Author Correction: Projecting the future incidence and burden of dengue in Southeast Asia

Dengue Epidemiology and Burden of Disease in Latin America and the Caribbean: A Systematic Review of the Literature and Meta-Analysis

BackgroundDengue is the fastest-spreading vector-borne viral disease worldwide. In Thailand, dengue is endemic and is associated with a high socioeconomic burden. A systematic literature review was conducted to assess and describe the epidemiological and economic burden of dengue in Thailand.MethodsEpidemiological and economic studies published in English and Thai between 2011–2019 and 2009–2019, respectively, were searched in MEDLINE, Embase, and Evidence-Based Medicines reviews databases. Reports published by the National Ministry of Public Health (MoPH) and other grey literature sources were also reviewed. Identified studies were screened according to predefined inclusion and exclusion criteria. Extracted data were descriptively summarised and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.ResultsA total of 155 publications were included in the review (39 journal articles and 116 grey literature). Overall, dengue incidence varied yearly, with the highest rates per 100,000 population in 2013 (dengue fever (DF) 136.6, dengue haemorrhagic fever (DHF) 100.9, dengue shock syndrome (DSS) 3.58) and 2015 (DF 133.1, DHF 87.4, DSS 2.14). Peak incidence coincided with the monsoon season, and annual mortality was highest for DSS, particularly in the age group 15–24-year-olds. The highest dengue incidence rates were reported in children (10–14-year-olds) and young adults (15-24-year-olds), irrespective of dengue case definition. Economic and societal burdens are extensive, with the average cost per case ranging from USD 41 to USD 261, total cost per year estimated at USD 440.3 million, and an average of 7.6 workdays lost for DHF and 6.6 days for DF.ConclusionsThe epidemiological, economic, and societal burden of dengue in Thailand is high and underreported due to gaps in national surveillance data. The use of expansion factors (EFs) is recommended to understand the true incidence of dengue and cost-benefit of control measures. Furthermore, as dengue is often self-managed and underreported, lost school and workdays result in substantial underestimation of the true economic and societal burden of dengue. The implementation of integrated strategies, including vaccination, is critical to reduce the disease burden and may help alleviate health disparities and equity challenges posed by dengue.

BackgroundDengue fever remains the most significant vector-borne disease in Southeast Asia, imposing a substantial burden on public health systems. Global warming and increased international mobility may exacerbate the disease’s prevalence. Furthermore, the unprecedented COVID-19 pandemic may have influenced the epidemiological patterns of dengue.ObjectiveThis study aimed to evaluate epidemiological changes in dengue incidence in Southeast Asia.MethodsWe conducted a retrospective, multicountry ecological study analyzing trends in dengue incidence in 7 Southeast Asian countries from January 2000 to December 2023. Data were extracted from official World Health Organization reports and national health department databases. Countries with data that were incomplete, inconsistent, or not publicly available were excluded from the final analysis. Annual incidence rates were analyzed, and linear trends were calculated to assess long-term patterns.ResultsEpidemiological data from 7 Southeast Asian countries, comprising Thailand, Singapore, Vietnam, Malaysia, the Philippines, Cambodia, and Taiwan, were analyzed across the 24-year study period. A notable nadir in dengue cases was observed coinciding with the COVID-19 pandemic. Significant increasing trends in dengue incidence were identified in Singapore, Vietnam, Malaysia, and the Philippines (slopes: 8.243, 6.513, 8.737, and 8.172; R2 values: 0.14, 0.34, 0.345, and 0.46, respectively, all P<.05).ConclusionsDengue fever continues to pose a significant public health challenge in Southeast Asia. Our analysis demonstrates a substantial increase in dengue cases in several countries over the study period. While a temporary decline was observed during the COVID-19 pandemic, a subsequent resurgence of cases highlights the persistent threat of dengue in the region. These findings underscore the critical need for sustained surveillance and innovative control strategies to mitigate the impact of dengue in Southeast Asia.

