Global burden of dengue from 1990 to 2021: a systematic analysis from the Global Burden of Disease study 2021

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Global warming, urbanization, and increased international travel have fueled the global spread of dengue. We analyzed the 2021 Global Burden of Disease (GBD) dataset to assess dengue fever's incidence, prevalence, mortality, and Disability-Adjusted Life Years (DALYs) from 1990 to 2021 across 204 countries. Data were stratified by age, sex, and socio-demographic index (SDI) using age-standardized rates, and time-trend analysis was conducted with general linear regression. Correlations between SDI and disease burden metrics were evaluated using Spearman’s rank correlation. From 1990 to 2021, the global burden of dengue increased, with ASIR rising by 0.56% (95% UI: 0.23–2.38), ASPR by 0.56% (95% UI: 0.23–2.36), and ASDR by 0.28% (95% UI: -0.38–0.92). In 2021, there were an estimated 58.96 million cases. Regionally, Tropical Latin America reported the highest ASIR (5,774.82; 95% UI: 1,774.731–11,624.76). At the national level, variations in the change of the ASIR were observed across countries from 1990 to 2021 with Tonga reported the highest ASIR in 2021. Males exhibited a higher ASDR compared to females, particularly in the 0–14 age group. Dengue burden trends varied across SDI regions, with high-middle and middle SDI regions showing increased ASIR, while low SDI regions experienced a decline. The analysis highlights the increase in dengue burden globally, with demographic and geographic disparities. The findings underscore the need for targeted prevention, control, and treatment strategies to mitigate the growing burden of dengue fever worldwide. Dengue fever Global Burden of Disease Incidence Mortality Disability-adjusted life years (DALYs) Socio-demographic Index (SDI) Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Dengue fever is an acute infectious disease caused by dengue virus, which is primarily transmitted by Aedes aegypti and Aedes albopictus mosquitoes 1 . In recent years, with global warming 2 , accelerated urbanization 3 , and increased international travel 4 , the incidence of dengue fever has shown an upward trend worldwide. According to the World Health Organization, there are approximately 50 to 100 million cases of dengue fever globally each year 5 . However, some studies suggest that the actual number of infections, including asymptomatic cases, may be much higher 6 . Dengue is a significant contributor to the global burden of infectious diseases, with far-reaching implications for public health, healthcare systems, and the economy. Dengue fever primarily occurs in tropical and subtropical regions, such as Southeast Asia, South Asia, Africa, and parts of Latin America 7 8 . In recent years, dengue fever outbreaks in countries such as Brazil 9 , Argentina 10 , and Paraguay 11 in South America have been particularly severe, with record-high numbers of reported cases 12 . Additionally, the incidence of dengue fever has also increased significantly in Southeast Asian countries like Cambodia, Laos, Malaysia, and Singapore 13 – 15 . Notably, the dengue fever epidemic is expanding northward, posing a risk of transmission to temperate regions, including Europe 16 17 . Some European countries, such as France 18 and Italy 16 , have already reported locally transmitted dengue fever cases, indicating the global spread of the dengue virus. As global warming intensifies, the habitats and activity ranges of the transmission vectors of dengue fever, Aedes aegypti and Aedes albopictus , are also expanding 19 20 . The proliferation of these vectors not only increases the risk of dengue virus transmission but also exposes non-epidemic areas to the risk of dengue fever transmission 21 22 . Several studies have provided valuable insights into the global burden of dengue. Some have analyzed dengue in conjunction with other vector-borne diseases 23 24 , while others have focused exclusively on specific regions or countries. For instance, Martha Anker reported on gender differences in the number of dengue fever cases reported in six Asian countries 25 . Another study examined dengue fever in Brazil from 2000 to 2015, reporting a 232.7% increase in cases across its 27 federated units 26 . The most recent comprehensive analyses of the dengue disease burden date back to 2017 (10.5 million cases) 23 and 2019 (56.7 million cases) 27 . However, there are disparities among these studies, and there are no updated estimates on the burden of dengue. Accurately tracking the evolving patterns and trends in the global and regional prevalence and burden of dengue fever is crucial for developing targeted prevention and control strategies, optimizing resource allocation, and enhancing global health outcomes. Consequently, we delved into the Global Burden of Disease (GBD) 2021 dataset to analyze the global, regional, and national incidence of dengue fever, along with mortality rates and disability-adjusted life-years (DALYs), from 1990 to 2021. This comprehensive examination was conducted by age, sex, and socio-demographic index (SDI), providing age-standardized rates and counts. The updated information on dengue fever serves as a valuable resource for policymakers and healthcare professionals, enabling informed decision-making in crafting control and prevention strategies and implementing effective policies to mitigate the impact of this infectious disease. Methods Selection of Data Source and Study Design The GBD study provides annual estimates for health loss caused by diseases and injuries, employing a comprehensive methodology to evaluate global health metrics, including incidence, prevalence, mortality, and Disability-Adjusted Life Years (DALYs). The analysis focused on dengue fever, examining temporal trends from 1990 to 2021. We included data from the general population across all age groups, genders, and socio-demographic index (SDI) regions. Disease Burden Metrics In this investigation, we compiled annual data metrics to evaluate the global and regional burden of dengue amongst general populations. Metrics entailed the enumeration of incident and prevalent cases, mortality counts, Years of Life Lost (YLLs) due to premature mortality, Years Lived with Disability (YLDs) accounting for non-fatal health outcomes, and Disability-Adjusted Life Years (DALYs), which amalgamate the measures into a single quantifier of overall disease burden. Stratification was applied by age groups to capture the nuances in disease impact. Temporally, the data spanned from 1990 to 2021, enabling a longitudinal perspective. Geographically, the analysis was partitioned into seven super-regions and 21 sub-regions, while individual country data (encompassing 204 nations) were further stratified into quintiles based on the SDI, a composite indicator that reflects income levels, educational attainment, and fertility rates, to assess and compare disease burden dynamics across varying socio-economic contexts. Patient and Public Involvement The research’s design, methodology, reporting and dissemination plans did not involve input from participants or the general public. However, we would like to thank all the participants for their willingness and cooperation in taking part in this study. We would like to express our sincere gratitude to the Global Burden of Disease (GBD) database for providing invaluable data and resources that have significantly contributed to our research. Statistical Analysis In our systematic analysis, epidemiological metrics for dengue incidence, prevalence, mortality, and DALYs were extracted from the GBD database, with age-standardization per 100,000 population using the GBD study's global reference. We conducted a time-trend analysis employing general linear regression to evaluate annual shifts in age-standardized DALY rates from 1990 to 2021, providing a longitudinal view of the disease's impact on the populations. Correlations between age-standardized DALY rates and the SDI were assessed using Spearman's rank correlation, with a significance threshold set at p < 0.05. These rigorous statistical methodologies ensure a comprehensive depiction of the global burden of dengue, enabling stakeholders to identify and prioritize public health interventions for children and adolescents. All analyses were conducted using R version 3.6.1 (R Foundation for Statistical Computing, Vienna, Austria). Results Global overview In 2021, an estimated 58,964,185 incident cases of dengue were reported globally (95% UI: 15,473,439–106,885,036), with an ASIR of 752.04 per 100,000 population (95% UI: 196.33–1363.35). Between 1990 and 2021, the incidence rate increased by 0.56% (95% UI: 0.23–0.38). The number of prevalent cases in 2021 was 3,517,384 (95% UI: 928,244–6,430,039), corresponding to an ASPR of 44.86 per 100,000 population (95% UI: 11.77–82.13). This represents an increase