SPATIAL - TEMPORAL ANALYSIS OF TB CASE NOTIFICATION IN NORTHERN MALAWI

Abstract

Tuberculosis (TB) presents a significant public health challenge, particularly in high disease burden countries in Africa, such as Malawi. The extent of this problem varies across different settings. Understanding the spatial variation and underlying causes of TB prevalence is crucial for comprehending and addressing the epidemic. Therefore, the utilization of geospatial analytical methods and spatial temporal models is vital in analysing and detecting spatial and spatial-temporal clustering of infectious diseases. This study investigated the spatial distribution and presence of spatial-temporal clusters of TB in various geographic settings over an eight-year period (2013 – 2020) in Northern Malawi. Specifically, the study aimed to identify temporal trends, spatial patterns, infectious disease clusters or hotspots and cluster coverage related to TB. Spatial and spatial temporal statistical analyses were employed, utilizing Kulldorff's scan statistics tool, through the implementation of Spatial and Spatial-temporal models. The findings revealed the presence of seven clusters or hotspots within the study area. The model identified a cluster pattern where hotspots were observed in areas characterized by relatively higher population sizes and densities, predominantly located within economically developed zones. Notably, the clusters or hotspots in Northern Malawi were found to form around Central Districts, District Hospitals, major rural hospitals, as well as urban and semi-urban centres, including Mzuzu City, Chintheche, Bolero, Bwengu, Mzimba Boma, Embangweni, Jenda, Chitimba, among others. By analysing time trends, the study observed a general decline in TB infection cases within the region, with an annual decrease of 1.08%. These results indicate significant progress in disease control efforts. However, TB still poses a considerable risk to the population residing in proximity to clustered health centres.