Global burden, economic impact, and management strategies for re-emerging dengue virus infections: a systematic review

1 Introduction

Over recent decades, dengue has re-emerged as the most significant vector borne viral diseases with a growing geographic footprint and rising epidemic intensity. Once largely confined to tropical regions, it has emerged as a global economic challenge, extending its reach into previously unaffected countries (1–3). Notably, in 2024, dengue has recurred as a global challenge and cases surpassed 14.6 million in the world, resulting in more than 12,000 deaths, highlighting a major public health concern (4). Despite this growing burden, there is no recent comprehensive assessment on its global economic impact. Earlier analysis estimates were approximately US$8.9 billion annually, a figure which continues to be supported in recent systematic reviews (4–6).

Threatening nearly half of the world’s population, this mosquito-borne illness is caused by the Dengue virus with four main serotypes, namely DENV-1, DENV-2, DENV-3, DENV-4 (7, 8). From transmission perspective, dengue is a mosquito borne disease; its primary vector is Aedes aegypti, with A. albopictus serving as secondary vector (9). A. aegypti is well adapted to the subtropical and tropical territories and exhibits strong anthropophilic behavior (6, 10). In contrast, A. albopictus can live in a broader temperature range and at cooler temperatures than A. aegypti, it is less attracted to humans (10, 11). Consequently, vector-controlling strategies remain the main focus of dengue prevention efforts worldwide (2).

Clinically, most infections of dengue are asymptomatic or mild, only about 25% of the cases develop symptoms (10, 12, 13). Only a small percentage of the human population develop severe dengue i.e. Dengue Hemorrhagic Fever (DHF) and require hospitalisation, which significantly contributes to overall economic burden. Dengue pathogenesis is further complicated by Antibody Dependent Enhancement (ADE) where antibodies from a primary infection fail to bind to the DENV particles during the secondary infection with a different serotype. As a result, there is an increase in the risk of developing severe dengue (8, 14).

Dengue poses an unprecedented global threat imposing a substantial economic burden on nations and communities, emphasising the urgent need for coordinated strategies to mitigate its impact on public health and economies worldwide. At the Global level, dengue causes an estimated millions infections annually, with the majority cases concentrated in tropical regions (2, 7). As illustrated in Figure 1, countries including India, Brazil, Indonesia, Bangladesh, Philippines and Thailand account the highest number of cases and deaths due to dengue. Common factors of these countries like high population density, suitable climate for mosquitoes and differences in healthcare and surveillance, add to the vulnerability.

The escalating burden of dengue imposes both direct and indirect economic liabilities on affected persons, and therefore, all costs associated with dengue (including those for diagnosis, treatment, and prevention) must be clearly outlined and understood (as shown in Figure 2). Beyond its clinical impact, its burden can be assessed through a) epidemiological measures, which include incidences, hospitalisations and mortality; and b) economic measures, including direct treatment cost and the indirect costs borne by patients and the households (15–23). However, measuring the true economic burden is an arduous task due to indirect cost estimation like lost productivity, income loss, transportation and other non-medical expenses which are further compounded by variations in methodologies and data sources across regions, hindering global comparisons.

One of the approaches widely used in economic evaluations is the disability adjusted life year (DALY), which combines year of life lost (YLL) due to premature mortality with years lived with disability (YLD) due to morbidity to provide a standardised measure of overall disease burden, with one DALY representing one lost year of healthy life (24, 25) (Figure 3).

To address these challenges, it is essential to analyze these burdens comprehensively using various mathematical and economic models, while also considering the human impact and societal implications of the disease. Therefore, this systematic review aims to assess the surveillance and economic burden of dengue infection globally, including direct healthcare costs, out-of-pocket expenditures, indirect productivity losses, and costs associated with treatment and prevention strategies such as vaccination and vector control.

2 Systematic literature review

2.1 Methods

2.1.1 Study design

This study was conducted as a systematic review to synthesise evidence on the economic burden of dengue, including direct medical costs, indirect costs, out-of-pocket expenditure, and the cost-effectiveness of interventions such as vaccination and vector control. The review was conducted in accordance with the PRISMA 2020 guidelines.

2.1.2 Search strategy

A comprehensive literature search was performed across multiple electronic databases, including PubMed, Scopus and Web of Science. Search terms were developed using a combination of keywords and Boolean operators, structured around three main concepts: (1) dengue, (2) economic burden/cost, and (3) prevention/control measure. Synonyms within each concept were combined using the Boolean operator “OR”, and the three concepts were combined using “AND”.

Database-specific filters were applied where appropriate. In PubMed, filters for English language and human studies were applied, resulting in 192 records from an initial 236. In Scopus, results were limited to English-language journal articles, yielding 391 records from an initial 591. In Web of Science, filters for English language and document types (articles and review articles) were applied, resulting in 220 records from an initial 234.

