Operational Silence and Climate-Driven Hidden Severe Malaria Burden in Sokoto State, Nigeria.

Authors

Charles Adeiza Umar, Emmanuel Ndenor Sambo, Yakubu Joel Cherima, Zubairul Islam, Ajibili Megida, Maryamu Mbaya, Usman Muhammed Ibrahim, Onwul Jacqueline Dakyen

Abstract

Malaria remains a major public health challenge in northern Nigeria, where climatic suitability, weak healthcare accessibility, and operational surveillance limitations may contribute to the severe malaria burden. This study analyzed the temporal and spatial dynamics of severe malaria in Sokoto State, Nigeria, from 2014 to 2024 and estimated climate-driven hidden transmission zones via integrated geospatial modeling. The monthly severe malaria surveillance records for 23 LGAs were combined with climate variables, the Plasmodium falciparum parasite rate (PfPR), the population distribution, travel-time accessibility, and settlement indicators. Temporal trends were evaluated via Sen’s slope and Mann–Kendall statistics, and a climate suitability index and accessibility-con-strained hidden burden framework were developed to estimate the potential underdetected severe malaria burden. A total of 184,429 reported severe malaria cases were recorded from 2014–2024, with the highest annual burden observed in 2015 (22,404 cases). October presented the highest mean monthly burden (117.89 cases), whereas Sabon Birni recorded the highest cumulative severe malaria burden (28,943 cases). Climate-driven burden analysis identified Rabah (hidden burden ratio = 11.04), Kebbe (7.31), and Dange-Shuni (3.03) as major hidden burden hotspots
characterized by high climate suitability and poor healthcare accessibility. Ward-level analysis further revealed highly localized operational silence zones within remote settlements. The findings demonstrate that integrating climate suitability with healthcare accessibility provides an effective framework for identifying hidden severe malaria transmission landscapes and operational surveillance gaps within semiarid environments.

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