Investigating setting-specific superspreading potential and generation intervals of COVID-19 in Hong Kong

Investigating setting-specific superspreading potential and generation intervals of COVID-19 in Hong Kong | 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 Article Investigating setting-specific superspreading potential and generation intervals of COVID-19 in Hong Kong Benjamin Cowling, Dongxuan Chen, Dillon Adam, Yiu-Chung Lau, Dong Wang, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4605560/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Jul, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Superspreading is an important feature of SARS-CoV-2, though few studies have investigated quantitatively how transmission characteristics can vary by setting. Using detailed clustering data comprising 8635 SARS-CoV-2 cases confirmed in Hong Kong between 2020–2021 and a negative binomial cluster size model, we estimate the mean number of new infections expected in a cluster C Z and the degree of overdispersion ( k ) by setting. Estimates of C Z ranged between 0.3–6.1 across eight distinct transmission settings. Close-social indoor (e.g. bars and clubs) and elderly care home settings had the highest C Z around 6, meaning for every introduction an average of six new infections is expected. Overdispersion also differed by setting, ranging from extremely heterogeneous ( k = 0.05) to less heterogeneous ( k = 1), and was highest in retail, close-social indoor, and care homes settings ( k < 0.1), where lower values of k indicate higher superspreading potential. We found that the mean generation interval (GI) also varied by setting (range: 4.4–7.2 days), and settings with shorter mean GIs were associated with smaller cluster sizes. Our results explicitly quantify and demonstrate that superspreading potential and transmission parameters such as the GI can vary across settings, which highlights the need of setting-specific interventions for effective outbreak control. Biological sciences/Immunology/Infectious diseases Biological sciences/Immunology Figures Figure 1 Figure 2 Figure 3 Full Text Additional Declarations Yes there is potential Competing Interest. BJC consults for AstraZeneca, Fosun Pharma, GSK, Haleon, Moderna, Novavax, Pfizer, Roche and Sanofi Pasteur. The authors report no other potential conflicts of interest. Supplementary Files Supplementaryclean.pdf nrreportingsummary.pdf Cite Share Download PDF Status: Published Journal Publication published 01 Jul, 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-4605560","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":318394208,"identity":"5a0f33a7-6248-4ae8-a4e1-64ea9a77ee75","order_by":0,"name":"Benjamin Cowling","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsElEQVRIiWNgGAWjYBACAxDxAEjyS7AxMDA2JBCpJQFISs4gTQuIcYNYLebsh49JJBTcsdt8uy1NgnFHGmEtlj1paRIJBs+St905dkyC8UwOEQ67wWN2I8HgcLLZjfQ2Cca2ChK0GM8gVYudgUQa0GFtRDgM6Jf0H0AtCRI30pItEtuI8D4wxA4bfPhz2J5/RprhjY9tyYS1wEBiA4hMIF4DA4M9KYpHwSgYBaNghAEAYjs8ITdRIlcAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-6297-7154","institution":"University of Hong Kong","correspondingAuthor":true,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Cowling","suffix":""},{"id":318394209,"identity":"53db8537-65cf-4a7e-b716-b5f9290ac4aa","order_by":1,"name":"Dongxuan Chen","email":"","orcid":"","institution":"The University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Dongxuan","middleName":"","lastName":"Chen","suffix":""},{"id":318394210,"identity":"6f0aebc9-83fc-4763-9c8b-8d0eb2390809","order_by":2,"name":"Dillon Adam","email":"","orcid":"","institution":"The University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Dillon","middleName":"","lastName":"Adam","suffix":""},{"id":318394211,"identity":"3f7eda12-e8e9-4f00-85f2-8a7d47b19497","order_by":3,"name":"Yiu-Chung Lau","email":"","orcid":"https://orcid.org/0000-0001-6618-9094","institution":"University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Yiu-Chung","middleName":"","lastName":"Lau","suffix":""},{"id":318394212,"identity":"af78db57-0821-4ec8-9654-9dc6793b522b","order_by":4,"name":"Dong Wang","email":"","orcid":"","institution":"University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Dong","middleName":"","lastName":"Wang","suffix":""},{"id":318394213,"identity":"39e894a2-eb27-4bf3-8d35-d29579fbfc73","order_by":5,"name":"Wey Wen Lim","email":"","orcid":"https://orcid.org/0000-0001-8514-2048","institution":"The University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Wey","middleName":"Wen","lastName":"Lim","suffix":""},{"id":318394214,"identity":"7150f5ec-eb19-4191-bc36-bad2e0f9fc34","order_by":6,"name":"Faith Ho","email":"","orcid":"","institution":"University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Faith","middleName":"","lastName":"Ho","suffix":""},{"id":318394215,"identity":"7ba6d538-29f2-456a-a52b-d9684b4d7397","order_by":7,"name":"Tim Tsang","email":"","orcid":"https://orcid.org/0000-0001-5037-6776","institution":"The