Trends and patterns of cholera epidemic in West Africa: a statistical modeling study. (23rd January 2023)

• Record Type: Journal Article
• Authors: Conde, Amadou; Dureh, Nurin; Ueranantasun, Attachai
• Is Part Of: Journal of water and health. Volume 21:Number 2(2023)
• Page Start: 261
• Page End: 270
• Publication Date: 2023-01-23
• Subjects: cholera -- incidence -- occurrence -- statistical model -- trends -- West Africa; Water quality management -- Periodicals; Water -- Pollution -- Environmental aspects -- Periodicals; Environmental health -- Periodicals; Water quality -- Health aspects -- Periodicals; Water -- Health aspects -- Periodicals; Water -- Pollution -- Health aspects -- Periodicals; Public Health; Water Pollution -- prevention & control; Quality Control; Water Microbiology; Water Supply -- standards; Health & Medicine (General); Hydrology; Environmental health; Water -- Health aspects; Water -- Pollution -- Environmental aspects; Water -- Pollution -- Health aspects; Water quality -- Health aspects; Water quality management; Water; Gezondheid; Periodical; Periodicals; 363.61
• DOI: 10.2166/wh.2023.241
• Languages: English
• ISSNs: 1477-8920

Abstract

Abstract: Cholera is a serious disease that affects a huge number of people, especially in underdeveloped nations, and is particularly prevalent in Africa and southern Asia. This study aimed to determine cholera incidence trends and patterns in West Africa, as well as to develop a statistical model for cholera incidence. The outcomes of this study were occurrence, which was given a value of 1 if a case occurred and a value of 0 otherwise, and incidence rate. Logistic regression was used to model occurrence, while log-linear regression was used to model incidence after excluding the records with zero cases. The trend of cholera incidence rate was approximately constant for the Democratic Republic of Congo, whereas rates vary substantially throughout the study period in other countries. A confidence intervals plot shows that cholera incidence was higher in September and October, lower in 2015–2017, higher in Guinea, Niger, and Congo (west), and lower in Cote de-Ivoire, Cameroon, the Democratic Congo and Central African republics, Togo and Guinea Bissau. These two models can fit the data quite well. As a result, the method used in this study may be considered as an alternative to the traditional Poisson regression and negative binomial regression models. HIGHLIGHTS: The analysis of disease cases can be separated into two steps of analysis, which are occurrence and incidence. Logistic regression can be used to predict the occurrence of disease. Log-linear regression model provides a good fit to the incidence rate when the data have a high right skew. Mali and Niger have both high occurrence and high incidence of cholera. Graphical Abstract