Effects of individual variation and seasonal vaccination on disease risks
Abstract
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.
Article Details
Authors (8)
William S. Hart
Wolfson Centre for Mathematical Biology, Mathematical Institute, Mathematical, Physical and Life Sciences Division, University of Oxford
Jina Amin
Hyeongki Park
Kosaku Kitagawa
Yong Dam Jeong
interdisciplinary Biology Laboratory, Division of Biological Science, Graduate School of Science, Nagoya University
Alexander R. Kaye
Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, Faculty of Science, Engineering and Medicine, University of Warwick
Shingo Iwami
interdisciplinary Biology Laboratory, Division of Biological Science, Graduate School of Science, Nagoya University
Robin N. Thompson
Wolfson Centre for Mathematical Biology, Mathematical Institute, Mathematical, Physical and Life Sciences Division, University of Oxford