The research team, led by Namita Kaushik and Andreas Tietz, screened 6,983 records and identified 341 studies reporting healthcare resource utilisation or economic outcomes in dengue. Of these, 44 studies reporting hospitalisation rates and 121 studies reporting length of stay met the rigorous feasibility criteria for quantitative synthesis. The work followed PRISMA guidelines, was registered prospectively in the PROSPERO database, and applied the Downs and Black checklist to appraise study quality. Data were drawn from five biomedical databases searched via the Ovid platform, supplemented by citation searches and conference abstracts, with no restriction on country of origin.

The headline result is a pooled global hospitalisation rate of 36.7 percent (95 percent confidence interval 29.0 to 44.4) among patients with dengue irrespective of severity, derived under a random-effects model. The mean length of stay across hospitalised patients was 4.9 days (95 percent CI 4.6 to 5.2). Both outcomes showed very high statistical heterogeneity, with I-squared values approaching 100 percent, reflecting the enormous diversity of settings, designs, and populations represented in the underlying literature. To understand that variation, the authors performed meta-regression across a range of study-level covariates, including geography, outbreak status, data source, and study design.

One variable dominated all others: disease severity. Severity was significantly associated with both higher hospitalisation rates and longer stays, explaining 31.4 percent of between-study variance in hospitalisation and 11.4 percent of the variance in length of stay, with p-values below 0.0001 in both models. Subgroup analyses quantified the gradient precisely. Patients with non-severe dengue without warning signs were hospitalised at a pooled rate of 17.7 percent, rising to 36.9 percent once WHO warning signs such as persistent vomiting, abdominal pain, mucosal bleeding, raised haematocrit, or thrombocytopaenia appeared. Among patients classified as having severe dengue, the pooled hospitalisation rate reached 79.4 percent.

Length of stay followed the same severity gradient. Patients with non-severe disease averaged 4.6 days in hospital, compared with 6.5 days for severe dengue. The most dramatic figures emerged when complications were considered: patients with severe dengue or dengue haemorrhagic fever who developed complications such as shock, renal impairment, platelet-transfusion-requiring thrombocytopaenia, or sepsis stayed a mean of 15.5 days, roughly double the 7.5 days observed in severe cases without complications. Co-infections with pathogens such as SARS-CoV-2 or chikungunya virus, and comorbidities including haematologic malignancies, autoimmune disease, and obesity, each added roughly a day or more to the average stay.

Regional patterns add a further layer of complexity. Hospitalisation rates were numerically higher in Asia, at 35.1 percent, than in Latin America, at 29.3 percent, and length of stay was correspondingly longer in Asian settings, at 5.1 days versus 4.1 days in Latin America. The authors note that this Asian excess echoes the 2016 analysis by Shepard and colleagues, which reported rates of 19.3 to 24.8 percent in Asian subregions against just 3.8 percent in Latin America and the Caribbean. Possible explanations include differing admission thresholds, a higher force of infection, multiple co-circulating serotypes, and demographic differences, but the authors emphasise that the drivers remain unclear and warrant targeted investigation.

The timing of the analysis is significant. Since the last global estimates were published, the world has witnessed record-breaking dengue waves, shifts in circulating serotypes, changing patient demographics, the disruption of the COVID-19 pandemic, and improvements in surveillance and clinical preparedness. The World Health Organization reported a doubling of reported cases from around 7 million in 2023 to approximately 14 million in 2024, while modelling work published in 2025 estimated that annual apparent cases rose from 26.45 million in 1990 to 58.96 million in 2021. Against that epidemiological backdrop, a hospitalisation rate approaching 37 percent implies a demand for inpatient beds, nursing capacity, and supportive care that many endemic health systems are ill-equipped to absorb during peak transmission seasons.

Methodological sensitivity analyses strengthen the central conclusions while exposing their limits. Excluding studies with fewer than 100 participants and those with more than 50,000 yielded a pooled hospitalisation rate of 29.4 percent with narrower confidence intervals, and excluding studies whose data were collected during the pandemic produced an estimate of 25.3 percent, hinting that overwhelmed COVID-era hospitals may have temporarily suppressed dengue admissions. A single exceptionally large nationwide Brazilian cohort dominated the fixed-effects estimate, but random-effects modelling, which the authors favoured given the heterogeneity, attenuated its influence. For length of stay, no evidence of publication bias was detected by Egger’s regression, and the GRADE certainty of evidence was rated low, primarily because of the observational design of the included studies rather than inconsistency or imprecision.

The findings carry immediate practical implications. Hospitalisation is recognised as a key outcome in dengue research: an international Delphi consensus involving experts from more than 30 countries identified the need for hospitalisation as a core endpoint for patients and clinicians. The new benchmarks should therefore help clinical trialists select endpoints and calculate sample sizes, and they align with recently published WHO target product profiles that recommend dengue-related hospitalisation as a secondary efficacy outcome in non-severe disease. For policymakers, the estimates provide a foundation for cost-effectiveness analyses of vaccines, antivirals, and vector-control strategies, and for identifying the regions where preventive investment would relieve the greatest pressure on hospitals.

