A comprehensive statistical analysis of Malaria dynamics in the Adamawa region of Cameroon, from 2018 to 2022
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Abstract
Malaria remains a prominent public health concern in Cameroon, with the potential for epidemic outbreaks, necessitating a robust understanding of its dynamics. This paper uses routinely collected surveillance data from health facilities in the Adamawa Region since January 2018. By applying statistical analysis, this study aims to enhance comprehension, enable data predictions, and facilitate informed decision-making for public health policy implementation. Focusing on weekly health districts data spanning from 2018 to 2022, our analysis employs key statistical metrics for central tendency, data spread, distribution shape, and variable dependence. The study reveals distinctive trends, highlighting peak malaria transmission periods consistently occurring between August and November each year. The highest weekly recorded case count in any health district reached 1,294. The data exhibits leptokurtic distributions, skewed to the left of the median. And in 2022, 11% of the population was reported to have contracted malaria. Despite an overall region-wide average growth rate of -1.21% over the past five years, maintaining vigilant attention to this critical health issue is imperative. Auto dependence analysis indicates that observations are weekly correlated, assuming the time series as stationary. The stationarity has been confirmed by ADF and KPSS tests that we performed. This comprehensive data analysis helps our understanding of the malaria landscape in the Adamawa Region of Cameroon. The paper also recommends the inclusion of additional variables in data collection for a more holistic perspective. These findings provide a basis for the formulation and implementation of targeted interventions by relevant stakeholders, aiding in the prediction of future cases and ultimately contributing to the effective management of malaria in the region.
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