Spatiotemporal analysis of malaria declines in an urban African setting: Limited association with climate variability in Dar es Salaam

Introduction: Urban malaria continues to be a significant public health problem in rapidly developing cities such as Dar es Salaam, where climate variation interacts with urban socio-environmental factors. It is crucial to understand these dynamics for efficient disease control measures. Methods: Using geospatial methods, this study looked at how changes in climate affected the number of malaria cases in the Dar es Salaam Region from 2015 to 2023, utilising climate data from the TerraClimate geoportal and malaria incidence data from the Ministry of Health. Mann-Kendall trend test, Sen’s slope estimator, Getis-Ord Gi* hotspot analysis, Pearson correlation, and regression models were employed in the study. Remote sensing and GIS software were used to examine spatial-temporal trends and malaria hotspots. Results: Validation of satellite rainfall data with ground-based data showed high agreement (r = 0.80, R² = 0.64). There were statistically insignificant rising trends in temperature and rainfall. Ubungo had temperature hotspots that were consistent, while Temeke and Ilala had cold spots that were consistent. Malaria cases decreased by more than 70%, with a strong monotonic decreasing trend (p < 0.001), and Ilala and Kigamboni were found to be consistent hotspots. Conclusion: The results show that non-climatic factors, like city infrastructure and public health measures, are becoming more important in how malaria spreads in Dar es Salaam. Geospatial tools can help us figure out where to focus our malaria control policies.