In tropical and subtropical regions of eastern and South-eastern Asia, dengue fever (DF) and dengue hemorrhagic fever (DHF) outbreaks occur frequently. Previous studies indicate an association between meteorological variables and dengue incidence using time series analyses. The impacts of meteorological changes can affect dengue outbreak. However, difficulties in collecting detailed time series data in developing countries have led to common use of monthly data in most previous studies. In addition, time series analyses are often limited to one area because of the difficulty in collecting meteorological and dengue incidence data in multiple areas. To gain better understanding, we examined the effects of meteorological factors on dengue incidence in three geographically distinct areas (Ratnapura, Colombo, and Anuradhapura) of Sri Lanka by time series analysis of weekly data. The weekly average maximum temperature and total rainfall and the total number of dengue cases from 2005 to 2011 (7 years) were used as time series data in this study. Subsequently, time series analyses were performed on the basis of ordinary least squares regression analysis followed by the vector autoregressive model (VAR). In conclusion, weekly average maximum temperatures and the weekly total rainfall did not significantly affect dengue incidence in three geographically different areas of Sri Lanka. However, the weekly total rainfall slightly influenced dengue incidence in the cities of Colombo and Anuradhapura.

SummaryBackgroundThe COVID-19 pandemic has resulted in unprecedented disruption to society, which indirectly affects infectious disease dynamics. We aimed to assess the effects of COVID-19-related disruption on dengue, a major expanding acute public health threat, in southeast Asia and Latin America.MethodsWe assembled data on monthly dengue incidence from WHO weekly reports, climatic data from ERA5, and population variables from WorldPop for 23 countries between January, 2014 and December, 2019 and fit a Bayesian regression model to explain and predict seasonal and multi-year dengue cycles. We compared model predictions with reported dengue data January to December, 2020, and assessed if deviations from projected incidence since March, 2020 are associated with specific public health and social measures (from the Oxford Coronavirus Government Response Tracer database) or human movement behaviours (as measured by Google mobility reports).FindingsWe found a consistent, prolonged decline in dengue incidence across many dengue-endemic regions that began in March, 2020 (2·28 million cases in 2020 vs 4·08 million cases in 2019; a 44·1% decrease). We found a strong association between COVID-19-related disruption (as measured independently by public health and social measures and human movement behaviours) and reduced dengue risk, even after taking into account other drivers of dengue cycles including climatic and host immunity (relative risk 0·01–0·17, p<0·01). Measures related to the closure of schools and reduced time spent in non-residential areas had the strongest evidence of association with reduced dengue risk, but high collinearity between covariates made specific attribution challenging. Overall, we estimate that 0·72 million (95% CI 0·12–1·47) fewer dengue cases occurred in 2020 potentially attributable to COVID-19-related disruption.InterpretationIn most countries, COVID-19-related disruption led to historically low dengue incidence in 2020. Continuous monitoring of dengue incidence as COVID-19-related restrictions are relaxed will be important and could give new insights into transmission processes and intervention options.FundingNational Key Research and Development Program of China and the Medical Research Council.

As we enter 2025, dengue fever continues to pose one of the most formidable public health challenges across tropical and subtropical regions including Pakistan, South Asia, Southeast Asia, and parts of the Middle East 1. The epidemiological landscape of dengue has changed considerably over the past decade, driven by climate variability, rapid urbanization, human mobility, and the expanding geographic distribution of Aedes mosquitoes. This year, global surveillance networks are already reporting earlier seasonal onset, higher viral circulation, and a worrisome rise in secondary infections that predispose patients to severe dengue 2. The burden of dengue in 2025 is not merely a continuation of past trends but a reflection of deeply rooted systemic vulnerabilities. Increased rainfall variability, unplanned urban settlements, and inadequate waste management systems have created ideal breeding environments for Aedes aegypti and Aedes albopictus 3. In high-density populations such as those in Lahore, Karachi, Rawalpindi, Dhaka, and Manila, mosquito indices have surpassed previous thresholds within the first quarter of the year. These patterns signal the potential for prolonged transmission, expanded outbreaks, and greater pressure on healthcare services 4.

