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The Epidemiological Case for Contact Tracing

Dr. Luca Ferretti gives ICTP-SISSA Colloquium 24 April

Dr. Luca Ferretti
Dr. Luca Ferretti

24/04/2020 - Trieste

ICTP was pleased to welcome Dr. Luca Ferretti for an online colloquium addressing some of the pressing questions provoked by the global pandemic. Currently at the Big Data Institute of Oxford University, UK, Dr. Ferretti’s research focuses on epidemiology, genetics, evolution, and viral host dynamics. The colloquium, titled 'Epidemic Control of COVID-19 Through Instantaneous Contact Tracing: The Case for a Mobile App-based Solution', took place on Friday 24 April at 14:00 CET, and considers the epidemiological reasoning for using mobile apps for widespread contact tracing.   

The colloquium was coordinated jointly with Scuola Internazionale Superiore di Studi Avanzati (SISSA), where Dr. Ferretti completed his PhD. The talk was followed by an opportunity to ask questions, moderated by Matteo Marsili of ICTP’s Quantitative Life Sciences section. 

A recording of the colloquium is available on ICTP's YouTube channel.

Abstract:
There is an ongoing public debate about mobile apps for contact tracing. Their implications in terms of privacy and data security are under intense scrutiny by cybersecurity experts, lawyers and politicians, as well as the general public. 

Unfortunately, the most important questions are often absent from this debate: what is the epidemiological rationale behind the suggestion to deploy such a risky tool? Which role would these apps play in the control of the COVID-19 epidemic, and why are they so relevant?

In this talk, I will present the scientific arguments underpinning the answers. I will summarise our understanding of COVID-19 epidemiology and SARS-CoV-2 transmission and I will discuss the challenges of different containment strategies for this epidemic. In this framework, I will highlight how speed and efficiency are the main determinants of the effectiveness of contact tracing in controlling the epidemic, and why digital solutions are the most promising ones. I will also discuss current limitations and challenges of app-based approaches.

 

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