No restrictions were applied on publication year to ensure comprehensive coverage of the literature. The final search was conducted on March 30, 2026. The full search strategies for all databases are provided in the Supplementary Table 1. Additionally, the reference lists of included studies were screened manually by all the authors independently. Any disagreements were resolved with discussion.

2.1.3 Eligibility criteria

Studies were included if they were original research articles reporting quantitative economic outcomes related to dengue, including direct medical costs, indirect costs, out-of-pocket expenditure, or cost-effectiveness measures such as cost per DALY averted. Eligible study designs included observational studies, cost-of-illness analyses, and economic evaluations, including modelling studies, conducted in human populations and published in English.

Studies were excluded if they were reviews, editorials, commentaries, or conference abstracts without primary data, or if they did not report quantitative economic outcomes.

2.1.4 Study selection and quality assessment

All identified records were screened based on titles and abstracts, followed by full-text assessment for eligibility. Duplicate records were removed prior to screening. Studies were selected based on predefined inclusion and exclusion criteria. A total of 93 studies were included in the final analysis.

The methodological quality of the included economic studies was assessed using an adapted economic evaluation checklist developed from commonly reported quality appraisal domains. The assessment focused on five key criteria: (1) clarity of the study objective, (2) appropriateness of the study design and methodology, (3) adequacy of data sources or sample characteristics, (4) transparency of economic cost or disability-adjusted life year (DALY) estimation methods, and (5) discussion of study limitations and underlying assumptions.

Each criterion was assigned a score of 1 when adequately addressed, resulting in a maximum possible score of 5. Studies were subsequently categorised as high quality (5 points), moderate quality (3–4 points), or low quality (≤2 points). Given the heterogeneity of study designs, settings, and outcome measures, the quality assessment was undertaken to provide an overall appraisal of methodological rigor rather than to determine study eligibility for inclusion. The detailed results of the quality assessment are presented in Supplementary Table 2.

2.1.5 Data extraction

Data were extracted using a standardised framework. Extracted variables included study characteristics (country and design), direct medical costs (outpatient, hospitalisation, and intensive care), indirect costs (productivity losses), out-of-pocket expenditure, total cost per episode, and national-level economic burden. Data on intervention-related costs, including vaccination and vector control strategies, as well as cost-effectiveness outcomes such as cost per DALY averted, were also collected where available.

To minimise duplication of evidence, burden estimates originating from previously published systematic reviews, meta-analyses, or modelling studies were identified during data extraction and were not double counted in the narrative synthesis. Where multiple publications reported overlapping estimates, the most comprehensive or original source was preferentially referenced. Due to substantial heterogeneity across included studies in terms of currency, price year, costing methodology, and healthcare system structure, formal cost standardisation (including inflation adjustment and purchasing power parity conversion) was not performed. Instead, cost estimates were extracted as reported in the original studies and synthesised descriptively. As a result, comparisons across countries should be interpreted as indicative of relative trends rather than direct economic equivalence.

2.1.6 Data synthesis

A narrative synthesis approach was used to summarise findings across studies. Results were stratified by geographic region, income level, and cost category (direct, indirect, out-of-pocket, and intervention-related costs). Where appropriate, findings were interpreted in relation to macroeconomic indicators such as gross domestic product (GDP) per capita and differences in healthcare financing structures (public versus private systems) to support contextual comparison.

2.2 Results of systematic literature review

2.2.1 Study selection

A total of 803 records were identified through database searching (PubMed:192; Scopus: 391; Web of Science: 220). After removal of duplicates, 506 records remained for screening. Following title and abstract screening, 139 articles were assessed for full-text eligibility. Of these, 93 studies met the inclusion criteria and were considered in the final synthesis (Figure 4).

2.2.2 Study characteristics

Across the 93 included studies, dengue imposes a substantial and heterogeneous economic burden globally, with strong variation across geographic regions, healthcare systems, and income levels (26–28). Multi-country analyses estimate the global annual economic burden to be in the order of several billion US dollars, with Southeast Asia and Latin America contributing the largest share of cases and costs (26, 27).

Country-level analyses demonstrated wide variability in cost per dengue episode. In low-income settings such as Burkina Faso, outpatient costs were reported as low as approximately USD 15 per case (29). In contrast, India reported outpatient costs ranging from approximately USD 20–100 and hospitalisation costs between USD 200–800 across multiple studies (30–33). Similar patterns were observed in Southeast Asia, where Thailand and Vietnam reported costs per episode ranging from approximately USD 100–1000 depending on disease severity and care level (34–36).

DALY estimates ranged from approximately 50–150 per million in subnational analyses (37) to 100–300 per million at national levels (25), with overall heterogeneous trends across Asia, the Americas, and the Caribbean. The majority of DALYs were attributable to years lived with disability, highlighting the predominance of non-fatal disease burden.

