Determinants of Dehydration Status and Associated Risk Factors of Cholera Outbreak in Oromia, Ethiopia

Alemayehu, Endale; Tilahun, Tsigereda; Mebrate, Eshetu

doi:10.11648/j.bsi.20200503.11

Cited by 3 publications

(9 citation statements)

References 4 publications

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“…This means people who take the three treatments have a better chance of survival from the disease as compared to those who have not taken the treatment. This result is also reliable with the same study [17].…”

Section: Discussionsupporting

confidence: 89%

“…On the other hand, dehydration status has a significant effect on cholera disease; the higher dehydration status indicates a less chance to survive from the disease. This result is associated with the study [17].…”

Section: Discussionsupporting

confidence: 82%

“…The factor of another sick person in the family was a significant effect on cholera status this means, if there is a person that already has cholera disease in the family, there is a high probability that the other can also develop the disease and have less chance survive. This variable was also significant in the study [17]. The treatment factors (ORS, IV, and antibiotics) were a significant effect on cholera status.…”

Section: Discussionmentioning

confidence: 70%

“…The LGM with approximation technique of INLA is efficient and the effectiveness and importance of the model helped by the study [16]. The significant variables in this study were related to the study [17].…”

Section: Discussionmentioning

confidence: 76%

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Determining Factors Associated with Cholera Disease in Ethiopia using Bayesian Hierarchical Modeling

Letta

Belay

Ali

2022

Preprint

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Background: Cholera is a diarrheal disease caused by infection of the intestine with the gram-negative bacteria Vibrio cholera. It is caused by the ingestion of food or water and infected all age groups. This study aimed at identifying risk factors associated with cholera disease in Ethiopia using the Bayesian hierarchical model. Methods: The study was conducted in Ethiopia across regions and this study used secondary data obtained from the Ethiopian public health institute. Latent Gaussian models were used in this study; which is a group of models that contains most statistical models used in practice. The posterior marginal distribution of the Latent Gaussian models with different priors is determined by R-Integrated Nested Laplace Approximation. Results: There were 2790 cholera patients in Ethiopia across the regions. There were 81.61% of patients are survived from cholera outbreak disease and the rest 18.39% have died. There was 39% variation across the region in Ethiopia. Latent Gaussian models including random and fixed effects with standard priors were the best model to fit the data based on deviance. The odds of surviving from cholera outbreak disease for inpatient status are 0.609 times less than the outpatient status. Conclusions: The authors conclude that the fitted latent Gaussian models indicate the predictor variables; admission status, aged between 15 and 44, another sick person in a family, dehydration status, oral rehydration salt, intravenous, and antibiotics were significantly associated with cholera outbreak disease.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionsupporting

confidence: 82%

Section: Discussionmentioning

confidence: 70%

Section: Discussionmentioning

confidence: 76%

See 2 more Smart Citations

Determining Factors Associated with Cholera Disease in Ethiopia using Bayesian Hierarchical Modeling

Letta

Belay

Ali

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The LGM with approximation technique of INLA is efficient and the effectiveness and importance of the model helped by the study [ 17 ]. The significant variables in this study were related to the study [ 18 ].…”

Section: Methodsmentioning

confidence: 99%

Determining factors associated with cholera disease in Ethiopia using Bayesian hierarchical modeling

2022

View full text Add to dashboard Cite

Background Cholera is a diarrheal disease caused by infection of the intestine with the gram-negative bacteria Vibrio cholera. It is caused by the ingestion of food or water and infected all age groups. This study aimed at identifying risk factors associated with cholera disease in Ethiopia using the Bayesian hierarchical model. Methods The study was conducted in Ethiopia across regions and this study used secondary data obtained from the Ethiopian public health institute. Latent Gaussian models were used in this study; which is a group of models that contains most statistical models used in practice. The posterior marginal distribution of the Latent Gaussian models with different priors is determined by R-Integrated Nested Laplace Approximation. Results There were 2790 cholera patients in Ethiopia across the regions. There were 81.61% of patients are survived from cholera outbreak disease and the rest 18.39% have died. There was 39% variation across the region in Ethiopia. Latent Gaussian models including random and fixed effects with standard priors were the best model to fit the data based on deviance. The odds of surviving from cholera outbreak disease for inpatient status are 0.609 times less than the outpatient status. Conclusions The authors conclude that the fitted latent Gaussian models indicate the predictor variables; admission status, aged between 15 and 44, another sick person in a family, dehydration status, oral rehydration salt, intravenous, and antibiotics were significantly associated with cholera outbreak disease.

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Investigation of cholera outbreak and its determinants in Shaggar city, Oromia, Ethiopia, 2024: a case-control study

Mideksa,

Botore,

Abdo

2024

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Introduction: Cholera, a severe acute diarrheal disease, with an epidemic-prone transmission patterns and serious public health emergencies that have a major impact on health and the economic in Ethiopia. A cholera outbreak was reported on 30 May 2023 in Shaggar City and declared the cholera outbreak after confirmed cases. In the city, the source and risk factors were unknown. The aim of this study was to verify and identify the determinants of the cholera outbreak and guide intervention measures in the sub-city of Shaggar City, Oromia, Ethiopia. Method An unmatched case-control study was carried out to assess the determinants of cholera outbreaks in the sub-city of the shaggar, Oromia with 1:1 case to control ratio. A total of 180 (60 cases and 120 controls) participants were included in the study. We interviewed study participants and collected data on demographic and cholera risk factors using a structured questionnaire. Data were entered into Epi-info 7.2.1.0 and analyzed with SPSS version 26. We used COR with p.value < 0.25 in bivariable analysis to identify candidate variables for multivariable regression analysis. In multivariable logistic regression, 95% CI with AOR were used to measure strength of association between outcome and independent variables and p.value < 0.05 was used to declare statistical significance. Results The median age of the cases and controls was 31 and 32 years respectively. 36 (60%) of the cases and 59 (49%) of the controls were men. The overall attack rate was 0.12 per 1000 population. According to multivariate analysis, people live in a household with overcrowding and poor sanitation(AOR: 0.03, 95% CI: (0.001–0.86), Eating outside of the home from different food and drink establishments AOR: 0.29, 95% CI: (0.08–1.02), Poor status of the latrine in the home [AOR: 6.76, 95% CI: (1.50-30.44)], Drinking water from a borehole [A OR:20.7,95%CI:(1.97-218.05] and deep well watercourse was a more likely risk in cases compared to controls, drinking water treatment and boiling (AOR:0.02, 95% CI:(0.003–0.210) were protective factors for the diseases. Conclusion Drinking unsafe water and household sanitation problem appears to be the major risk factors in the recent cholera outbreak in the sub-city. Health education, chlorination of drinking water, and strengthening surveillance were implemented. To reduce the risk of future outbreaks of cholera; environmental hygiene practices and the use and accessibility of safe drinking water should be promoted at the community level.

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Determinants of Dehydration Status and Associated Risk Factors of Cholera Outbreak in Oromia, Ethiopia

Cited by 3 publications

References 4 publications

Determining Factors Associated with Cholera Disease in Ethiopia using Bayesian Hierarchical Modeling

Determining Factors Associated with Cholera Disease in Ethiopia using Bayesian Hierarchical Modeling

Determining factors associated with cholera disease in Ethiopia using Bayesian hierarchical modeling

Investigation of cholera outbreak and its determinants in Shaggar city, Oromia, Ethiopia, 2024: a case-control study

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