Research Colloquium on Computational Social Science/Data Sciences

Modelling the impact of testing, contact tracing and household quarantine on second wave of COVID-19 

Esteban Moro, Reseacher, Data Scientist, Professor, MIT IDSS (visiting) and Universidad Carlos III (Tenured)

While severe social-distancing measures have proven effective in slowing the coronavirus disease 2019 (COVID-19) pandemic, second-wave scenarios are likely to emerge as restrictions are lifted. Here we integrate anonymized, geolocalized mobility data with census and demographic data to build a detailed agent-based model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in the Boston metropolitan area. We find that a period of strict social distancing followed by a robust level of testing, contact-tracing and household quarantine could keep the disease within the capacity of the healthcare system while enabling the reopening of economic activities. Our results show that a response system based on enhanced testing and contact tracing can have a major role in relaxing social-distancing interventions in the absence of herd immunity against SARS-CoV-2.

Esteban Moro is a researcher, data scientist and professor at MIT IDSS (visiting) and Universidad Carlos III (UC3M) in Spain (tenured). He was previously researcher at University of Oxford. He is affiliate faculty at Joint Institute UC3M-Santander on Big Data at UC3M and the Joint Institute of Mathematical Sciences (Spain). He has published extensively throughout his career (more than 100 articles) and have led many projects funded by government agencies and/or private companies.

Esteban's work lies in the intersection of big data and computational social science, with special attention to human dynamics, collective intelligence, social networks and urban mobility in problems like viral marketing, natural disaster management, or economical segregation in cities. Apart from his academic career he has worked closely with companies like Twitter, Telefónica or BBVA in the use of massive datasets to understand problems like how humans communicate, how to political opinion spreads in social networks or building alternative wellbeing indexes. He has received numerous awards for his research, including the “Shared University Award” from IBM in 2007 for his research in modeling viral marketing in social networks and the “Excellence in Research” Awards in 2013 and 2015 from UC3M.

Esteban work appeared in major journals including PNAS or Science Advances and is regularly covered by media outlets The Atlantic, The Washington Post, The Wall Street Journal, El País (Spain). 

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