2.2.3 Direct medical costs

Direct medical costs of dengue varied substantially across settings but were consistently dominated by hospitalisation-related expenditures. Across included studies, the cost per hospitalised case ranged from approximately USD 150–800 in India and Sri Lanka (31, 38), increasing to USD 250–900 in Vietnam (36, 39) and USD 500–1,500 in Brazil (40, 41). The highest reported costs were observed in China, where estimates frequently exceeded USD 800 and reached up to USD 1,000 per case (42, 43).

In Latin America, Brazil reported outpatient costs of approximately USD 100–120 and hospitalisation costs ranging from USD 500–1500 (40, 44, 45). Severe dengue cases in Mexico demonstrated substantially higher costs, with intensive care episodes reaching around USD 700–800 per case (46, 47). High-income countries such as Singapore reported costs per case frequently exceeding USD 200–600 for hospitalised patients (48, 49).

Disease severity was a major determinant of cost, with severe dengue cases incurring approximately two to five-fold higher expenditures compared to non-severe cases (46, 50). This increase was primarily driven by intensive care utilisation, prolonged hospitalisation, and greater diagnostic and therapeutic requirements (51).

Across multiple studies, private healthcare systems were associated with consistently higher costs than public systems, typically ranging from 1.1 to 4.5 times higher (45, 52), contributing further to variability in direct medical expenditure across countries.

2.2.4 Indirect and out-of-pocket costs

Indirect and out-of-pocket (OOP) costs constituted a substantial proportion of the overall economic burden, particularly in low- and middle-income countries (LMIC). Reported OOP expenditure per dengue episode ranged from approximately USD 70–300 in Bangladesh (53, 54), USD 100–400 in Thailand (35, 55), USD 150–500 in Malaysia (19, 56) and USD 200–600 in Peru (57).

Productivity losses due to illness and caregiving responsibilities contributed significantly to total costs, accounting for approximately 30–60% of the overall economic burden per case in several studies (26, 27). In addition, multiple studies reported catastrophic health expenditure among hospitalised patients, particularly in Southeast Asia, highlighting the disproportionate financial impact of dengue on households in resource-limited settings (58).

Across the dataset, indirect costs (including productivity loss and premature mortality) ranged from USD 3.8–1332 for outpatient cases and USD 6.7–1445.9 for hospitalised cases, while fatal cases resulted in productivity losses exceeding USD 1 million in high-income valuation settings (5). These costs accounted for approximately 40–42% of the total global dengue burden, with combined indirect and OOP costs frequently exceeding direct medical costs and representing 50–75% of total per-episode expenditure across multiple LMIC studies (48).

2.2.5 Economic burden of dengue

The overall economic burden of dengue was substantial across endemic regions and varied depending on transmission intensity, healthcare systems, and outbreak dynamics. National-level estimates indicated an annual economic burden of approximately USD 1.1 billion in India (31, 32), while estimates in Brazil ranged from USD 300 million to over USD 1 billion depending on epidemic conditions (40, 59).

In Indonesia, the burden was estimated at USD 300–500 million annually (60, 61) with Mexico reporting USD 170–300 million (46, 47) and Puerto Rico between USD 40 and 100 million annually (16, 62).

At the regional level, the economic burden in Southeast Asia was estimated to exceed USD 1 billion annually (26). Across studies, the average cost per dengue case ranged from USD 200 to 1,500 depending on severity, healthcare access, and country income level (50). Epidemic periods were associated with a two- to three-fold increase in total economic burden, reflecting both increased case numbers and heightened pressure on healthcare systems (63). Table 1 shows the details of the same.

Table 1. Country-wise cost of dengue (comparative economic burden).

Source: Compiled by authors.

Globally, the total annual economic burden of dengue has been estimated at approximately USD 8.9 billion, although this likely represents an underestimate due to underreporting and incomplete capture of indirect costs (6, 66).

2.2.6 Cost of dengue vaccination strategies

Vaccination costs were primarily derived from modelling studies, with vaccine prices commonly assumed at approximately USD 20 per dose and USD 60–120 per fully vaccinated individual including delivery costs (67–69). Cost-effectiveness analyses across endemic regions reported incremental cost-effectiveness ratios ranging from approximately USD 3000–5000 per DALY averted (67, 69–71).

National-level investment requirements varied widely, with medium-burden countries requiring approximately USD 10–100 million annually and high-burden countries exceeding USD 100–500 million depending on coverage (67, 69). Additional costs, including pre-vaccination screening and logistics, were identified as major contributors to total programme cost (68). Table 2 shows the details of the same.

Table 2. Dengue vaccination cost and programme comparison.

Source: Compiled by the authors.

2.2.7 Cost of vector control strategies

Routine vector control programmes were associated with annual per capita costs ranging from less than USD 1 to over USD 30 depending on implementation intensity (56, 72, 73). Chemical control strategies required repeated applications, contributing to sustained operational costs and reduced efficiency due to insecticide resistance (72).

