IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-38476-8.html
   My bibliography  Save this article

No evidence of sustained nonzoonotic Plasmodium knowlesi transmission in Malaysia from modelling malaria case data

Author

Listed:
  • Kimberly M. Fornace

    (University of Glasgow
    National University of
    London School of Hygiene and Tropical Medicine)

  • Hillary M. Topazian

    (Imperial College London)

  • Isobel Routledge

    (Imperial College London
    University of California, San Francisco)

  • Syafie Asyraf

    (Universiti Malaysia Sabah)

  • Jenarun Jelip

    (Ministry of Health Malaysia)

  • Kim A. Lindblade

    (World Health Organization)

  • Mohammad Saffree Jeffree

    (Universiti Malaysia Sabah)

  • Pablo Ruiz Cuenca

    (London School of Hygiene and Tropical Medicine)

  • Samir Bhatt

    (Imperial College London
    University of Copenhagen)

  • Kamruddin Ahmed

    (Universiti Malaysia Sabah)

  • Azra C. Ghani

    (Imperial College London)

  • Chris Drakeley

    (London School of Hygiene and Tropical Medicine)

Abstract

Reported incidence of the zoonotic malaria Plasmodium knowlesi has markedly increased across Southeast Asia and threatens malaria elimination. Nonzoonotic transmission of P. knowlesi has been experimentally demonstrated, but it remains unknown whether nonzoonotic transmission is contributing to increases in P. knowlesi cases. Here, we adapt model-based inference methods to estimate RC, individual case reproductive numbers, for P. knowlesi, P. falciparum and P. vivax human cases in Malaysia from 2012–2020 (n = 32,635). Best fitting models for P. knowlesi showed subcritical transmission (RC 1) was estimated historically for P. falciparum and P. vivax, with declines in RC estimates observed over time consistent with local elimination. Together, this suggests sustained nonzoonotic P. knowlesi transmission is highly unlikely and that new approaches are urgently needed to control spillover risks.

