#covid19 #Mobile phone data #epidemics

Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas

Authors: Alberto Aleta, David Martín-Corral, Michiel A.Bakker, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova , Matteo Chinazzi, Natalie E. Dean, M. Elizabeth Halloran,Ira M. Longini,Jr, Alex Pentland, Alessandro Vespignani, Yamir Moreno, and Esteban Moro. Publication: PNAS (2022). Link Abstract: Detailed characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission across different settings can help design less disruptive interventions. We used real-time, privacy-enhanced mobility data in the New York City, NY and Seattle, WA metropolitan areas to build a detailed agent-based model of SARS-CoV-2infection to estimate the where, when, and magnitude of transmission events during thepandemic’s first wave. ...

#walking #covid19 #Mobile Phone Data

Study: More people walked during the pandemic, but how much depended on their income level

Article in Boston.com about how COVID19 has affected our walking and exercise behaviors. Study: More people walked during the pandemic, but how much depended on their income level “I think mental and physical health have been hugely affected, and once again the most vulnerable populations are the ones suffering from this." Many people took up walking during the height of the pandemic last year, according to a recently released study from MIT. ...

#covid19 #walking #Mobile phone data

Effect of COVID-19 response policies on walking behavior in US cities

Authors: Ruth F. Hunter, Leandro Garcia, Thiago Herick de Sa, Belen Zapata-Diomedi, Christopher Millett, James Woodcock, Alex ’Sandy’ Pentland, and Esteban Moro Publication: Nature Communications (2021). Link Abstract: The COVID-19 pandemic is causing mass disruption to our daily lives. We integrate mobility data from mobile devices and area-level data to study the walking patterns of 1.62 million anonymous users in 10 metropolitan areas in the United States. The data covers the period from mid-February 2020 (pre-lockdown) to late June 2020 (easing of lockdown restrictions). ...

#covid19 #super-spreading #Mobile phone data

Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas

Authors: Alberto Aleta, David Martin-Corral, Michiel Bakker, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova, Matteo Chinazzi, Natalie E Dean,M. Elizabeth Halloran, Ira M Longini, Alex Pentland, Alessandro Vespignani, Yamir Moreno, Esteban Moro Publication: medRxiv (2020). Link Abstract: Detailed characterizations of SARS-CoV-2 transmission risk across different social settings can inform the design of targeted and less disruptive non-pharmaceutical interventions (NPI), yet these data have been lacking. Here we integrate real-time, anonymous and privacy-enhanced geolocalized mobility data with census and demographic data in the New York City and Seattle metropolitan areas to build a detailed agent-based model of SARS-CoV-2 transmission. ...

#covid19 #Mobility #epidemics

Modeling the impact of social distancing, testing, contact tracing and household quarantine on second-wave scenarios of the COVID-19 epidemic

Authors: Alberto Aleta, David Martíın-Corral, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova, Matteo Chinazzi, Natalie E. Dean, M. Elizabeth Halloran, Ira M. Longini, Jr., Stefano Merler, Alex Pentland, Alessandro Vespignani, Esteban Moro & Yamir Moreno Publication: Nature Human Behavior(2020). Link Abstract: 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. ...