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Viral Infections and Outbreaks Research / Mosquito Borne Diseases and Control / Data Driven Disease Surveillance · Journal article
Dhaka University Journal of Science · August 30, 2026
Encouraging direction, but not yet definitive.
This Bayesian meta-analysis of 41 cross-sectional studies estimates that approximately one-third (33.9%) of dengue cases progress to severe dengue in Bangladesh, with low between-study heterogeneity and convergent MCMC diagnostics. The estimate is derived from observational prevalence data and should inform public health surveillance planning, though the cross-sectional design precludes direct causal inference and generalisability beyond Bangladesh remains uncertain.
Systematic review and Bayesian random-effects meta-analysis of cross-sectional studies. Dengue-infected individuals identified in cross-sectional studies conducted in Bangladesh. Bangladesh.
Pooled prevalence of severe dengue among dengue cases in Bangladesh estimated at 33.9% (95% CrI: 25.4–42.0%) using Bayesian random-effects model with strongly informative prior Between-study heterogeneity (I²) = 0.074, indicating low heterogeneity across the 41 included cross-sectional studies MCMC model diagnostics demonstrated adequate mixing and convergence with no evidence of autocorrelation in chains
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This prevalence estimate suggests that severe dengue constitutes a substantial disease burden in Bangladesh and may inform resource allocation and clinical surveillance protocols. However, as a prevalence figure derived from cross-sectional data, it does not directly quantify incidence or clinical outcomes and should be interpreted alongside prospective data on progression risk and outcomes.
A systematic meta-analysis of 41 cross-sectional studies using Bayesian methods with appropriate diagnostics, but prevalence is a surrogate for clinical burden and cross-sectional design limits causal inference; findings need confirmation in prospective studies.
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Quoted from the source exactly as published.
This prevalence estimate suggests that severe dengue constitutes a substantial disease burden in Bangladesh and may inform resource allocation and clinical surveillance protocols. However, as a prevalence figure derived from cross-sectional data, it does not directly quantify incidence or clinical outcomes and should be interpreted alongside prospective data on progression risk and outcomes.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
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)
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