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ASSESSING COVID-19 SPREAD AND VACCINATION EFFECTIVENESS IN CHAD THROUGH MEAN KERNEL DENSITY ESTIMATION
Keywords:
COVID-19, vaccination, mean kernel density estimation, infection trends, epidemiological data analysisDOI:
https://doi.org/10.17654/0972361725016Abstract
This study introduces an innovative approach to assess the impact of COVID-19 vaccination on the spread of the virus in Chad by employing mean kernel density (MKD) estimation for non-parametric analysis. Utilizing epidemiological data collected between January 2021 and June 2023, we explore the correlation between vaccination rates and confirmed cases across various regions of Chad. Our analysis demonstrates that the application of MKD provides a smoother and more accurate visualization of infection trends before and after vaccination campaigns. The results reveal a significant reduction in confirmed cases post-vaccination, particularly in areas with higher vaccination rates. Correlation analysis further highlights the effectiveness of vaccination campaigns, showing a strong association between vaccination rates and the decrease in infections. However, the data also suggest a reactive vaccination strategy in regions with initially high infection rates. This innovative application of mean KDE provides new insights into the dynamics of vaccination efforts and their crucial role in reducing the spread of COVID-19 in Chad.
Received: October 21, 2024
Accepted: December 10, 2024
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