| Sumario: | Aim: Dengue fever, caused by the Dengue virus and spread by mosquitoes, is a major public health concern in many parts of the world, including Bangladesh. Climatic factors, i.e, humidity, temperature, precipitation, and wind speed play a critical role in transmitting dengue fever. Developing efficient ways to manage and prevent the spread of the disease requires an understanding of the role that climate risk variables play in this process. The aim of this study is to identify an appropriate model that can precisely determine the way climatic risk factors affect dengue outbreaks. Subjects and methods: The complex relationship between climatic risk factors and dengue transmission was modeled using zero-inflated Conway–Maxwell Poisson regression, zero-inflated Poisson regression, zero-truncated Conway–Maxwell Poisson regression, and zero-truncated negative binomial to aid in the creation of efficient preventative and control measures. Results: According to the results of the Akaike information criterion (AIC) and Bayesian information criterion (BIC), the zero-truncated negative binomial regression model was selected as the best model. Humidity (95% CI: 1.101%, 1.124%), precipitation (95% CI: 0.97%, 0.99%), and wind speed (95% CI: 0.79%, 0.87%) were all found to play a major role in the spread of dengue fever. Conclusion: The findings of this study can be used to guide the development of effective strategies for preventing and controlling dengue outbreaks in Bangladesh and other countries facing similar public health challenges.
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