Biological control strategies, particularly Wolbachia-based interventions, demonstrated implementation costs of approximately USD 3–6 per person with favourable long-term cost-effectiveness (74–78). Table 3 provides a comprehensive overview of dengue vector control strategies and associated cost profiles across the included countries, summarising the dominant interventions, key cost characteristics, and differences by country income group.

Table 3. Dengue vector control strategies and cost profiles.

Source: Compiled by the authors.

3 Empirical spatio-temporal analysis of DALYs, incidence and mortality (1990–2023)

3.1 Data and descriptive statistics

Annual country-level estimates of dengue-related disability-adjusted life years (DALYs), incidence rate and death rates were obtained from the Institute for Health Metrics and Evaluation (IHME) Global Burden of Disease (GBD) Results Tool for the period 1990–2023. The GBD database reports DALY rates, incidence rate, and death rates as age-standardised rates per 100,000 population enabling direct comparisons across countries and over time.

The analysis included 15 dengue-endemic countries selected to represent diverse geographic and economic settings. Countries were classified according to the World Bank income categories as Lower-Middle-Income Countries (LMICs): Bangladesh, Cambodia, India, Indonesia, Nicaragua, Pakistan, Philippines, Sri Lanka, and Viet Nam and Upper-Middle/High-Income Countries (UMIC/HICs): Brazil, Colombia, Malaysia, the Maldives, Peru, and Thailand. The final balanced panel comprised 510 observations (15 countries × 34 years). DALY rates served as the dependent variable, reflecting the combined burden of premature mortality and disability, while dengue death rates and incidence rates were used as the principal explanatory variable.

3.2 Empirical methodology

To quantify the determinants of dengue burden, a fixed-effects panel regression model was estimated using annual country-level observations from 15 countries between 1990 and 2023:

DALYit=αi+β1×(Deathit)+β2×(Incidenceit)+ϵit

where:

• ▪ DALYit ​ represents the DALY burden for country i in year t
• ▪ αi represents unobserved time-invariant country-specific effects
• ▪ Deathit represents the dengue death rate per 100,000 population
• ▪ Incidenceit represents the dengue incidence rate per 100,000 population
• ▪ ϵit ​ represents the error term

The fixed-effects specification was chosen to account for unobserved structural factors such as climate suitability, urbanisation, vector ecology, and baseline health-system capacity that remain relatively constant within countries over time. Robust standard errors were used to address heteroskedasticity and serial correlation. The model was estimated using STATA.

To characterise heterogeneity in temporal patterns, dual-axis line plots were generated for each country showing annual DALYs and mortality rates from 2010 to 2023. These plots were used to identify periods in which mortality and disability burden moved in parallel or diverged. In addition, separate country-specific robust linear regressions were conducted to estimate the magnitude of the mortality, incidence and DALY association within each setting (Tables 4, 5).

Table 4. Fixed-effects panel regression examining the association between dengue-related disability-adjusted life years (DALYs), death rates, and incidence rates across 15 endemic countries, 1990–2023.

Robust SE in parentheses. ***p < 0.001.

Table 5. Country-specific regression analyses of the association between dengue-related disability-adjusted life years (DALYs), death rates, and incidence rates across 15 endemic countries (1990–2023).

Robust standard errors in parentheses. *** p < 0.001.

3.3 Empirical results

3.3.1 Fixed-effects panel regression

The fixed-effects regression demonstrated that both dengue mortality and dengue incidence were significant predictors of DALY burden across the 15 countries (Table 5). The estimated coefficient for death rate was 68.56 (95% CI: 52.81-84.30; p < 0.001), indicating that each increase of one dengue death per 100,000 population was associated with an average increase of approximately 68.6 DALYs per 100,000 population, after controlling for incidence.

Incidence also exhibited a strong positive association with DALYs (β₂ = 0.00962; 95% CI: 0.00945–0.00979; p < 0.001). This indicates that increases in dengue transmission contribute substantially to overall health loss beyond the effect of mortality alone.

The model demonstrated exceptionally strong explanatory power, with a within-country R² of 0.966, indicating that annual changes in mortality and incidence explained approximately 96.6% of year-to-year variation in DALYs within countries. The overall R² was 0.983, suggesting that the model captured nearly all variation in dengue burden across countries and years.

The intraclass correlation coefficient (ρ = 0.699) indicated that approximately 70% of total DALY variation was attributable to persistent country-specific characteristics, highlighting the importance of structural factors such as health-system capacity, environmental conditions, and long-term epidemiological patterns.

