Extreme heat and disease burden in Southern Africa: a systematic review - George, Maeti Antoinette (Frontiers in Applied Mathematics and Statistics, 2025)
Global climate change affects human populations, as well as aquatic and terrestrial ecosystems, highlighting the interconnected nature of the intervention strategies that seek to improve human health. Statistical applications and mathematical modeling are pivotal and crucial for quantifying the future outcomes and understanding the effects of climate change on diseases. The study was intended to identify the extent to which predictive modeling was utilized in Lesotho in relation to the impact of drought on the spread of disease in human beings. This was a systematic review of literature focused on projections and predictions related to impacts on ecosystems and biodiversity in vulnerable communities, and ultimately on human health. Furthermore, the extent of research regarding the utilization of models in an attempt to curb the spread of climate-related diseases and their effectiveness, so that countries can respond promptly, was reviewed. It has been concluded that predictive modeling has not been applied in Lesotho, and this risks crop failure, disease spread, anxiety and mental health problems for the affected communities. If used, statistical and predictive disease modeling and predictions along the interconnected threats brought by drought would enable an understanding of how and when diseases may spread, and how their spread can be controlled. The review recommends that southern African countries should develop predictive models using available hydrological parameters, meteorological and disease data. Decision-makers should also use climate and disease forecasts, provided they are supported by available climate and health data.