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Estimating spatiotemporally varying malaria reproduction numbers in a near elimination setting

Author

Listed:
  • Isobel Routledge

    (Imperial College London)

  • José Eduardo Romero Chevéz

    (Ministry of Health (MINSAL))

  • Zulma M. Cucunubá

    (Imperial College London)

  • Manuel Gomez Rodriguez

    (Max Planck Institute for Software Systems)

  • Caterina Guinovart

    (MACEPA, PATH)

  • Kyle B. Gustafson

    (Institute for Disease Modeling)

  • Kammerle Schneider

    (MACEPA, PATH)

  • Patrick G.T. Walker

    (Imperial College London)

  • Azra C. Ghani

    (Imperial College London)

  • Samir Bhatt

    (Imperial College London)

Abstract

In 2016 the World Health Organization identified 21 countries that could eliminate malaria by 2020. Monitoring progress towards this goal requires tracking ongoing transmission. Here we develop methods that estimate individual reproduction numbers and their variation through time and space. Individual reproduction numbers, Rc, describe the state of transmission at a point in time and differ from mean reproduction numbers, which are averages of the number of people infected by a typical case. We assess elimination progress in El Salvador using data for confirmed cases of malaria from 2010 to 2016. Our results demonstrate that whilst the average number of secondary malaria cases was below one (0.61, 95% CI 0.55–0.65), individual reproduction numbers often exceeded one. We estimate a decline in Rc between 2010 and 2016. However we also show that if importation is maintained at the same rate, the country may not achieve malaria elimination by 2020.

Suggested Citation

  • 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.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-04577-y
    DOI: 10.1038/s41467-018-04577-y
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    Cited by:

    1. 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.

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