University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Tim","middleName":"","lastName":"Tsang","suffix":""},{"id":318394216,"identity":"8bcc40fd-5cc4-4d11-aa52-fee2824136cc","order_by":8,"name":"Eric H. Y. Lau","email":"","orcid":"","institution":"University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"H. Y.","lastName":"Lau","suffix":""},{"id":318394217,"identity":"03285fd3-495c-4e11-b290-501855fba3e3","order_by":9,"name":"Peng Wu","email":"","orcid":"https://orcid.org/0000-0003-1157-9401","institution":"The University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"Wu","suffix":""},{"id":318394218,"identity":"66b925ce-7980-4b24-9688-3e3df64211f2","order_by":10,"name":"Jacco Wallinga","email":"","orcid":"","institution":"National Institute for Public Health and the Environment","correspondingAuthor":false,"prefix":"","firstName":"Jacco","middleName":"","lastName":"Wallinga","suffix":""},{"id":318394219,"identity":"8a83b859-8de2-49ce-8862-14d775469b84","order_by":11,"name":"Sheikh Taslim Ali","email":"","orcid":"https://orcid.org/0000-0002-8631-9076","institution":"The University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Sheikh","middleName":"Taslim","lastName":"Ali","suffix":""}],"badges":[],"createdAt":"2024-06-19 11:26:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4605560/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4605560/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-60591-x","type":"published","date":"2025-07-01T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59031615,"identity":"e72a3de5-e1ff-437a-bb61-70c6bb30bfa9","added_by":"auto","created_at":"2024-06-25 14:11:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":425630,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEmpirical transmission cluster size distribution and cluster category frequency during COVID-19 pandemic in Hong Kong from 23 January 2020 and 15 December 2021.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, Boxplots of cluster size distribution overall and stratified by transmission setting, single index case was counted as size of 1 in each setting. Box showed the inter-quartile range (IQR), bold line within box showed the median, whisker showed upper quartile plus 1.5 times IQR, dots showed the empirical values. The y-axis shows the cluster size at log scale, the numbers under the labels of x-axis indicate number of clusters identified in each transmission setting. Number of clusters involved at least 2 cases in each setting sum together equals to 2214 as in all clusters, while number of single index cases in each setting sum together equals to 1588, but number of single index cases in all clusters is 1576, due to 12 household cluster members were defined as single index cases for care home setting particularly. \u003cstrong\u003eb\u003c/strong\u003e, Histogram of empirical cluster size distribution in each setting.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4605560/v1/64152b2c8d39abf89023a1ba.png"},{"id":59031614,"identity":"6c9c213b-162f-49c4-a417-6351fc5bf927","added_by":"auto","created_at":"2024-06-25 14:11:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":356529,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eJointly estimated dispersion parameters k and mean cluster size 1 + cz in all clusters and in each transmission setting, and visualization of transmission heterogeneity.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, 95% confidence ellipse of jointly estimated k and \u0026nbsp;\u0026nbsp;\u0026nbsp;and the central estimates (as shown by points), for all clusters and in each specific setting; \u003cstrong\u003eb\u003c/strong\u003e, Proportion of clusters with top number of cluster sizes that accounted for 80% of all new infections identified in each specific settingbased on the central estimates of k and \u0026nbsp;\u0026nbsp;(as shown by points), color in red from light to dark indicate proportion in descending order. Note both the x and y-axis are at log scale. Lower values of the dispersion parameter k indicate a more heterogeneous distribution of number of new infections per cluster.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4605560/v1/ae574a8ba77022d20ff9efe9.png"},{"id":59031608,"identity":"8c24e74f-8056-4cea-8fb4-137df1bc6f13","added_by":"auto","created_at":"2024-06-25 14:11:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":331319,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEstimated generation interval distribution in each transmission setting. a, \u003c/strong\u003eEstimated mean generation interval (as shown in points) with 95% bootstrap confidence interval (as shown in error bars) in each transmission setting, horizontal dashed line indicate pooled mean generation interval of all clusters; \u003cstrong\u003eb, \u003c/strong\u003eEstimated standard deviation of the generation interval (as shown in points) with 95% bootstrap confidence interval (as shown in error bars) in each transmission setting, horizontal dashed line indicate pooled standard deviation of all clusters; \u003cstrong\u003ec\u003c/strong\u003e, Probability density of inferred generation interval distribution based on central estimates in each transmission setting, density plotted by dashed line indicate inferred distribution based on pooled mean and standard deviation of all clusters. Colors in green, grey, orange, blue, teal, purple, pink and brown represent all clusters, households, office work, restaurants, manual labour work, retail \u0026amp; leisure, nosocomial, close-social indoor and care homes respectively.