Dengue presents a formidable and growing global economic and disease burden, with around half the world's population estimated to be at risk of infection. There is wide variation and substantial uncertainty in current estimates of dengue disease burden and, consequently, on economic burden estimates. Dengue disease varies across time, geography and persons affected. Variations in the transmission of four different viruses and interactions among vector density and host's immune status, age, pre-existing medical conditions, all contribute to the disease's complexity. This systematic review aims to identify and examine estimates of dengue disease burden and costs, discuss major sources of uncertainty, and suggest next steps to improve estimates. Economic analysis of dengue is mainly concerned with costs of illness, particularly in estimating total episodes of symptomatic dengue. However, national dengue disease reporting systems show a great diversity in design and implementation, hindering accurate global estimates of dengue episodes and country comparisons. A combination of immediate, short-, and long-term strategies could substantially improve estimates of disease and, consequently, of economic burden of dengue. Suggestions for immediate implementation include refining analysis of currently available data to adjust reported episodes and expanding data collection in empirical studies, such as documenting the number of ambulatory visits before and after hospitalization and including breakdowns by age. Short-term recommendations include merging multiple data sources, such as cohort and surveillance data to evaluate the accuracy of reporting rates (by health sector, treatment, severity, etc.), and using covariates to extrapolate dengue incidence to locations with no or limited reporting. Long-term efforts aim at strengthening capacity to document dengue transmission using serological methods to systematically analyze and relate to epidemiologic data. As promising tools for diagnosis, vaccination, vector control, and treatment are being developed, these recommended steps should improve objective, systematic measures of dengue burden to strengthen health policy decisions.

BackgroundDengue fever is the most widespread infectious disease of humans transmitted by Aedes mosquitoes. It is the leading cause of hospitalization and death in children in the Southeast Asia and western Pacific regions. We analyzed surveillance records from health centers in Vietnam collected between 2001–2012 to determine seasonal trends, develop risk maps and an incidence forecasting model.MethodsThe data were analyzed using a hierarchical spatial Bayesian model that approximates its posterior parameter distributions using the integrated Laplace approximation algorithm (INLA). Meteorological, altitude and land cover (LC) data were used as predictors. The data were grouped by province (n = 63) and month (n = 144) and divided into training (2001–2009) and validation (2010–2012) sets. Thirteen meteorological variables, 7 land cover data and altitude were considered as predictors. Only significant predictors were kept in the final multivariable model. Eleven dummy variables representing month were also fitted to account for seasonal effects. Spatial and temporal effects were accounted for using Besag-York-Mollie (BYM) and autoregressive (1) models. Their levels of significance were analyzed using deviance information criterion (DIC). The model was validated based on the Theil’s coefficient which compared predicted and observed incidence estimated using the validation data. Dengue incidence predictions for 2010–2012 were also used to generate risk maps.ResultsThe mean monthly dengue incidence during the period was 6.94 cases (SD 14.49) per 100,000 people. Analyses on the temporal trends of the disease showed regular seasonal epidemics that were interrupted every 3 years (specifically in July 2004, July 2007 and September 2010) by major fluctuations in incidence. Monthly mean minimum temperature, rainfall, area under urban settlement/build-up areas and altitude were significant in the final model. Minimum temperature and rainfall had non-linear effects and lagging them by two months provided a better fitting model compared to using unlagged variables. Forecasts for the validation period closely mirrored the observed data and accurately captured the troughs and peaks of dengue incidence trajectories. A favorable Theil’s coefficient of inequality of 0.22 was generated.ConclusionsThe study identified temperature, rainfall, altitude and area under urban settlement as being significant predictors of dengue incidence. The statistical model fitted the data well based on Theil’s coefficient of inequality, and risk maps generated from its predictions identified most of the high-risk provinces throughout the country.