of 0.56 per 100,000 population (95% UI: 0.23 to–2.36) from 1990 to 2021. The global ASDR for dengue rose from 21.63 per 100,000 population (95% UI: 15.09–26.92) in 1990 to 27.76 per 100,000 population (95% UI: 14.21–41.65) in 2021. This change represents a percentage increase of 0.28 (95% UI: -0.38–0.92) compared to 1990. (Table 1, Supplementary File 1, Table S1 ). Regional level On a regional scale, Tropical Latin America reported the highest ASIR in 2021, with 5,775 cases per 100,000 population (95% UI: 1,775–11,625) and over 13.04 million incident cases (95% UI: 3,996,126–26,305,622). South Asia ranked second, with an ASIR of 1,727 per 100,000 (95% UI: 102–3,636) and 31.81 million cases (95% UI: 3,996,126–26,305,622). This is consistent with the ASIR and ASPR ranking in 1990 (Supplementary File 2, Fig. S1 ). The highest ASPR was observed in Tropical Latin America (343.77, 95% UI: 107.963–700.31), followed by South Asia (103.22, 95% UI: 5.90–220.59), and Central Latin America (67.95, 95% UI: 40.54–97.63) (Table 1, Supplementary File 3, Fig. S2 ). In terms of ASDR, Southeast Asia, Tropical Latin America, and South Asia recorded higher ASDRs than other countries, with ASDRs of 147.04 (95% UI: 95.32–200.97), 63.76 (95% UI: 22.43–136.04), and 53.46 (95% UI: 19.54–91.91) in 2021, respectively. The lowest ASDRs were observed in high-income countries in Europe and North America (Fig. 1 , Table 1). National level At the national level, variations in the change of the ASIR were observed across countries from 1990 to 2021. Tonga reported the highest ASIR in 2021, with 14,363 cases per 100,000 population (95% UI: 136–50,917). Other countries with significant dengue incidence included the Republic of Seychelles, Union of the Comoros, Republic of the Marshall Islands, Republic of Singapore, and Republic of Cabo Verde. By contrast, Comoros reported the highest ASIR in 1990 (11,154.07, 95% UI: 1,653.69–44,214.37), followed by Djibouti, Marshall Islands, and Singapore. In 2012, Tonga, also had the highest ASPR of 854.37 (95% UI: 7.35–3,178.87), followed by Seychelles (735.66, 95% UI: 126.68–3,086.71) and Comoros (707.55, 95% UI: 0.13–4,795.15), respectively. In terms of ASDR, Indonesia experienced the highest dengue burden in 2021, with 279.79 DALYs per 100,000 population (95% UI: 170.92–404.43). Tonga ranked second with 168.65 per 100,000 (95% UI: 14.61–563.73), followed by the Philippines with 126.60 (95% UI: 95.17–164.20). Variations in the change of the ASPR and ASDR were also observed across countries from 1990 to 2021 as detailed in Fig. 1 , Supplementary File 4, Table S2 . Temporal Trends by SDI Our analysis revealed a global increase in the ASIR, with similar trends observed in high-middle and middle SDI regions. In the high-middle SDI region, the ASIR rose from 98.43 (95% UI: 12.22–263.08) per 100,000 population in 1990 to 215.66 (95% UI: 91.61–372.30) per 100,000 population in 2021. Likewise, in the middle SDI region, the ASIR increased from 782.97 (95% UI: 51.81–1,725.40) per 100,000 population to 1,269.27 (95% UI: 437.36–2,268.00) per 100,000 population (Supplementary File 5, Table S3 ). In contrast, the low SDI region experienced a decrease in ASIR, from 431.07 (95% UI: 242.88–648.05) per 100,000 population in 1990 to 368.03 (95% UI: 11.69–884.71) per 100,000 population in 2021. The ASPR increased across all regions, except in low-SDI regions, where a decline was observed from 25.64 (95% UI: 14.03–39.36) per 100,000 population in 1990 to 21.87 (95% UI: 0.68–54.56) per 100,000 population in 2021 (Supplementary File 6, Table S4 ). Similarly, the ASDR of dengue fever exhibited comparable patterns in the high-middle, middle, and low-middle SDI regions. In both the high-SDI and low-SDI regions, the ASDR fluctuated over time. Notably, the high-SDI region experienced a peak of 1.03 (95% UI: 0.22–2.55) per 100,000 population per 100,000 in 2005. The low-SDI region, by contrast, showed relatively stable trends, fluctuating between 11.84 (95% UI: 8.11–16.08) per 100,000 population and 12.78 (95% UI: 4.86–22.81) per 100,000 population from 1990 to 2021 (Fig. 2 ). Age and sex patterns Our comprehensive global analysis of dengue burden from 1990 to 2021 revealed distinct variations across different age groups, highlighting the dynamic nature of dengue transmission across various demographics (Fig. 3 ). Overall, both incidence and prevalence rates across all age groups showed an upward trend from 1990 to 2021, particularly before 2015. The DALYs in the 0–14 age group were generally higher than in other groups but exhibited fluctuations over time. The 15–49 age group had the highest number of incident and prevalent cases (Fig. 3 A), though the 0–14 age group demonstrated higher incidence and prevalence rates (Fig. 3 B). Similarly, the ASDR for the 0–14 age group was higher than in other groups. However, a significant decline in ASIR, ASPR, and ASDR across all age groups occurred after 2015 (Fig. 3 B). From 1990 to 2021, ASIR and ASPR were slightly higher among females compared to males. However, males exhibited a higher ASDR, as shown in Supplementary File 7, Fig. S3 . In 2021, there were 31.6 million dengue cases among females and 27.3 million among males. Among females aged 15–49, the highest number of cases was recorded at 16,530,266 (95% UI: 4,357,395 − 29,724,055), with an incidence rate of 848.20 per 100,000 population (95% UI: 223.59–1,525.21), closely followed the incidence rate in the 0–14 age group at 849.66 per 100,000 (95% UI: 211.05–1,552.60) (Fig. 4 A). Males aged 0–14 recorded 7,607,459 cases, with an incidence rate of 732.78 per 100,000 (95% UI: 758.90–1,568.64), reflecting a high infection level. In contrast, males aged 50 and above had the fewest cases and the lowest incidence rates (Supplementary File 8, Table S5 ). Similarly, females aged 15–49 had the highest number of prevalent cases, with 986,187 cases (95% UI: 252,58–1,788,33) and a prevalence rate of 50.60 per 100,000 (95% UI: 12.96–91.76) (Fig. 4 B). Females aged 0–14 had the sixth-highest number of cases, totaling 493,502 (95% UI: 120,397–904,087), yet they exhibited the highest prevalence rate at 50.68 per 100,000 (95% UI: 12.36–92.85) (Supplementary File 9, Table S6 ). By comparison, males aged 50 and above recorded the lowest incidence and prevalence rates. Regarding ASDR, males across all age groups had higher rates than females, particularly in the 0–14 age group, where DALYs were significantly higher at 49.75 per 100,000 (95% UI: 25.88–71.56) (Fig. 4 C). Relationship between DALYs and SDI We conducted a regional and national-level analysis of the ASIR, ASPR, and ASDR of dengue across 204 countries in relation to the SDI over time. The results revealed a non-linear association between ASIR and SDI at the regional level. Interestingly, high dengue incidence was not restricted to the least developed regions or countries. Nations such as Tonga, Seychelles, Comoros, the Marshall Islands, and Singapore exhibited significantly higher ASIR levels than expected. Conversely, countries like the United States and South Sudan demonstrated ASIR levels that were notably lower than anticipated (Fig. 5 , Supplementary File 10, Fig. S4 ). A similar non-linear association was observed between ASPR, ASDR, and SDI. There was no negative correlation between ASPR or ASDR and SDI across all regions. Countries such as Tonga, the Philippines, Comoros, and Seychelles exhibited ASDR levels that were considerably higher than expected. In contrast, countries including Spain and Greece exhibited lower age-standardized DALY rates than predicted (Fig. 5 , Supplementary File 10, Fig. S4 ). Discussion Dengue fever, a mosquito-borne viral disease, continues to pose a significant global health burden, as evidenced by the substantial increase in incident and prevalent cases reported globally from 1990 to 2021. Our comprehensive analysis, utilizing robust epidemiological data and statistical modeling, reveals several key insights into the dynamics and patterns of dengue burden across different regions, countries, age groups, and sexes, underscoring the need for targeted interventions and global cooperation to address the growing threat of dengue fever. Globally, the estimated incident cases of dengue increased from 1990 to 2021, with a notable rise in the ASIR and ASPR. Our study shows consistency with the previous global burden of disease study by Yang et al., which reported an increase from 30.7 million cases in 1990 to 56.9 million cases in 2019 across all age groups 8 . This trend is particularly concerning, as it suggests a potential intensification of dengue transmission worldwide. The observed increase in the ASDR further underscores the severity of the disease burden, particularly in light of the modest change in percentage. Dengue primarily impacts tropical and subtropical countries. A previous systematic review on dengue global epidemiology reported the predominant