Effects of individual variation and seasonal vaccination on disease risks

Estimates of the risk of a large outbreak resulting from pathogen introduction into a population are valuable for planning interventions. Two key factors affecting outbreak risks are variation in transmission between individuals (e.g., superspreading individuals) and change over time (e.g., through seasonality or changing population immunity due to vaccination). Here, we develop an outbreak risk estimation framework that accounts for both features simultaneously. To demonstrate the real-world application of our framework, we consider the design of annual COVID-19 booster vaccination campaigns, using a multi-scale approach incorporating an individual-level model of vaccine-induced antibody dynamics. Near the start of annual vaccine distribution, when population immunity is low, a high outbreak risk is possible; this can be mitigated by distributing vaccines over a longer period. We show that longer distribution periods are particularly beneficial if vaccine coverage and/or effectiveness is high, and if seasonality in transmission is limited.

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Publication Details

Journal
Nature Communications
Published
2025-09-26
DOI
https://doi.org/10.1038/s41467-025-63375-5
Citations
1
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
1.40

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article

Effects of individual variation and seasonal vaccination on disease risks

Hyeongki Park, Robin N. Thompson, William S. Hart, Alexander R. Kaye et al.
1 citations
Nature Communications
SARS-CoV-2 and COVID-19 Research
1.40
article

Effects of individual variation and seasonal vaccination on disease risks

Hyeongki Park, Robin N. Thompson, William S. Hart, Alexander R. Kaye, Yong Dam Jeong, Kosaku Kitagawa, Shingo Iwami, Jubel Amin
article en
1 citations

Abstract

Estimates of the risk of a large outbreak resulting from pathogen introduction into a population are valuable for planning interventions. Two key factors affecting outbreak risks are variation in transmission between individuals (e.g., superspreading individuals) and change over time (e.g., through seasonality or changing population immunity due to vaccination). Here, we develop an outbreak risk estimation framework that accounts for both features simultaneously. To demonstrate the real-world application of our framework, we consider the design of annual COVID-19 booster vaccination campaigns, using a multi-scale approach incorporating an individual-level model of vaccine-induced antibody dynamics. Near the start of annual vaccine distribution, when population immunity is low, a high outbreak risk is possible; this can be mitigated by distributing vaccines over a longer period. We show that longer distribution periods are particularly beneficial if vaccine coverage and/or effectiveness is high, and if seasonality in transmission is limited.

Nature CommunicationsVol. 16(1)
Kyushu University (JP), Kyoto University (JP), University of Warwick (GB), University of Oxford (GB), RIKEN (JP), Mathematical Institute of the Slovak Academy of Sciences (SK), Science Groove (Japan) (JP), Japanese Foundation For Cancer Research (JP), Pusan National University (KR), Nagoya University (JP)
University of Oxford, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 16%
SARS-CoV-2 and COVID-19 Research
1.40
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