The authors are careful to frame the pooled figures as average trends across highly diverse settings rather than universal constants. Admission thresholds, clinical practice, healthcare-seeking behaviour, and reporting conventions differ substantially between countries, and the denominator in most studies was skewed towards patients already seeking care, which may inflate the apparent hospitalisation rate relative to all symptomatic infections. The observation that some patients with warning signs or severe disease were nonetheless not hospitalised may reflect symptom misclassification, resource constraints, or emergency department stays that were never recorded as admissions. Even so, the overall message is difficult to escape: dengue’s demand on hospital infrastructure has likely risen considerably over the past decade, and quantifying the associated direct and indirect costs, productivity losses, and caregiver burden is now an urgent priority for global health planning.

Subject of Research: Global hospitalisation rates and length of stay for dengue patients

Article Title: Global burden of dengue on healthcare systems: a meta-analysis of healthcare resource utilisation

Article References: Kaushik, N., Subramanian, S., Gedif, K., Nallagangula, T. K., Singuru, S., Panchal, S., Meyer-Andrieux, I., Gruenberger, J.-B., McBride, A., Yacoub, S., & Tietz, A. (2026). Global burden of dengue on healthcare systems: a meta-analysis of healthcare resource utilisation. eClinicalMedicine, 100, Article 104217. https://doi.org/10.1016/j.eclinm.2026.104217

Image Credits: AI Generated

DOI: 10.1016/j.eclinm.2026.104217

Keywords: dengue, hospitalisation rate, length of stay, meta-analysis, healthcare resource utilisation, systematic review, global health burden, WHO warning signs, severe dengue, Aedes mosquitoes, health systems, eClinicalMedicine

The research team set out to correct a critical bias that had affected earlier syntheses of the evidence. A previous meta-analysis published in 2015 had pooled studies of serotype and severity, but it included investigations that sampled only hospitalised patients. Because hospitalisation itself requires a certain threshold of illness severity, restricting the denominator to hospitalised cases artificially inflates the estimated probability that a symptomatic infection becomes severe. The new analysis therefore excluded studies that monitored severe disease only among hospitalised patients, and it also kept severe cases defined under the WHO 1997 guidelines, the WHO 2009 guidelines, and hospitalisation as three separate classification systems rather than merging them, since these definitions capture clinically distinct constructs.

The search strategy was exhaustive. The authors queried Medline, Global Health, and Embase Classic plus Embase for all relevant studies published up to 20 January 2025, generating 8,533 records. After de-duplication and screening, 73 studies passed the review criteria, of which 71 contributed data to the meta-analysis. To be included, studies had to report laboratory-confirmed symptomatic dengue cases with matched serotype and severity information for the same group of people, and prior exposure-serotype combinations involving fewer than five cases were excluded to avoid unstable estimates. Patients with non-dengue co-infections or chronic conditions such as diabetes and hypertension were also excluded, as these are known risk factors for severe outcomes that could confound the serotype-specific signals the team sought to isolate.

Methodologically, the study represents a substantial advance over conventional random-effects meta-analysis. The authors developed a Bayesian inferential framework implemented in the Stan probabilistic programming language, fitting a generalised linear mixed additive logit model in which each study outcome, the number of severe cases among a given number of symptomatic cases, was assumed to follow a binomial distribution. The model estimated an intercept, a geographic region effect distinguishing Asia from the Americas, and separate coefficients for every prior exposure-serotype combination, with Asia-secondary-DENV2 serving as the reference scenario. Crucially, the framework accounted for correlation between multiple outcomes reported within the same study through multivariate normal random effects with scenario-specific covariance matrices, allowing data from one region to inform estimates in the other where individual scenarios lacked sufficient studies for pooling.

The headline quantitative findings are sobering. Under the WHO 1997-type classification, secondary DENV3 infection in Asia emerged as the most severe scenario overall, with a pooled 37.61 percent of symptomatic cases developing dengue haemorrhagic fever or dengue shock syndrome, a credible interval spanning 24.19 to 52.32 percent. Secondary DENV4 produced the lowest proportion of DHF and DSS among secondary infections, at 26.00 percent in Asia and 15.80 percent in the Americas. Yet when the authors formally compared serotypes conditional on the same prior exposure status, the differences were not statistically significant. Even the contrast between the most and least severe secondary infections, DENV3 versus DENV4, yielded an odds ratio of 2.16 with a 95 percent credible interval of 0.56 to 6.05, crossing unity.

