Spatio-temporal patterns of cholera outbreak in rural settings of Ethiopia, 2023
Objectives: The aim of this study was to assess the spatio-temporal pattern of cholera in rural settings of Ethiopia. Methods: A spatiotemporal analysis of daily cholera cases in 59 Kebeles across 7 districts in the Gedeo zone from April 2 to November 18, 2023, obtained from the Gedeo Zone Health De...
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| Language: | English |
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Elsevier
2025-01-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844025003421 |
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| author | Solomon Hailemariam Tesfaye Andualem Mamo Wondayehu Berihanu Serawit Elias |
| author_facet | Solomon Hailemariam Tesfaye Andualem Mamo Wondayehu Berihanu Serawit Elias |
| author_sort | Solomon Hailemariam Tesfaye |
| collection | DOAJ |
| description | Objectives: The aim of this study was to assess the spatio-temporal pattern of cholera in rural settings of Ethiopia. Methods: A spatiotemporal analysis of daily cholera cases in 59 Kebeles across 7 districts in the Gedeo zone from April 2 to November 18, 2023, obtained from the Gedeo Zone Health Department, was conducted. The global Moran's I statistic was used for spatial autocorrelation analysis, and the retrospective space-time scan statistic was used to analyze spatiotemporal clusters of cholera. Results: Throughout the outbreak, 792 cholera cases were reported, corresponding to an annual incidence of 169.4 per 100,000 population. The spatial distribution showed strong autocorrelation, with a global Moran's I coefficient of 0.272 (P-value <0.001). Five statistically significant clusters were identified by space-time scan statistics using a discrete Poisson model. These identified clusters overlapped in time and had longer durations with a relatively high risk of cholera in the study areas. Conclusion: The identification of high-risk clusters specific to rural settings forms the basis for rapid public health emergency response and resource allocation by prioritizing the significantly high-risk clusters to control and eventually eliminate cholera. There is room to improve the public health response to cholera outbreaks in the study settings. |
| format | Article |
| id | doaj-art-977a474e5fd647019efc1676b247efcc |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-977a474e5fd647019efc1676b247efcc2025-02-02T05:28:39ZengElsevierHeliyon2405-84402025-01-01112e41962Spatio-temporal patterns of cholera outbreak in rural settings of Ethiopia, 2023Solomon Hailemariam Tesfaye0Andualem Mamo1Wondayehu Berihanu2Serawit Elias3School of Public Health, College of Health Sciences and Medicine, Dilla University, Dilla, Ethiopia; Corresponding author. Dilla University, P.O.Box 419, Ethiopia.Gedeo Zone Health Department, Dilla, EthiopiaGedeo Zone Health Department, Dilla, EthiopiaGedeo Zone Health Department, Dilla, EthiopiaObjectives: The aim of this study was to assess the spatio-temporal pattern of cholera in rural settings of Ethiopia. Methods: A spatiotemporal analysis of daily cholera cases in 59 Kebeles across 7 districts in the Gedeo zone from April 2 to November 18, 2023, obtained from the Gedeo Zone Health Department, was conducted. The global Moran's I statistic was used for spatial autocorrelation analysis, and the retrospective space-time scan statistic was used to analyze spatiotemporal clusters of cholera. Results: Throughout the outbreak, 792 cholera cases were reported, corresponding to an annual incidence of 169.4 per 100,000 population. The spatial distribution showed strong autocorrelation, with a global Moran's I coefficient of 0.272 (P-value <0.001). Five statistically significant clusters were identified by space-time scan statistics using a discrete Poisson model. These identified clusters overlapped in time and had longer durations with a relatively high risk of cholera in the study areas. Conclusion: The identification of high-risk clusters specific to rural settings forms the basis for rapid public health emergency response and resource allocation by prioritizing the significantly high-risk clusters to control and eventually eliminate cholera. There is room to improve the public health response to cholera outbreaks in the study settings.http://www.sciencedirect.com/science/article/pii/S2405844025003421Spatio-temporalCholeraOutbreakRuralPatternsEthiopia |
| spellingShingle | Solomon Hailemariam Tesfaye Andualem Mamo Wondayehu Berihanu Serawit Elias Spatio-temporal patterns of cholera outbreak in rural settings of Ethiopia, 2023 Heliyon Spatio-temporal Cholera Outbreak Rural Patterns Ethiopia |
| title | Spatio-temporal patterns of cholera outbreak in rural settings of Ethiopia, 2023 |
| title_full | Spatio-temporal patterns of cholera outbreak in rural settings of Ethiopia, 2023 |
| title_fullStr | Spatio-temporal patterns of cholera outbreak in rural settings of Ethiopia, 2023 |
| title_full_unstemmed | Spatio-temporal patterns of cholera outbreak in rural settings of Ethiopia, 2023 |
| title_short | Spatio-temporal patterns of cholera outbreak in rural settings of Ethiopia, 2023 |
| title_sort | spatio temporal patterns of cholera outbreak in rural settings of ethiopia 2023 |
| topic | Spatio-temporal Cholera Outbreak Rural Patterns Ethiopia |
| url | http://www.sciencedirect.com/science/article/pii/S2405844025003421 |
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