Impact of waning immunity against SARS-CoV-2 severity exacerbated by vaccine hesitancy
The SARS-CoV-2 pandemic has generated a considerable number of infections and associated morbidity and mortality across the world. Recovery from these infections, combined with the onset of large-scale vaccination, have led to rapidly-changing population-level immunological landscapes. In turn, these complexities have highlighted a number of important unknowns related to the breadth and strength of immunity following recovery or vaccination. Using simple mathematical models, we investigate the medium-term impacts of waning immunity against severe disease on immuno-epidemiological dynamics. We find that uncertainties in the duration of severity-blocking immunity (imparted by either infection or vaccination) can lead to a large range of medium-term population-level outcomes (i.e. infection characteristics and immune landscapes). Furthermore, we show that epidemiological dynamics are sensitive to the strength and duration of underlying host immune responses; this implies that determining infection levels from hospitalizations requires accurate estimates of these immune parameters. More durable vaccines both reduce these uncertainties and alleviate the burden of SARS-CoV-2 in pessimistic outcomes. However, heterogeneity in vaccine uptake drastically changes immune landscapes toward larger fractions of individuals with waned severity-blocking immunity. In particular, if hesitancy is substantial, more robust vaccines have almost no effects on population-level immuno-epidemiology, even if vaccination rates are compensatorily high among vaccine-adopters. This pessimistic scenario for vaccination heterogeneity arises because those few individuals that are vaccine-adopters are so readily re-vaccinated that the duration of vaccinal immunity has no appreciable consequences on their immune status. Furthermore, we find that this effect is heightened if vaccine-hesitants have increased transmissibility (e.g. due to riskier behavior). Overall, our results illustrate the necessity to characterize both transmission-blocking and severity-blocking immune time scales. Our findings also underline the importance of developing robust next-generation vaccines with equitable mass vaccine deployment.
Authors
- Rachel E. Baker (ORCID: https://orcid.org/0000-0002-2661-8103)
- Andrea L. Graham (ORCID: https://orcid.org/0000-0002-6580-2755)
- Bryan T. Grenfell (ORCID: https://orcid.org/0000-0003-3227-5909)
- Madhav Marathe (ORCID: https://orcid.org/0000-0003-1653-0658)
- Caroline E. Wagner (ORCID: https://orcid.org/0000-0001-5193-2797)
- Mike Boots (ORCID: https://orcid.org/0000-0003-3763-6136)
- Sinead E. Morris (ORCID: https://orcid.org/0000-0001-8626-1698)
- Bryan Lewis (ORCID: https://orcid.org/0000-0003-0793-6082)
- Simon A. Levin (ORCID: https://orcid.org/0000-0002-8216-5639)
- Jeremy Farrar (ORCID: https://orcid.org/0000-0002-2700-623X)
- Chadi M. Saad-Roy (ORCID: https://orcid.org/0000-0002-2217-3071)
- C. Jessica E. Metcalf (ORCID: https://orcid.org/0000-0003-3166-7521)
Institutions
- Princeton University (US)
- University of Exeter (GB)
- Brown University (US)
- Columbia University Irving Medical Center (US)
- Princeton Public Schools (US)
- Miller College (US)
- Biocom (US)
- McGill University (CA)
- University of Virginia (US)
- Wellcome Trust (GB)
- University of California, Berkeley (US)
Publication Details
- Journal
- PLoS Computational Biology
- Published
- 2024-08-05
- DOI
- https://doi.org/10.1371/journal.pcbi.1012211
- Citations
- 11
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 4.35
Funders
- National Science Foundation
- James S. McDonnell Foundation
- Microsoft
- Virginia Department of Health
- Adolph C. and Mary Sprague Miller Institute for Basic Research in Science, University of California Berkeley
- Flu Lab
- C3.ai Digital Transformation Institute
- Centers for Disease Control and Prevention
- Defense Threat Reduction Agency