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Geographical drivers and climate-linked dynamics of Lassa fever in Nigeria

Author

Listed:
  • David W. Redding

    (Zoological Society of London, Regent’s Park
    University College London)

  • Rory Gibb

    (University College London)

  • Chioma C. Dan-Nwafor

    (Nigeria Centre for Disease Control)

  • Elsie A. Ilori

    (Nigeria Centre for Disease Control)

  • Rimamdeyati Usman Yashe

    (Nigeria Centre for Disease Control)

  • Saliu H. Oladele

    (Nigeria Centre for Disease Control
    World Health Organisation)

  • Michael O. Amedu

    (Nigeria Centre for Disease Control)

  • Akanimo Iniobong

    (Nigeria Centre for Disease Control)

  • Lauren A. Attfield

    (Zoological Society of London, Regent’s Park
    University College London
    Imperial College London)

  • Christl A. Donnelly

    (Imperial College London
    University of Oxford)

  • Ibrahim Abubakar

    (University College London)

  • Kate E. Jones

    (Zoological Society of London, Regent’s Park
    University College London)

  • Chikwe Ihekweazu

    (Nigeria Centre for Disease Control)

Abstract

Lassa fever is a longstanding public health concern in West Africa. Recent molecular studies have confirmed the fundamental role of the rodent host (Mastomys natalensis) in driving human infections, but control and prevention efforts remain hampered by a limited baseline understanding of the disease’s true incidence, geographical distribution and underlying drivers. Here, we show that Lassa fever occurrence and incidence is influenced by climate, poverty, agriculture and urbanisation factors. However, heterogeneous reporting processes and diagnostic laboratory access also appear to be important drivers of the patchy distribution of observed disease incidence. Using spatiotemporal predictive models we show that including climatic variability added retrospective predictive value over a baseline model (11% decrease in out-of-sample predictive error). However, predictions for 2020 show that a climate-driven model performs similarly overall to the baseline model. Overall, with ongoing improvements in surveillance there may be potential for forecasting Lassa fever incidence to inform health planning.

Suggested Citation

  • David W. Redding & Rory Gibb & Chioma C. Dan-Nwafor & Elsie A. Ilori & Rimamdeyati Usman Yashe & Saliu H. Oladele & Michael O. Amedu & Akanimo Iniobong & Lauren A. Attfield & Christl A. Donnelly & Ibr, 2021. "Geographical drivers and climate-linked dynamics of Lassa fever in Nigeria," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-25910-y
    DOI: 10.1038/s41467-021-25910-y
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    Cited by:

    1. Mathieu Mateo & Stéphanie Reynard & Natalia Pietrosemoli & Emeline Perthame & Alexandra Journeaux & Kodie Noy & Clara Germain & Xavier Carnec & Caroline Picard & Virginie Borges-Cardoso & Jimmy Hortio, 2023. "Rapid protection induced by a single-shot Lassa vaccine in male cynomolgus monkeys," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    2. Evan A. Eskew & Brian H. Bird & Bruno M. Ghersi & James Bangura & Andrew J. Basinski & Emmanuel Amara & Mohamed A. Bah & Marilyn C. Kanu & Osman T. Kanu & Edwin G. Lavalie & Victor Lungay & Willie Rob, 2024. "Reservoir displacement by an invasive rodent reduces Lassa virus zoonotic spillover risk," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    3. Obiora Cornelius Collins & Kevin Jan Duffy, 2023. "Using Data of a Lassa Fever Epidemic in Nigeria: A Mathematical Model Is Shown to Capture the Dynamics and Point to Possible Control Methods," Mathematics, MDPI, vol. 11(5), pages 1-18, February.

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