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1.
Nat Commun ; 14(1): 2310, 2023 04 21.
Article in English | MEDLINE | ID: covidwho-2305975

ABSTRACT

Diversity of physical encounters in urban environments is known to spur economic productivity while also fostering social capital. However, mobility restrictions during the pandemic have forced people to reduce urban encounters, raising questions about the social implications of behavioral changes. In this paper, we study how individual income diversity of urban encounters changed during the pandemic, using a large-scale, privacy-enhanced mobility dataset of more than one million anonymized mobile phone users in Boston, Dallas, Los Angeles, and Seattle, across three years spanning before and during the pandemic. We find that the diversity of urban encounters has substantially decreased (by 15% to 30%) during the pandemic and has persisted through late 2021, even though aggregated mobility metrics have recovered to pre-pandemic levels. Counterfactual analyses show that behavioral changes including lower willingness to explore new places further decreased the diversity of encounters in the long term. Our findings provide implications for managing the trade-off between the stringency of COVID-19 policies and the diversity of urban encounters as we move beyond the pandemic.


Subject(s)
COVID-19 , Cell Phone , Humans , COVID-19/epidemiology , Pandemics , Benchmarking , Income
2.
Proc Natl Acad Sci U S A ; 119(26): e2112182119, 2022 06 28.
Article in English | MEDLINE | ID: covidwho-1890404

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-2 infection to estimate the where, when, and magnitude of transmission events during the pandemic's first wave. We estimate that only 18% of individuals produce most infections (80%), with about 10% of events that can be considered superspreading events (SSEs). Although mass gatherings present an important risk for SSEs, we estimate that the bulk of transmission occurred in smaller events in settings like workplaces, grocery stores, or food venues. The places most important for transmission change during the pandemic and are different across cities, signaling the large underlying behavioral component underneath them. Our modeling complements case studies and epidemiological data and indicates that real-time tracking of transmission events could help evaluate and define targeted mitigation policies.


Subject(s)
COVID-19 , Contact Tracing , SARS-CoV-2 , COVID-19/transmission , Humans , New York City/epidemiology , Pandemics , Population Dynamics , Time Factors , Washington/epidemiology
3.
Nat Commun ; 12(1): 3652, 2021 06 16.
Article in English | MEDLINE | ID: covidwho-1275918

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). We detect when users were walking, distance walked and time of the walk, and classify each walk as recreational or utilitarian. Our results reveal dramatic declines in walking, particularly utilitarian walking, while recreational walking has recovered and even surpassed pre-pandemic levels. Our findings also demonstrate important social patterns, widening existing inequalities in walking behavior. COVID-19 response measures have a larger impact on walking behavior for those from low-income areas and high use of public transportation. Provision of equal opportunities to support walking is key to opening up our society and economy.


Subject(s)
COVID-19 , Health Policy , Walking/statistics & numerical data , Accelerometry/instrumentation , COVID-19/epidemiology , Cell Phone , Cities , Communicable Disease Control , Humans , Obesity/epidemiology , Prevalence , Recreation , Socioeconomic Factors , Transportation , United States , Weather
4.
Nat Hum Behav ; 4(9): 964-971, 2020 09.
Article in English | MEDLINE | ID: covidwho-695170

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. 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.


Subject(s)
Betacoronavirus , Clinical Laboratory Techniques/statistics & numerical data , Contact Tracing/statistics & numerical data , Coronavirus Infections/epidemiology , Infection Control/statistics & numerical data , Pandemics/statistics & numerical data , Pneumonia, Viral/epidemiology , Boston/epidemiology , COVID-19 , COVID-19 Testing , Coronavirus Infections/diagnosis , Coronavirus Infections/prevention & control , Family Characteristics , Hospitalization/statistics & numerical data , Humans , Infection Control/methods , Models, Statistical , Pandemics/prevention & control , Pneumonia, Viral/diagnosis , Pneumonia, Viral/prevention & control , SARS-CoV-2
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