantly high risk clusters. Cholera hotspots were defined as districts whose center fell within a significantly high risk cluster or where a significantly high risk cluster was completely superimposed onto a district. A zero-inflated negative binomial regression model was employed to identify the district level risk factors for cholera. In total 11,030 cases of cholera were reported during the 6-year period. 37(33%) of 112 districts reported cholera outbreaks in one of the six years, and 20 (18%) districts experienced cholera at least twice in those years. We identified 22 districts as high risk for cholera, of which 13 were near a border of Democratic Republic of Congo (DRC), while 9 districts were near a border of Kenya. The relative risk of having cholera inside the high-risk districts (hotspots) were 2 to 22 times higher than elsewhere in the country. In total, 7 million people were within cholera hotspots. The negative binomial component of the ZINB model shows people living near a lake or the Nile river were at increased risk for cholera (incidence rate ratio, IRR = 0.98, 95% CI: 0.97 to 0.99, p < .01); people living near the border of DRC/Kenya or higher incidence rate in the neighboring districts were increased risk for cholera in a district (IRR = 0.99, 95% CI: 0.98 to 1.00, p = .02 and IRR = 1.02, 95% CI: 1.01 to 1.03, p < .01, respectively). The zero inflated component of the ZINB model yielded shorter distance to Kenya or DRC border, higher incidence rate in the neighboring districts, and higher annual rainfall in the district were associated with the risk of having cholera in the district.The study identified cholera hotspots during the period 2011-2016. The people located near the international borders, internationally shared lakes and river Nile were at higher risk for cholera outbreaks than elsewhere in the country. Targeting cholera interventions to these locations could prevent and ultimately eliminate cholera in Uganda.

Project description:BackgroundTanzania is one of seven countries with the highest disease burden caused by cholera in Africa. We studied the evolution of Vibrio cholerae O1 isolated in Tanzania during the past three decades.Methodology/principal findingsGenome-wide analysis was performed to characterize V. cholerae O1 responsible for the Tanzanian 2015-2017 outbreak along with strains causing outbreaks in the country for the past three decades. The genomes were further analyzed in a global context of 590 strains of the seventh cholera pandemic (7PET), as well as environmental isolates from Lake Victoria. All Tanzanian cholera outbreaks were caused by the 7PET lineage. The T5 sub-lineage (ctxB3) dominated outbreaks until 1997, followed by the T10 atypical El Tor (ctxB1) up to 2015, which were replaced by the T13 atypical El Tor of the current third wave (ctxB7) causing most cholera outbreaks until 2017 with T13 being phylogenetically related to strains from East African countries, Yemen and Lake Victoria. The strains were less drug resistant with approximate 10-kb deletions found in the SXT element, which encodes resistance to sulfamethoxazole and trimethoprim. Nucleotide deletions were observed in the CTX prophage of some strains, which warrants further virulence studies. Outbreak strains share 90% of core genes with V. cholerae O1 from Lake Victoria with as low as three SNPs difference and a significantly similar accessory genome, composed of genomic islands namely the CTX prophage, Vibrio Pathogenicity Islands; toxin co-regulated pilus biosynthesis proteins and the SXT-ICE element.Conclusion/significanceCharacterization of V. cholerae O1 from Tanzania reveals genetic diversity of the 7PET lineage composed of T5, T10 and T13 sub-lineages with introductions of new sequence types from neighboring countries. The presence of these sub-lineages in environmental isolates suggests that the African Great Lakes may serve as aquatic reservoirs for survival of V. cholerae O1 favoring continuous human exposure.

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Project description:The global burden of cholera is increasing, with the majority (60%) of the cases occurring in sub-Saharan Africa. In Zambia, widespread cholera outbreaks have occurred since 1977, predominantly in the capital city of Lusaka. During both the 2016 and 2018 outbreaks, the Ministry of Health implemented cholera vaccination in addition to other preventative and control measures, to stop the spread and control the outbreak. Given the limitations in vaccine availability and the logistical support required for vaccination, oral cholera vaccine (OCV) is now recommended for use in the high risk areas ("hotspots") for cholera. Hence, the aim of this study was to identify areas with an increased risk of cholera in Zambia. Retrospective cholera case data from 2008 to 2017 was obtained from the Ministry of Health, Department of Public Health and Disease Surveillance. The Zambian Central Statistical Office provided district-level population data, socioeconomic and water, sanitation and hygiene (WaSH) indicators. To identify districts at high risk, we performed a discrete Poisson-based space-time scan statistic to account for variations in cholera risk across both space and time over a 10-year study period. A zero-inflated negative binomial regression model was employed to identify the district level risk factors for cholera. The risk map was generated by classifying the relative risk of cholera in each district, as obtained from the space-scan test statistic. In total, 34,950 cases of cholera were reported in Zambia between 2008 and 2017. Cholera cases varied spatially by year. During the study period, Lusaka District had the highest burden of cholera, with 29,080 reported cases. The space-time scan statistic identified 16 districts to be at a significantly higher risk of having cholera. The relative risk of having cholera in these districts was significantly higher and ranged from 1.25 to 78.87 times higher when compared to elsewhere in the country. Proximity to waterbodies was the only factor associated with the increased risk for cholera (P<0.05). This study provides a basis for the cholera elimination program in Zambia. Outside Lusaka, the majority of high risk districts identified were near the border with the DRC, Tanzania, Mozambique, and Zimbabwe. This suggests that cholera in Zambia may be linked to movement of people from neighboring areas of cholera endemicity. A collaborative intervention program implemented in concert with neighboring countries could be an effective strategy for elimination of cholera in Zambia, while also reducing rates at a regional level.

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

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

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