3.3.2 Country-specific regression heterogeneity

Country-specific regression analyses revealed substantial heterogeneity in the relationship between dengue mortality, incidence, and DALY burden. The mortality coefficient (β₁) was positive and statistically significant in all 15 countries (p < 0.001), although its magnitude varied considerably. The largest mortality effects were observed in Indonesia (β₁ = 126.79), the Maldives (β₁ = 79.74), the Philippines (β₁ = 77.16), Cambodia (β₁ = 76.55), and Thailand (β₁ = 74.16), indicating that increases in dengue mortality were associated with substantial increases in overall health burden. Smaller but still significant mortality effects were observed in Bangladesh (β₁ = 32.77), Brazil (β₁ = 38.52), and India (β₁ = 38.90).

The incidence coefficient (β₂) was statistically significant in 13 of the 15 countries and was generally positive, with estimates ranging from 0.0068 to 0.0112. Strong incidence effects were observed in Bangladesh (β₂ = 0.0112), Thailand (β₂ = 0.0099), Pakistan (β₂ = 0.0098), Viet Nam(β₂ = 0.0098), Nicaragua (β₂ = 0.0097), and Peru (β₂ = 0.0097), highlighting the important contribution of transmission intensity and non-fatal morbidity to overall DALY variation. In contrast, the coefficient for incidence rate (β₂) was not statistically significant in Indonesia and Malaysia after adjustment for mortality. India represented a notable exception, exhibiting a significant negative incidence coefficient (β₂ = −0.0622, p < 0.001), suggesting a more complex relationship between incidence, mortality, and disease burden in that setting.

Overall, the country-specific models demonstrated excellent explanatory power, with R² values ranging from 0.928 to 1.000. These findings indicate that mortality (β₁) and incidence (β₂) together explain the vast majority of temporal variation in dengue-related DALYs across endemic countries. Table 5 summarises the country-specific regression coefficients and model fit statistics for the period 1990–2023.

3.3.3 Country-specific temporal patterns

The country-specific trend analyses revealed substantial heterogeneity in the evolution of dengue burden across endemic settings (Figure 5). Indonesia consistently exhibited the highest DALY rates throughout the study period, with values exceeding 300 per 100,000 population despite a gradual decline in both DALYs and death rates over time, indicating persistently intense endemic transmission. India demonstrated a progressive increase in DALY burden from 2010 to 2017, followed by relative stabilisation at approximately 90 DALYs per 100,000 population, while mortality rates remained comparatively stable. The Philippines showed one of the most pronounced declines, with DALY rates decreasing from more than 225 per 100,000 population in 2010 to fewer than 40 per 100,000 population by 2023, accompanied by a parallel reduction in mortality.

Several countries displayed highly volatile epidemic patterns. Nicaragua experienced the most extreme fluctuations, with DALY rates rising sharply during major outbreak years, particularly in 2013, 2019, and 2023, when rates exceeded 470 per 100,000 population. The 2023 resurgence was particularly notable, with DALY rates rising sharply in Bangladesh (26.9), Brazil (92.0), Nicaragua (476.3), and Peru (71.4), while death rates increased more modestly, suggesting that non-fatal morbidity accounted for a substantial proportion of total health loss. In contrast, Thailand and Colombia exhibited sustained long-term declines in both DALY and death rates, consistent with improved disease control and clinical management.

Overall, the graphical analysis (Figure 6) identified three broad epidemiological profiles: countries with persistently high endemic burden, exemplified by Indonesia; countries characterised by intermittent but severe epidemic spikes, such as Nicaragua, Brazil, and Peru; and countries demonstrating gradual reductions in burden over time, including Thailand and Colombia. The divergence observed between DALY and mortality trajectories in several upper-middle-income countries indicates that substantial health losses can occur even when case-fatality rates remain relatively low, underscoring the growing importance of non-fatal disability as a contributor to the total dengue burden.

3.3.4 Income group comparisons

LMICs generally exhibited tighter coupling between mortality and DALY burden, reflecting the greater contribution of premature death to overall health loss. In contrast, UMIC/HIC countries often displayed substantial DALY volatility with relatively stable death rates, implying better case-fatality control but persistent morbidity during outbreaks.

4 Discussion

This study provides an integrated assessment of the economic and epidemiological burden of dengue by combining a systematic review of cost-of-illness studies with an empirical panel analysis of disability-adjusted life years (DALYs), incidence, and mortality trends across 15 endemic countries from 1990 to 2023. Together, these complementary approaches demonstrate that dengue imposes a substantial and persistent burden on health systems, households, and national economies, and that this burden is shaped by marked heterogeneity in transmission intensity, healthcare capacity, and socioeconomic context.

