Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance Data
BackgroundContact tracing and intensive testing programs are essential for controlling the spread of COVID-19. However, conventional contact tracing is resource intensive and may not result in the tracing of all cases due to recall bias and cases not knowing the identity of s...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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JMIR Publications
2021-11-01
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| Series: | JMIR Public Health and Surveillance |
| Online Access: | https://publichealth.jmir.org/2021/11/e30968 |
| _version_ | 1797735511660429312 |
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| author | Ka Chun Chong Katherine Jia Shui Shan Lee Chi Tim Hung Ngai Sze Wong Francisco Tsz Tsun Lai Nancy Chau Carrie Ho Kwan Yam Tsz Yu Chow Yuchen Wei Zihao Guo Eng Kiong Yeoh |
| author_facet | Ka Chun Chong Katherine Jia Shui Shan Lee Chi Tim Hung Ngai Sze Wong Francisco Tsz Tsun Lai Nancy Chau Carrie Ho Kwan Yam Tsz Yu Chow Yuchen Wei Zihao Guo Eng Kiong Yeoh |
| author_sort | Ka Chun Chong |
| collection | DOAJ |
| description |
BackgroundContact tracing and intensive testing programs are essential for controlling the spread of COVID-19. However, conventional contact tracing is resource intensive and may not result in the tracing of all cases due to recall bias and cases not knowing the identity of some close contacts. Few studies have reported the epidemiological features of cases not identified by contact tracing (“unlinked cases”) or described their potential roles in seeding community outbreaks.
ObjectiveFor this study, we characterized the role of unlinked cases in the epidemic by comparing their epidemiological profile with the linked cases; we also estimated their transmission potential across different settings.
MethodsWe obtained rapid surveillance data from the government, which contained the line listing of COVID-19 confirmed cases during the first three waves in Hong Kong. We compared the demographics, history of chronic illnesses, epidemiological characteristics, clinical characteristics, and outcomes of linked and unlinked cases. Transmission potentials in different settings were assessed by fitting a negative binomial distribution to the observed offspring distribution.
ResultsTime interval from illness onset to hospital admission was longer among unlinked cases than linked cases (median 5.00 days versus 3.78 days; P<.001), with a higher proportion of cases whose condition was critical or serious (13.0% versus 8.2%; P<.001). The proportion of unlinked cases was associated with an increase in the weekly number of local cases (P=.049). Cluster transmissions from the unlinked cases were most frequently identified in household settings, followed by eateries and workplaces, with the estimated probability of cluster transmissions being around 0.4 for households and 0.1-0.3 for the latter two settings.
ConclusionsThe unlinked cases were positively associated with time to hospital admission, severity of infection, and epidemic size—implying a need to design and implement digital tracing methods to complement current conventional testing and tracing. To minimize the risk of cluster transmissions from unlinked cases, digital tracing approaches should be effectively applied in high-risk socioeconomic settings, and risk assessments should be conducted to review and adjust the policies. |
| first_indexed | 2024-03-12T13:00:08Z |
| format | Article |
| id | doaj.art-19add4c76fbf47a9b25962b0407c640b |
| institution | Directory Open Access Journal |
| issn | 2369-2960 |
| language | English |
| last_indexed | 2024-03-12T13:00:08Z |
| publishDate | 2021-11-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Public Health and Surveillance |
| spelling | doaj.art-19add4c76fbf47a9b25962b0407c640b2023-08-28T19:47:02ZengJMIR PublicationsJMIR Public Health and Surveillance2369-29602021-11-01711e3096810.2196/30968Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance DataKa Chun Chonghttps://orcid.org/0000-0001-5610-1298Katherine Jiahttps://orcid.org/0000-0001-8875-2415Shui Shan Leehttps://orcid.org/0000-0003-1448-765XChi Tim Hunghttps://orcid.org/0000-0003-2103-8377Ngai Sze Wonghttps://orcid.org/0000-0003-3788-8114Francisco Tsz Tsun Laihttps://orcid.org/0000-0002-9121-1959Nancy Chauhttps://orcid.org/0000-0002-4893-9602Carrie Ho Kwan Yamhttps://orcid.org/0000-0001-8353-9711Tsz Yu Chowhttps://orcid.org/0000-0002-1295-6646Yuchen Weihttps://orcid.org/0000-0002-6821-4617Zihao Guohttps://orcid.org/0000-0001-9002-0483Eng Kiong Yeohhttps://orcid.org/0000-0002-1721-9450 BackgroundContact tracing and intensive testing programs are essential for controlling the spread of COVID-19. However, conventional contact tracing is resource intensive and may not result in the tracing of all cases due to recall bias and cases not knowing the identity of some close contacts. Few studies have reported the epidemiological features of cases not identified by contact tracing (“unlinked cases”) or described their potential roles in seeding community outbreaks. ObjectiveFor this study, we characterized the role of unlinked cases in the epidemic by comparing their epidemiological profile with the linked cases; we also estimated their transmission potential across different settings. MethodsWe obtained rapid surveillance data from the government, which contained the line listing of COVID-19 confirmed cases during the first three waves in Hong Kong. We compared the demographics, history of chronic illnesses, epidemiological characteristics, clinical characteristics, and outcomes of linked and unlinked cases. Transmission potentials in different settings were assessed by fitting a negative binomial distribution to the observed offspring distribution. ResultsTime interval from illness onset to hospital admission was longer among unlinked cases than linked cases (median 5.00 days versus 3.78 days; P<.001), with a higher proportion of cases whose condition was critical or serious (13.0% versus 8.2%; P<.001). The proportion of unlinked cases was associated with an increase in the weekly number of local cases (P=.049). Cluster transmissions from the unlinked cases were most frequently identified in household settings, followed by eateries and workplaces, with the estimated probability of cluster transmissions being around 0.4 for households and 0.1-0.3 for the latter two settings. ConclusionsThe unlinked cases were positively associated with time to hospital admission, severity of infection, and epidemic size—implying a need to design and implement digital tracing methods to complement current conventional testing and tracing. To minimize the risk of cluster transmissions from unlinked cases, digital tracing approaches should be effectively applied in high-risk socioeconomic settings, and risk assessments should be conducted to review and adjust the policies.https://publichealth.jmir.org/2021/11/e30968 |
| spellingShingle | Ka Chun Chong Katherine Jia Shui Shan Lee Chi Tim Hung Ngai Sze Wong Francisco Tsz Tsun Lai Nancy Chau Carrie Ho Kwan Yam Tsz Yu Chow Yuchen Wei Zihao Guo Eng Kiong Yeoh Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance Data JMIR Public Health and Surveillance |
| title | Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance Data |
| title_full | Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance Data |
| title_fullStr | Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance Data |
| title_full_unstemmed | Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance Data |
| title_short | Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance Data |
| title_sort | characterization of unlinked cases of covid 19 and implications for contact tracing measures retrospective analysis of surveillance data |
| url | https://publichealth.jmir.org/2021/11/e30968 |
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