Spatiotemporal analysis of climate variability and malaria incidence in Lokoja metropolis, Kogi State, Nigeria

Abstract

Malaria remains one of the most consequential public health challenges in Nigeria, and the conditions that govern its transmission are strongly climatic. This study examined the influence of climate variability on malaria incidence in Lokoja Metropolis, Kogi State, between 2019 and 2024, and mapped the resulting geography of risk. Records of temperature, rainfall and relative humidity were obtained from the Nigerian Meteorological Agency and malaria case records from the Kogi State Ministry of Health. Descriptive statistics and Pearson product moment correlation were applied to the climate and health series, and a geospatial workflow comprising spatial interpolation, kernel density estimation, hot spot analysis using the Getis–Ord Gi* statistic, spatial autocorrelation and weighted overlay was implemented in ArcGIS Pro and QGIS. Mean annual temperature rose steadily from 29.3 to 31.3 degrees Celsius, rainfall from 1,250 to 1,425 millimetres and relative humidity from 74 to 82 percent, corresponding to trends of 0.40 degrees Celsius, 35.9 millimetres and 1.60 percent per year respectively. Reported malaria cases rose in parallel from 12,500 in 2019 to 16,500 in 2024, an increase of 32.0 percent, while the case mortality rate rose from 2.1 to 3.2 percent. Correlation analysis returned strong positive associations between malaria incidence and temperature (r = 0.82), rainfall (r = 0.76) and relative humidity (r = 0.79), each significant at p < 0.01. Geospatial analysis localised the burden: incidence, kernel density and Gi* hot spots converged on densely settled, low lying neighbourhoods close to the Niger and Benue channels, while elevated and sparsely settled peripheries formed cold spots. The weighted overlay classified floodplain and wetland margins as zones of very high risk. The findings confirm that climate variability has intensified transmission in Lokoja, while indicating that thermal conditions are approaching the upper range for efficient vector and parasite development. Integration of climate information into malaria surveillance, seasonally timed intervention, drainage and sanitation improvement, and spatially targeted allocation of control resources are recommended.