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4605560/v1/e43b69cb3cda4f144dceba74.png"},{"id":85832530,"identity":"17da6214-1455-4fce-b51d-937f0085290f","added_by":"auto","created_at":"2025-07-02 07:59:48","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1740113,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptclean.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4605560/v1_covered_e1ff530c-1289-48b1-9419-63bd0e7796e3.pdf"},{"id":59031616,"identity":"a3f472dc-bceb-4712-95e1-a3275a358100","added_by":"auto","created_at":"2024-06-25 14:11:31","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1544894,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Supplementaryclean.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4605560/v1/5edf68be1d0236ac8b97b110.pdf"},{"id":59031617,"identity":"ccba90c0-40ad-4cd2-80f6-634c4ec9ea1c","added_by":"auto","created_at":"2024-06-25 14:11:32","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1646736,"visible":true,"origin":"","legend":"","description":"","filename":"nrreportingsummary.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4605560/v1/a24689b48d015161640d5033.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nBJC consults for AstraZeneca, Fosun Pharma, GSK, Haleon, Moderna, Novavax, Pfizer, Roche and Sanofi Pasteur. The authors report no other potential conflicts of interest.","formattedTitle":"Investigating setting-specific superspreading potential and generation intervals of COVID-19 in Hong Kong","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4605560/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4605560/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSuperspreading is an important feature of SARS-CoV-2, though few studies have investigated quantitatively how transmission characteristics can vary by setting. Using detailed clustering data comprising 8635 SARS-CoV-2 cases confirmed in Hong Kong between 2020–2021 and a negative binomial cluster size model, we estimate the mean number of new infections expected in a cluster C\u003csub\u003eZ\u003c/sub\u003e and the degree of overdispersion (\u003cem\u003ek\u003c/em\u003e) by setting. Estimates of C\u003csub\u003eZ\u003c/sub\u003e ranged between 0.3–6.1 across eight distinct transmission settings. Close-social indoor (e.g. bars and clubs) and elderly care home settings had the highest C\u003csub\u003eZ\u003c/sub\u003e around 6, meaning for every introduction an average of six new infections is expected. Overdispersion also differed by setting, ranging from extremely heterogeneous (\u003cem\u003ek\u003c/em\u003e = 0.05) to less heterogeneous (\u003cem\u003ek\u003c/em\u003e = 1), and was highest in retail, close-social indoor, and care homes settings (\u003cem\u003ek\u003c/em\u003e \u0026lt; 0.1), where lower values of \u003cem\u003ek\u003c/em\u003e indicate higher superspreading potential. We found that the mean generation interval (GI) also varied by setting (range: 4.4–7.2 days), and settings with shorter mean GIs were associated with smaller cluster sizes. Our results explicitly quantify and demonstrate that superspreading potential and transmission parameters such as the GI can vary across settings, which highlights the need of setting-specific interventions for effective outbreak control.\u003c/p\u003e","manuscriptTitle":"Investigating setting-specific superspreading potential and generation intervals of COVID-19 in Hong Kong","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-25 14:11:22","doi":"10.21203/rs.3.rs-4605560/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"227adbd4-251d-4b18-bdb8-e4fa28e34d1c","owner":[],"postedDate":"June 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33665626,"name":"Biological sciences/Immunology/Infectious diseases"},{"id":33665627,"name":"Biological sciences/Immunology"}],"tags":[],"updatedAt":"2025-07-02T07:59:38+00:00","versionOfRecord":{"articleIdentity":"rs-4605560","link":"https://doi.org/10.1038/s41467-025-60591-x","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-07-01 04:00:00","publishedOnDateReadable":"July 1st, 2025"},"versionCreatedAt":"2024-06-25 14:11:22","video":"","vorDoi":"10.1038/s41467-025-60591-x","vorDoiUrl":"https://doi.org/10.1038/s41467-025-60591-x","workflowStages":[]},"version":"v1","identity":"rs-4605560","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4605560","identity":"rs-4605560","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}