4.1 Principal findings

The systematic review showed that dengue generates considerable direct medical, indirect, and out-of-pocket costs across endemic regions. Hospitalisation-related expenditures constituted the largest component of direct medical costs, while productivity losses and caregiver time accounted for a substantial proportion of the total economic burden. In many low- and middle-income countries (LMICs), out-of-pocket spending was sufficiently high to trigger catastrophic health expenditure among affected households. National estimates indicated that annual dengue-related economic losses reach hundreds of millions to billions of US dollars in highly endemic countries such as India, Brazil, and Indonesia (31, 40, 41, 60). These findings are consistent with prior global assessments, which have estimated dengue to impose an annual worldwide economic burden exceeding US$8–9 billion (6, 46).

The empirical analysis corroborated these findings by demonstrating that both dengue mortality and incidence are major determinants of disease burden. In the fixed-effects panel regression, each additional death per 100,000 population was associated with an increase of approximately 68.6 DALYs per 100,000 population, while incidence exhibited an independent and highly significant positive effect. Together, mortality and incidence explained 96.6% of within-country variation in DALYs and 98.3% of overall variation, indicating that fluctuations in dengue burden are driven predominantly by changes in transmission intensity and mortality rather than random variation. These findings suggest that DALYs closely track both the frequency and severity of dengue outbreaks.

The descriptive and country-specific analyses further revealed pronounced heterogeneity in disease dynamics. Indonesia maintained persistently high DALY rates throughout the study period, reflecting sustained endemic transmission. Nicaragua, Brazil, and Peru experienced abrupt epidemic surges, whereas Thailand and Colombia demonstrated long-term declines. Several upper-middle-income countries displayed substantial increases in DALYs without corresponding increases in mortality, indicating that improved clinical management may reduce fatality while large non-fatal morbidity burdens remain.

4.2 Comparison with previous literature

The systematic review findings align closely with published cost-of-illness studies demonstrating that hospitalisation costs, outpatient visits, diagnostic investigations, and lost productivity are major contributors to the economic burden of dengue (27, 50). Similar to previous reviews, our synthesis identified considerable variation in cost estimates across settings, attributable to differences in healthcare pricing, disease severity, and methodological approaches (79, 80).

The strong relationship observed between incidence, mortality and DALYs is also consistent with the conceptual structure of DALYs, which combine years of life lost due to premature mortality and years lived with disability (81). While mortality primarily contributes through the years-of-life-lost component, incidence reflects the volume of symptomatic infections generating disability and healthcare utilisation. The exceptionally high explanatory power of the model suggests that these two epidemiological indicators capture the majority of variation in dengue burden across endemic countries. This finding aligns with recent Global Burden of Disease analyses demonstrating that both transmission intensity and mortality jointly determine overall dengue burden (82, 83).

The substantial increases observed in 2023 mirror recent reports of record dengue transmission in the Americas and Asia, likely driven by climatic variability, urbanisation, vector expansion, and post-pandemic changes in population immunity and surveillance (2, 3). These trends reinforce the view that dengue is becoming an increasingly important global public health challenge.

4.3 Income-based differences and health equity

A major contribution of this study is the comparison of dengue burden across countries grouped by economic status. Lower-middle-income countries generally exhibited tighter coupling between mortality and DALYs, indicating that deaths contribute disproportionately to total health loss. This pattern suggests that delayed diagnosis, constrained hospital capacity, and limited access to supportive care may amplify the consequences of severe disease.

In contrast, upper-middle- and high-income countries often showed substantial DALY fluctuations despite relatively stable mortality rates. This apparent decoupling suggests that stronger healthcare systems may prevent deaths but cannot eliminate the considerable morbidity associated with large outbreaks. Consequently, wealth modifies the composition of disease burden rather than eliminating it.

These findings underscore important equity considerations. In poorer settings, dengue imposes a dual burden: elevated health losses and substantial household financial strain. Out-of-pocket costs can represent a significant proportion of monthly income, pushing vulnerable families into financial hardship. In wealthier countries, the burden is more likely to manifest through productivity losses, healthcare utilisation, and broader macroeconomic disruption. Thus, the same infection can have fundamentally different consequences depending on socioeconomic context.

4.4 Interpretation of the mortality-incidence–DALY relationship

The fixed-effects panel regression demonstrated that both dengue mortality and incidence were significant predictors of DALY burden across the 15 endemic countries. The estimated coefficient for death rate (β₁ = 68.56; p < 0.001) indicates that, holding incidence constant, each additional dengue death per 100,000 population was associated with an increase of approximately 68.6 DALYs per 100,000 population. Similarly, the incidence coefficient (β₂ = 0.0096; p < 0.001) indicates that increases in dengue transmission contribute independently to overall health loss, even after accounting for mortality.

The inclusion of incidence substantially improved model performance. The within-country R² increased to 0.966, indicating that annual changes in mortality and incidence together explained approximately 96.6% of year-to-year variation in DALYs. Likewise, the overall R² of 0.983 demonstrates excellent explanatory power across countries and over time. These findings suggest that DALY burden is driven not only by fatal outcomes but also by fluctuations in disease transmission and non-fatal morbidity.

