Systematic review and meta-analysis of the spatio-temporal changes in apparent tsetse fly density in Uganda from 1980 to 2022

of high agricultural and livestock farming potential in sub-Saharan Africa (SSA). Despite its constraints to animal health and production, no accurate national and sub-national level data describing the distribution of tsetse flies has been produced for Uganda. To inform the tsetse fly density (flies/trap/day, or FTD) in Uganda and help advance along the progressive control pathway (PCP) for animal trypanosomiasis, we estimated FTD across sub-counties in Uganda and explored factors influencing variations in FTD across studies. Tsetse fly publications (n = 3462) were retrieved for Uganda from five life sciences databases, focusing on studies which inform the spatial distribution of tsetse flies, particularly reporting FTD across the nation. Following PRISMA guidelines, we conducted a systematic review and meta-analysis of 42 publications with the aim of producing an updated map to describe the spatial distribution of tsetse flies from pooled publication data. Current findings highlight substantial spatial data gaps with highly fragmented temporal collection periods. Of the 42 papers evaluated, only 20 reported FTD and were included in meta-analyses. To exhaust insights from extracted data, a zero-inflated multilevel Poisson was built to estimate the spatial distribution of tsetse flies. Meta-regression results found that the interaction of space (i.e. sub-county), time (i.e. collection period) and Glossina species explained the majority (87.32%) of observed FTD variations. Though several studies did not perform speciation of captured flies, the most predominant species reported in Uganda was Glossina fuscipes fuscipes. Across all records obtained, the western region of Uganda was severely under-sampled. Despite the limitations, like underrepresentation of some regions and declining report of FTD over years, we identified a basis for future research and recommend sub-county estimates be used to target spatial clusters when implementing risk-based tsetse control programs. Moreover, future research should target identifying environmental and climactic predictors of tsetse fly habitats, and we established a solid foundation for the future development of a national-level information system for the vectors of trypanosomiasis (i.e. an 'atlas').