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Epidemic Models of Contact Tracing: Systematic Review of Transmission Studies of Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome
Open accessAbstract
The emergence and reemergence of coronavirus epidemics sparked renewed concerns from global epidemiology researchers and public health administrators. Mathematical models that represented how contact tracing and follow-up may control Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) transmissions were developed for evaluating different infection control interventions, estimating likely number of infections as well as facilitating understanding of their likely epidemiology. We reviewed mathematical models for contact tracing and follow-up control measures of SARS and MERS transmission. Model characteristics, epidemiological parameters and intervention parameters used in the mathematical models from seven studies were summarized. A major concern identified in future epidemics is whether public health administrators can collect all the required data for building epidemiological models in a short period of time during the early phase of an outbreak. Also, currently available models do not explicitly model constrained resources. We urge for closed-loop communication between public health administrators and modelling researchers to come up with guidelines to delineate the collection of the required data in the midst of an outbreak and the inclusion of additional logistical details in future similar models.
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“In conclusion, when SARS-CoV-2 was first identified, initial assessments of its potential epidemic impact and intervention options were informed by epidemiological and modelling analyses.”
From Severe acute respiratory syndrome (SARS) mathematical models and disease parameters: a systematic review (2025) · cites this paper as [26]
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“The analyses, in the absence of characterisation of the new coronavirus, assumed that its natural history and epidemiology (eg, degree of superspreading) would be similar to those of SARS-CoV-1 and MERS-CoV.25,26,129,130”
From Severe acute respiratory syndrome (SARS) mathematical models and disease parameters: a systematic review (2025) · cites this paper as [26]
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Cited by
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Tang, B., Wang, X., Li, Q., Bragazzi, N. L., Tang, S., Xiao, Y., & Wu, J. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9020462 · Cited by 1,431
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BackgroundCommunity Responses during Early Phase of COVID-19 Epidemic, Hong Kong
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Estimate of the Basic Reproduction Number for COVID-19: A Systematic Review and Meta-analysis
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Background
Metadata
- Authors
- Kwok, K. O., Tang, A., Wei, V. W. I., Park, W. H., Yeoh, E. K., & Riley, S.
- Affiliations
- Chinese University of Hong Kong (HK)
- Sungkyunkwan University (KR)
- Imperial College London (GB)
- Corresponding author
- Kwok, Kin On
- Tang, Arthur
- Venue
- Computational and Structural Biotechnology Journal
- Published
- 2019-01
- Volume
- 17
- Pages
- 186-194
- ISSN
- 2001-0370 (ISSN-L)
- PMC
- PMC6376160
- OpenAlex
- W2913820390
- Semantic Scholar
- 3baedc51f6e23ad1e8bf4b65980bd40e161a148f
- Cited by
- 172
- References
- 46
- Citations by year
- 2026: 2 · 2025: 9 · 2024: 10 · 2023: 15 · 2022: 22 · 2021: 53 · 2020: 59 · 2019: 1
- FWCI
- 5.52
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computational and Structural Biotechnology Journal (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Spiral (Imperial College London) (submittedVersion, cc-by-nc-nd)
- Funders
- Wellcome Trust (200861/Z/16/Z)
- National Institute of General Medical Sciences (MIDAS U01 GM110721-01)
- Health and Medical Research Fund (17160302)
- National Institute for Health Research
- Topics
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical and Theoretical Epidemiology and Ecology Models
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Infectious Diseases › Viral Infections and Outbreaks Research
- Keywords
- contact tracing, follow-up, SARS, MERS, coronavirus transmission, epidemic modeling, mathematical model, infection control interventions, epidemiological parameters, resource constraints, public health administration
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