Modeling the impact of testing, contact tracing and household quarantine on second waves of COVID-19
By A. Aleta, D. Martín-Corral, A. Pastore y Piontti, M. Ajelli, M. Litvinova, Matteo Chinazzi, N. Dean, M. Halloran, Ira M. Longini Jr, S. Merler and 4 more. Nature Human Behaviour, 2020
695 citations recorded by the source corpus.
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. An agent-based model of SARS-CoV-2 transmission shows that testing, contact tracing and household quarantine could keep new COVID-19 waves under control while allowing the reopening of the economy with minimal social-distancing interventions.
Subfields: Epidemiology, Information Systems, Modeling and Simulation
View Paper: https://www.semanticscholar.org/paper/d925baa5c772e8bc5f4eee155958536e18f4454b
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Citations in the corpus
- Reinforcement Learning for Optimization of COVID-19 Mitigation Policies (2020, methodology): “In such cases, network models (Bansal, Gren-fell, and Meyers 2007; Liu et al. 2018; Khadilkar, Ganu, and Seetharam 2020) and agent-based models (Grefenstette et al. 2013; Del Valle, Mniszewski, and Hyman 2013; Aleta et al. 2020) may be more useful predictors.”
- Mobile phone location data for disasters: A review from natural hazards and epidemics (2021, neutral): “( Aleta et al., 2020; Huang et al., 2021; Yin et al., 2021) Kogan et al. used multiple sources of data including mobile phone location data, social media data, and web search data, to prodive early warning signals of COVID-19 outbreaks.”
- Non-pharmaceutical interventions during the COVID-19 pandemic: A review (2020, methodology): “[137] Alberto Aleta, David Martín-Corral, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova, Matteo Chinazzi, Natalie E.”