Analysis of risk factors for confirmed cases and resurgence of measles epidemics associated to Covid-19 effects, in Senegal

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Introduction : Measles is one of the most contagious infectious diseases, responsible for significant morbidity and mortality through recurring epidemics. With Covid-19, a resurgence of measles cases was observed, with epidemics occurring between 2021 and 2024. The goal of this study is to identify significant factors associated with confirmed cases of measles epidemics in the post-Covid-19 context. It also specifically aimed to investigate the influence of Covid-19-related factors on the resurgence of measles. Methodology : A cross-sectional analytical study was conducted on confirmed cases of measles recorded in the health districts of Senegal from January 2015 to December 2024. Statistical analyses were performed using R software with Cramer's v, Multiple Correspondence Analysis and multiple binary logistic regression. Results/findings : A total of 2 448 confirmed cases were recorded. Patients ranged in age from 1 to 81 years, with a mean age of 9 years. Several factors were associated with the occurrence of measles outbreaks. The Kédougou region (OR : 5, 95% CI [3.71-6.78], p < 0.000) was associated with a fivefold increased risk of contracting measles. Insufficient vaccination coverage for the second dose (RR2) was strongly linked to the spread of the disease (OR : 3.34, 95% CI [2.83-3.95], p < 0.000). The risk was also four times higher in unvaccinated individuals (OR : 4.03, 95% CI [3.54-4.6], p < 0.000). Finally, children aged 1 to 5 years (OR : 1.39, 95% CI [1.23-1.55], p = 0.000) appear to be a particularly vulnerable age group, with an increased risk compared to other age groups. Conclusion : The study ranked the risk factors associated with the resurgence of measles epidemics in Senegal in order of importance. It also proposed integrating these factors into a machine learning algorithm to develop an application for the automatic detection of measles cases and extending it to other diseases with epidemic potential.

Article activity feed