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The Effectiveness of Contact Tracing in Emerging Epidemics

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  • Don Klinkenberg
  • Christophe Fraser
  • Hans Heesterbeek

Abstract

Background: Contact tracing plays an important role in the control of emerging infectious diseases, but little is known yet about its effectiveness. Here we deduce from a generic mathematical model how effectiveness of tracing relates to various aspects of time, such as the course of individual infectivity, the (variability in) time between infection and symptom-based detection, and delays in the tracing process. In addition, the possibility of iteratively tracing of yet asymptomatic infecteds is considered. With these insights we explain why contact tracing was and will be effective for control of smallpox and SARS, only partially effective for foot-and-mouth disease, and likely not effective for influenza. Methods and Findings: We investigate contact tracing in a model of an emerging epidemic that is flexible enough to use for most infections. We consider isolation of symptomatic infecteds as the basic scenario, and express effectiveness as the proportion of contacts that need to be traced for a reproduction ratio smaller than 1. We obtain general results for special cases, which are interpreted with respect to the likely success of tracing for influenza, smallpox, SARS, and foot-and-mouth disease epidemics. Conclusions: We conclude that (1) there is no general predictive formula for the proportion to be traced as there is for the proportion to be vaccinated; (2) variability in time to detection is favourable for effective tracing; (3) tracing effectiveness need not be sensitive to the duration of the latent period and tracing delays; (4) iterative tracing primarily improves effectiveness when single-step tracing is on the brink of being effective.

Suggested Citation

  • Don Klinkenberg & Christophe Fraser & Hans Heesterbeek, 2006. "The Effectiveness of Contact Tracing in Emerging Epidemics," PLOS ONE, Public Library of Science, vol. 1(1), pages 1-7, December.
    • Handle: RePEc:plo:pone00:0000012
    DOI: 10.1371/journal.pone.0000012
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    References listed on IDEAS

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    1. Neil M. Ferguson & Christl A. Donnelly & Roy M. Anderson, 2001. "Transmission intensity and impact of control policies on the foot and mouth epidemic in Great Britain," Nature, Nature, vol. 413(6855), pages 542-548, October.
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    1. Fetzer, Thiemo & Graeber, Thomas, 2020. "Does Contact Tracing Work? Quasi-Experimental Evidence from an Excel Error in England," CEPR Discussion Papers 15494, C.E.P.R. Discussion Papers.
    2. Raghu Raman & Krishnashree Achuthan & Ricardo Vinuesa & Prema Nedungadi, 2021. "COVIDTAS COVID-19 Tracing App Scale—An Evaluation Framework," Sustainability, MDPI, vol. 13(5), pages 1-19, March.
    3. Rachid Laajaj & Duncan Webb & Danilo Aristizabal & Eduardo Behrentz & Raquel Bernal & Giancarlo Buitrago & Zulma Cucunubá & Fernando de la Hoz, 2021. "Understanding how socioeconomic inequalities drive inequalities in SARS-CoV-2 infections," Documentos CEDE 19241, Universidad de los Andes, Facultad de Economía, CEDE.
    4. Ian E. Fellows & Mark S. Handcock, 2023. "Modeling of networked populations when data is sampled or missing," METRON, Springer;Sapienza Università di Roma, vol. 81(1), pages 21-35, April.
    5. Kenji Mizumoto & Keisuke Ejima & Taro Yamamoto & Hiroshi Nishiura, 2013. "Vaccination and Clinical Severity: Is the Effectiveness of Contact Tracing and Case Isolation Hampered by Past Vaccination?," IJERPH, MDPI, vol. 10(3), pages 1-14, February.
    6. Howell, Bronwyn E. & Potgieter, Petrus H., 2022. "Smartphone-Based COVID-19 contact tracing apps – antipodean insights," 31st European Regional ITS Conference, Gothenburg 2022: Reining in Digital Platforms? Challenging monopolies, promoting competition and developing regulatory regimes 265635, International Telecommunications Society (ITS).
    7. Andrew Perrault & Marie Charpignon & Jonathan Gruber & Milind Tambe & Maimuna Majumder, 2020. "Designing Efficient Contact Tracing Through Risk-Based Quarantining," NBER Working Papers 28135, National Bureau of Economic Research, Inc.
    8. T Déirdre Hollingsworth & Don Klinkenberg & Hans Heesterbeek & Roy M Anderson, 2011. "Mitigation Strategies for Pandemic Influenza A: Balancing Conflicting Policy Objectives," PLOS Computational Biology, Public Library of Science, vol. 7(2), pages 1-11, February.
    9. Atul Pokharel & Robert Soulé & Avi Silberschatz, 2021. "A case for location based contact tracing," Health Care Management Science, Springer, vol. 24(2), pages 420-438, June.
    10. Esra Ozdenerol & Rebecca Michelle Bingham-Byrne & Jacob Seboly, 2023. "Female Leadership during COVID-19: The Effectiveness of Diverse Approaches towards Mitigation Management during a Pandemic," IJERPH, MDPI, vol. 20(21), pages 1-36, November.
    11. Choi, K. & Choi, Hoyun & Kahng, B., 2022. "COVID-19 epidemic under the K-quarantine model: Network approach," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    12. Bjarke Frost Nielsen & Kim Sneppen & Lone Simonsen & Joachim Mathiesen, 2021. "Differences in social activity increase efficiency of contact tracing," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(10), pages 1-11, October.
    13. Ting Wan Tan & Han Ling Tan & Man Na Chang & Wen Shu Lin & Chih Ming Chang, 2021. "Effectiveness of Epidemic Preventive Policies and Hospital Strategies in Combating COVID-19 Outbreak in Taiwan," IJERPH, MDPI, vol. 18(7), pages 1-19, March.

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