Identifying Hidden Severe Malaria Burden, Treatment Gaps, and Priority Investment Areas in Kano State, Nigeria, via an Accessibility-Adjusted Geospatial Index

Abstract

Malaria remains a major public health challenge in northern Nigeria, yet substantial spatial inequalities persist in severe malaria burdens, treatment access, and healthcare service delivery. This study developed a geospatial framework to identify hidden severe malaria burdens and prioritize underserved local government areas (LGAs) for malaria investments in Kano State, Nigeria. Annual severe malaria surveillance records, artesunate treatment data, population distributions, health facility locations, nighttime light intensities, and malaria endemicity indicators from the Malaria Atlas Project were integrated at the LGA level. A hidden burden–treatment gap index (HBTGI) was first developed to identify LGAs where the severe malaria burden exceeded the observed treatment response. An Accessibility-Adjusted Severe Malaria Treatment Gap Index (AASMTGI) was subsequently constructed by combining disease burden, treatment deficits, healthcare accessibility, and socioeconomic indicators. Kano State recorded 190,875 severe malaria cases, 170,995 of which received artesunate treatment, leaving an estimated treatment gap of 24,425 cases. The HBTGI revealed pronounced spatial disparities, with Gwarzo, Tsanyawa, Bichi, Rogo, and Dambatta exhibiting the greatest hidden burden–treatment gaps. The AASMTGI identified Gwarzo, Dambatta, Rogo, Takai, and Dawakin Tofa as the highest-priority LGAs for malaria investment. Correlation analysis indicated that treatment deficits and severe malaria burden were the strongest determinants of investment priority. The proposed framework provides a practical decision-support tool for geographically targeted malaria interventions and resource allocation in high-burden settings.