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Identifying cholera "hotspots" in Uganda: An analysis of cholera surveillance data from 2011 to 2016.

ABSTRACT: 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.

SUBMITTER: Bwire G

PROVIDER: S-EPMC5746206 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Identifying cholera "hotspots" in Uganda: An analysis of cholera surveillance data from 2011 to 2016.

Bwire Godfrey G Ali Mohammad M Sack David A DA Nakinsige Anne A Naigaga Martha M Debes Amanda K AK Ngwa Moise C MC Brooks W Abdullah WA Garimoi Orach Christopher C

PLoS neglected tropical diseases 20171228 12

<h4>Background</h4>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.<h4>Methodology/principle findings</h4>We obtained district level confirmed cholera outbreak data ...[more]

PMID: 29284003

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Project description:BackgroundIn war-torn Yemen, reports of confirmed cholera started in late September, 2016. The disease continues to plague Yemen today in what has become the largest documented cholera epidemic of modern times. We aimed to describe the key epidemiological features of this epidemic, including the drivers of cholera transmission during the outbreak.MethodsThe Yemen Health Authorities set up a national cholera surveillance system to collect information on suspected cholera cases presenting at health facilities. Individual variables included symptom onset date, age, severity of dehydration, and rapid diagnostic test result. Suspected cholera cases were confirmed by culture, and a subset of samples had additional phenotypic and genotypic analysis. We first conducted descriptive analyses at national and governorate levels. We divided the epidemic into three time periods: the first wave (Sept 28, 2016, to April 23, 2017), the increasing phase of the second wave (April 24, 2017, to July 2, 2017), and the decreasing phase of the second wave (July 3, 2017, to March 12, 2018). We reconstructed the changes in cholera transmission over time by estimating the instantaneous reproduction number, Rt. Finally, we estimated the association between rainfall and the daily cholera incidence during the increasing phase of the second epidemic wave by fitting a spatiotemporal regression model.FindingsFrom Sept 28, 2016, to March 12, 2018, 1 103 683 suspected cholera cases (attack rate 3·69%) and 2385 deaths (case fatality risk 0·22%) were reported countrywide. The epidemic consisted of two distinct waves with a surge in transmission in May, 2017, corresponding to a median Rt of more than 2 in 13 of 23 governorates. Microbiological analyses suggested that the same Vibrio cholerae O1 Ogawa strain circulated in both waves. We found a positive, non-linear, association between weekly rainfall and suspected cholera incidence in the following 10 days; the relative risk of cholera after a weekly rainfall of 25 mm was 1·42 (95% CI 1·31-1·55) compared with a week without rain.InterpretationOur analysis suggests that the small first cholera epidemic wave seeded cholera across Yemen during the dry season. When the rains returned in April, 2017, they triggered widespread cholera transmission that led to the large second wave. These results suggest that cholera could resurge during the ongoing 2018 rainy season if transmission remains active. Therefore, health authorities and partners should immediately enhance current control efforts to mitigate the risk of a new cholera epidemic wave in Yemen.FundingHealth Authorities of Yemen, WHO, and Médecins Sans Frontières.

Project description:BackgroundMozambique suffers recurrent annual cholera outbreaks especially during the rainy season between October to March. The African Cholera Surveillance Network (Africhol) was implemented in Mozambique in 2011 to generate accurate detailed surveillance data to support appropriate interventions for cholera control and prevention in the country.Methodology/principal findingsAfrichol was implemented in enhanced surveillance zones located in the provinces of Sofala (Beira), Zambézia (District Mocuba), and Cabo Delgado (Pemba City). Data were also analyzed from the three outbreak areas that experienced the greatest number of cases during the time period under observation (in the districts of Cuamba, Montepuez, and Nampula). Rectal swabs were collected from suspected cases for identification of Vibrio cholerae, as well as clinical, behavioral, and socio-demographic variables. We analyzed factors associated with confirmed, hospitalized, and fatal cholera using multivariate logistic regression models. A total of 1,863 suspected cases and 23 deaths (case fatality ratio (CFR), 1.2%) were reported from October 2011 to December 2015. Among these suspected cases, 52.2% were tested of which 23.5% were positive for Vibrio cholerae O1 Ogawa. Risk factors independently associated with the occurrence of confirmed cholera were living in Nampula city district, the year 2014, human immunodeficiency virus infection, and the primary water source for drinking.Conclusions/significanceCholera was endemic in Mozambique during the study period with a high CFR and identifiable risk factors. The study reinforces the importance of continued cholera surveillance, including a strong laboratory component. The results enhanced our understanding of the need to target priority areas and at-risk populations for interventions including oral cholera vaccine (OCV) use, and assess the impact of prevention and control strategies. Our data were instrumental in informing integrated prevention and control efforts during major cholera outbreaks in recent years.

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.

Project description:BackgroundWider healthcare-strengthening interventions are recommended in cholera hotspots and could benefit other types of diarrhoeal diseases which contribute to greater mortality than cholera.ObjectiveDescribe facility capacity and provider knowledge for case management of diarrhoea and cholera surveillance in cholera hotspots in the Democratic Republic of Congo (DRC) among health facilities, drug shops, and traditional health practitioners.MethodsWe conducted a sequential exploratory mixed-method study, using focus group discussions, facility audits, and provider knowledge questionnaires during September and October 2022 in North Kivu and Tanganyika provinces, Eastern DRC. Content analysis was used for qualitative data. Quantitative data were summarised by facility level and healthcare provider type. Audit and knowledge scores (range 0-100) were generated. Multivariable linear regression estimated association between scores and explanatory factors. Qualitative and quantitative data were triangulated during interpretation.ResultsOverall, 244 facilities and 308 providers were included. The mean audit score for health facilities was 51/100 (SD: 17). Private facilities had an -11.6 (95% CI, -16.7 to -6.6) lower adjusted mean score compared to public. Mean knowledge score was 59/100 (95% CI, 57 to 60) for health facility personnel, 46/100 (95% CI, 43 to 48) for drug shop vendors and 37/100 (95% CI, 34 to 39) for traditional health practitioners. Providers had particularly low knowledge concerning when to check for low blood sugar, use of nasogastric tubes, and dosing schedules. Knowledge about case definitions for cholera was similar between groups (range 41-58%) except for traditional health practitioners for the definition during an outbreak 15/73 (21%).ConclusionsIncreasing awareness of cholera case definitions in this context could help improve cholera surveillance and control. Increased support and supervision, especially for private providers, could help ensure facilities are equipped to provide safe care. More nuanced aspects of case management should be emphasised in provider training.

Dataset Information

Identifying cholera "hotspots" in Uganda: An analysis of cholera surveillance data from 2011 to 2016.

Publications

Identifying cholera "hotspots" in Uganda: An analysis of cholera surveillance data from 2011 to 2016.

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