Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania

Hounmanou, Yaovi Mahuton Gildas; Mølbak, Kåre; Kähler, Jonas; Mdegela, Robinson H.; Olsen, John Elmerdahl; Dalsgaard, Anders

doi:10.1186/s13104-019-4731-0

Cited by 9 publications

(6 citation statements)

References 18 publications

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“…These differences could result from the fact that we used data for a longer time period (10 years) with rigorous statistical methods and ignored mean annual incidence ≤ 2 cases per 100 000 people while the desk review data spanned six years using mean annual incidence of 1 case per 100 000 inhabitants. As we found in this study, SaTScan has been widely used and found very helpful in identification and classification of cholera clusters (hotspots) to inform intervention measures in SSA including Cameroon [ 17 ], Uganda [ 18 ], Zambia [ 46 ], and Tanzania [ 47 ]. However, the GTFCC method is relatively new and we found no evidence of its use in published reports.…”

Section: Discussionmentioning

confidence: 99%

The cholera risk assessment in Kano State, Nigeria: A historical review, mapping of hotspots and evaluation of contextual factors

Ngwa

Ihekweazu²,

Okwor³

et al. 2021

PLoS Negl Trop Dis

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Nigeria is endemic for cholera since 1970, and Kano State report outbreaks annually with high case fatality ratios ranging from 4.98%/2010 to 5.10%/2018 over the last decade. However, interventions focused on cholera prevention and control have been hampered by a lack of understanding of hotspot Local Government Areas (LGAs) that trigger and sustain yearly outbreaks. The goal of this study was to identify and categorize cholera hotspots in Kano State to inform a national plan for disease control and elimination in the State. We obtained LGA level confirmed and suspected cholera data from 2010 to 2019 from the Nigeria Centre for Disease Control (NCDC) and Kano State Ministry of Health. Data on inland waterbodies and population numbers were obtained from online sources and NCDC, respectively. Clusters (hotspots) were identified using SaTScan through a retrospective analysis of the data for the ten-year period using a Poisson discrete space-time scan statistic. We also used a method newly proposed by the Global Task Force on Cholera Control (GTFCC) to identify and rank hotspots based on two epidemiological indicators including mean annual incidence per 100 000 population of reported cases and the persistence of cholera for the study period. In the ten-year period, 16,461 cholera cases were reported with a case fatality ratio of 3.32% and a mean annual incidence rate of 13.4 cases per 100 000 population. Between 2010 and 2019, the most severe cholera exacerbations occurred in 2014 and 2018 with annual incidence rates of 58.01 and 21.52 cases per 100 000 inhabitants, respectively. Compared to 2017, reported cases and deaths increased by 214.56% and 406.67% in 2018. The geographic distribution of outbreaks revealed considerable spatial heterogeneity with the widest in 2014. Space-time clustering analysis identified 18 out of 44 LGAs as high risk for cholera (hotspots) involving both urban and rural LGAs. Cholera clustered around water bodies, and the relative risk of having cholera inside the hotspot LGA were 1.02 to 3.30 times higher than elsewhere in the State. A total of 4,894,144 inhabitants were in these hotspots LGAs. Of these, six LGAs with a total population of 1.665 million had a relative risk greater than 2 compared to the state as a whole. The SaTScan (statistical) and GTFCC methods were in agreement in hotspots identification. This study identified cholera hotspots LGAs in Kano State from 2010–2019. Hotspots appeared in both urban and rural settings. Focusing control strategies on these hotspots will facilitate control and eliminate cholera from the State.

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Section: Discussionmentioning

confidence: 99%

The cholera risk assessment in Kano State, Nigeria: A historical review, mapping of hotspots and evaluation of contextual factors

Ngwa

Ihekweazu²,

Okwor³

et al. 2021

PLoS Negl Trop Dis

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“…Les aires de santé de l'axe lac Tanganyika sont quasiment les seules contributrices des cas de choléra, surtout celle de Moba-Port. La proximité avec le lac Tanganyika et le recours à ses eaux pour l'alimentation et l'usage domestique constituent des facteurs de risque importants, comme le souligne Shapiroet al [29], Taylor et al [9], Hounmanouet al [30] et Bompangweet al [10] concernant les lacs Victoria, Nyasa et Tanganyika. Il a été constaté que plus on s'éloigne du lac, la notification des cas de choléra dans le système de surveillance des maladies devient nulle.…”

Section: Resultatsunclassified

Observance Des Mesures Barrières De Lutte Contre La Maladie A Coronavirus-19 & Morbi-Mortalités Liées Au Cholera En Zone EndemoEpidémique De La République Démocratique Du Congo

