Prevalence of Severe Dengue Infection in Bangladesh: A Bayesian Meta-analysis

Abstract

Severe dengue represents a critical and potentially life-threatening stage of dengue infection, often characterizes by internal bleeding which leads to death. Several studies existed on severe dengue but a meta-analysis can provide robust understanding of the epidemiology of the disease. This study aimed to estimate the pooled prevalence of dengue cases which developed to severe dengue in Bangladesh. A systematic literature search was conducted across five databases between January 2000 and June 2025: PubMed, Google Scholar, Cochrane Central, Science Direct, and BanglaJOL. After title and abstract screening and full text review, this study included 41 cross-sectional studies. The quality of included studies were assessed using the STROBE checklist. Bayesian random-effects model was applied to estimate the pooled prevalence, with both non-informative and informative priors. Further, model diagnostics including trace plots and autocorrelation checks were used to assess MCMC convergence. A Bayesian random-effects model using the strongly informative prior estimated a pooled prevalence of 33.9% (95% Credible Interval: 25.4, 42.0), and a between-study heterogeneity () of 0.074. Model diagnostics were further supported these findings by the evidence of adequate mixing and convergence, with no signs of autocorrelation in the MCMC chains. However, this study have found one-third of the dengue cases developed to severe dengue cases which indicates a serious burden for the healthcare system of the country. These findings have important implications for public health surveillance and can inform policymakers in planning and prioritizing interventions to manage severe dengue cases in Bangladesh.

Dhaka Univ. J. Sci. 74(2): 301–310, 2026 (July)