Model-based spatial-temporal mapping of opisthorchiasis in endemic countries of Southeast Asia

  1. Ting-Ting Zhao
  2. Yi-Jing Feng
  3. Pham Ngoc Doanh
  4. Somphou Sayasone
  5. Virak Khieu
  6. Choosak Nithikathkul
  7. Men-Bao Qian
  8. Yuan-Tao Hao
  9. Ying-Si Lai  Is a corresponding author
  1. Sun Yat-Sen University, China
  2. Vietnam Academy of Sciences and Technology, Viet Nam
  3. Ministry of Health, Lao People's Democratic Republic
  4. Ministry of Health, Cambodia
  5. Mahasarakham University, Thailand
  6. Chinese Center for Disease Control and Prevention; Ministry of Health, China

Abstract

Opisthorchiasis is an overlooked danger to Southeast Asia. High-resolution disease risk maps are critical but haven't been available for Southeast Asia. Georeferenced disease data and potential influencing factor data were collected through a systematic review of literatures and open-access databases, respectively. Bayesian spatial-temporal joint models were developed to analyze both point- and area-level disease data, within a logit regression in combination of potential influencing factors and spatial-temporal random effects. The model-based risk mapping identified areas of low, moderate and high prevalence across the study region. Even though the overall population-adjusted estimated prevalence presented a trend down, a total of 12.39 million (95% BCI: 10.10-15.06) people were estimated infected with O. viverrini in 2018 in four major endemic countries (i.e., Thailand, Laos, Cambodia, and Vietnam), highlighting the public health importance of the disease in the study region. The high-resolution risk maps provide valuable information for spatial targeting of opisthorchiasis control interventions.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 2-7, Figure 2-figure supplement 1, Figure 3-figure supplement 1, Figure 6-figure supplement 1-9.

Article and author information

Author details

  1. Ting-Ting Zhao

    Department of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, China
    Competing interests
    The authors declare that no competing interests exist.
  2. Yi-Jing Feng

    Department of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Pham Ngoc Doanh

    Department of Parasitology, Institute of Ecology and Biological Resources, Graduate University of Science and Technology, Vietnam Academy of Sciences and Technology, Hanoi, Viet Nam
    Competing interests
    The authors declare that no competing interests exist.
  4. Somphou Sayasone

    Lao Tropical and Public Health Institute, Ministry of Health, Vientiane Capital, Lao People's Democratic Republic
    Competing interests
    The authors declare that no competing interests exist.
  5. Virak Khieu

    National Center for Parasitology, Entomology and Malaria Control, Ministry of Health, Phnom Penh, Cambodia
    Competing interests
    The authors declare that no competing interests exist.
  6. Choosak Nithikathkul

    Tropical and Parasitic Diseases Research Unit, Faculty of Medicine, Mahasarakham University, Mahasarakham, Thailand
    Competing interests
    The authors declare that no competing interests exist.
  7. Men-Bao Qian

    National Institute of Parasitic Diseases; WHO Collaborating Centre for Tropical Diseases, Key Laboratory of Parasite and Vector Biology, Chinese Center for Disease Control and Prevention; Ministry of Health, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Yuan-Tao Hao

    Department of Medical Statistics, School of Public Health; Sun Yat-sen Global Health Institute, Sun Yat-Sen University, Guangzhou, China
    Competing interests
    The authors declare that no competing interests exist.
  9. Ying-Si Lai

    Department of Medical Statistics, School of Public Health; Sun Yat-sen Global Health Institute, Sun Yat-Sen University, Guangzhou, China
    For correspondence
    laiys3@mail.sysu.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4324-5465

Funding

National Natural Science Foundation of China (81703320)

  • Ying-Si Lai

National Natural Science Foundation of China (82073665)

  • Ying-Si Lai

Natural Science Foundation of Guangdong Province (2017A030313704)

  • Ying-Si Lai

China Medical Board (17-274)

  • Ying-Si Lai

The Sun Yat-Sen University One Hundred Talent Grant

  • Ying-Si Lai

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

Reviewing Editor

  1. Talía Malagón, McGill University, Canada

Ethics

Human subjects: This work was based on survey data pertaining to the prevalence of opisthorchiasis extracted from open published peer-reviewed literatures. All data were aggregated and did not contain any information at the individual or household levels. Therefore, there were no specific ethical issues warranted special attention.

Version history

  1. Received: June 7, 2020
  2. Accepted: January 11, 2021
  3. Accepted Manuscript published: January 12, 2021 (version 1)
  4. Version of Record published: February 8, 2021 (version 2)

Copyright

© 2021, Zhao 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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  1. Ting-Ting Zhao
  2. Yi-Jing Feng
  3. Pham Ngoc Doanh
  4. Somphou Sayasone
  5. Virak Khieu
  6. Choosak Nithikathkul
  7. Men-Bao Qian
  8. Yuan-Tao Hao
  9. Ying-Si Lai
(2021)
Model-based spatial-temporal mapping of opisthorchiasis in endemic countries of Southeast Asia
eLife 10:e59755.
https://doi.org/10.7554/eLife.59755

Share this article

https://doi.org/10.7554/eLife.59755

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