The strong contribution of incidence is consistent with the structure of DALYs, which incorporate both Years of Life Lost (YLLs) due to premature mortality and Years Lived with Disability (YLDs) resulting from symptomatic disease. During outbreak periods, large increases in incidence may generate substantial health losses through hospitalisation, outpatient illness, lost productivity, and temporary disability, even when mortality remains relatively low. Consequently, incidence captures an important component of dengue burden that is not reflected by death rates alone.

Country-specific regressions further highlighted substantial heterogeneity in the relative importance of mortality and incidence. Mortality coefficients (β₁) ranged from 32.8 in Bangladesh to 126.8 in Indonesia, indicating considerable variation in the extent to which deaths contribute to overall disease burden. Incidence coefficients (β₂) were positive and statistically significant in most countries, suggesting that increasing transmission generally translated into higher DALY burdens. However, notable exceptions were observed. In Indonesia and the Maldives Malaysia, incidence was not significantly associated with DALYs after controlling for mortality, whereas India demonstrated a significant negative incidence coefficient. These findings may reflect differences in surveillance systems, age distributions, disease severity profiles, healthcare access, or potential collinearity between mortality and incidence trends within individual countries.

The combined evidence from the panel model and country-specific analyses suggests that dengue burden is shaped by both the severity and the scale of transmission. Mortality remains an important contributor to health loss, particularly in settings where severe cases result in premature death, while incidence captures the substantial disability burden associated with large outbreaks. The pronounced increases in dengue burden observed in several countries during 2023, including Bangladesh, Brazil, Nicaragua, and Peru, likely reflect the interaction of rising transmission intensity, climate variability, urban expansion, vector proliferation, and post-pandemic disruptions to public health programmes.

Overall, the results indicate that effective dengue control requires strategies that simultaneously reduce mortality and suppress transmission. Focusing exclusively on case-fatality reduction may lower deaths but will not eliminate the substantial disability burden generated by large outbreaks. Therefore, strengthening surveillance, vector control, vaccination programmes where appropriate, and timely clinical management remains essential for reducing the total health burden of dengue.

4.5 Policy implications

The findings have several implications for dengue control policy. First, investments in early diagnosis, triage, and supportive clinical care are likely to generate substantial reductions in DALYs, particularly in lower-resource settings where mortality contributes heavily to overall burden. Second, because non-fatal morbidity accounts for a large share of total burden, prevention strategies such as integrated vector management, environmental interventions and targeted vaccination remain essential even in countries with low case-fatality rates. However, the role of vaccination in dengue control remains complex and should be interpreted beyond cost-effectiveness alone. The effectiveness of dengue vaccines varies according to prior dengue exposure, age group, transmission intensity, and local epidemiological conditions. In several settings, pre-vaccination serological screening may be required to maximise benefits and minimise potential risks, which increases programme costs and logistical complexity. Furthermore, real-world implementation can be constrained by vaccine availability, coverage, public acceptance, cold-chain requirements, and healthcare infrastructure. Although modelling studies included in this review generally reported favourable cost-effectiveness profiles, actual programme performance may differ from modelled estimates because of uncertainties regarding long-term protection, population uptake, and changing transmission patterns. Consequently, vaccination should be viewed as one component of a broader dengue-control strategy that also includes surveillance, vector control, community engagement, and timely clinical management.

Third, the substantial household costs identified in the systematic review highlight the need for financial protection mechanisms, including universal health coverage, subsidised diagnostics, and paid sick leave policies. Fourth, the pronounced resurgence observed in 2023 underscores the importance of strengthening surveillance systems and epidemic preparedness, particularly in the context of climate change and expanding vector habitats. Finally, cost-effectiveness analyses of emerging vaccines and vector-control interventions should explicitly account for both healthcare savings and reductions in DALYs to capture the full societal value of dengue prevention.

Overall, this indicates that economic development does not eliminate dengue outbreaks, but it appears to alter the composition of disease burden. Higher-income countries tend to convert a larger proportion of severe infections into non-fatal disability, whereas lower-income settings continue to experience a greater mortality component. This distinction has important policy implications. Lower-resource settings should prioritise rapid diagnosis, access to supportive care and hospital surge capacity, while countries with lower case-fatality rates may derive greater benefit from preventive strategies such as vaccination, vector control, and surveillance strengthening. Nevertheless, successful vaccine deployment requires careful consideration of local epidemiology, implementation feasibility, population acceptance, and programme sustainability. Tailoring vaccination strategies to country-specific transmission patterns and health-system capacity is therefore essential to maximise public health impact.

4.6 Strengths of the study

This study has several notable strengths. First, it integrates evidence from a systematic review with empirical econometric analysis, providing a more comprehensive assessment than either approach alone. Second, the use of standardised GBD estimates allowed consistent comparison across multiple countries and years. Third, the fixed-effects panel model controlled for unobserved time-invariant country characteristics, improving internal validity. Fourth, country-specific visualisations and regression analyses provided detailed insights into heterogeneity in dengue burden.

