Effects of individual variation and seasonal vaccination on disease risks

Effects of individual variation and seasonal vaccination on disease risks | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Biological Sciences - Article Effects of individual variation and seasonal vaccination on disease risks William Hart, Jina Amin, Hyeongki Park, Kosaku Kitagawa, Yong Dam Jeong, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6193835/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Sep, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Estimates of the risk of a large infectious disease outbreak resulting from the introduction of a pathogen into a population are valuable for planning public health measures. Two key factors affecting outbreak risk estimates are variations in transmission between individuals (e.g., “superspreaders”) (1) and over time (e.g., through seasonality (2,3) or changing population immunity, such as through vaccination (4)). However, existing outbreak risk estimation frameworks do not consider both features simultaneously. Here we develop an approach for estimating outbreak risks that accounts for both individual heterogeneity and time dependence. 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 that incorporates an individual-level model of vaccine-induced antibody dynamics (5–7). Our results indicate that a high outbreak risk is possible near the start of annual vaccine distribution, when population immunity is low, which can be mitigated by distributing vaccines over a longer period. A longer distribution period is particularly beneficial in scenarios with high vaccine coverage and/or effectiveness, and if seasonality in transmission is limited. These insights are applicable to routine vaccination campaigns against COVID-19 and other diseases, particularly in vulnerable populations in which outbreak prevention is critical. Health sciences/Diseases/Infectious diseases/Viral infection Physical sciences/Mathematics and computing/Applied mathematics Health sciences/Medical research/Epidemiology Full Text Additional Declarations There is NO Competing Interest. Supplementary Files ExtendedDataFigures.pdf Extended Data Figures 1-5 SupplementaryMethods.pdf Supplementary Methods ExtendedDataTable.pdf Extended Data Table 1 Cite Share Download PDF Status: Published Journal Publication published 26 Sep, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6193835","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Biological Sciences - Article","associatedPublications":[],"authors":[{"id":433156219,"identity":"ec70ac14-c8c6-4694-a876-78d660264423","order_by":0,"name":"William 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