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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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In the citing paper
“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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Cites
PRISMA-P Group, Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., & Stewart, L. A. (2015) · Systematic Reviews · doi:10.1186/2046-4053-4-1 · Cited by 26,223 · cited 1×
“The current systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis: The PRISMA statement [14].”
Infectious Diseases of Humans: Dynamics and Control
(1992) · Annals of Internal Medicine · doi:10.7326/0003-4819-117-2-174_4 · Cited by 7,819
Evidence of Airborne Transmission of the Severe Acute Respiratory Syndrome Virus
Yu, I. T. S., Li, Y., Wong, T. W., Tam, W., Chan, A., Lee, J. H. W., Leung, D. Y. C., & Ho, T. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa032867 · Cited by 1,255 · cited 1×
“For example, SARS transmission in high-rise buildings among residents of Amoy Gardens suggested possible airborne transmission [46,47] and government officials were prone to political pressures regarding quarantine.”
Riley, S., Fraser, C., Donnelly, C. A., Ghani, A. C., Abu-Raddad, L. J., Hedley, A. J., Leung, G. M., Ho, L., Lam, T.-H., Thach, T., et al. (2003) · Science · doi:10.1126/science.1086478 · Cited by 1,152 · cited 3×
“Quarantine and Isolation Efficiency Contact tracing is shown to be an essential and successful public health tool in reducing the transmission risk of new emerging infectious diseases such as SARS among Hong Kong population [10].”
Self-citationFactors that make an infectious disease outbreak controllable
Fraser, C., Riley, S., Anderson, R. M., & Ferguson, N. M. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307506101 · Cited by 1,144 · cited 10×
“[19] defined a distribution characterizing an individual person who had not been isolated by the time since infection to reflect isolation delay.”
InfluentialSelf-citationDonnelly, C. A., Ghani, A. C., Leung, G. M., Hedley, A. J., Fraser, C., Riley, S., Abu-Raddad, L. J., Ho, L.-M., Thach, T.-Q., Chau, P., et al. (2003) · The Lancet · doi:10.1016/s0140-6736(03)13410-1 · Cited by 940 · cited 2×
“In the 2003 SARS outbreak, it was observed that the time between symptoms onset and hospitalization was 3–5 days, with longer times earlier in the epidemic [27].”
Self-citationChan, J. F., Lau, S. K. P., To, K. K., Cheng, V. C., Woo, P. C. Y., & Yuen, K. (2015) · Clinical Microbiology Reviews · doi:10.1128/cmr.00102-14 · Cited by 894 · cited 1×
“The majority of SARS cases occurred amonghealthcareworkers;while substantial number of MERS cases were patients [3], with most MERS severe cases and mortality being individuals with comorbidities [6].”
Appropriate Models for the Management of Infectious Diseases
Wearing, H. J., Rohani, P., & Keeling, M. J. (2005) · PLoS Medicine · doi:10.1371/journal.pmed.0020174 · Cited by 538
Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study
Chowell, G., Abdirizak, F., Lee, S., Lee, J., Jung, E., Nishiura, H., & Viboud, C. G. (2015) · BMC Medicine · doi:10.1186/s12916-015-0450-0 · Cited by 492 · cited 4×
“The majority of SARS cases occurred amonghealthcareworkers;while substantial number of MERS cases were patients [3], with most MERS severe cases and mortality being individuals with comorbidities [6].”
InfluentialMiddle East Respiratory Syndrome Coronavirus (MERS-CoV)
Jolly, G. (2016) · Texila international journal of public health · doi:10.21522/tijph.2013.04.04.art033 · Cited by 452
Flagged first, then by citations
1 of the 46 references couldn’t be matched to a known paper.
Research works printed but not linked: 5
- WHO : Summary of probable SARS cases with onset of illness from 1 November 2002 to 31 July. : 2018: 2003.
- WHO : MERS situation update July 2018. : 2018.
- Incubation. In: Encyclopedia of Public Health. Edited by W. Kirch. Dordrecht: Springer 2008. · DOI
- Latency. In: Encyclopedia of Public Health. Edited by W. Kirch. Dordrecht: Springer 2008. · DOI
- South Korean man infected by MERS virus, first case in 3 years. : 2018. [Reuters/AFP/aj].
