Co-Occurrence of Hidden Severe Malaria Burden and Zero-Dose Childhood Vulnerability Across Kano State, Nigeria

Authors

Yakubu Joel Cherima, Charles Adeiza Umar, Yonwul Jacqueline Dakyen, Usman Muhammad Ibrahim, Uchenna Stephen Nwokenna, Fauwzia Sanusi, Odira Irene Okoye

Abstract

Severe malaria treatment gaps and routine immunization (RI) zero-dose childhood vulnerability are major but often independently investigated public health challenges in sub-Saharan Africa, despite the common health system and accessibility constraints. This study examined the spatial co-occurrence of hidden severe malaria burden and RI zero-dose childhood vulnerability across Kano State, Nigeria, and developed a dual vulnerability index (DVI) to support integrated intervention prioritization. An LGA-level geospatial database integrating severe malaria surveillance records, treatment coverage indicators, RI microcensus data, malaria transmission metrics, population estimates, health facility density, and socioeconomic proxies was analyzed via descriptive statistics, Spearman correlation, hotspot analysis, K-means clustering, and composite vulnerability modeling. Spatial co-occurrence was quantified via the Hidden Burden Treatment Gap Index (HBTGI), the Artesunate-Adjusted Severe Malaria Treatment Gap Index (AASMTGI), and the RI zero-dose rates, whereas the DVI integrated the malaria treatment gap and immunization deprivation indicators under alternative weighting schemes. Significant positive spatial autocorrelation was observed for hidden severe malaria burden (Moran’s I = 0.412, p < 0.001), RI zero-dose vulnerability (Moran’s I = 0.339, p < 0.001), and the composite co-occurrence score (Moran’s I = 0.240, p = 0.003), demonstrating geographically concentrated vulnerability clusters. Gwarzo, Bichi, Rogo, Sumaila, Bagwai, Rano, Takai, Wudil, Gaya, and Dambatta emerged as the highest-priority LGAs exhibiting simultaneous high hidden malaria burdens, severe treatment gaps, and elevated RI zero-dose rates. K-means clustering identified three distinct malaria–immunization vulnerability typologies, with the most vulnerable cluster comprising 12 LGAs exhibiting an average co-occurrence score of 79.7 and RI zero-dose rates of 66.6%. Sensitivity analyses revealed that DVI rankings were robust across equal, PCA, and entropy weighting approaches. The findings demonstrate that the hidden severe malaria burden and childhood immunization deprivation exhibit substantial spatial overlap in Kano State and highlight the value of the proposed DVI as a geospatial decision-support framework for targeting integrated malaria control, immunization strengthening, and primary healthcare interventions.

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