STATISTICAL SPATIAL MODELLING FOR THE TREATMENT OF TYPHOID (ENTERIC) FEVER IN MAIDUGURI, BORNO STATE, NIGERIA

Abstract

Typhoid Fever (TF) remains a critical health is- sue in Maiduguri (M), Nigeria, with its prevalence and spatial distribution posing significant challenges to effective treatment and prevention. This study employs statistical spatial modeling techniques to analyze the spatial patterns of Typhoid Fever cases in Maiduguri, providing valuable insights for targeted treatment strategies. Utilizing Geographic Information System (GIS) tools, we mapped the distribution of reported typhoid cases in the city and conducted spatial autocorrelation analysis to identify clustering patterns. Hotspot analysis further pinpointed areas with significantly higher case incidence than expected by chance. Spatial interpolation techniques were applied to estimate the risk surface across the urban landscape. The findings reveal spatially correlated clusters of Typhoid Fever cases, offering a foundation for improved resource allocation and intervention planning. This research underscores the importance of spatial modeling in enhancing the understanding and management of Typhoid Fever in Maiduguri (M), ultimately contributing to more effective Public Health (PH) initiatives.