Cited by
Sorted by citations
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Real-time Privacy Preserving Framework for Covid-19 Contact Tracing
Bhardwaj, A., Mohamed, A. A., Kumar, M., Alshehri, M., & Abugabah, A. (2021) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2022.018736 · Cited by 4
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Pinotti, F., Obolski, U., Wikramaratna, P. S., Giovanetti, M., Paton, R. S., Klenerman, P., Thompson, C., Gupta, S., & Lourenço, J. (2021) · Scientific Reports · doi:10.1038/s41598-021-84672-1 · Cited by 4
Yu, S., Cui, S., Rui, J., Zhao, Z., Deng, B., Liu, C., Li, K., Wang, Y., Yang, Z., Li, Q., et al. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2021.799536 · Cited by 4
Lanzarotti, E., Santi, L., Castro, R., Roslan, F., & Groisman, L. (2021) · Winter Simulation Conference · doi:10.1109/wsc52266.2021.9715445 · Cited by 3
“…Lanzarotti, Francisco Roslan, Leandro Groisman, Lucio Santi and Rodrigo Castro that allow users to understand infection dynamics and test multiple scenarios where different intervention strategies can be tested, like contact tracing, isolation, lockdowns, vaccination, etc. Kwok et al. (2019).”
BackgroundA contact tracing SIR model for randomly mixed populations
Bednarski, S., Cowen, L. L. E., Ma, J., Philippsen, T., den Driessche, P. V., & Wang, M. (2022) · Journal of Biological Dynamics · doi:10.1080/17513758.2022.2153938 · Cited by 3
“Specifically, contact tracing is a crucial public health intervention strategy for emerging and re-emerging infectious diseases to contain and prevent the further spread of the disease [16, 27].”
BackgroundWen, B., Teng, Z., & Liu, B. (2024) · Communications in Nonlinear Science and Numerical Simulation · doi:10.1016/j.cnsns.2024.107868 · Cited by 3
Wang, Z., Yang, P., Wang, R., Luca Ferretti, A., Zhao, L., Pei, S., Wang, X., Jia, L., Zhang, D., Liu, Y., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-50487-7 · Cited by 3
Nakashima, A., Takeya, M., Kuba, K., Takano, M., & Nakashima, N. (2020) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2020.100442 · Cited by 3
“6 turmoil even with the aid of next-generation sequencing [15,60,61].”
Saleh, F., & Sleem, A. (2020) · Medical Sciences · doi:10.3390/medsci9010001 · Cited by 3
“The TTT strategy is not a new one, as it has been used before and proved its effectiveness in other outbreaks, such as the 2014 Ebola virus outbreak, the outbreak of Middle East respiratory syndrome (MERS) in 2012, and in the severe acute respiratory syndrome (SARS) outbreak in 2003 [4].”
MethodEvolution of Outbreaks, Lessons Learnt and Challenges Towards “New Normalcy”—Post COVID-19 World
Vaithilingam, C. A., Natesan, S., Rajalaxmi, R. R., Tamilarasi, K., Praveena, N., & Karim, S. A. A. (2021) · Studies in systems, decision and control · doi:10.1007/978-3-030-79610-5_1 · Cited by 3
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“All three viruses are pathogenic and cause pneumonia in humans (3, 4).”
BackgroundCOVID-19: a pandemic challenging healthcare systems
Wang, L., & Alexander, C. A. (2021) · IISE Transactions on Healthcare Systems Engineering · doi:10.1080/24725579.2021.1933269 · Cited by 3
“A recent study demonstrated that chloroquine and Remdesivir could successfully control COVID-19 in vitro (Lai et al., 2020).”
BackgroundMorgenstern, C., Rawson, T., Routledge, I., Kont, M. D., Imai, N., Skarp, J. E., Doohan, P., McCain, K., Johnson, R., Unwin, H. J. T., et al. (2024) · medRxiv · doi:10.1101/2024.08.13.24311934 · Cited by 3
Inferring contact network characteristics from epidemic data via compact mean-field models
Guzmán, A., Malizia, F., Park, G. H., Choi, B., Cole, D., & Kiss, I. Z. (2025) · Journal of Complex Networks · doi:10.1093/comnet/cnaf018 · Cited by 2
“Although collecting data from contact networks is feasible in certain cases, such as sexually transmitted infections [36, 37, 38, 39], it remains challenging for respiratory diseases [40, 41, 42].”
