Space-Time Mapping of Malaria Local Endemicity in Nigeria using Two Decades Incidence Rate Data

Authors: Nkeki, F.N. And Omoroghomwan, A.E.

DOI Info: http://doi.org/10.5281/zenodo.8093816

ABSTRACT

The few obtainable literatures focusing on the mapping of malaria endemicity are highly descriptive in approach. No studies have attempted to objectively identify the local strata of the endemicity or long-term hotspot and coldspot of malaria in high burden areas. Hence, this study analyses the spatial and temporal pattern of falciparum malaria endemicity using 20 years of incidence data on a second-level administrative boundary of Nigeria. Getis-Ord Gi* hotspot detection statistic designed to identify significant hotspot and coldspot was used to identify the spatial dynamics of hotspot and coldspot. To detect malaria-endemic areas and derived the significant endemic temporal cluster maps, emerging hotspot analysis and local outlier analysis were carried out using an initially generated space-time cube. The result shows that there is local heterogeneity in the clustering patterns of the malaria incidence rate. Also, a local endemicity map was produced and this shows that high endemic malaria strata seem to cluster around the Nigeria-Benin Republic border and Nigeria-Cameroon border. This suggests that cross border transmission may be taking place over these years. The adopted approach in this study is a robust and appropriate way of modelling space-time data. In epidemiology, the major challenge in intervention deployment, smart resource allocation, surveillance, monitoring and evaluation is the ability to locate spatial clusters of disease infection. The implication of these results is that they provide the springboard for the design of various malaria control and elimination strategies and this will serve as a vital tool for informed decision-making during interventions and surveillance.

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