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

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, Ibrahim Abubakar, Kate E. Jones and Chikwe Ihekweazu
Additional contact information
David W. Redding: Zoological Society of London, Regent’s Park
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
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
Christl A. Donnelly: Imperial College London
Ibrahim Abubakar: University College London
Kate E. Jones: Zoological Society of London, Regent’s Park
Chikwe Ihekweazu: Nigeria Centre for Disease Control

Nature Communications, 2021, vol. 12, issue 1, 1-10

Abstract: 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.

Date: 2021
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DOI: 10.1038/s41467-021-25910-y

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