Details

Autor(en) / Beteiligte

• Hladish, Thomas J
• Pillai, Alexander N
• Pearson, Carl A B
• Toh, Kok Ben
• Tamayo, Andrea C
• Stoltzfus, Arlin
• Longini, Ira M
• Pitzer, Virginia E.

Titel

Evaluating targeted COVID-19 vaccination strategies with agent-based modeling

Ist Teil von

• PLoS computational biology, 2024-05, Vol.20 (5), p.e1012128

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2024

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• We evaluate approaches to vaccine distribution using an agent-based model of human activity and COVID-19 transmission calibrated to detailed trends in cases, hospitalizations, deaths, seroprevalence, and vaccine breakthrough infections in Florida, USA. We compare the incremental effectiveness for four different distribution strategies at four different levels of vaccine supply, starting in late 2020 through early 2022. Our analysis indicates that the best strategy to reduce severe outcomes would be to actively target high disease-risk individuals. This was true in every scenario, although the advantage was greatest for the intermediate vaccine availability assumptions and relatively modest compared to a simple mass vaccination approach under high vaccine availability. Ring vaccination, while generally the most effective strategy for reducing infections, ultimately proved least effective at preventing deaths. We also consider using age group as a practical surrogate measure for actual disease-risk targeting; this approach also outperforms both simple mass distribution and ring vaccination. We find that quantitative effectiveness of a strategy depends on whether effectiveness is assessed after the alpha, delta, or omicron wave. However, these differences in absolute benefit for the strategies do not change the ranking of their performance at preventing severe outcomes across vaccine availability assumptions.