The first outbreaks of dengue haemorrhagic fever (DHF) and dengue shock syndrome (DSS) in the Americas followed the introduction of two new dengue serotypes (DEN 1 and DEN 2) into the region in 1977 and 1981 respectively (Gubler and Kuno 1997). The discontinuation of several programmes to control Aedes aegypti in the region in the 1970s and early 1980s also added to the burden of disease attributable to the dengue virus (Kouri et al. 1989; Rico- Hesse 1990). Today DHF and DSS are on the increase throughout the Caribbean region where 700000 cases of classical dengue and 6000 cases of DHF were recorded in 1998 and 1995 respectively (Gubler and Kuno 1997; Pinheiro and Corber 1997; Keating 2001). In Trinidad the continuation of programmes to control Ae. aegypti throughout the 1980s and 1990s resulted in a slower increase in the incidence of classical dengue than observed elsewhere in the Caribbean but a significant increase from 17 cases in 1981 to >2000 in 1997 was still recorded (Keating 2001). DHF was relatively late in reaching Trinidad the first few cases (five) not being seen until 1992 (Teelucksingh et al. 1997) but is also gradually becoming more common - there were 108 cases in 1997 (Chadee 2001). The increases in the incidence of classical dengue and DHF in Trinidad have been caused by numerous factors including the importation of new dengue serotypes (Rico-Hesse 1990) larger vector populations (Chadee 2001) behavioural changes in the vector (Chadee and Martinez 2000) demographic changes (Gubler and Kuno 1997; Chadee and Martinez 2000) and the immunological naivity of most of the human population (Focks and Chadee 1997). It also seems likely that the percentage of cases of dengue who are detected and recorded has increased over the last two decades with under-reporting being more of a problem before the arrival of DHF and the occurrence of severe illness and deaths attributable to the dengue virus. The recent importation of DEN 3 from South-east Asia has increased the risk of DHF outbreaks in the entire Caribbean region including Trinidad (Chadee and Martinez 2000). In the present study the spatial and temporal distributions of classical dengue and DHF in Trinidad in 1998 were investigated so that the epidemiology of these illnesses could be better understood. (excerpt)

Background : Dengue is a mosquito-borne (Ades Agepti) infection which in recent years has become a major public health problem. It is now endemic in more than 100 countries in Africa, America, Eastern Mediterranean, South-East Asia and Western Pacific areas. According to WHO currently approximately 50 million cases of dengue fever occur every year.Objective : To evaluate the current clinical picture, outcome and serology of children suffering from dengue fever admitted in a tertiary care children hospital.Methodology : It is a hospital based prospective observational study carried out among the children having Dengue infection admitted during the period of June to December 2016 in Dhaka Shishu (Children) Hospital. After obtaining informed consent 78 suspected cases of dengue fever patients were enrolled for this study. Patient with any identified specific infection or febrile illness more than 14 days and serologically dengue negative cases were excluded from the study. A detailed history, demographic variables, clinical examination and relevant laboratory investigations were assessed. The data were collected in a predesigned structured questionnaire and were analyzedwith the help of SPSS-21.Result : Out of 78 suspected dengue cases a total of 56 cases were serologically dengue positive. Therefore 22 serologically dengue negative cases were excluded. Most common presenting symptoms were fever (100%) followed by myalgia76.79%, retro-orbital pain73.21%, and conjunctival hemorrhage 55.35%, skin rash 55.35%, with other symptoms constituting the rest. Among the serologically positive dengue cases those who presented with fever for 3 days or of lesser duration, NS1 Ag was positive in 34 cases ( 43.58%) and those who presented with fever for 6 days or more, 14 cases (17.95%) were dengue IgM positive and 8 cases (10.25%) were dengue IgG positive with accompanying low level IgM positive; platelet count 94333/mm3 (±68330), PCV 35 (±3.95) and SGPT 210 U/L(±80).Among 56 dengue positive cases 31(55.4%) were male and 25 (44.6%) were female, The age range was 1 years to 18 years with mean 6.66 ±3.69, predominant age group was 6 years to 12 years. Final diagnosis according to WHO classification were DF 42.68%, DHF-l 32.14%, DHF–ll 16.07%,DHF-lll 8.93%. Outcome of the disease were 89.3% discharge with advice (DA),7.1% discharge on request(DOR), 3.6% left against medical advice(LAMA) and no death.Conclusion : The trend of Dengue infection in Bangladesh has been changing very rapidly. In this study our observation was incidence of dengue was more in male child, peak age group being 6 years to 12 years with most admissions during the month of September. Fever with pain (body ache, retro orbital pain), headache and maculopapular rash, positive NS1Ag and dengue IgM were the main findings found in children with dengue. Most of the dengue cases were DF and DHF-l in our study.Northern International Medical College Journal Vol.9(1) July 2017: 274-277

