Effects of Lockdowns And Its Impacts On Age-Specific Transmission Dynamics of SARS-Cov-2 In Georgia, USA

Effects of Lockdowns And Its Impacts On Age-Specific Transmission Dynamics of SARS-Cov-2 In Georgia, USA | 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 Effects of Lockdowns And Its Impacts On Age-Specific Transmission Dynamics of SARS-Cov-2 In Georgia, USA Max SY Lau, Carol Liu, Aaron Siegler, Patrick Sullivan, Lance A. Waller, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1171299/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Social distancing measures are effective in reducing overall community transmission but much remains unknown about how they have impacted finer-scale dynamics. In particular, much is unknown about how changes of contact patterns and other behaviors including adherence to social distancing, induced by these measures, may have impacted finer-scale transmission dynamics among different age groups. In this paper, we build a stochastic age-specific transmission model to systematically characterize the degree and variation of age-specific transmission dynamics, before and after lifting the lockdown in Georgia, USA. We perform Bayesian (missing-) data-augmentation model inference, leveraging reported age-specific case, seroprevalence and mortality data. We estimate that community-level transmissibility was reduced to 41.2% with 95% CI [39%, 43.8%] of the pre-lockdown level in about a week of the announcement of the shelter-in-place order. Although it subsequently increased after the lockdown was lifted, it only bounced back to 62% [58%, 67.2%] of the pre-lockdown level after about a month. We also find that during the lockdown susceptibility to infection increases with age. Specifically, relative to the oldest age group (>65+), susceptibility for the youngest age group (0-17 years) is 0.13 [0.09, 0.18], and it increases to 0.53 [0.49, 0.59] for 18-44 and 0.75 [0.68, 0.82] for 45- 64. More importantly, our results reveal clear changes of age-specific susceptibility (defined as average risk of getting infected during an infectious contact incorporating age-dependent behavioral factors) after the lockdown was lifted, with a trend largely consistent with reported age-specific adherence levels to social distancing and preventive measures. Specifically, the older groups (>45) (with the highest levels of adherence) appear to have the most significant reductions of susceptibility (e.g., post-lockdown susceptibility reduced to 31.6% [29.3%, 34%] of the estimate before lifting the lockdown for the 65+ group). Finally, we find heterogeneity in case reporting rates among different age groups, with the lowest rate occurring among the 0-18 group (9.7% [6.4%, 19%]). Our results provide a more fundamental understanding of the impacts of stringent lockdown measures, and finer evidence that other social distancing and preventive measures may be effective in reducing SARS-CoV-2 transmission. These results may be exploited to guide more effective implementations of these measures in many current settings (with low vaccination rate globally and emerging variants) and in future potential outbreaks of novel pathogens. reducing transmission adherence effective Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryInformation.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 19 Jan, 2022 Reviews received at journal 04 Jan, 2022 Reviewers agreed at journal 02 Jan, 2022 Reviewers invited by journal 02 Jan, 2022 Editor assigned by journal 02 Jan, 2022 Editor invited by journal 30 Dec, 2021 Submission checks completed at journal 30 Dec, 2021 First submitted to journal 14 Dec, 2021 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-1171299","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":73301682,"identity":"8ac426bf-9d33-454a-bd45-9f5ce745b396","order_by":0,"name":"Max SY Lau","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYLCCBwwMcjA2YwNRWhIYGIxJ15IIU0lYi27/GQOGhJrD6f1ih4995mGwkd1wgIAWsxs5QC3HDufOnJ2WPJuHIc2YCC08QC1sh3M33M4xZuZhOJxIWMt5kMP+HU63h2j5T4SWA0CHJbYdTjCQBms5QISWG2kFBxL70g1n3E5LZpxjkGw8k7DDDm988OGbtTz/7OTDDG8q7GT7CGlhYOAwgKthAgYFMYD9AZzJ+IMoHaNgFIyCUTDSAAB2Y0Rak4FraQAAAABJRU5ErkJggg==","orcid":"","institution":"Rollins School of Public Health, Emory University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Max","middleName":"SY","lastName":"Lau","suffix":""},{"id":73301683,"identity":"46709636-317d-4e57-98b5-b81b6cc60c2f","order_by":1,"name":"Carol Liu","email":"","orcid":"","institution":"Emory University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Carol","middleName":"","lastName":"Liu","suffix":""},{"id":73301684,"identity":"df895991-2f13-4313-a570-4ae16c08b038","order_by":2,"name":"Aaron Siegler","email":"","orcid":"","institution":"Emory University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Aaron","middleName":"","lastName":"Siegler","suffix":""},{"id":73301685,"identity":"9313a551-8205-47fa-acc8-f5ef38405f76","order_by":3,"name":"Patrick Sullivan","email":"","orcid":"","institution":"Emory University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"","lastName":"Sullivan","suffix":""},{"id":73301686,"identity":"269f2a7e-18d5-4fb5-bf6f-467a65072826","order_by":4,"name":"Lance A. Waller","email":"","orcid":"","institution":"Rollins School of Public Health","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lance","middleName":"A.","lastName":"Waller","suffix":""},{"id":73301687,"identity":"0d9a33fe-d59e-4dd3-92d7-82a3f4c3ee67","order_by":5,"name":"Kayoko Shioda","email":"","orcid":"","institution":"Emory University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kayoko","middleName":"","lastName":"Shioda","suffix":""},{"id":73301688,"identity":"332f6dbd-2446-4055-a434-d2f6b04ced91","order_by":6,"name":"Benjamin Lopman","email":"","orcid":"","institution":"Emory University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Lopman","suffix":""}],"badges":[],"createdAt":"2021-12-14 17:59:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1171299/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1171299/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":16959293,"identity":"8373fee4-e395-4570-b10b-f15661044659","added_by":"auto","created_at":"2022-01-03 23:47:51","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":466855,"visible":true,"origin":"","legend":"","description":"","filename":"main.