Estimating the effect of self-protection on transmission dynamics of SARS-CoV-2 in Germany in 2021: A modelling study

Estimating the effect of self-protection on transmission dynamics of SARS-CoV-2 in Germany in 2021: A modelling study | 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 Research Article Estimating the effect of self-protection on transmission dynamics of SARS-CoV-2 in Germany in 2021: A modelling study Marvin Schulte, Neele Leithäuser, Jan Mohring This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8553245/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Apr, 2026 Read the published version in BMC Public Health → Version 1 posted 14 You are reading this latest preprint version Abstract Background During the COVID-19 pandemic, German states implemented non pharmaceutical interventions, while individuals also adopted self-initiated protective behavior. Most epidemiological studies tend to focus on one of these aspects, but in reality, both factors influence transmission dynamics simultane ously. In this study, we investigate the effect of self-protection and NPIs on the transmission dynamics of SARS-CoV-2 in Germany during 2021 and identify the corresponding model parameters based on publicly available data. Methods We present a mathematical model that integrates both self-initiated protective behavior and mandated policies. By using infection and intensive care unit data from four German states, we identify all behavioral and some viral parameters, while some are set according to literature values. Since the data alone do not reveal the cause of reduction, we use the different functional structures of self29 protection and non-pharmaceutical interventions to determine their respective influence. Based on these parameters, we conduct counterfactual simulations, modeling the absence of one of the mechanisms, respectively. Results Our findings indicate that both mechanisms substantially reduced transmission. Self-protection re duced the transmission less than mandated policies most of the time, but provided between 67.6 (± 0.69) % and 81.9 (± 0.21) % further reduction of the critical contact rate at highest reported values of intensive care unit occupancy. Through counterfactual simulations, we demonstrate that the absence of policies or self-protection would have resulted in higher case numbers or the need for stronger adaptations. Conclusion The results emphasize the crucial role of self-protection in addition to mandated policies in controlling the spread of the virus. Our research high42 lights the importance of incorporating self-protective behavior in epidemiological models, which are used for policy evaluation. Behavioral-epidemiological model Adaptive behavior Compartmental model Infectious disease dynamics Epidemiology COVID-19 Parameter estimation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 14 Apr, 2026 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Revision requested 23 Feb, 2026 Reviews received at journal 21 Feb, 2026 Reviews received at journal 18 Feb, 2026 Reviews received at journal 17 Feb, 2026 Reviewers agreed at journal 24 Jan, 2026 Reviewers agreed at journal 21 Jan, 2026 Reviewers agreed at journal 21 Jan, 2026 Reviewers agreed at journal 20 Jan, 2026 Reviewers agreed at journal 19 Jan, 2026 Reviewers invited by journal 15 Jan, 2026 Editor invited by journal 14 Jan, 2026 Editor assigned by journal 13 Jan, 2026 Submission checks completed at journal 13 Jan, 2026 First submitted to journal 08 Jan, 2026 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-8553245","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":577091772,"identity":"9c154b54-7ebf-43b3-b040-0c557ce689ba","order_by":0,"name":"Marvin 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Most epidemiological studies tend to focus on one of these \u0026nbsp;aspects, but in reality, both factors influence transmission dynamics simultane ously. In this study, we investigate the effect of self-protection and NPIs on the \u0026nbsp;transmission dynamics of SARS-CoV-2 in Germany during 2021 and identify \u0026nbsp;the corresponding model parameters based on publicly available data. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e We present a mathematical model that integrates both self-initiated protective \u0026nbsp;behavior and mandated policies. By using infection and intensive care unit data \u0026nbsp;from four German states, we identify all behavioral and some viral parameters, \u0026nbsp;while some are set according to literature values. Since the data alone do not \u0026nbsp;reveal the cause of reduction, we use the different functional structures of self29 protection and non-pharmaceutical interventions to determine their respective influence. Based on these parameters, we conduct counterfactual simulations, \u0026nbsp;modeling the absence of one of the mechanisms, respectively. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e Our findings indicate that both mechanisms substantially reduced transmission. \u0026nbsp;Self-protection re duced the transmission less than mandated policies most of \u0026nbsp;the time, but provided between 67.6 (± 0.69) % and 81.9 (± 0.21) % further \u0026nbsp;reduction of the critical contact rate at highest reported values of intensive care \u0026nbsp;unit occupancy. Through counterfactual simulations, we demonstrate that the \u0026nbsp;absence of policies or self-protection would have resulted in higher case numbers \u0026nbsp;or the need for stronger adaptations. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion \u003c/strong\u003eThe results emphasize the crucial role of self-protection in addition \u0026nbsp;to mandated policies in controlling the spread of the virus. Our research high42 lights the importance of incorporating self-protective behavior in epidemiological \u0026nbsp;models, which are used for policy evaluation.\u003c/p\u003e","manuscriptTitle":"Estimating the effect of self-protection on transmission dynamics of SARS-CoV-2 in Germany in 2021: A modelling study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-20 15:33:02","doi":"10.21203/rs.3.rs-8553245/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-23T06:22:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-21T20:44:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-18T17:39:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-17T17:46:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"299554692694446521057763645703780280133","date":"2026-01-24T12:55:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33632133776266957076891101609323109904","date":"2026-01-21T16:55:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81759590402098684467024556878215302850","date":"2026-01-21T13:19:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54657517405836168958221120339463840836","date":"2026-01-21T04:14:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"250695483477365350592994323837896444631","date":"2026-01-19T21:43:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-15T22:13:59+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-14T09:52:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-13T13:06:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-13T13:04:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-01-08T15:36:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3497c63a-2170-46b0-8d66-65fa8f68e0ea","owner":[],"postedDate":"January 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-20T16:04:08+00:00","versionOfRecord":{"articleIdentity":"rs-8553245","link":"https://doi.org/10.1186/s12889-026-27264-w","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2026-04-14 15:59:36","publishedOnDateReadable":"April 14th, 2026"},"versionCreatedAt":"2026-01-20 15:33:02","video":"","vorDoi":"10.1186/s12889-026-27264-w","vorDoiUrl":"https://doi.org/10.1186/s12889-026-27264-w","workflowStages":[]},"version":"v1","identity":"rs-8553245","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8553245","identity":"rs-8553245","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}