Abstract
Despite significant advancements achieved in the last two decades in reducing the worldwide impact of malaria, the disease still poses a substantial public health challenge. Moreover, there exists a growing apprehension that climate change could potentially broaden the regions conducive to disease transmission. This research focuses on investigating the impact of climate variability on malaria incidence in the Yamaltu/Deba Local Government Area (LGA) of Gombe State, Nigeria, from 2013 to 2022. Precipitation and temperature records were sourced from the Upper Benue River Basin Development Authority’s Dadin-Kowa Meteorological station, while confirmed uncomplicated malaria cases were obtained from the Gombe State Primary Healthcare Development Agency.The study entails an examination of the relationship between climate variability and malaria incidence in the study area. Pearson’s product-moment correlation coefficient was employed for this purpose. Furthermore, time series analysis was conducted to assess trends in rainfall, temperature, and malaria cases. The findings revealed an increasing trend in both rainfall and malaria cases, while maximum and minimum temperatures displayed negligible decreases over the specified period. Notably, correlation analysis unveiled a positive relationship between rainfall and malaria, with an r value of 0.319. Conversely, maximum and minimum temperatures exhibited a strong negative correlation, with r values of -0.152 and -0.534, respectively. Seasonal analysis highlighted a greater prevalence of malaria cases during the late rainy season, specifically in the months of July and October. October emerged as the month with the highest recorded malaria cases, totaling 44,351 cases, while May exhibited the lowest number of cases at 15,488. Given these findings, it is recommended to prioritize vector control initiatives and raise public awareness regarding the effective implementation of intervention measures, such as indoor residual sprays. These efforts are especially crucial during peak periods characterized by favorable weather conditions to mitigate malaria outbreaks effectively.
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