Singh, D., Sarangi, S. S., Acharya, M., Sahoo, S., Prusty, S. K., & Rout, S. (2020) · Coronaviruses · doi:10.2174/2666796701999200901184905 · Cited by 2
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Abdalla, M., & Anter, A. M. (2023) · Springer eBooks · doi:10.1007/978-3-031-45952-8_5 · Cited by 2
Coronaviruses: Pandemic SARS-CoV-2
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Lessons learned from the COVID-19 pandemic in Latin America: A Data Science standpoint
Villar, J., Maçaira, P., & Baião, F. (2025) · PLoS ONE · doi:10.1371/journal.pone.0324171 · Cited by 2
“whose spread led to four large-scale outbreaks [1]: the Severe Acute respiratory Syndrome (SARS) in 2003, two Middle East respiratory Syndrome (MERS) - the first in the Middle East in 2012 and the second in South Korea in 2015 -, and the COVID-19 pandemic that began in 2019.”
Early prediction and analysis of corona pandemic outbreak using deep learning technique
Gampala, V., Nandankar, P. V., Kathiravan, M., Karunakaran, S., Nalla, A. R., & Gaddam, R. R. (2021) · World Journal of Engineering · doi:10.1108/wje-03-2021-0145 · Cited by 2
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“However, with the advancement of current vaccine research and development technology, contact tracing and follow-up control measures have become particularly important in the early stages of epidemic control (Müller et al., 2000; Kwok et al., 2019; Read et al., 2020; Walker et al., 2020).”
BackgroundCOVID-19 at the community level: What are the countermeasures?
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Contact tracing and isolation reduces covid-19 incidence in a structured agent-based modelPreprint
Low, M., & Geffen, N. (2020) · medRxiv · doi:10.1101/2020.10.06.20207761 · Cited by 2
“[9] The model we report on here is novel in that it (1) is a high performance ABM calibrated to various Covid-19 parameters, (2) contains structure in the form of households, school classes, workplaces, public transport and neighbourhood blocks, and (3) allows for the modelling of interventions…”
MethodZha, W.-T., Zhou, N., Li, G., Li, W., Zhang, H., Zhang, S., Chen, M., Feng, R., Li, T., & Lv, Y. (2020) · doi:10.21203/rs.3.rs-16659/v1 · Cited by 2
Contact Tracing Apps for the COVID-19 Pandemic: A Responsible Innovation Perspective
Ogoh, G., Akintoye, S., Eke, D., Leach, T., Ochang, P. A., Owoseni, A., Oyeniji, O. A., & Stahl, B. C. (2022) · Philosophy of engineering and technology · doi:10.1007/978-3-031-08424-9_4 · Cited by 1
Truong, J. M., Meyer, L. G., Karirirwe, G., Cory, C., Dennehy, T. J., Williams, R., Jackman, J. M., Clement, W., Collins, J. N., Gettel, A., et al. (2023) · Journal of Humanistic Psychology · doi:10.1177/00221678221144954 · Cited by 1
“Case investigation and contact tracing are well-established public health mitigation strategies that have been key in addressing disease outbreaks such as the COVID-19 pandemic (Centers for Disease Control and Prevention [CDC], 2021a; Kwok et al., 2019; Lewis, 2020; Maduka et al., 2016).”
BackgroundZeng, Y., Xv, J., & Cui, L. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1589683 · Cited by 1
Distribution and determinants of COVID-19 seroprevalence in a hard-to-access health district in Mali
Thera, S. O., Cissoko, M., Landier, J., Doumbia, Z., Dolo, M., Traoré, S., Sangaré, A. K., Berthe, I., Théra, I., Berthe, H., et al. (2025) · PLOS Global Public Health · doi:10.1371/journal.pgph.0004842 · Cited by 1
“However, our estimate (R0 > 1) highlights the need to implement interventions to control the spread of the infection in this population [44].”