proportion of dengue patients, accounting for 72.4% of the total, were reported from the Western Pacific region, closely followed by the American region with 19.4% of cases, and the Southeast Asia Region contributing 4.8% of all reported dengue cases 28 . In our study, Tropical Latin America and South Asia emerged as regions with the highest ASIR and ASPR. This finding is likely attributed to the consistently warm temperatures these regions experience throughout the year, creating a conducive environment for the proliferation of mosquito vectors, which are the primary transmitters of the dengue virus. Moreover, many of these regions are characterized by rapid population growth and unplanned urbanization, all of which contribute to an increased risk of mosquito breeding and dengue transmission. Furthermore, the increasing global incidence of dengue has been associated with factors such as global warming and rapid urbanization 23 29 . The distinct age and sex patterns observed in our analysis provide valuable insights into the epidemiology of dengue. The 15–49 age group had the highest number of incident and prevalent cases, while the 0–14 age group exhibited higher incidence and prevalence rates. This aligns with previous studies, which have reported that dengue is responsible for significant morbidity and mortality in children residing in tropical and subtropical regions 30 . This finding underscores the vulnerability of young adults and children to dengue and highlights the importance of targeted interventions to protect these populations. The heightened vulnerability of children to dengue infection can be attributed to their immature immune systems and their tendency to play outdoors, where protection against Aedes mosquitoes is limited. Additionally, the higher ASDR among males across all age groups, particularly in the 0–14 age group, emphasizes the need for gender-specific prevention and treatment strategies. A study conducted by Anker et al. supported our findings, demonstrating a higher predilection for dengue in males in across six culturally and economically diverse countries 25 . Biological and gender-related factors can change over the human lifespan and can differ across countries. Therefore, further research is required to identify the causes of these sex-specific differences. In general, high economic levels are often associated with lower incidence rates of infectious diseases 31 – 33 , but this relationship is influenced by various factors, including social, environmental, and policy aspects 34 35 . Our analysis highlights temporal variations in dengue burden across different SDI regions. Notably, the burden of dengue is not confined to either developed or less developed countries. While high-middle and middle SDI regions experienced an increase in ASIR, the low SDI region saw a decline. These observations align with the findings from the GBD 2017 and a study conducted by Tian 36 . This discrepancy may be attributed to differences in healthcare infrastructure, disease surveillance, and control measures across regions. However, the consistent increase in ASPR and ASDR across all SDI regions, except low-SDI, underscores the persistence of dengue as a significant public health concern regardless of socio-economic status. Therefore, understanding the multifaceted and interactive reasons for the varying burden of dengue across different regions is crucial for developing effective strategies to control and prevent the disease. While this study presents valuable insights and abundant information on the GBD for dengue, it holds significant importance in guiding dengue prevention and control efforts, fostering international cooperation and exchange, and enhancing global health standards. It is noteworthy, however, that several limitations persist in our study. Firstly, there are often notable discrepancies between the GBD estimates of dengue burden and the actual number of reported cases 37 38 . This may stem from various factors, such as differences in monitoring systems, the sophistication of reporting mechanisms, and the diversity of dengue symptoms. Therefore, when interpreting GBD data, it is crucial to acknowledge these limitations and conduct comprehensive analyses that integrate actual conditions. Second, the GBD database stands as a crucial resource in the public health domain, consistently endeavoring to enhance data quality and timeliness to furnish more precise evidence for global health policy formulation and intervention measures. Nevertheless, the GBD data exhibits a lag, primarily due to the challenges in data collection, the complexity of processing, and the periodic nature of its updates and releases. The diversity and quality discrepancies of global data, the intricate process of model selection and validation, coupled with the rigorous review process during regular research cycles, collectively extend the timeline from data collection to final publication. Additionally, funding limitations, resource shortages, and even political and social factors can potentially hinder the timely circulation of data. We have not conducted a comparative analysis of the latest dengue disease data, such as from 2022 and 2023, with the prediction results from GBD. Third, existing surveillance systems are not sensitive, and mild febrile illnesses are less likely to be diagnosed and reported. Data about dengue were only available in limited regions and countries, and we have no data from much of Central Europe, Eastern Europe, and Western Europe. Conclusion In summary, this analysis highlights increase in incident cases, prevalence, and DALYs rates globally, with demographic and geographic disparities. Furthermore, the non-linear relationship between dengue burden and development level highlights the complexity of the disease. Our findings contribute to the academic community by providing a nuanced understanding of the global dengue landscape and its evolving trends. Practically, they inform policy-makers and healthcare providers on the importance of targeted prevention, control, and treatment strategies to mitigate the growing burden of dengue fever worldwide. Declarations Ethics approval and consent to participate Not applicable. Consent for publication All participants consented to have their data published. Availability of data and materials Data used in the analyses can be obtained from the Global Health Data Exchange Global Burden of Disease Results Tool(https://ghdx.healthdata.org/gbd-results-tool). Competing interests We declare no competing interests. Funding This study was supported by the National Key Research and Development Program of China (No. 2021YFC2300800, 2021YFC2300804) and the International Joint Laboratory on Tropical Diseases Control in Greater Mekong Subregion (No. 21410750200). The funders had no role in study design, data collection, analysis and interpretation, or in writing the report and the decision to submit the article for publication. Authors' Contributors The study was designed and the manuscript was drafted by FXY and ZJX. They also provided critical intellectual input and revised the manuscript. 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Frontiers in microbiology 2024;15:1458166. doi: 10.3389/fmicb.2024.1458166 [published Online First: 2024/08/31] Anker M, Arima Y. Male-female differences in the number of reported incident dengue fever cases in six Asian countries. Western Pacific surveillance and response journal : WPSAR 2011;2(2):17-23. doi: 10.5365/wpsar.2011.2.1.002 [published Online First: 2011/04/01] Araújo VEM, Bezerra JMT, Amâncio FF, et al. Increase in the burden of dengue in Brazil and federated units, 2000 and 2015: analysis of the Global Burden of Disease Study 2015. Revista brasileira de epidemiologia = Brazilian journal of epidemiology 2017;20Suppl 01(Suppl 01):205-16. doi: 10.1590/1980-5497201700050017 [published Online First: 2017/06/29] Ilic I, Ilic M. Global Patterns of Trends in Incidence and Mortality of Dengue, 1990-2019: An Analysis Based on the Global Burden of Disease Study. 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Infectious Diseases, Trade, and Economic Growth: a Panel Analysis of Developed and Developing Countries. 