Geo-spatial hotspots of Tuberculosis in the global general population: a systematic review

Abstract INTRODUCTION: The objective of this systematic review is to identify tuberculosis hotspots among the general population globally. The review was conducted using the following steps: elaboration of the research question, search for relevant publications, selection of studies found, data extraction, analysis, and evidence synthesis. METHODS The guiding question was elaborated with the CoCoPop acronym (condition, context and population): where are the geo-spatial hotspots of tuberculosis (Co) in general population (Pop) in the global context (Co)? For bibliographic search, controlled and free vocabularies that address the question to be investigated was used. The searches were carried out in five scientific literature databases and on Google Scholar. RESULTS A total of 79 published articles between 1982 and 2022 which is a 40 years study period were evaluated. To answer these questions above, out of the 79 studies, China has the highest number of studies constituting 40% of all countries that have carried out geospatial analysis of TB followed by Brazil with 23%, Iran and Ethiopia both have 6% and others 2% and 1%. Various maps were used in the various studies and the most used is the thematic map (32%), rate map (26%), map of temporal tendency (20%), and others like the kernel density map (6%). The characteristics of the hotspots and the factors that affects hotspot’s location is evident through studies related to poor socioeconomic conditions constituting (39%), followed by high population density (17%), climate related clustering (15%), hotspots spread to neighboring cities (13%), unstable and non-random cluster (11%). CONCLUSION There exist specific hotspots for Tb which are areas that are related to low socioeconomic conditions and spectacular weather conditions, these areas when well-known will be easy targets for intervention by policy makers. We recommend that more studies making use of spatial, temporal and spatio-temporal analysis be carried to point out territories and populations that are vulnerable to TB.