Temporal and demographic patterns of malaria prevalence in Adiyan, Ogun State, Nigeria (2019–2022): A retrospective study using antimalarial drug sales as an indicator of disease burden

Abstract

Background: Malaria remains a major epidemic in Nigeria, continuing to impact lives negatively through-out the country and especially in semi-urban settlements such as Adiyan Ogun state. In spite of efforts to educate and promote awareness of malaria to the people and to help them control it, there continues to be a slow increase in cases during certain seasonal periods and an uneven distribution based on age (teenagers vs. adults). A thorough examination of local pharmacy sales will offer more accurate insight into the actual burden of malarial disease because medical professionals may be unable to properly capture all cases in traditional surveillance methods. Objectives: Provide insight into the seasonal and age-related distribution of malaria cases in Adiyan for the time frame of 2019-2022 by providing management of the medications that are being issued for treatment of malaria.  Methods: The study examined the effect of weather and seasonality on malaria incidence. Data sources included historical sales data from Kotz Pharmacy in Ogun State, categorized into three groups based on age: Adults, teenagers, and Children. Seasonal trend analysis was performed to identify any seasonal patterns in malaria cases within each age group. ANOVA and Tukey's post-hoc tests were performed to determine if there were differences between the age groups regarding the number of malaria cases. Pearson correlations were performed to determine how closely the number of malaria cases tracked across all three(age) groups. Result: Adult (Ages 18-64) Anti-Malarial Purchases were over 78% of total 'over-the-counter' sales of Anti-Malarials during the rainy season (between June and August) of each year, and peaked (142) in July 2021. The burden of disease was significantly greater among adults, than either Children, or Teenagers (ANOVA statistic F(2, 107) = 109.28, p< .001). The result reveals that there was strong relationship between the teen and child (r = +0.72, p < 0.001), but the pattern did not hold between adults and children (r = +0.25, p = 0.090). Conclusion: The findings make it clear: malaria in Adiyan follows a seasonal rhythm and hits adults hardest. Using pharmacy sales data alongside environmental information paints a more detailed picture and can help tailor malaria prevention efforts by age group.

Keywords: Malaria, ANOVA, Proxy indicator, Seasonality, Age groups, Antimalarial drug