{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T02:45:02Z","timestamp":1751510702148,"version":"3.37.3"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T00:00:00Z","timestamp":1631059200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Health and Medical Research Fund of Food and Health Bureau"},{"name":"Hong Kong Special Administrative Region Government","award":["COVID190105","INF-CUHK-1","19181132"],"award-info":[{"award-number":["COVID190105","INF-CUHK-1","19181132"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,10,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Contact tracing of reported infections could enable close contacts to be identified, tested, and quarantined for controlling further spread. This strategy has been well demonstrated in the surveillance and control of COVID-19 (coronavirus disease 2019) epidemics. This study aims to leverage contact tracing data to investigate the degree of spread and the formation of transmission cascades composing of multiple clusters.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>An algorithm on mining relationships between clusters for network analysis is proposed with 3 steps: horizontal edge creation, vertical edge consolidation, and graph reduction. The constructed network was then analyzed with information diffusion metrics and exponential-family random graph modeling. With categorization of clusters by exposure setting, the metrics were compared among cascades to identify associations between exposure settings and their network positions within the cascade using Mann-Whitney U test.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Experimental results illustrated that transmission cascades containing or seeded by daily activity clusters spread faster while those containing social activity clusters propagated farther. Cascades involving work or study environments consisted of more clusters, which had a higher transmission range and scale. Social activity clusters were more likely to be connected, whereas both residence and healthcare clusters did not preferentially link to clusters belonging to the same exposure setting.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>The proposed algorithm could contribute to in-depth epidemiologic investigation of infectious disease transmission to support targeted nonpharmaceutical intervention policies for COVID-19 epidemic control.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocab175","type":"journal-article","created":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T19:11:26Z","timestamp":1628104286000},"page":"2385-2392","source":"Crossref","is-referenced-by-count":8,"title":["Mining relationships between transmission clusters from contact tracing data: An application for investigating COVID-19 outbreak"],"prefix":"10.1093","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2855-5038","authenticated-orcid":false,"given":"Tsz Ho","family":"Kwan","sequence":"first","affiliation":[{"name":"Stanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Shatin, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ngai Sze","family":"Wong","sequence":"additional","affiliation":[{"name":"Stanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Shatin, Hong Kong"},{"name":"Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eng-Kiong","family":"Yeoh","sequence":"additional","affiliation":[{"name":"Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Shatin, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shui Shan","family":"Lee","sequence":"additional","affiliation":[{"name":"Stanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Shatin, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2021,9,8]]},"reference":[{"issue":"9","key":"2021101218234834000_ocab175-B1","doi-asserted-by":"crossref","first-page":"1156","DOI":"10.1001\/jamainternmed.2020.2020","article-title":"Contact tracing assessment of COVID-19 transmission dynamics in Taiwan and risk at different exposure periods before and after symptom onset","volume":"180","author":"Cheng","year":"2020","journal-title":"JAMA Intern Med"},{"issue":"1","key":"2021101218234834000_ocab175-B2","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1080\/22221751.2020.1718554","article-title":"Incorporation of information diffusion model for enhancing analyses in HIV molecular 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