Introduction: Road traffic crashes are a significant public health concern worldwide, causing numerous injuries and fatalities. While various factors contribute to these crashes, the influence of weather and climate conditions has emerged as an important area of research. This study aimed to access the influence of temperature and rainfall on road traffic crashes in the Greater Kumasi Metropolitan Area (GKMA) of Ghana using a Bayesian spatiotemporal modeling approach.Method: Monthly road traffic crash data from 2010 to 2021, along with monthly temperature and rainfall, were analyzed. A Bayesian geo-spatiotemporal model was self-developed to quantify the effects of climate variables on road crashes while accounting for spatial and temporal dependencies.Results: The findings revealed that a one-degree Celsius decrease in monthly average temperature was associated with a 0.049 increase in the risk of road crashes. On the other hand, one-millimeter increase in monthly average rainfall was associated with a 0.008 increase in crash risk. Significant spatial and temporal patterns were observed, with districts traversed by major highways exhibiting consistently higher relative risks of crashes.Conclusion: This study revealed a significant relationship between monthly average rainfall and monthly road traffic crashes in the Greater Kumasi Metropolitan Area. This finding informs the need for targeted infrastructure improvements and enhancing public awareness campaigns to promote safe driving practices during rainy seasons.
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Idan et al. (2026) studied this question.
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