<p>Paediatric malaria is a major cause of child mortality in Nigeria. Despite the numerous antimalaria interventions, paediatric malaria remains a major public health concern in the country. An understanding of the geographic pattern of paediatric malaria in the country would therefore assist policymakers and the government in making informed decisions on malaria elimination. This study aimed to examine the geographic pattern of paediatric malaria in Nigeria, and identify their climatic, demographic, environmental, and socio-economic drivers. Data used in this study were from published sources. Spatial analytical techniques including Global Moran’s I and Getis-Ord Gi* were used to determine the degree of spatial clustering of paediatric malaria and identify hotspot regions for paediatric malaria in each year. We found that paediatric malaria in Nigeria significantly clustered in space. Hotspots were identified in different areas across the study periods while coldspots were generally found in the southwest corner of Nigeria. Stepwise linear regression analysis identified poverty (R<sup>2</sup> = 0.43.5) as the dominant predictor of paediatric malaria in Nigeria. The study concludes that free anti-malaria treatment for children and poverty reduction <i>inter alia</i> may be required to reduce the malaria burden in Nigeria.</p>

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Geographic Patterns and Drivers of Paediatric Malaria in Nigeria: Walking in the shadow of Poverty

  • Tolulope Osayomi,
  • Oluwatomi Adeyinka Adedun

摘要

Paediatric malaria is a major cause of child mortality in Nigeria. Despite the numerous antimalaria interventions, paediatric malaria remains a major public health concern in the country. An understanding of the geographic pattern of paediatric malaria in the country would therefore assist policymakers and the government in making informed decisions on malaria elimination. This study aimed to examine the geographic pattern of paediatric malaria in Nigeria, and identify their climatic, demographic, environmental, and socio-economic drivers. Data used in this study were from published sources. Spatial analytical techniques including Global Moran’s I and Getis-Ord Gi* were used to determine the degree of spatial clustering of paediatric malaria and identify hotspot regions for paediatric malaria in each year. We found that paediatric malaria in Nigeria significantly clustered in space. Hotspots were identified in different areas across the study periods while coldspots were generally found in the southwest corner of Nigeria. Stepwise linear regression analysis identified poverty (R2 = 0.43.5) as the dominant predictor of paediatric malaria in Nigeria. The study concludes that free anti-malaria treatment for children and poverty reduction inter alia may be required to reduce the malaria burden in Nigeria.