Dengue is an arboviral disease that clinically ranges from mild febrile illness to life-threatening hemorrhagic fever and shock syndrome. In Bangladesh, dengue incidence rose sharply over the past decade, culminating in the country’s largest outbreak in 2023. There are 321,179 confirmed cases and 1,705 deaths (case fatality rate: 0.53%) and the outbreak has not ended. Effective disease surveillance is essential for early outbreak detection, monitoring, and response. As the dengue burden continues to grow, the capacity of Bangladesh’s surveillance systems is increasingly constrained by challenges related to coordination, coverage, data integration, and insufficient funding. This narrative review synthesizes evidence from 20 peer-reviewed studies published between 2018 and 2024, using thematic analysis and an adapted PRISMA approach to examine existing dengue surveillance systems and identify opportunities to strengthen the capacity in Bangladesh. Two core surveillance modalities were identified, passive surveillance and active surveillance, supplemented by two predictive analytics approaches: forecasting and predictive modeling. Across these modalities, two primary surveillance approaches emerged: hospitalization and patient-record reporting, and community-level monitoring. Early warning systems were also identified within the forecasting and predictive modeling literature. Findings reveal substantial variability in data quality, timeliness, and interoperability across surveillance modalities and analytics tools. Passive and hospital-based reporting offer nationwide coverage but are limited by underreporting and delays, while active surveillance provides earlier signals yet lacks systematic integration with national platforms. Forecasting and predictive models show promise for anticipatory outbreak detection but require more robust validation and standardized data inputs. Overall, this review underscores the need for a more cohesive and integrated dengue surveillance architecture in Bangladesh. By strengthening data sharing, standardizing reporting practices, and adopting digital surveillance tools, public health systems could significantly enhance outbreak detection, preparedness, and response. Such an integrated system may also serve as a model for other dengue-endemic countries.

Introduction: Dengue Hemorrhagic Fever (DHF) is a disease caused by the dengue virus that infects the body. Dengue is a common viral infection in warm tropical climates. The infection is caused by one of four closely related dengue viruses. The disease now plagues many countries and even more than 100 countries within the WHO, including Africa, the Americas, the Eastern Mediterranean, Southeast Asia, and the Western Pacific. The Americas, Southeast Asia, and the Western Pacific are the most severely affected regions, with Asia representing 70% of the global disease burden. The high incidence rate of DHF in various regions of Indonesia is the background by several factors, one of which is the density of the seaters. The aim of this study was to analyze the correlation between population density and larvae free index and Incidence Rate (IR) Dengue Hemorrhagic Fever (DHF) in Blitar Regency in 2013-2017. Methods: The data were analyzed quantitatively using Spearman correlation tests to analyze relationships between variables. Result: The results of the analysis found there was no correlation between dengue fever incidence rate and larvae free index (p = 0.603 r = -0.117), and there was a correlation between the incidence rate of dengue fever and population density (p = 0.002 r = 0.619). Conclusion: High population density is a risk factor for DHF events in Blitar Regency, so there needs to be an anticipation of preventive measures such as the implementation of 3M and counseling of the impact of high population density.

