Conference Abstract | Volume 8, Abstract ELIC2025311 (Oral 107) | Published: 15 Aug 2025
Rory Gibb1, Arminder Deol2, Marouf Dhaikh3, Christian Happi4, Devaraj Gopinathan5, Elise Gallois6, Matt Graham5, Christinah Mukandavire2, Jonathan Heeney7, Ibrahim Abubakar8, Natalie Imirzian6, Ed Lowther5, David Redding6, Danny Scarponi2, Dimitra Salmanidou5, Daniel Storisteanu7, Simon Frost3, Kate E. Jones1,&
1Department of Genetics, Evolution & Environment, University College London (UCL), 2Coalition for Epidemic Preparedness Innovations (CEPI), London, UK, 3London School of Hygiene & Tropical Medicine (LSHTM), 4Redeemer’s University, Nigeria / African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), 5Advanced Research Computing Centre, University College London (UCL), 6Science Department, Natural History Museum, London, 7Department of Veterinary Medicine, University of Cambridge, 8UCL Institute for Global Health, University College London (UCL)
&Corresponding author: Kate E. Jones, Department of Genetics, Evolution & Environment, University College London (UCL). Email: kate.e.jones@ucl.ac.uk
Received: 20 May 2025, Accepted: 09 Aug 2025, Published: 15 Aug 2025
Domain: Infectious Disease Epidemiology
Keywords: Lassa Fever, Forecasting, Vaccination, Zoonoses, Risk Assessment, Public Health Surveillance
©Rory Gibb et al. Journal of Interventional Epidemiology and Public Health (ISSN: 2664-2824). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article: Rory Gibb et al., Forecasting Lassa fever risk to enable smarter, targeted interventions. Journal of Interventional Epidemiology and Public Health. 2025;8(ConfProc5):00107. https://doi.org/10.37432/JIEPH-CONFPRO5-00107
Lassa fever poses a growing public health threat across West Africa, with outbreaks shaped by complex ecological and socio-environmental dynamics. Delays in detection limit the effectiveness of reactive responses. In collaboration with national and international partners, we developed the Sentinel Forecasting System: An open-source platform integrating nowcasts and short-term monthly forecasts to support anticipatory public health action, including vaccine trial planning and outbreak preparedness.
Sentinel combines ecological models of Mastomys natalensis habitat, remotely sensed environmental data (e.g. rainfall, vegetation), population and mobility layers, and surveillance data from Nigeria (2012–2023). A Bayesian hierarchical spatiotemporal model generates nowcasts and monthly forecasts. Outputs informed modelling of routine and reactive vaccination strategies across Nigeria and West Africa, including estimates of vaccine impact, demand, and stockpiling needs.
Sentinel accurately captured seasonal and interannual shifts in risk. Vaccine effectiveness modelling found that routine vaccination before the Lassa season (August–November) could avert up to 70% of severe cases, compared to ~25% with outbreak response starting in January. Targeting high-incidence or environmentally suitable areas offers substantial impact with feasible coverage. Ecological models identified broader spillover zones across West Africa; routine vaccination in these areas or stockpiling (e.g. 1M doses for pregnant people, 35,000 for healthcare workers) would improve protection in hard-to-reach regions.
By integrating diverse data streams into real-time forecasts, Sentinel enables more proactive and targeted Lassa fever interventions. The approach supports smarter decision-making for vaccine trial planning, surveillance, and response. Next steps include regional scale-up and embedding Sentinel within national public health systems.
Menu