1. Epidemiology and Global Health
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Spatio-temporal associations between deforestation and malaria incidence in Lao PDR

  1. Francois Rerolle  Is a corresponding author
  2. Emily Dantzer
  3. Andrew A Lover
  4. John M Marshall
  5. Bouasy Hongvanthong
  6. Hugh JW Sturrock
  7. Adam Bennett
  1. University of California, San Francisco, United States
  2. University of Massachusetts-Amherst, United States
  3. University of California, Berkeley, United States
  4. Ministry of Health, Lao PDR, Lao People's Democratic Republic
Research Article
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Cite this article as: eLife 2021;10:e56974 doi: 10.7554/eLife.56974

Abstract

As countries in the Greater Mekong Sub-region (GMS) increasingly focus their malaria control and elimination efforts on reducing forest-related transmission, greater understanding of the relationship between deforestation and malaria incidence will be essential for programs to assess and meet their 2030 elimination goals. Leveraging village-level health facility surveillance data and forest cover data in a spatio-temporal modeling framework, we found evidence that deforestation is associated with short-term increases, but long-term decreases in confirmed malaria case incidence in Lao People's Democratic Republic (Lao PDR). We identified strong associations with deforestation measured within 30 km of villages but not with deforestation in the near (10 km) and immediate (1 km) vicinity. Results appear driven by deforestation in densely forested areas and were more pronounced for infections with Plasmodium falciparum (P. falciparum) than for Plasmodium vivax (P. vivax). These findings highlight the influence of forest activities on malaria transmission in the GMS.

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, 3, 4 and 5 and for Tables 1, 2 and 3.

The following previously published data sets were used

Article and author information

Author details

  1. Francois Rerolle

    Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, United States
    For correspondence
    francois.rerolle@ucsf.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3837-5700
  2. Emily Dantzer

    Institute of Global Health Sciences, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Andrew A Lover

    Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts-Amherst, Amherst, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2181-3559
  4. John M Marshall

    Division of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0603-7341
  5. Bouasy Hongvanthong

    Center for Malariology, Parasitology and Entomology, Ministry of Health, Lao PDR, Vientiane, Lao People's Democratic Republic
    Competing interests
    The authors declare that no competing interests exist.
  6. Hugh JW Sturrock

    Institute of Global Health Sciences, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Adam Bennett

    Institute of Global Health Sciences, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

Bill and Melinda Gates Foundation (OPP1116450)

  • Francois Rerolle
  • Emily Dantzer
  • Andrew A Lover
  • Bouasy Hongvanthong
  • Hugh JW Sturrock
  • Adam Bennett

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

Ethics

Human subjects: This study was approved by the National Ethics Committee for Health Research at the Lao Ministry of Health (Approval #2016-014; 8/22/2016) and by the UCSF ethical review board (Approvals #16-19649 and #17-22577). The informed consent process was consistent with local norms, and all study areas had a consultation meeting with, and approvals from, village elders. All participants provided informed written consent; caregivers provided consent for all children under 18, and all children aged 10 and above also provided consent directly. The study was conducted according to the ethical principles of the Declaration of Helsinki of October 2002.

Reviewing Editor

  1. Ben S Cooper, Mahidol University, Thailand

Publication history

  1. Received: March 16, 2020
  2. Accepted: February 19, 2021
  3. Accepted Manuscript published: March 9, 2021 (version 1)
  4. Version of Record published: April 6, 2021 (version 2)

Copyright

© 2021, Rerolle 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. Further reading

Further reading

  1. How does cutting down forests influence the spread of malaria?

    1. Ecology
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    Identifying the key vector and host species that drive the transmission of zoonotic pathogens is notoriously difficult but critical for disease control. We present a nested approach for quantifying the importance of host and vectors that integrates species’ physiological competence with their ecological traits. We apply this framework to a medically important arbovirus, Ross River virus (RRV), in Brisbane, Australia. We find that vertebrate hosts with high physiological competence are not the most important for community transmission; interactions between hosts and vectors largely underpin the importance of host species. For vectors, physiological competence is highly important. Our results identify primary and secondary vectors of RRV and suggest two potential transmission cycles in Brisbane: an enzootic cycle involving birds and an urban cycle involving humans. The framework accounts for uncertainty from each fitted statistical model in estimates of species’ contributions to transmission and has has direct application to other zoonotic pathogens.