Saraff, S., Rishipal, R., Bhattacharyya, C., Brahma, D., & Nag, S. (2018) · EAI Endorsed Transactions on Smart Cities · doi:10.4108/eai.5-10-2020.166544 · Cited by 1
“Steps that are as coercive as selfquarantine, seclusion or confinement, should only be used when an ailment is acknowledged by substantial scientific study to be transmittable and may be limited to people that have been exposed to the ailment [19] [20].”
BackgroundHilfiker, L., & Ganguly, S. (2020) · Disaster Resilience and Green Growth · doi:10.1007/978-981-15-7679-9_2 · Cited by 1
Kumar, A. (2021) · Studies in big data · doi:10.1007/978-981-33-4412-9_9 · Cited by 1
Analyzing Security and Privacy Concerns of Contact Tracing Applications
Migiro, L., Shahriar, H., & Sneha, S. (2021) · IEEE International Conference on Digital Health (ICDH) · doi:10.1109/icdh52753.2021.00052 · Cited by 1
Kudo, H. (2022) · Central and Eastern European eDem and eGov Days · doi:10.24989/ocg.v341.25 · Cited by 1
“The effectiveness of contact tracing has been confirmed by many previous cases of contagious diseases [3] [27] [13]; although it is difficult to isolate the effectiveness of contact tracing strategy from other measures, as various measures have been introduced together in different combinations in…”
BackgroundMethodFernández, N., Prada, S., Villanueva-Congote, J., & Rodríguez, S. (2022) · Revista Urología Colombiana / Colombian Urology Journal · doi:10.1055/s-0042-1748051 · Cited by 6
Methods and Directions of Contact Tracing in Epidemic Discovery
Abdalla, M., AbdelAziz, A. M., Alarabi, L., Basalamah, S. M., & Hendawi, A. (2022) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2022.0130698 · Cited by 1
“In [71], the authors present an analysis of different models, proposed to simulate the spread of two epidemics: SARS and Middle East Respiratory Syndrome (MERS).”
BackgroundEffects of Contact Tracing and Self-Reporting in a Network Disease Model
Gandhi, P., Robert, M. A., Palacios, J. L., & Chan, D. M. (2023) · Letters in Biomathematics · doi:10.30707/lib9.1.1681913305.219107 · Cited by 1
Emergence failure of early epidemics: A mathematical modeling approach
Breban, R. (2024) · PLoS ONE · doi:10.1371/journal.pone.0301415 · Cited by 1
Disease Spread Model in Structurally Complex Spaces: An Open Markov Chain Approach
García-Maya, B. I., Morales-Huerta, Y., & Salgado-García, R. (2025) · Journal of Computational Biology · doi:10.1089/cmb.2024.0630 · Cited by 1
An Epidemic Model of COVID-19 Incorporating Both the Latent and the Asymptomatic Infectious
王, 雪. (2020) · Advances in Applied Mathematics · doi:10.12677/aam.2020.95083 · Cited by 1
Libraries on the Global Health Crisis
Ajaykumar, C. (2021) · Advances in library and information science (ALIS) book series · doi:10.4018/978-1-7998-6449-3.ch010 · Cited by 1
Kontaktkutatás, vezetői információs rendszer
Bokányi, E., Pollner, P., & Joó, T. (2021) · Scientia et Securitas · doi:10.1556/112.2021.00015 · Cited by 1
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Vaithilingam, C. A., Gayathri, S., Lalitha, R., Rajalakshmi, R. R., & Jagadeeshwaran, A. (2021) · Studies in systems, decision and control · doi:10.1007/978-3-030-79606-8_2 · Cited by 1
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Anni, D. J. S., Nabeel, M., Meharunnisa, A., Kavyakannan, & Hiba, K. F. (2021) · International Conference on Information Systems and Computer Networks (ISCON) · doi:10.1109/iscon52037.2021.9702457 · Cited by 1
CoVID-19 in Singapore: Impact of Contact Tracing and Self-awareness on Healthcare DemandPreprint
Huang, Q., Wang, L., Yang, Y., Huang, L., Du, Z., & Xiao, G. (2020) · medRxiv · doi:10.1101/2020.06.04.20122879 · Cited by 1
Craig, K. J. T., Rizvi, R. F., Willis, V. C., Kassler, W. J., & Jackson, G. P. (2021) · doi:10.2196/preprints.32468 · Cited by 1
Mobaraki, K., Ahmadzadeh, J., & Vahabzadeh, D. (2020) · doi:10.36811/ojprm.2020.110008
“Percentage of case fatality rates (%CFR) for this infection calculated about 10% [3,4].”