2022;13(3):2547-83. doi: 10.1007/s13132-021-00811-z Kim D. Exploratory study on the spatial relationship between emerging infectious diseases and urban characteristics: Cases from Korea. Sustainable cities and society 2021;66:102672. doi: 10.1016/j.scs.2020.102672 [published Online First: 2021/02/02] Whelan PI, Kurucz N, Pettit WJ, et al. Elimination of Aedes aegypti in northern Australia, 2004-2006. Journal of vector ecology : journal of the Society for Vector Ecology 2020;45(1):118-26. doi: 10.1111/jvec.12379 [published Online First: 2020/06/04] Trewin BJ, Darbro JM, Jansen CC, et al. The elimination of the dengue vector, Aedes aegypti, from Brisbane, Australia: The role of surveillance, larval habitat removal and policy. PLoS neglected tropical diseases 2017;11(8):e0005848. doi: 10.1371/journal.pntd.0005848 [published Online First: 2017/08/29] Tian N, Zheng JX, Guo ZY, et al. Dengue Incidence Trends and Its Burden in Major Endemic Regions from 1990 to 2019. Tropical medicine and infectious disease 2022;7(8) doi: 10.3390/tropicalmed7080180 [published Online First: 2022/08/26] Lee SY, Shih HI, King CC, et al. Substantial discrepancies in dengue case estimates between the Global Burden of Disease Study and Taiwan Centers for Disease Control. Journal of travel medicine 2024;31(2) doi: 10.1093/jtm/taae009 [published Online First: 2024/01/18] Lee SY, Shih HI, Lo WC, et al. Discrepancies in dengue burden estimates: a comparative analysis of reported cases and global burden of disease study, 2010-2019. Journal of travel medicine 2024;31(4) doi: 10.1093/jtm/taae069 [published Online First: 2024/05/02] Table Table 1 is available in the Supplementary Files section. Supplementary Files Table1.xlsx Table 1 Global burden of dengue at global and regional level, 1990-2021 Supplementaryfile1TableS1.xlsx Supplementary File Supplementary file 1: Table S1 Global and regional burden of dengue: incidence, prevalence, and DALYs from 1990 to 2021 Supplementaryfile2Fig.S1Incidence5.pdf Supplementary file 2: Fig. S1 Age-standardized incidence rates by geographical regions Supplementaryfile3Fig.S2Prevalence2.pdf Supplementary file 3: Fig. S2 Age-standardized prevalence rates by geographical regions Supplementaryfile4TableS2.csv Supplementary file 4: Table S2 Age-standardized DALYs rate of Dengue per 100 000 population in 2021 by country. supplementaryfile5tableS3Incidence.csv Supplementary file 5: Table S3 Age-standardized incidence rates of Dengue per 100 000 population by sociodemographic index (five categories; countries with a high, high-middle, middle, low-middle, or low sociodemographic index) from 1990 to 2019. supplementaryfile6tableS4prevalence2.csv Supplementary file 6: Table S4 Age-standardized prevalence rates of Dengue per 100 000 population by sociodemographic index (five categories; countries with a high, high-middle, middle, low-middle, or low sociodemographic index) from 1990 to 2019. Supplementaryfile7Fig.S3.pdf Supplementary file 7: Fig. S3 Temporal trends of incidence, prevalence, and DALYs (both males and females separately) from 1990 to 2020 Supplementaryfile8tableS5Incidence.csv Supplementary file 8: Table S5 Age-standardized incidence rates of Dengue per 100 000 population by age and sex, 2021. Supplementaryfile9tableS6Prevalence.csv Supplementary file 9: Table S6 Age-standardized prevalence rates of Dengue per 100 000 population by age and sex, 2021. SupplementaryFile10Fig.S4.pdf Supplementary file 10: Fig. S4 Relationship between SDI and Age-Standardized Rates across countries, colored by their respective Socio-demographic Index (SDI). Cite Share Download PDF Status: Published Journal Publication published 16 Oct, 2025 Read the published version in Infectious Diseases of Poverty → Version 1 posted Editorial decision: Major revision 13 May, 2025 Reviewers agreed at journal 19 Apr, 2025 Reviewers invited by journal 16 Apr, 2025 Editor assigned by journal 16 Apr, 2025 First submitted to journal 15 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6434758","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":444116198,"identity":"e807dc41-51f3-47ca-b15d-dfccccc97ba0","order_by":0,"name":"Jinxin Zheng","email":"","orcid":"","institution":"Shanghai Jiao Tong University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jinxin","middleName":"","lastName":"Zheng","suffix":""},{"id":444116199,"identity":"cf46c1dd-529a-4faa-8385-d993a3f1b6c7","order_by":1,"name":"Hai 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03:31:29","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":66391,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal Trends of dengue burden by age-standardized DALYs rates (ASDR), both sexes combined, 1990-2021.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/eed60bd726efdd17172ef8e4.jpg"},{"id":82122988,"identity":"6455f66d-334a-4f04-898d-99c1e6f4e0db","added_by":"auto","created_at":"2025-05-07 03:31:30","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":182968,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in disease incidence, prevalence, disability-adjusted life years (dalys), and age-specific rates per 10 0,000 population across age groups and time periods: 1990-2020. A: the trends of dengue burden indicated by incident cases, prevalent cases and DALYs, B: the trends of dengue burden indicated by age-standardized incidence rates (ASIR), prevalence rate (ASPR) and DALYs rates (ASDR)\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/94aab869b7dff5599b3cee51.jpg"},{"id":82121383,"identity":"255ffcec-ede4-47a3-8237-8cf5db26c7b6","added_by":"auto","created_at":"2025-05-07 03:23:30","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":110237,"visible":true,"origin":"","legend":"\u003cp\u003eThe dengue burden for male and female attributed to dengue in 2019. A: the dengue burden for male and female indicated by incident cases and age-standardized incidence rates (ASIR), B: the dengue burden for male and female indicated by prevalent cases and prevalence age-standardized rate (ASPR)，C: the dengue burden for male and female indicated by DALY and age-standardized rate DALYs rates (ASDR)\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/f0aae0755292b46a3832ea7f.jpg"},{"id":82121338,"identity":"e30125c4-4b45-417a-ad2c-ec5ddfae2e56","added_by":"auto","created_at":"2025-05-07 03:23:28","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":144183,"visible":true,"origin":"","legend":"\u003cp\u003eThe association between SDI and age-standardized DALYs rates (ASDR) of dengue by 21 GBD regions and 204 countries and territories, both sexes combined, 2021.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/c020ba39222074c6e3eb0b9b.jpg"},{"id":93956033,"identity":"404b45bb-8d07-4eb6-b704-337e3a2c19bc","added_by":"auto","created_at":"2025-10-20 16:09:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1261315,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/fa07b566-034f-4bf3-b227-f614751b4fc1.pdf"},{"id":82121400,"identity":"32eff53d-fa81-40c0-9925-a9c543ffb907","added_by":"auto","created_at":"2025-05-07 03:23:30","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13900,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1 Global burden of dengue at global and regional level, 1990-2021\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/d89987557daaa6c21b3a1ee5.xlsx"},{"id":82121384,"identity":"6e5656ad-460a-4188-b7d3-fc291e1679b0","added_by":"auto","created_at":"2025-05-07 03:23:30","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":19742,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary File\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary file 1: Table S1 Global and regional burden of dengue: incidence, prevalence, and DALYs from 1990 to 2021\u003c/p\u003e","description":"","filename":"Supplementaryfile1TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/8b61718135b8be082980a088.xlsx"},{"id":82121364,"identity":"b4168925-4c4c-4474-9cfa-b07e01357b4f","added_by":"auto","created_at":"2025-05-07 03:23:28","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":3928783,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary file 2: Fig. S1 Age-standardized incidence rates by geographical regions\u003c/p\u003e","description":"","filename":"Supplementaryfile2Fig.S1Incidence5.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/be080b2732d16ab25b9dc872.pdf"},{"id":82121382,"identity":"df64d998-e2bd-4cf2-9bd9-7db26c5ea2f3","added_by":"auto","created_at":"2025-05-07 03:23:29","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":3785545,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary file 3: Fig. S2 Age-standardized prevalence rates by geographical regions\u003c/p\u003e","description":"","filename":"Supplementaryfile3Fig.S2Prevalence2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/9e9dd21deaf03e3def24f130.pdf"},{"id":82121409,"identity":"1b75d24a-f540-4de0-9612-fe28a3b1eb89","added_by":"auto","created_at":"2025-05-07 03:23:31","extension":"csv","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":9695,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary file 4: Table S2 Age-standardized DALYs rate of Dengue per 100 000 population in 2021 by country.\u003c/p\u003e","description":"","filename":"Supplementaryfile4TableS2.csv","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/d4401157017b4e256a1c0490.csv"},{"id":82121398,"identity":"35865e60-f528-46e7-a3db-fe89e685ad22","added_by":"auto","created_at":"2025-05-07 03:23:30","extension":"csv","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":10137,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary file 5: Table S3 Age-standardized incidence rates of Dengue per 100 000 population by sociodemographic index (five categories; countries with a high, high-middle, middle, low-middle, or low sociodemographic index) from 1990 to 2019.