The picture changed decisively when the analysis turned to prior exposure. Under 1997-type severity, secondary DENV2 and secondary DENV3 were both significantly more severe than primary infections of the same serotype, and secondary DENV3 was significantly more severe than primary infections of any other serotype for which estimates were available. This pattern is consistent with the well-characterised immunopathology of dengue, in which a first infection confers long-lasting homotypic immunity but only transient heterotypic protection, and secondary infection with a different serotype can trigger antibody-dependent enhancement. In this mechanism, individuals carrying intermediate titres of pre-existing cross-reactive antibodies experience enhanced viral entry into Fc-receptor-bearing cells, elevating the risk of the vascular leakage that defines severe dengue relative to both dengue-naive individuals and those with high antibody titres.

Geography also left its mark on the estimates, though less robustly. Using 1997-type severity, the odds of a dengue case being severe in the Americas were on average roughly half those in Asia, an odds ratio of 0.53 with a credible interval of 0.27 to 0.91 that excluded one. However, this regional difference lost statistical significance in sensitivity analyses that excluded cases with unknown prior exposure status or applied stricter de-duplication criteria, suggesting that differences in population-level immunity profiles and underlying demographics, rather than an intrinsic regional virulence, may drive the apparent excess of severe dengue in Asia. Historically higher rates of DHF in Asia have also been attributed to variation in circulating viral genotypes and to differences in healthcare practice, including the clinical laboratory tests, such as haematocrit measurement, that the 1997 classification requires.

The authors subjected their results to an unusually thorough battery of validation and sensitivity checks. A simplified model fitted only to data from the long-running Nicaraguan and Thai cohort studies reproduced the central finding that DENV3 was the most severe primary and secondary infection, although this restricted dataset did reveal significant serotype differences within the same prior exposure status, with secondary DENV2 and DENV3 emerging as the most severe. Pooled estimates of hospitalisation proportions for DENV1, DENV2 and DENV4 with unknown prior exposure aligned well with observed hospitalisation rates in the placebo arm of the TAK-003 vaccine trial at 57 months of follow-up, though DENV3 estimates ran two- to threefold higher than trial observations, a discrepancy the authors attribute partly to country-specific hospitalisation practices, since most trial DENV3 cases came from the Philippines. Leave-one-out analyses, stricter de-duplication, and prior-distribution sensitivity analyses all left the core conclusions intact, and risk-of-bias assessment using an adapted Hoy tool classified no study as high risk.

Substantial statistical heterogeneity remained a persistent feature of many scenarios, with I-squared values exceeding 75 percent in all 1997-type scenarios where prior exposure was unknown, and prediction intervals were correspondingly wide; the prediction interval for primary DENV2 in the Americas stretched from 0.02 to 56.06 percent around a central estimate of just 4.08 percent. The authors identify several plausible contributors: regional differences in healthcare practice, genetic variation in circulating strains, varying proportions of primary and secondary infections among participants, patient age, study design differences, and exposure to other flaviviruses, notably Zika virus, which has been shown to enhance subsequent dengue disease risk. Data limitations also precluded modelling patient age or the sequence of infecting serotypes across a lifetime, both of which have been implicated in clinical outcomes.

The practical implications reach from the clinic to the modelling suite. Clinically, the absence of serotype-specific severity differences means that the infecting serotype alone, independent of other patient parameters, cannot be used to predict the course of illness or to guide triage. For outbreak response, knowledge of the dominant circulating serotype, considered separately from historical transmission dynamics, is unlikely to determine healthcare and hospital demand, which underscores the value of seroprevalence surveys in reconstructing population immunity profiles. The estimates generated here are intended to parameterise mathematical models of dengue transmission and burden, informing projections of the impact and cost-effectiveness of vaccination, antiviral drugs and vector control, including Wolbachia-based strategies, under current and changing climatic conditions. With the Qdenga vaccine deployed in Brazilian public campaigns since February 2024 and its efficacy known to depend on both pre-vaccination serostatus and infecting serotype, quantifying severe disease risk across the full matrix of exposure and serotype combinations has become a public health priority that this analysis now addresses with unprecedented rigour.

Subject of Research: Association between dengue virus serotypes, prior exposure and severe disease outcomes

Article Title: Association of dengue severity with the serotype of infection: a systematic review and meta-analysis

Article References: Ang, H. J., McCormack, C., Donnelly, C. A., & Dorigatti, I. (2026). Association of dengue severity with the serotype of infection: a systematic review and meta-analysis. eClinicalMedicine, 100, Article 104218. https://doi.org/10.1016/j.eclinm.2026.104218

Image Credits: AI Generated

DOI: 10.1016/j.eclinm.2026.104218

Keywords: dengue, DENV serotypes, severe dengue, meta-analysis, antibody-dependent enhancement, WHO classification, secondary infection, hospitalisation, Bayesian modelling, vaccination, epidemiology, global health