Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing

By L. Ferretti, C. Wymant, M. Kendall, L. Zhao, A. Nurtay, D. Bonsall, Christophe Fraser. medRxiv, 2020

534 citations recorded by the source corpus.

The newly emergent human virus SARS-CoV-2 is resulting in high fatality rates and incapacitated health systems. Preventing further transmission is a priority. We analysed key parameters of epidemic spread to estimate the contribution of different transmission routes and determine requirements for case isolation and contact-tracing needed to stop the epidemic. We conclude that viral spread is too fast to be contained by manual contact tracing, but could be controlled if this process was faster, more efficient and happened at scale. A contact-tracing App which builds a memory of proximity contacts and immediately notifies contacts of positive cases can achieve epidemic control if used by enough people. By targeting recommendations to only those at risk, epidemics could be contained without need for mass quarantines ('lock-downs') that are harmful to society. We discuss the ethical requirements for an intervention of this kind.

Subfields: Epidemiology, Information Systems, Modeling and Simulation

View Paper: https://www.semanticscholar.org/paper/3822f2e4bfd9174f3c3ed984963b66d3bfba2ae6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. D. Golinelli
2. E. Boetto
3. G. Carullo
4. Andrea Giovanni Nuzzolese
5. M. Landini
6. M. Fantini
7. Stefano Miccoli
8. Marino Gatto

Citations in the corpus

• Covasim: An agent-based model of COVID-19 dynamics and interventions (2020, unknown): “We take a default assumption that it is not, but include a parameter that can be modified as needed depending on the modeling application or context, noting that some studies have used much lower rates of infectiousness for asymptomatic individuals [61].”
• Information technology solutions, challenges, and suggestions for tackling the COVID-19 pandemic (2020, unknown): “Public trust and confidence are necessary to people’s adoption of various technologies including sharing their data to address the challenges caused by this pandemic (Ferretti et al., 2020).”
• Identifying airborne transmission as the dominant route for the spread of COVID-19 (2020, unknown): “Differentiation of the effects of those mitigation measures in China is challenging (19), since the implementation occurred almost simultaneously in January 2020.”
• Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature (2020, background): “Grade of innovation Health care system targets Reference ID Global Innovating Clients/patients, health care providers, health systems/resource managers, data services Zhai et al [17] Local Innovating Clients/patients, health care providers, health systems/resource managers, data services Wang W et a”
• Digital Health Strategies to Fight COVID-19 Worldwide: Challenges, Recommendations, and a Call for Papers (2020, background): “For all these reasons, digital approaches can be received in very different ways when they are applied in high-income, medium-income, or low-income areas or when they are deployed in individualistic versus collectivistic countries [49].”
• Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures (2020, background): “This underpins that greatly improved contact tracing has the potential to stop the spread of the epidemic if reliably used on sufficiently large numbers (52).”