Estimates of the global burden of Japanese Encephalitis and the impact of vaccination from 2000-2015

  1. Tran Minh Quan
  2. Tran Thi Nhu Thao
  3. Nguyen Manh Duy
  4. Tran Minh Nhat
  5. Hannah Clapham  Is a corresponding author
  1. University of Notre Dame, United States
  2. Oxford University Clinical Research Unit, Wellcome Trust Asia Program, Viet Nam

Abstract

Japanese encephalitis (JE) is a mosquito-borne disease, known for its high mortality and disability rate among symptomatic cases. Many effective vaccines are available for JE, and the use of a recently developed and inexpensive vaccine, SA 14-14-2, has been increasing over the recent years particularly with Gavi support. Estimates of the local burden and the past impact of vaccination are therefore increasingly needed, but difficult due to the limitations of JE surveillance. In this study, we implemented a mathematical modelling method (catalytic model) combined with age-stratifed case data from our systematic review which can overcome some of these limitations. We estimate in 2015 JEV infections caused 100,308 JE cases (95%CI: 61,720 - 157,522) and 25,125 deaths (95%CI: 14,550 - 46,031) globally, and that between 2000 and 2015 307,774 JE cases (95%CI: 167,442- 509,583) were averted due to vaccination globally. Our results highlight areas that could have the greatest benefit from starting vaccination or from scaling up existing programs and will be of use to support local and international policymakers in making vaccine allocation decisions.

Data availability

This study conducted a literature review and collated all data on age-stratified JE cases from these papers. The full list of these papers and the data extracted is available in the supplement.The code and data is available here: https://github.com/tranquanc123/JE_burden_estimates.

Article and author information

Author details

  1. Tran Minh Quan

    Biological Science Department, University of Notre Dame, South Bend, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3337-161X
  2. Tran Thi Nhu Thao

    Oxford University Clinical Research Unit, Wellcome Trust Asia Program, Ho Chi Minh City, Viet Nam
    Competing interests
    The authors declare that no competing interests exist.
  3. Nguyen Manh Duy

    Oxford University Clinical Research Unit, Wellcome Trust Asia Program, Ho Chi Minh City, Viet Nam
    Competing interests
    The authors declare that no competing interests exist.
  4. Tran Minh Nhat

    Oxford University Clinical Research Unit, Wellcome Trust Asia Program, Ho Chi Minh City, Viet Nam
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9500-8341
  5. Hannah Clapham

    Oxford University Clinical Research Unit, Wellcome Trust Asia Program, Ho Chi Minh City, Viet Nam
    For correspondence
    hannah.clapham@nus.edu.sg
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2531-161X

Funding

Bill and Melinda Gates Foundation and Gavi (Vaccine Impact Modelling Consortium)

  • Tran Minh Quan
  • Tran Thi Nhu Thao
  • Nguyen Manh Duy
  • Tran Minh Nhat

Wellcome Trust (089276/B/09/7)

  • Hannah Clapham

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Quan et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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https://doi.org/10.7554/eLife.51027

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