\u003c/p\u003e","description":"","filename":"supplementaryfile5tableS3Incidence.csv","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/a6a23f8b634aff7a330a3fbb.csv"},{"id":82122992,"identity":"002b386c-0bf3-4dd3-94fb-24fa6ef913b9","added_by":"auto","created_at":"2025-05-07 03:31:31","extension":"csv","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":10141,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary file 6: Table S4 Age-standardized prevalence rates of Dengue per 100 000 population by sociodemographic index (five categories; countries with a high, high-middle, middle, low-middle, or low sociodemographic index) from 1990 to 2019.\u003c/p\u003e","description":"","filename":"supplementaryfile6tableS4prevalence2.csv","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/2a82854226bed18df2c904db.csv"},{"id":82121372,"identity":"b07b0c28-41db-4f21-bbd6-26a42171eba0","added_by":"auto","created_at":"2025-05-07 03:23:29","extension":"pdf","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":6462,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary file 7: Fig. S3 Temporal trends of incidence, prevalence, and DALYs (both males and females separately) from 1990 to 2020\u003c/p\u003e","description":"","filename":"Supplementaryfile7Fig.S3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/489a4a3c9e307b205553d345.pdf"},{"id":82121402,"identity":"0f30ab30-d558-4699-aba8-b1187dd24f05","added_by":"auto","created_at":"2025-05-07 03:23:30","extension":"csv","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":1265,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary file 8: Table S5 Age-standardized incidence rates of Dengue per 100 000 population by age and sex, 2021.\u003c/p\u003e","description":"","filename":"Supplementaryfile8tableS5Incidence.csv","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/02636a7e38facd7ea0c75c66.csv"},{"id":82121397,"identity":"602294ef-36e7-4b69-8c95-4cba41f79dd8","added_by":"auto","created_at":"2025-05-07 03:23:30","extension":"csv","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":1196,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary file 9: Table S6 Age-standardized prevalence rates of Dengue per 100 000 population by age and sex, 2021.\u003c/p\u003e","description":"","filename":"Supplementaryfile9tableS6Prevalence.csv","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/535f2bea331653c1f2334abe.csv"},{"id":82122989,"identity":"d39d84a8-c7b2-48c0-905f-7254f1a9ac8d","added_by":"auto","created_at":"2025-05-07 03:31:30","extension":"pdf","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":27820,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary file 10: Fig. S4 Relationship between SDI and Age-Standardized Rates across countries, colored by their respective Socio-demographic Index (SDI).\u003c/p\u003e","description":"","filename":"SupplementaryFile10Fig.S4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6434758/v1/43e3a11a41441fd225eaad4f.pdf"}],"financialInterests":"","formattedTitle":"Global burden of dengue from 1990 to 2021: a systematic analysis from the Global Burden of Disease study 2021","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDengue fever is an acute infectious disease caused by dengue virus, which is primarily transmitted by \u003cem\u003eAedes aegypti\u003c/em\u003e and \u003cem\u003eAedes albopictus\u003c/em\u003e mosquitoes \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In recent years, with global warming \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, accelerated urbanization \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, and increased international travel \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, the incidence of dengue fever has shown an upward trend worldwide. According to the World Health Organization, there are approximately 50 to 100\u0026nbsp;million cases of dengue fever globally each year \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, some studies suggest that the actual number of infections, including asymptomatic cases, may be much higher \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Dengue is a significant contributor to the global burden of infectious diseases, with far-reaching implications for public health, healthcare systems, and the economy.\u003c/p\u003e \u003cp\u003eDengue fever primarily occurs in tropical and subtropical regions, such as Southeast Asia, South Asia, Africa, and parts of Latin America \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In recent years, dengue fever outbreaks in countries such as Brazil \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, Argentina \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, and Paraguay \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e in South America have been particularly severe, with record-high numbers of reported cases \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Additionally, the incidence of dengue fever has also increased significantly in Southeast Asian countries like Cambodia, Laos, Malaysia, and Singapore \u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Notably, the dengue fever epidemic is expanding northward, posing a risk of transmission to temperate regions, including Europe \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Some European countries, such as France \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and Italy \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, have already reported locally transmitted dengue fever cases, indicating the global spread of the dengue virus. As global warming intensifies, the habitats and activity ranges of the transmission vectors of dengue fever, \u003cem\u003eAedes aegypti\u003c/em\u003e and \u003cem\u003eAedes albopictus\u003c/em\u003e, are also expanding \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The proliferation of these vectors not only increases the risk of dengue virus transmission but also exposes non-epidemic areas to the risk of dengue fever transmission \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSeveral studies have provided valuable insights into the global burden of dengue. Some have analyzed dengue in conjunction with other vector-borne diseases \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, while others have focused exclusively on specific regions or countries. For instance, Martha Anker reported on gender differences in the number of dengue fever cases reported in six Asian countries \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Another study examined dengue fever in Brazil from 2000 to 2015, reporting a 232.7% increase in cases across its 27 federated units \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The most recent comprehensive analyses of the dengue disease burden date back to 2017 (10.5\u0026nbsp;million cases) \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e and 2019 (56.7\u0026nbsp;million cases) \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. However, there are disparities among these studies, and there are no updated estimates on the burden of dengue.\u003c/p\u003e \u003cp\u003eAccurately tracking the evolving patterns and trends in the global and regional prevalence and burden of dengue fever is crucial for developing targeted prevention and control strategies, optimizing resource allocation, and enhancing global health outcomes. Consequently, we delved into the Global Burden of Disease (GBD) 2021 dataset to analyze the global, regional, and national incidence of dengue fever, along with mortality rates and disability-adjusted life-years (DALYs), from 1990 to 2021. This comprehensive examination was conducted by age, sex, and socio-demographic index (SDI), providing age-standardized rates and counts. The updated information on dengue fever serves as a valuable resource for policymakers and healthcare professionals, enabling informed decision-making in crafting control and prevention strategies and implementing effective policies to mitigate the impact of this infectious disease.\u003c/p\u003e"},{"header":"Methods","content":"\n\u003ch3\u003eSelection of Data Source and Study Design\u003c/h3\u003e\n\u003cp\u003eThe GBD study provides annual estimates for health loss caused by diseases and injuries, employing a comprehensive methodology to evaluate global health metrics, including incidence, prevalence, mortality, and Disability-Adjusted Life Years (DALYs). The analysis focused on dengue fever, examining temporal trends from 1990 to 2021. We included data from the general population across all age groups, genders, and socio-demographic index (SDI) regions.