Assessing the impact of climatic factors on dengue fever transmission in Bangladesh

Dengue fever is a virus-borne disease spread by mosquitos, and its global prevalence has risen significantly in recent years. The aim of this study was to analyze the impact and association of climatic factors on the spread of dengue incidence in Bangladesh. From January 2011 to December 2021, the study used secondary data on monthly dengue cases and the monthly average of climatic factors. In addition to the descriptive statistics, bivariate analyses of Kendall's tau-b and Spearman's rho have been performed for measuring the association of climatic factors on dengue infection. The generalized linear negative binomial regression model with and without lag was applied to evaluate the impacts of climatic factors on dengue transmission. Results of goodness of fit statistics (AIC,BIC,anddeviance)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(AIC, BIC, and deviance)$$\end{document} showed that NBR model with one month lag best fitted to our data. The model findings revealed that temperature (IRR:1.223,95%CI:1.089-1.374)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(IRR:1.223, 95\% CI:1.089-1.374)$$\end{document}, humidity (IRR:1.131,95%CI:1.103-1.159)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(IRR:1.131, 95\% CI:1.103-1.159)$$\end{document}, precipitation (IRR:1.158,95%CI:1.072-1.253)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(IRR:1.158, 95\% CI:1.072-1.253)$$\end{document}, and air pressure (IRR:5.279,95%CI:1.411-19.046)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(IRR:5.279, 95\% CI:1.411-19.046)$$\end{document} were significantly positively influenced the spread of dengue incidence in Bangladesh. Additionally, dengue fever cases are anticipated to rise by 1.223, 1.131, 1.158, and 5.279 times, respectively, for the everyone-unit increase in the monthly average mean temperature, humidity, precipitation, and air pressure range. The findings on the epidemiological trends of the dengue epidemic and weather changes may interest policymakers and health officials.