4.7 Limitations

Several limitations should be acknowledged. The systematic review included only English-language publications, which may have excluded relevant studies from non-English-speaking countries. Additionally, the economic synthesis was limited by substantial heterogeneity in costing methodologies across studies. Cost estimates were reported in different currencies, price years, healthcare settings, and analytical perspectives, and many studies did not adjust costs to a common reference year or purchasing power parity (PPP) standard. As a result, direct comparisons of economic burden estimates across countries should be interpreted with caution. Variations in inflation rates, exchange-rate fluctuations, healthcare pricing structures, and resource utilisation patterns may contribute to differences in reported costs that do not necessarily reflect true differences in dengue burden. Furthermore, economic burden estimates derived from modelling studies are sensitive to assumptions regarding disease incidence, healthcare utilisation, productivity losses, and cost inputs. While this review provides a comprehensive overview of the economic impact of dengue, future studies would benefit from standardised costing methodologies and inflation- and PPP-adjusted estimates to improve cross-country comparability and strengthen economic evaluations.

The empirical analysis relied on IHME Global Burden of Disease estimates, which are model-based and subject to uncertainty related to surveillance completeness and input data quality. The revised panel model incorporated both dengue death rates and incidence rates as explanatory variables; however, other potentially important determinants of dengue burden, including healthcare expenditure, climatic variability, urbanisation, vector-control interventions, health-system capacity, and surveillance quality, were not included because of data availability constraints. Consequently, some degree of omitted-variable bias may remain, and the estimated associations should not be interpreted as strictly causal. In addition, although the study employed a balanced panel spanning 15 countries over 34 years, the relatively limited number of countries constrained the inclusion of a larger set of covariates and more complex model specifications.

4.8 Future research

Future studies should incorporate climate indicators, socioeconomic variables, healthcare expenditure, and intervention coverage to better explain temporal variation in dengue burden. Standardisation of costing methods and adjustment to a common currency year would improve comparability across economic studies. Extending the analysis to additional endemic countries and subnational regions could provide a more granular understanding of inequities in dengue burden and resource allocation.

In addition, future econometric work could evaluate the impact of specific interventions, including vaccination programmes, Wolbachia-based vector control, and integrated surveillance systems, on both DALY reduction and economic outcomes. Dynamic forecasting models that incorporate meteorological and demographic variables may also help identify emerging hotspots and support more efficient allocation of public health resources.

5 Conclusion

Dengue represents a substantial and increasingly important global health and economic burden, with significant implications for healthcare systems, affected populations, and broader socioeconomic development. This study demonstrates that dengue imposes a multifaceted burden across endemic countries, encompassing direct healthcare costs, productivity losses, household financial hardship, and considerable health loss measured in disability-adjusted life years (DALYs).

The findings highlight a complex interplay between disease transmission, mortality, morbidity, and economic impact. The empirical analysis demonstrated that both dengue mortality and incidence are significant determinants of DALY burden across endemic countries, indicating that overall health loss is driven not only by premature mortality but also by the substantial contribution of non-fatal disease. While mortality remains a major determinant of overall disease burden, fluctuations in incidence and associated morbidity contributes substantially to temporal and geographic variation in DALY patterns. Although economic development may reduce mortality risk through improved healthcare access and clinical management, it does not eliminate the broader disability and economic consequences of dengue.

The projected and observed increases in dengue burden underscore the urgent need for integrated, context-specific, and cost-effective control strategies. Strengthening surveillance systems, expanding access to preventive interventions, enhancing vector control programmes, and improving financial protection mechanisms are essential to mitigating both current and future impacts of the disease. In particular, effective dengue control requires a combined approach incorporating clinical management, vaccination strategies where available, and sustained vector control efforts.

Despite growing evidence, critical gaps remain in accurately quantifying the true economic burden of dengue, largely due to limited updated data, small sample sizes, methodological heterogeneity, and insufficient consideration of context-specific factors. Future research should prioritise multidisciplinary approaches integrating epidemiological, economic, health-system and environmental perspectives. Greater efforts are needed to generate standardised and inflation-adjusted economic estimates, improve cross-country comparability, and incorporate additional determinants of dengue burden such as climate variability, urbanisation, healthcare expenditure, and vector-control interventions. Such evidence will be essential for informing equitable and cost-effective dengue prevention and control strategies in an increasingly dynamic global epidemiological landscape.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fviro.2026.1878325/full#supplementary-material

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Footnotes

Edited by: Tushar Ranjan, Bihar Agricultural University, India

Reviewed by: Prem Prakash, Meharry Medical College, United States

Aditya Gupta, Agricultural Research Service (USDA), United States