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDisease Burden Metrics\u003c/h2\u003e \u003cp\u003eIn this investigation, we compiled annual data metrics to evaluate the global and regional burden of dengue amongst general populations. Metrics entailed the enumeration of incident and prevalent cases, mortality counts, Years of Life Lost (YLLs) due to premature mortality, Years Lived with Disability (YLDs) accounting for non-fatal health outcomes, and Disability-Adjusted Life Years (DALYs), which amalgamate the measures into a single quantifier of overall disease burden. Stratification was applied by age groups to capture the nuances in disease impact. Temporally, the data spanned from 1990 to 2021, enabling a longitudinal perspective. Geographically, the analysis was partitioned into seven super-regions and 21 sub-regions, while individual country data (encompassing 204 nations) were further stratified into quintiles based on the SDI, a composite indicator that reflects income levels, educational attainment, and fertility rates, to assess and compare disease burden dynamics across varying socio-economic contexts.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePatient and Public Involvement\u003c/h3\u003e\n\u003cp\u003eThe research\u0026rsquo;s design, methodology, reporting and dissemination plans did not involve input from participants or the general public. However, we would like to thank all the participants for their willingness and cooperation in taking part in this study. We would like to express our sincere gratitude to the Global Burden of Disease (GBD) database for providing invaluable data and resources that have significantly contributed to our research.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eIn our systematic analysis, epidemiological metrics for dengue incidence, prevalence, mortality, and DALYs were extracted from the GBD database, with age-standardization per 100,000 population using the GBD study's global reference. We conducted a time-trend analysis employing general linear regression to evaluate annual shifts in age-standardized DALY rates from 1990 to 2021, providing a longitudinal view of the disease's impact on the populations. Correlations between age-standardized DALY rates and the SDI were assessed using Spearman's rank correlation, with a significance threshold set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. These rigorous statistical methodologies ensure a comprehensive depiction of the global burden of dengue, enabling stakeholders to identify and prioritize public health interventions for children and adolescents. All analyses were conducted using R version 3.6.1 (R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eGlobal overview\u003c/h2\u003e\n \u003cp\u003eIn 2021, an estimated 58,964,185 incident cases of dengue were reported globally (95% UI: 15,473,439\u0026ndash;106,885,036), with an ASIR of 752.04 per 100,000 population (95% UI: 196.33\u0026ndash;1363.35). Between 1990 and 2021, the incidence rate increased by 0.56% (95% UI: 0.23\u0026ndash;0.38). The number of prevalent cases in 2021 was 3,517,384 (95% UI: 928,244\u0026ndash;6,430,039), corresponding to an ASPR of 44.86 per 100,000 population (95% UI: 11.77\u0026ndash;82.13). This represents an increase of 0.56 per 100,000 population (95% UI: 0.23 to\u0026ndash;2.36) from 1990 to 2021. The global ASDR for dengue rose from 21.63 per 100,000 population (95% UI: 15.09\u0026ndash;26.92) in 1990 to 27.76 per 100,000 population (95% UI: 14.21\u0026ndash;41.65) in 2021. This change represents a percentage increase of 0.28 (95% UI: -0.38\u0026ndash;0.92) compared to 1990. (Table 1, Supplementary File 1, Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eRegional level\u003c/h2\u003e\n \u003cp\u003eOn a regional scale, Tropical Latin America reported the highest ASIR in 2021, with 5,775 cases per 100,000 population (95% UI: 1,775\u0026ndash;11,625) and over 13.04 million incident cases (95% UI: 3,996,126\u0026ndash;26,305,622). South Asia ranked second, with an ASIR of 1,727 per 100,000 (95% UI: 102\u0026ndash;3,636) and 31.81 million cases (95% UI: 3,996,126\u0026ndash;26,305,622). This is consistent with the ASIR and ASPR ranking in 1990 (Supplementary File 2, Fig. \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). The highest ASPR was observed in Tropical Latin America (343.77, 95% UI: 107.963\u0026ndash;700.31), followed by South Asia (103.22, 95% UI: 5.90\u0026ndash;220.59), and Central Latin America (67.95, 95% UI: 40.54\u0026ndash;97.63) (Table 1, Supplementary File 3, Fig. \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003e). In terms of ASDR, Southeast Asia, Tropical Latin America, and South Asia recorded higher ASDRs than other countries, with ASDRs of 147.04 (95% UI: 95.32\u0026ndash;200.97), 63.76 (95% UI: 22.43\u0026ndash;136.04), and 53.46 (95% UI: 19.54\u0026ndash;91.91) in 2021, respectively. The lowest ASDRs were observed in high-income countries in Europe and North America (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, Table 1).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eNational level\u003c/h3\u003e\n\u003cp\u003eAt the national level, variations in the change of the ASIR were observed across countries from 1990 to 2021. Tonga reported the highest ASIR in 2021, with 14,363 cases per 100,000 population (95% UI: 136\u0026ndash;50,917). Other countries with significant dengue incidence included the Republic of Seychelles, Union of the Comoros, Republic of the Marshall Islands, Republic of Singapore, and Republic of Cabo Verde. By contrast, Comoros reported the highest ASIR in 1990 (11,154.07, 95% UI: 1,653.69\u0026ndash;44,214.37), followed by Djibouti, Marshall Islands, and Singapore. In 2012, Tonga, also had the highest ASPR of 854.37 (95% UI: 7.35\u0026ndash;3,178.87), followed by Seychelles (735.66, 95% UI: 126.68\u0026ndash;3,086.71) and Comoros (707.55, 95% UI: 0.13\u0026ndash;4,795.15), respectively. In terms of ASDR, Indonesia experienced the highest dengue burden in 2021, with 279.79 DALYs per 100,000 population (95% UI: 170.92\u0026ndash;404.43). Tonga ranked second with 168.65 per 100,000 (95% UI: 14.61\u0026ndash;563.73), followed by the Philippines with 126.60 (95% UI: 95.17\u0026ndash;164.20). Variations in the change of the ASPR and ASDR were also observed across countries from 1990 to 2021 as detailed in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, Supplementary File 4, Table \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003e.\u003c/p\u003e\n\u003ch3\u003eTemporal Trends by SDI\u003c/h3\u003e\n\u003cp\u003eOur analysis revealed a global increase in the ASIR, with similar trends observed in high-middle and middle SDI regions. In the high-middle SDI region, the ASIR rose from 98.43 (95% UI: 12.22\u0026ndash;263.08) per 100,000 population in 1990 to 215.66 (95% UI: 91.61\u0026ndash;372.30) per 100,000 population in 2021. Likewise, in the middle SDI region, the ASIR increased from 782.97 (95% UI: 51.81\u0026ndash;1,725.40) per 100,000 population to 1,269.27 (95% UI: 437.36\u0026ndash;2,268.00) per 100,000 population (Supplementary File 5, Table \u003cspan class=\"InternalRef\"\u003eS3\u003c/span\u003e). In contrast, the low SDI region experienced a decrease in ASIR, from 431.07 (95% UI: 242.88\u0026ndash;648.05) per 100,000 population in 1990 to 368.03 (95% UI: 11.69\u0026ndash;884.71) per 100,000 population in 2021. The ASPR increased across all regions, except in low-SDI regions, where a decline was observed from 25.64 (95% UI: 14.03\u0026ndash;39.36) per 100,000 population in 1990 to 21.87 (95% UI: 0.68\u0026ndash;54.56) per 100,000 population in 2021 (Supplementary File 6, Table \u003cspan class=\"InternalRef\"\u003eS4\u003c/span\u003e). Similarly, the ASDR of dengue fever exhibited comparable patterns in the high-middle, middle, and low-middle SDI regions. In both the high-SDI and low-SDI regions, the ASDR fluctuated over time. Notably, the high-SDI region experienced a peak of 1.03 (95% UI: 0.22\u0026ndash;2.55) per 100,000 population per 100,000 in 2005. The low-SDI region, by contrast, showed relatively stable trends, fluctuating between 11.84 (95% UI: 8.11\u0026ndash;16.08) per 100,000 population and 12.78 (95% UI: 4.86\u0026ndash;22.81) per 100,000 population from 1990 to 2021 (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eAge and sex patterns\u003c/h2\u003e\n \u003cp\u003eOur comprehensive global analysis of dengue burden from 1990 to 2021 revealed distinct variations across different age groups, highlighting the dynamic nature of dengue transmission across various demographics (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Overall, both incidence and prevalence rates across all age groups showed an upward trend from 1990 to 2021, particularly before 2015. The DALYs in the 0\u0026ndash;14 age group were generally higher than in other groups but exhibited fluctuations over time. The 15\u0026ndash;49 age group had the highest number of incident and prevalent cases (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA), though