BUKASA

MONGANE

Marie

et al. 2021

IJSMS

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Introduction : Le cholera est une maladie diarrhéique hautement contagieuse et en lien étroit avec le déficit de l’observance stricte des mesures d’hygiène. Il constitue un véritable problème de santé publique dans les pays en voie de développement. Cette étude avait pour objectif de déterminer l’impact de l’observance des mesures d’hygiène pendant la période de la maladie à coronavirus-19 sur l’épidémiologie de cholera dans notre milieu. Méthode : Il s’agit d’une revue documentaire des cas de choléra notifiés et validés durant la période allant de Janvier 2018 à Mars 2021 dans la zone de santéendémo-épidémique de Moba, province du Tanganyika, en République Démocratique du Congo. Résultats : 1935 cas de choléra ont été rapportés durant la période d’étude, avec respectivement un taux d’attaque pour 100 milles de 196,5 en 2018, 277,2en 2019 et 68,8 en 2020. Le sexe masculin a été le plus affecté en 2018 (n=368 ; 53,8%) et 2019 (n=527 ; 53,0%), contrairement avec 2020 en faveur des femmes (n=153 ; 60,2%). Les mois pluvieux ont été les plus contributeurs en nombre des cas de choléra notifies. La majorité des malades arrivait avec la déshydratation sévère. Le séjour moyen aux centres de traitement des maladies diarrhéiques (CTMD) et unités de traitement des maladies diarrhéiques (UTMD) a été presqu’uniforme durant la période étudiée, variant de 3,1 à 3,2 jours. Les décès liés au cholera ont été de 1 cas sur 254 en 2020, 19 cas sur 994 en 2019 et 11 cas sur 684 en 2018, soit une létalité de 0,4 % en 2020, 1,9 % en 2019 et 1,6% en 2018 et une morbidité proportionnelle de 35,4%, 51,4 % et 13,1%. Conclusion : La limitation des déplacements et l’intensification des mesures d’hygiène instaurées pendant la période de la pandémie de la maladie à coronavirus ont eu un impact significatif sur l’endémicité, l’épidémicité et la mortalité de choléra, spécifiquement le taux d’attaque pour 100 milles et la létalité. En outre, cette période de la maladie à coronavirus expose les femmes à contracter le cholera par rapport à leurs homologues masculins.

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“…A few countries in Africa including Zimbabwe and Ghana have investigated the temporal trends and the nature of spatial interaction of cholera (Ngwa et al, 2016; Osei & Stein, 2018; Luque Fernandez et al, 2012). Furthermore, studies on spatio-temporal trend of cholera have been extensively done in Cameroon, Uganda, Zambia, and Tanzania to identify cholera clusters and provide valuable insights for implementing intervention measures (Mwaba et al, 2020; Hounmanou et al, 2019; Bwire et al, 2017; Ngwa et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Spatial and temporal analysis of cholera cases in high-risk areas of Kenya

Mageto,

Mutono,

Aboge

et al. 2023

Preprint

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Cholera outbreaks remain an important public health challenge in Kenya, especially in areas with poor sanitation and hygiene including urban informal settlements, refugee camps and rural areas bordering large water bodies. Even in endemic settings, the distribution of cases exhibits spatial and temporal variations. Utilizing a Poisson discrete space-time scan statistic (SaTScan), this study investigated the temporal trends and the nature of spatial spread of cholera within selected high-risk areas in Kenya. The study was conducted in an urban informal settlement in Nairobi (Mukuru), a refugee camp in Northern Kenya (Dadaab) and the four counties bordering Lake Victoria region. Retrospective cholera line list data from January 2012 to December 2022 in the selected high-risk areas was used. SaTScan v10.1.2 was used to carry out Spatiotemporal analysis and generate spatial clusters. Throughout the study period, a total of 7,372 cholera cases were reported, corresponding to a lower annual incidence rate of 12.2 per 100,000 people compared to a mean annual incidence of 25 cases per 100,000 population previously reported in Kenya. The highest number of cases (n=5934) were reported between 2015 and 2018 with an annual incidence rate of 27.0 per 100,000 people, indicating a relative risk (RR) of 7.22 and a log-likelihood ratio (LLR) of 3015.17 (p< 0.001). The risky clusters (RR>1) were in Dadaab, Fafi, Suna West, Nyatike, Ugunja, Ndhiwa and Suna East sub counties with annual cases of 111.6, 164.1, 28.4, 19.9, 19.4, 14.0 and 13.9 per 100,000, respectively. The sub-counties of Nyakach, Nyando, Rachuonyo East, Kisumu East and Kisumu Central were reported as low-risk clusters, with a relative risk of 0.055 and an annual incidence rate of 1.1 cases per 100,000 individuals. Out of the thirty-two sub-counties included in the study, ten of them did not report any cases of cholera during the study period. Cholera cases waxed every three years in the selected high-risk areas. This data on hotspots specific to endemic settings forms a basis for prompt public health response and resource allocation by prioritizing the significantly high-risk clusters to control and eventually eliminate the disease.

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Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania

Cited by 9 publications

References 18 publications

The cholera risk assessment in Kano State, Nigeria: A historical review, mapping of hotspots and evaluation of contextual factors

The cholera risk assessment in Kano State, Nigeria: A historical review, mapping of hotspots and evaluation of contextual factors

Observance Des Mesures Barrières De Lutte Contre La Maladie A Coronavirus-19 & Morbi-Mortalités Liées Au Cholera En Zone EndemoEpidémique De La République Démocratique Du Congo

Spatial and temporal analysis of cholera cases in high-risk areas of Kenya

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