BackgroundCoronavirus disease 2019: Lessons, risks and challenges
Richards, G. A., & Stacey, S. L. (2020) · African Journal of Thoracic and Critical Care Medicine · doi:10.7196/ajtccm.2020.v26i2.068
“While case fatality rates (CFRs) in the SARS-CoV-1 and MERSCoV outbreaks were 7 - 10% and 30%, respectively,[8] in the current epidemic, the CFR is estimated to be ~1 - 2% of confirmed cases, although this may not take into account a larger denominator that includes asymptomatic or mildly symptomatic cases not present…”
BackgroundModelling for the COVID-19 with the Contacting DistancePreprint
Ma, Z., Wang, S., Lin, X., Li, X., Han, X., Wang, H., & Liu, H. (2021) · Research Square · doi:10.21203/rs.3.rs-329034/v1
“These outbreaks have resulted in more than 8, 000 and 2, 200 confirmed SARS and MERS cases, respectively [Kwok et al., 2019; Chen et al., 2020].”
BackgroundCarpenter, N., & Dabrowski, A. (2021) · CRC Press eBooks · doi:10.1201/9781003181590-49
Modeling the Effect of Quarantine and Isolation for COVID-19 Spreading
Singh, A. K., Bhasin, S., Gakhar, B., & Arquam, M. (2021) · Algorithms for intelligent systems · doi:10.1007/978-981-16-1220-6_37
Optimizing the order of actions in contact tracingPreprint
Meister, M., & Kleinberg, J. M. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.09803
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Migiro, L., Shahriar, H., & Sneha, S. (2021) · doi:10.2196/preprints.28887
Modelling for The COVID-19 with The Contacting DistancePreprint
Ma, Z., Wang, S., Lin, X., Li, X., Han, X., Wang, H., & Liu, H. (2021) · Research Square · doi:10.21203/rs.3.rs-329034/v2
Can digital health support COVID-19 contact tracing? A scoping review (Preprint)Preprint
Fortuin, J., Patientia, R. F., Najaar, B., & Madini, N. (2020) · doi:10.2196/preprints.21352
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Bhuyan, H. K., & Pani, S. K. (2022) · Wiley eBooks · doi:10.1002/9781119792376.ch9
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Bai, Z., Ma, Z., Jing, L., Li, Y., Wang, S., Wang, B.-G., Wu, Y. Y., Zhang, J., & Wang, H. (2022) · Research Square · doi:10.21203/rs.3.rs-1709788/v1
Das, K. P., Pramanik, S., Karmakar, P. S., & Mondal, S. S. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-29959-9_37
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“AI with Machine learning programme serves the system with accuracy development and prediction for the screening of infectious and non-infectious diseases [1], [19].”
BackgroundExploring the needs and experiences of contact tracing staff during the COVID-19 pandemic in Ireland
Fulham-McQuillan, H., O’Donovan, R., Buckley, C. M., Crowley, P., Gilmore, B., Martin, J., McAuliffe, É., Martin, G., Moore, G., Morrissey, M., et al. (2024) · PLoS ONE · doi:10.1371/journal.pone.0298799
Sarkar, A., Agnihotri, K., & Das, K. P. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-56307-2_10
Pemmada, S. K., Das, S., Nayak, S. C., & Vimal, S. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-97-8093-8_24
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Singh, T. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-9301-7.ch009
Perspectives on Bioterrorism and Pandemics
Maxwell, D. N., Raj, D., & Perl, T. M. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-54841-0.00003-2
Cheng, Z., Liang, H., Gao, F., Chen, X., Liu, X., Zhou, Y., Chen, X., Jiang, H., Cockings, S., Tatem, A. J., et al. (2026) · GeoHealth · doi:10.1029/2026gh001838
“Despite its accuracy and epidemiological value, survey‐based contact tracing can be constrained by limited timeliness and spatial coverage when facing highly transmissible pathogens with pandemic potential (Kwok et al., 2019).”
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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