the 0\u0026ndash;14 age group demonstrated higher incidence and prevalence rates (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB). Similarly, the ASDR for the 0\u0026ndash;14 age group was higher than in other groups. However, a significant decline in ASIR, ASPR, and ASDR across all age groups occurred after 2015 (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\n \u003cp\u003eFrom 1990 to 2021, ASIR and ASPR were slightly higher among females compared to males. However, males exhibited a higher ASDR, as shown in Supplementary File 7, Fig. \u003cspan class=\"InternalRef\"\u003eS3\u003c/span\u003e. In 2021, there were 31.6 million dengue cases among females and 27.3 million among males. Among females aged 15\u0026ndash;49, the highest number of cases was recorded at 16,530,266 (95% UI: 4,357,395\u0026thinsp;\u0026minus;\u0026thinsp;29,724,055), with an incidence rate of 848.20 per 100,000 population (95% UI: 223.59\u0026ndash;1,525.21), closely followed the incidence rate in the 0\u0026ndash;14 age group at 849.66 per 100,000 (95% UI: 211.05\u0026ndash;1,552.60) (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA). Males aged 0\u0026ndash;14 recorded 7,607,459 cases, with an incidence rate of 732.78 per 100,000 (95% UI: 758.90\u0026ndash;1,568.64), reflecting a high infection level. In contrast, males aged 50 and above had the fewest cases and the lowest incidence rates (Supplementary File 8, Table \u003cspan class=\"InternalRef\"\u003eS5\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eSimilarly, females aged 15\u0026ndash;49 had the highest number of prevalent cases, with 986,187 cases (95% UI: 252,58\u0026ndash;1,788,33) and a prevalence rate of 50.60 per 100,000 (95% UI: 12.96\u0026ndash;91.76) (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB). Females aged 0\u0026ndash;14 had the sixth-highest number of cases, totaling 493,502 (95% UI: 120,397\u0026ndash;904,087), yet they exhibited the highest prevalence rate at 50.68 per 100,000 (95% UI: 12.36\u0026ndash;92.85) (Supplementary File 9, Table \u003cspan class=\"InternalRef\"\u003eS6\u003c/span\u003e). By comparison, males aged 50 and above recorded the lowest incidence and prevalence rates. Regarding ASDR, males across all age groups had higher rates than females, particularly in the 0\u0026ndash;14 age group, where DALYs were significantly higher at 49.75 per 100,000 (95% UI: 25.88\u0026ndash;71.56) (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eRelationship between DALYs and SDI\u003c/h2\u003e\n \u003cp\u003eWe conducted a regional and national-level analysis of the ASIR, ASPR, and ASDR of dengue across 204 countries in relation to the SDI over time. The results revealed a non-linear association between ASIR and SDI at the regional level. Interestingly, high dengue incidence was not restricted to the least developed regions or countries. Nations such as Tonga, Seychelles, Comoros, the Marshall Islands, and Singapore exhibited significantly higher ASIR levels than expected. Conversely, countries like the United States and South Sudan demonstrated ASIR levels that were notably lower than anticipated (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, Supplementary File 10, Fig. \u003cspan class=\"InternalRef\"\u003eS4\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eA similar non-linear association was observed between ASPR, ASDR, and SDI. There was no negative correlation between ASPR or ASDR and SDI across all regions. Countries such as Tonga, the Philippines, Comoros, and Seychelles exhibited ASDR levels that were considerably higher than expected. In contrast, countries including Spain and Greece exhibited lower age-standardized DALY rates than predicted (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, Supplementary File 10, Fig. \u003cspan class=\"InternalRef\"\u003eS4\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDengue fever, a mosquito-borne viral disease, continues to pose a significant global health burden, as evidenced by the substantial increase in incident and prevalent cases reported globally from 1990 to 2021. Our comprehensive analysis, utilizing robust epidemiological data and statistical modeling, reveals several key insights into the dynamics and patterns of dengue burden across different regions, countries, age groups, and sexes, underscoring the need for targeted interventions and global cooperation to address the growing threat of dengue fever.\u003c/p\u003e \u003cp\u003eGlobally, the estimated incident cases of dengue increased from 1990 to 2021, with a notable rise in the ASIR and ASPR. Our study shows consistency with the previous global burden of disease study by Yang et al., which reported an increase from 30.7\u0026nbsp;million cases in 1990 to 56.9\u0026nbsp;million cases in 2019 across all age groups \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. This trend is particularly concerning, as it suggests a potential intensification of dengue transmission worldwide. The observed increase in the ASDR further underscores the severity of the disease burden, particularly in light of the modest change in percentage. Dengue primarily impacts tropical and subtropical countries. A previous systematic review on dengue global epidemiology reported the predominant proportion of dengue patients, accounting for 72.4% of the total, were reported from the Western Pacific region, closely followed by the American region with 19.4% of cases, and the Southeast Asia Region contributing 4.8% of all reported dengue cases \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In our study, Tropical Latin America and South Asia emerged as regions with the highest ASIR and ASPR. This finding is likely attributed to the consistently warm temperatures these regions experience throughout the year, creating a conducive environment for the proliferation of mosquito vectors, which are the primary transmitters of the dengue virus. Moreover, many of these regions are characterized by rapid population growth and unplanned urbanization, all of which contribute to an increased risk of mosquito breeding and dengue transmission. Furthermore, the increasing global incidence of dengue has been associated with factors such as global warming and rapid urbanization\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe distinct age and sex patterns observed in our analysis provide valuable insights into the epidemiology of dengue. The 15\u0026ndash;49 age group had the highest number of incident and prevalent cases, while the 0\u0026ndash;14 age group exhibited higher incidence and prevalence rates. This aligns with previous studies, which have reported that dengue is responsible for significant morbidity and mortality in children residing in tropical and subtropical regions \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. This finding underscores the vulnerability of young adults and children to dengue and highlights the importance of targeted interventions to protect these populations. The heightened vulnerability of children to dengue infection can be attributed to their immature immune systems and their tendency to play outdoors, where protection against Aedes mosquitoes is limited. Additionally, the higher ASDR among males across all age groups, particularly in the 0\u0026ndash;14 age group, emphasizes the need for gender-specific prevention and treatment strategies. A study conducted by Anker et al. supported our findings, demonstrating a higher predilection for dengue in males in across six culturally and economically diverse countries \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Biological and gender-related factors can change over the human lifespan and can differ across countries. Therefore, further research is required to identify the causes of these sex-specific differences.\u003c/p\u003e \u003cp\u003eIn general, high economic levels are often associated with lower incidence rates of infectious diseases\u003csup\u003e\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, but this relationship is influenced by various factors, including social, environmental, and policy aspects\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Our analysis highlights temporal variations in dengue burden across different SDI regions. Notably, the burden of dengue is not confined to either developed or less developed countries. While high-middle and middle SDI regions experienced an increase in ASIR, the low SDI region saw a decline. These observations align with the findings from the GBD 2017 and a study conducted by Tian \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. This discrepancy may be attributed to differences in healthcare infrastructure, disease surveillance, and control measures across regions. However, the consistent increase in ASPR and ASDR across all SDI regions, except low-SDI, underscores the persistence of dengue as a significant public health concern regardless of socio-economic status. Therefore, understanding the multifaceted and interactive reasons for the varying burden of dengue across different regions is crucial for developing effective strategies to control and prevent the disease.