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1171299/v1_covered.pdf"},{"id":16959292,"identity":"a0e30352-a1b2-47e3-a281-f4a13a139600","added_by":"auto","created_at":"2022-01-03 23:47:46","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1461444,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1171299/v1/72b095dcd2d7648940ab616b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEffects of Lockdowns And Its Impacts On Age-Specific Transmission Dynamics of SARS-Cov-2 In Georgia, USA\u003c/p\u003e","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-1171299/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"reducing, transmission, adherence, effective","lastPublishedDoi":"10.21203/rs.3.rs-1171299/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1171299/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSocial distancing measures are effective in reducing overall community transmission but much remains unknown about how they have impacted finer-scale dynamics. In particular, much is unknown about how changes of contact patterns and other behaviors including adherence to social distancing, induced by these measures, may have impacted finer-scale transmission dynamics among different age groups. In this paper, we build a stochastic age-specific transmission model to systematically characterize the degree and variation of age-specific transmission dynamics, before and after lifting the lockdown in Georgia, USA. We perform Bayesian (missing-) data-augmentation model inference, leveraging reported age-specific case, seroprevalence and mortality data. We estimate that community-level transmissibility was reduced to 41.2% with 95% CI [39%, 43.8%] of the pre-lockdown level in about a week of the announcement of the shelter-in-place order. Although it subsequently increased after the lockdown was lifted, it only bounced back to 62% [58%, 67.2%] of the pre-lockdown level after about a month. We also find that during the lockdown susceptibility to infection increases with age. Specifically, relative to the oldest age group (\u0026gt;65+), susceptibility for the youngest age group (0-17 years) is 0.13 [0.09, 0.18], and it increases to 0.53 [0.49, 0.59] for 18-44 and 0.75 [0.68, 0.82] for 45- 64. More importantly, our results reveal clear changes of age-specific susceptibility (defined as average risk of getting infected during an infectious contact incorporating age-dependent behavioral factors) after the lockdown was lifted, with a trend largely consistent with reported age-specific adherence levels to social distancing and preventive measures. Specifically, the older groups (\u0026gt;45) (with the highest levels of adherence) appear to have the most significant reductions of susceptibility (e.g., post-lockdown susceptibility reduced to 31.6% [29.3%, 34%] of the estimate before lifting the lockdown for the 65+ group). Finally, we find heterogeneity in case reporting rates among different age groups, with the lowest rate occurring among the 0-18 group (9.7% [6.4%, 19%]). Our results provide a more fundamental understanding of the impacts of stringent lockdown measures, and finer evidence that other social distancing and preventive measures may be effective in reducing SARS-CoV-2 transmission. These results may be exploited to guide more effective implementations of these measures in many current settings (with low vaccination rate globally and emerging variants) and in future potential outbreaks of novel pathogens.\u003c/p\u003e","manuscriptTitle":"Effects of Lockdowns And Its Impacts On Age-Specific Transmission Dynamics of SARS-Cov-2 In Georgia, USA","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-01-03 23:47:44","doi":"10.21203/rs.3.rs-1171299/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-01-19T07:14:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-01-04T10:47:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6e7cb72a-ee9b-4913-ad1c-28764f63a57c","date":"2022-01-03T02:25:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-01-03T00:30:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-01-02T18:26:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-12-30T12:21:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-12-30T10:26:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2021-12-14T17:44:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"57e8fa9c-ba37-4491-b74b-8c166c3413f7","owner":[],"postedDate":"January 3rd, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-03-07T10:14:13+00:00","versionOfRecord":[],"versionCreatedAt":"2022-01-03 23:47:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1171299","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1171299","identity":"rs-1171299","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}