Suggested Citation

  • Kimberly M. Fornace & Hillary M. Topazian & Isobel Routledge & Syafie Asyraf & Jenarun Jelip & Kim A. Lindblade & Mohammad Saffree Jeffree & Pablo Ruiz Cuenca & Samir Bhatt & Kamruddin Ahmed & Azra C., 2023. "No evidence of sustained nonzoonotic Plasmodium knowlesi transmission in Malaysia from modelling malaria case data," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38476-8
    DOI: 10.1038/s41467-023-38476-8
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-38476-8
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-38476-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Isobel Routledge & José Eduardo Romero Chevéz & Zulma M. Cucunubá & Manuel Gomez Rodriguez & Caterina Guinovart & Kyle B. Gustafson & Kammerle Schneider & Patrick G.T. Walker & Azra C. Ghani & Samir B, 2018. "Estimating spatiotemporally varying malaria reproduction numbers in a near elimination setting," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    2. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    3. Lindgren, Finn & Rue, Håvard, 2015. "Bayesian Spatial Modelling with R-INLA," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i19).
    4. Katelyn M Gostic & Lauren McGough & Edward B Baskerville & Sam Abbott & Keya Joshi & Christine Tedijanto & Rebecca Kahn & Rene Niehus & James A Hay & Pablo M De Salazar & Joel Hellewell & Sophie Meaki, 2020. "Practical considerations for measuring the effective reproductive number, Rt," PLOS Computational Biology, Public Library of Science, vol. 16(12), pages 1-21, December.
    5. Nathan D. Wolfe & Claire Panosian Dunavan & Jared Diamond, 2007. "Origins of major human infectious diseases," Nature, Nature, vol. 447(7142), pages 279-283, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cho, Daegon & Hwang, Youngdeok & Park, Jongwon, 2018. "More buzz, more vibes: Impact of social media on concert distribution," Journal of Economic Behavior & Organization, Elsevier, vol. 156(C), pages 103-113.
    2. Andre Python & Andreas Bender & Marta Blangiardo & Janine B. Illian & Ying Lin & Baoli Liu & Tim C.D. Lucas & Siwei Tan & Yingying Wen & Davit Svanidze & Jianwei Yin, 2022. "A downscaling approach to compare COVID‐19 count data from databases aggregated at different spatial scales," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 202-218, January.
    3. Jacqueline D. Seufert & Andre Python & Christoph Weisser & Elías Cisneros & Krisztina Kis‐Katos & Thomas Kneib, 2022. "Mapping ex ante risks of COVID‐19 in Indonesia using a Bayesian geostatistical model on airport network data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2121-2155, October.
    4. Johnson, Blair T. & Sisti, Anthony & Bernstein, Mary & Chen, Kun & Hennessy, Emily A. & Acabchuk, Rebecca L. & Matos, Michaela, 2021. "Community-level factors and incidence of gun violence in the United States, 2014–2017," Social Science & Medicine, Elsevier, vol. 280(C).
    5. Zhang, Shen & Liu, Xin & Tang, Jinjun & Cheng, Shaowu & Qi, Yong & Wang, Yinhai, 2018. "Spatio-temporal modeling of destination choice behavior through the Bayesian hierarchical approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 537-551.
    6. Paige, John & Fuglstad, Geir-Arne & Riebler, Andrea & Wakefield, Jon, 2022. "Bayesian multiresolution modeling of georeferenced data: An extension of ‘LatticeKrig’," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    7. Daniela Castro‐Camilo & Raphaël Huser & Håvard Rue, 2022. "Practical strategies for generalized extreme value‐based regression models for extremes," Environmetrics, John Wiley & Sons, Ltd., vol. 33(6), September.
    8. Aaron Osgood‐Zimmerman & Jon Wakefield, 2023. "A Statistical Review of Template Model Builder: A Flexible Tool for Spatial Modelling," International Statistical Review, International Statistical Institute, vol. 91(2), pages 318-342, August.
    9. William Gonzalez Daza & Renata L. Muylaert & Thadeu Sobral-Souza & Victor Lemes Landeiro, 2023. "Malaria Risk Drivers in the Brazilian Amazon: Land Use—Land Cover Interactions and Biological Diversity," IJERPH, MDPI, vol. 20(15), pages 1-16, August.
    10. Sameh Abdulah & Yuxiao Li & Jian Cao & Hatem Ltaief & David E. Keyes & Marc G. Genton & Ying Sun, 2023. "Large‐scale environmental data science with ExaGeoStatR," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.
    11. John M. Humphreys & Robert B. Srygley & David H. Branson, 2022. "Geographic Variation in Migratory Grasshopper Recruitment under Projected Climate Change," Geographies, MDPI, vol. 2(1), pages 1-19, January.
    12. John M. Humphreys, 2022. "Amplification in Time and Dilution in Space: Partitioning Spatiotemporal Processes to Assess the Role of Avian-Host Phylodiversity in Shaping Eastern Equine Encephalitis Virus Distribution," Geographies, MDPI, vol. 2(3), pages 1-16, July.
    13. Waterman, I. & Marek, L. & Ahuriri-Driscoll, A. & Mohammed, J. & Epton, M. & Hobbs, M., 2024. "Investigating the spatial and temporal variation of vape retailer provision in New Zealand: A cross-sectional and nationwide study," Social Science & Medicine, Elsevier, vol. 349(C).
    14. Álvaro Briz-Redón, 2021. "Respondent Burden Effects on Item Non-Response and Careless Response Rates: An Analysis of Two Types of Surveys," Mathematics, MDPI, vol. 9(17), pages 1-16, August.
    15. Dong Liang & Genevieve Nesslage & Michael Wilberg & Thomas Miller, 2017. "Bayesian Calibration of Blue Crab (Callinectes sapidus) Abundance Indices Based on Probability Surveys," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(4), pages 481-497, December.
    16. Silius M. Vandeskog & Sara Martino & Daniela Castro-Camilo & Håvard Rue, 2022. "Modelling Sub-daily Precipitation Extremes with the Blended Generalised Extreme Value Distribution," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(4), pages 598-621, December.
    17. Humphreys, John M. & Srygley, Robert B. & Lawton, Douglas & Hudson, Amy R. & Branson, David H., 2022. "Grasshoppers exhibit asynchrony and spatial non-stationarity in response to the El Niño/Southern and Pacific Decadal Oscillations," Ecological Modelling, Elsevier, vol. 471(C).
    18. Carlos Díaz-Avalos & Pablo Juan & Somnath Chaudhuri & Marc Sáez & Laura Serra, 2020. "Association between the New COVID-19 Cases and Air Pollution with Meteorological Elements in Nine Counties of New York State," IJERPH, MDPI, vol. 17(23), pages 1-18, December.
    19. Beręsewicz Maciej, 2019. "Correlates of Representation Errors in Internet Data Sources for Real Estate Market," Journal of Official Statistics, Sciendo, vol. 35(3), pages 509-529, September.
    20. Deslatte, Aaron & Scott, Tyler A. & Carter, David P., 2019. "Specialized governance and regional land-use outcomes: A spatial analysis of Florida community development districts," Land Use Policy, Elsevier, vol. 83(C), pages 227-239.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38476-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.