\u003c/p\u003e \u003cp\u003eWhile this study presents valuable insights and abundant information on the GBD for dengue, it holds significant importance in guiding dengue prevention and control efforts, fostering international cooperation and exchange, and enhancing global health standards. It is noteworthy, however, that several limitations persist in our study. Firstly, there are often notable discrepancies between the GBD estimates of dengue burden and the actual number of reported cases\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. This may stem from various factors, such as differences in monitoring systems, the sophistication of reporting mechanisms, and the diversity of dengue symptoms. Therefore, when interpreting GBD data, it is crucial to acknowledge these limitations and conduct comprehensive analyses that integrate actual conditions. Second, the GBD database stands as a crucial resource in the public health domain, consistently endeavoring to enhance data quality and timeliness to furnish more precise evidence for global health policy formulation and intervention measures. Nevertheless, the GBD data exhibits a lag, primarily due to the challenges in data collection, the complexity of processing, and the periodic nature of its updates and releases. The diversity and quality discrepancies of global data, the intricate process of model selection and validation, coupled with the rigorous review process during regular research cycles, collectively extend the timeline from data collection to final publication. Additionally, funding limitations, resource shortages, and even political and social factors can potentially hinder the timely circulation of data. We have not conducted a comparative analysis of the latest dengue disease data, such as from 2022 and 2023, with the prediction results from GBD. Third, existing surveillance systems are not sensitive, and mild febrile illnesses are less likely to be diagnosed and reported. Data about dengue were only available in limited regions and countries, and we have no data from much of Central Europe, Eastern Europe, and Western Europe.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, this analysis highlights increase in incident cases, prevalence, and DALYs rates globally, with demographic and geographic disparities. Furthermore, the non-linear relationship between dengue burden and development level highlights the complexity of the disease. \u0026nbsp;Our findings contribute to the academic community by providing a nuanced understanding of the global dengue landscape and its evolving trends. Practically, they inform policy-makers and healthcare providers on the importance of targeted prevention, control, and treatment strategies to mitigate the growing burden of dengue fever worldwide.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants consented to have their data published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData used in the analyses can be obtained from the Global Health Data Exchange Global Burden of Disease Results Tool(https://ghdx.healthdata.org/gbd-results-tool).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the National Key Research and Development Program of China (No. 2021YFC2300800, 2021YFC2300804) and the International Joint Laboratory on Tropical Diseases Control in Greater Mekong Subregion (No. 21410750200). The funders had no role in study design, data collection, analysis and interpretation, or in writing the report and the decision to submit the article for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was designed and the manuscript was drafted by FXY and ZJX. They also provided critical intellectual input and revised the manuscript. The statistical analysis, figures, and appendix were coded by ZJX, HT, SP, DL, and SJH in collaboration with FXY, CMX, and ZXN cross-checked the data and results. FXY edited the language. All authors agreed to the final manuscript, and the corresponding author confirms that all eligible contributors were included.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWilder-Smith A, Lindsay SW, Scott TW, et al. 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Discrepancies in dengue burden estimates: a comparative analysis of reported cases and global burden of disease study, 2010-2019. \u003cem\u003eJournal of travel medicine\u003c/em\u003e 2024;31(4) doi: 10.1093/jtm/taae069 [published Online First: 2024/05/02]\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"infectious-diseases-of-poverty","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"idop","sideBox":"Learn more about [Infectious Diseases of Poverty](http://idpjournal.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/idop/default.aspx","title":"Infectious Diseases of Poverty","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Dengue fever, Global Burden of Disease, Incidence, Mortality, Disability-adjusted life years (DALYs), Socio-demographic Index (SDI)","lastPublishedDoi":"10.21203/rs.3.rs-6434758/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6434758/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDengue fever remains a major global public health challenge, with increasing incidence and burden over recent decades. Global warming, urbanization, and increased international travel have fueled the global spread of dengue.\u003c/p\u003e \u003cp\u003eWe analyzed the 2021 Global Burden of Disease (GBD) dataset to assess dengue fever's incidence, prevalence, mortality, and Disability-Adjusted Life Years (DALYs) from 1990 to 2021 across 204 countries. Data were stratified by age, sex, and socio-demographic index (SDI) using age-standardized rates, and time-trend analysis was conducted with general linear regression. Correlations between SDI and disease burden metrics were evaluated using Spearman\u0026rsquo;s rank correlation.\u003c/p\u003e \u003cp\u003eFrom 1990 to 2021, the global burden of dengue increased, with ASIR rising by 0.56% (95% UI: 0.23\u0026ndash;2.38), ASPR by 0.56% (95% UI: 0.23\u0026ndash;2.36), and ASDR by 0.28% (95% UI: -0.38\u0026ndash;0.92). In 2021, there were an estimated 58.96\u0026nbsp;million cases. Regionally, Tropical Latin America reported the highest ASIR (5,774.82; 95% UI: 1,774.731\u0026ndash;11,624.76). At the national level, variations in the change of the ASIR were observed across countries from 1990 to 2021 with Tonga reported the highest ASIR in 2021. Males exhibited a higher ASDR compared to females, particularly in the 0\u0026ndash;14 age group. Dengue burden trends varied across SDI regions, with high-middle and middle SDI regions showing increased ASIR, while low SDI regions experienced a decline.\u003c/p\u003e \u003cp\u003eThe analysis highlights the increase in dengue burden globally, with demographic and geographic disparities. The findings underscore the need for targeted prevention, control, and treatment strategies to mitigate the growing burden of dengue fever worldwide.\u003c/p\u003e","manuscriptTitle":"Global burden of dengue from 1990 to 2021: a systematic analysis from the Global Burden of Disease study 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 03:23:12","doi":"10.21203/rs.3.rs-6434758/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2025-05-13T22:37:45+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-04-19T06:12:01+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-17T03:11:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-16T07:40:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Infectious Diseases of Poverty","date":"2025-04-15T05:16:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"infectious-diseases-of-poverty","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"idop","sideBox":"Learn more about [Infectious Diseases of Poverty](http://idpjournal.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/idop/default.aspx","title":"Infectious Diseases of Poverty","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f0e7ff3a-0425-4590-bc02-a5dae90d846d","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-20T16:02:48+00:00","versionOfRecord":{"articleIdentity":"rs-6434758","link":"https://doi.org/10.1186/s40249-025-01365-x","journal":{"identity":"infectious-diseases-of-poverty","isVorOnly":false,"title":"Infectious Diseases of Poverty"},"publishedOn":"2025-10-16 15:57:58","publishedOnDateReadable":"October 16th, 2025"},"versionCreatedAt":"2025-05-07 03:23:12","video":"","vorDoi":"10.1186/s40249-025-01365-x","vorDoiUrl":"https://doi.org/10.1186/s40249-025-01365-x","workflowStages":[]},"version":"v1","identity":"rs-6434758","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6434758","identity":"rs-6434758","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}