Quantifying the impact of a broadly protective sarbecovirus vaccine in a future SARS-X pandemic

Charles Whittaker (), Gregory Barnsley, Daniela Olivera Mesa, Victoria Cox, Daniel J. Laydon, Chee Wah Tan, Feng Zhu, Rob Johnson, Patrick Doohan, Lilith K. Whittles, Gemma Nedjati-Gilani, Peter Winskill, Alexandra B. Hogan, Arminder Deol, Christinah Mukandavire, Katharina Hauck, David Chien Boon Lye, Lin-Fa Wang, Oliver J. Watson and Azra C. Ghani ()
Additional contact information
Charles Whittaker: Imperial College London
Gregory Barnsley: London School of Hygiene and Tropical Medicine
Daniela Olivera Mesa: Imperial College London
Victoria Cox: Imperial College London
Daniel J. Laydon: Imperial College London
Chee Wah Tan: Duke-NUS Medical School
Feng Zhu: National University of Singapore
Rob Johnson: Imperial College London
Patrick Doohan: Imperial College London
Lilith K. Whittles: Imperial College London
Gemma Nedjati-Gilani: Imperial College London
Peter Winskill: Imperial College London
Alexandra B. Hogan: Imperial College London
Arminder Deol: Coalition for Epidemics Preparedness Innovations
Christinah Mukandavire: Coalition for Epidemics Preparedness Innovations
Katharina Hauck: Imperial College London
David Chien Boon Lye: National Centre for Infectious Diseases
Lin-Fa Wang: Duke-NUS Medical School
Oliver J. Watson: Imperial College London
Azra C. Ghani: Imperial College London

Nature Communications, 2025, vol. 16, issue 1, 1-12

Abstract: Abstract COVID-19 has underscored the need for more timely access to vaccines during future pandemics. This has motivated development of broad-spectrum vaccines providing protection against entire viral families, which could be stockpiled and deployed rapidly following detection. Using mathematical modelling, we assess the utility of a broadly protective sarbecovirus vaccine during a hypothetical SARS-X outbreak, for a range of implementation strategies including ring-vaccination, spatial-targeting and mass vaccination of high-risk groups. Broadly protective sarbecovirus vaccine ring- or spatial strategies alone are insufficient to contain epidemics driven by a SARS-CoV-2-like virus, but when paired with rapid isolation and quarantine, can achieve containment of a SARS-CoV-1-like virus. Where suppression fails, broadly protective sarbecovirus vaccine utilisation still reduces the effective reproduction number and slows epidemic growth - buying valuable time for health-system response and virus-specific vaccine development. Vaccination of high-risk populations with the broadly protective sarbecovirus vaccine ahead of virus-specific vaccine availability could reduce mortality and enable shorter and less stringent non-pharmaceutical interventions to be imposed; results are sensitive to vaccine properties (e.g., efficacy), health system capabilities (e.g. rollout speed) and timeline to virus-specific vaccine availability. Our modelling suggests that broadly protective sarbecovirus vaccine delivery to those aged 60+ years could have averted 21-78 % of COVID-19 deaths during the pandemic’s first year, depending on the size of the stockpile. Realising this potential impact will require investment in manufacturing, delivery capacity and equitable access ahead of future pandemics.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-025-63399-x Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-63399-x

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-025-63399-x

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().