The global distribution and burden of dengue

Journal name:
Nature
Volume:
496,
Pages:
504–507
Date published:
DOI:
doi:10.1038/nature12060
Received
Accepted
Published online
Corrected online

Dengue is a systemic viral infection transmitted between humans by Aedes mosquitoes1. For some patients, dengue is a life-threatening illness2. There are currently no licensed vaccines or specific therapeutics, and substantial vector control efforts have not stopped its rapid emergence and global spread3. The contemporary worldwide distribution of the risk of dengue virus infection4 and its public health burden are poorly known2, 5. Here we undertake an exhaustive assembly of known records of dengue occurrence worldwide, and use a formal modelling framework to map the global distribution of dengue risk. We then pair the resulting risk map with detailed longitudinal information from dengue cohort studies and population surfaces to infer the public health burden of dengue in 2010. We predict dengue to be ubiquitous throughout the tropics, with local spatial variations in risk influenced strongly by rainfall, temperature and the degree of urbanization. Using cartographic approaches, we estimate there to be 390 million (95% credible interval 284–528) dengue infections per year, of which 96 million (67–136) manifest apparently (any level of disease severity). This infection total is more than three times the dengue burden estimate of the World Health Organization2. Stratification of our estimates by country allows comparison with national dengue reporting, after taking into account the probability of an apparent infection being formally reported. The most notable differences are discussed. These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue. We anticipate that they will provide a starting point for a wider discussion about the global impact of this disease and will help to guide improvements in disease control strategies using vaccine, drug and vector control methods, and in their economic evaluation.

At a glance

Figures

  1. Global estimates of total dengue infections.
    Figure 1: Global estimates of total dengue infections.

    Comparison of previous estimates of total global dengue infections in individuals of all ages, 1985–2010. Black triangle, ref. 5; dark blue triangle, ref. 15; green triangle, ref. 17; orange triangle, ref. 16; light blue triangle, ref. 30; pink triangle, ref. 10; red triangle, apparent infections from this study. Estimates are aligned to the year of estimate and, if not stated, aligned to the publication date. Red shading marks the credible interval of our current estimate, for comparison. Error bars from ref. 10 and ref. 16 replicated the confidence intervals provided in these publications.

  2. Global evidence consensus, risk and burden of dengue in 2010.
    Figure 2: Global evidence consensus, risk and burden of dengue in 2010.

    a, National and subnational evidence consensus on complete absence (green) through to complete presence (red) of dengue4. b, Probability of dengue occurrence at 5km×5km spatial resolution of the mean predicted map (area under the receiver operator curve of 0.81 (±0.02 s.d., n = 336)) from 336 boosted regression tree models. Areas with a high probability of dengue occurrence are shown in red and areas with a low probability in green. c, Cartogram of the annual number of infections for all ages as a proportion of national or subnational (China) geographical area.

Change history

Corrected online 24 April 2013
Minor changes were made to the text about disease severity, and an additional citation to ref. 6 was added.

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Author information

Affiliations

  1. Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK

    • Samir Bhatt,
    • Peter W. Gething,
    • Oliver J. Brady,
    • Jane P. Messina,
    • Andrew W. Farlow,
    • Catherine L. Moyes,
    • John M. Drake,
    • Monica F. Myers,
    • G. R. William Wint &
    • Simon I. Hay
  2. Oxitec Limited, Milton Park, Abingdon OX14 4RX, UK

    • Oliver J. Brady
  3. Odum School of Ecology, University of Georgia, Athens, Georgia 30602, USA

    • John M. Drake
  4. Department of Pediatrics, Harvard Medical School and Children’s Hospital Informatics Program, Boston Children’s Hospital, Boston, Massachusetts 02115, USA

    • John S. Brownstein
  5. Department of Community and Family Medicine, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire 03755, USA

    • Anne G. Hoen
  6. INDEPTH Network Secretariat, East Legon, PO Box KD 213, Accra, Ghana

    • Osman Sankoh
  7. School of Public Health, University of the Witwatersrand, Braamfontein 2000, Johannesburg, South Africa

    • Osman Sankoh
  8. Institute of Public Health, University of Heidelberg, 69120 Heidelberg, Germany

    • Osman Sankoh
  9. Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892, USA

    • Dylan B. George,
    • Thomas W. Scott &
    • Simon I. Hay
  10. Section Clinical Tropical Medicine, Department of Infectious Diseases, Heidelberg University Hospital, INF 324, D 69120 Heidelberg, Germany

    • Thomas Jaenisch
  11. Environmental Research Group Oxford (ERGO), Tinbergen Building, Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK

    • G. R. William Wint
  12. Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam

    • Cameron P. Simmons &
    • Jeremy J. Farrar
  13. Centre for Tropical Medicine, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK

    • Cameron P. Simmons &
    • Jeremy J. Farrar
  14. Department of Entomology, University of California Davis, Davis, California 95616, USA

    • Thomas W. Scott
  15. Department of Medicine, National University of Singapore, 119228 Singapore

    • Jeremy J. Farrar

Contributions

S.I.H. and J.J.F. conceived the research. S.B. and S.I.H. drafted the manuscript. S.B. drafted the Supplementary Information with significant support on sections A (O.J.B., C.L.M.), B (J.P.M., G.R.W.W.), C (P.W.G.), D (O.J.B., T.W.S.), and O.J.B. wrote section E. J.S.B. and A.G.H. provided HealthMap occurrence data and advice on its provenance. O.J.B. reviewed all the occurrence data. S.B. did the modelling and analysis with advice from J.M.D., P.W.G. and S.I.H. J.P.M. created all maps. All authors discussed the results and contributed to the revision of the final manuscript.

Competing financial interests

The authors declare no competing financial interests.

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    This file contains Supplementary Information Sections A-F – see contents for details.

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