Dengue infection in patients with febrile illness and its relationship to climate factors: A case study in the city of Jeddah, Saudi Arabia, for the period 2010–2014

BACKGROUND AND AIM Limited knowledge is known about the impact of hydrometeorological conditions on dengue incidence in China, and the associated disease burden in the climate-changing future. This study projects the attributable excess risk of dengue in 365 cities across mainland China under climate change scenarios. METHODS The association between Palmer drought severity index (PDSI) and dengue in the historical period (2013-2019) was estimated with a spatiotemporal Bayesian model. We developed a dengue transmission biological model to project the potential risk area of dengue by 2100 under three representative concentration pathways (RCP 2.6, 4.5, and 8.5). The association combined with biological model was then used to project the annual excess risks of dengue related to PDSI by 2100. We further calculated attributable excess risk for dry and wet conditions. RESULTS A total of 93,101 dengue cases were reported between 2013-2019 in mainland China. Dry and wet conditions within three months lag were associated with increased risk of dengue. Locations with potential dengue risk in China will expand in the future. The hydrometeorological changes are projected to substantially affect the risk of dengue in regions with mid-low latitude, especially the coastal areas under high emission scenarios. By 2100, the annual average increased excess risk is expected to range from 7.49% (95% empirical CI: 4.55-16.64) in northwest to 71.89% (55.66-123.62) in south under RCP 8.5. Moderate dry is predicted to have the greatest impact on dengue risk across all regions. CONCLUSIONS Hydrometeorological conditions are predicted to increase the dengue risk in the future in the south, east, and central areas of mainland China in disproportional patterns. Our findings have implications for the preparation of public health interventions to minimize the health hazards of non-optimal hydrometeorological conditions under climate change context. KEYWORDS Climate change; Dengue; Hydrometeorology; Palmer drought severity index

Ovarian cancer (OC) is a growing public health challenge in Asia, with rising incidence and regional disparities. Using the Global Burden of Disease (GBD) 2021 dataset, this study assessed temporal trends, spatial patterns, and determinants of OC burden in Asia from 1990 to 2021, with projections to 2036. Data were extracted from GBD 2021 for all Asian regions. Three indicators were analyzed: age-standardized incidence rate (ASIR), mortality rate (ASMR), and disability-adjusted life years rate (ASDR). Trends were evaluated using estimated annual percentage change (EAPC) and Joinpoint regression. Decomposition analysis examined contributions of population aging, growth, and epidemiological shifts. Age-period-cohort (APC) analysis was performed to disentangle the effects of age, period, and cohort on OC incidence. Future burden (2022-2036) was projected with an autoregressive integrated moving average (ARIMA) model. From 1990 to 2021, OC burden increased markedly. Southeast, South, and Central Asia had the greatest rises in ASIR, ASMR, and ASDR, while East Asia and high-income Asia Pacific showed stable or declining trends, likely due to healthcare advances and early detection. Higher sociodemographic index (SDI) correlated with greater incidence and mortality. Decomposition revealed aging as the main driver in East Asia and high-income Asia Pacific, while population growth dominated in South Asia. APC analysis highlighted age as the primary risk factor, with a rising period effect and a declining cohort effect. ARIMA projections (2022-2036) show steady ASIR growth and U-shaped trajectories (initial decline then rise) for ASMR and ASDR. The increasing OC burden in Southeast, South, and Central Asia underscores the urgent need for region-specific strategies. Interventions focusing on early diagnosis, equitable healthcare, and addressing demographic and epidemiological drivers are essential to mitigate the projected rise by 2036.