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@article{210033,
        author = {Ugwu Clement James and Bernard S Helda and Fatai O Afeez and Tahir Muhammad Aminu},
        title = {Spatiotemporal Variation in Facility-Reported Malaria Burden in Kaduna Metropolis, Kaduna},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {5},
        pages = {4055-4066},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=210033},
        abstract = {Malaria remains a major public health challenge in Kaduna Metropolis despite the ongoing control intervention. This study examined the spatiotemporal variation in facility-reported malaria burden in Kaduna Metropolis from 2020 to 2025, which makes identification of disease burden important for surveillance and intervention. Annual RDT positive malaria records were obtained from 14 selected public and private healthcare, while malaria case rates were calculated per 1,000 projected LGA population. Kernel Density Estimation was used to map the spatial clustering of reported cases across the metropolis. The results revealed substantial variation in reported case rates across the study period, where Kaduna North recorded the highest rate in five of the six years, rising from 17.08 cases per 1,000 population in 2020 to 29.71 in 2024 before declining to 28.46 in 2025. Kaduna South peaked at 22.60 in 2023, while Chikun reached 9.53 in 2024. Igabi records showed an increase from 1.15 in 2024 to 1.85 in 2025. The spatial maps showed a persistent central hotspot around Jowako - Ashmed - Kabala - Tudun Wada corridor and adjoining areas from 2020 - 2024, followed by the emergence of a second hotspot along the southern metropolitan corridor of Television PHC, Makera, Kakuri Gwari, Romi and Gonin Gora in 2025. The findings demonstrate spatial persistence with temporal restructuring of facility-reported malaria burden. Routine GIS-based surveillance is therefore recommended to support geographically targeted malaria interventions and resource allocation.},
        keywords = {Malaria case rate, spatiotemporal analysis, spatial clustering, Kernel Density Estimation, healthcare facilities, Kaduna Metropolis.},
        month = {October},
        }