ArticleJMIR public health and surveillance2020
No Place Like Home: Cross-National Data Analysis of the Efficacy of Social Distancing During the COVID-19 Pandemic.
Article in JMIR public health and surveillance, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.
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Who cites it
45 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction Models for Public Health Containment Measures on COVID-19 Using Artificial Intelligence and Machine Learning: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- Dynamic interactions of COVID-19 incidences, mobility, and social distancing policies in seoul: A VAR model approach.Scientific reports · 2025Article
- An analysis of the spatio-temporal behavior of COVID-19 patients using activity trajectory data.Heliyon · 2023Article
- Media exposure, threat processing, and mitigation behaviors in Gulf Coast residents facing the co-occurring threats of COVID-19 and hurricanes.Risk analysis : an official publication of the Society for Risk Analysis · 2023Article
- A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study.JMIR formative research · 2023Article
- Uneven impacts of COVID-19 on residents' utilization of urban parks: A case study of Guangzhou, China.Applied geography (Sevenoaks, England) · 2023Article
- A qualitative descriptive study of the impact of the COVID-19 pandemic on staff in a Canadian intensive care unit.Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2023Article
- Using passive Wi-Fi for community crowd sensing during the COVID-19 pandemic.Journal of big data · 2023Article
- Prognosis of COVID-19 patients using lab tests: A data mining approach.Health science reports · 2023Article
- A Machine Learning Framework for Assessing the Risk of Venous Thromboembolism in Patients Undergoing Hip or Knee Replacement.Journal of healthcare informatics research · 2022Article
- The Apple Mobility Trends Data in Human Mobility Patterns during Restrictions and Prediction of COVID-19: A Systematic Review and Meta-Analysis.Healthcare (Basel, Switzerland) · 2022Review
- COVID-19 and organisational resilience in Brazil's water sector.The Science of the total environment · 2022Article
- Social distancing causally impacts the spread of SARS-CoV-2: a U.S. nationwide event study.BMC infectious diseases · 2022Article
- Quarantine, physical distancing and social isolation measures in individuals potentially exposed to SARS-CoV-2 in community settings and health services: a scoping review.Nepal journal of epidemiology · 2022Article
- The adverse effect of the COVID-19 pandemic on health service usage among patients with type 2 diabetes in North Karelia, Finland.BMC health services research · 2022Article
- A global experiment on motivating social distancing during the COVID-19 pandemic.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Observational
- Association of stay-at-home orders and COVID-19 incidence and mortality in rural and urban United States: a population-based study.BMJ open · 2022Article
- Lockdowns, Community Mobility Patterns, and COVID-19: A Retrospective Analysis of Data from 16 Countries.Healthcare informatics research · 2022Article
- High Acceptance of COVID-19 Tracing Technologies in Taiwan: A Nationally Representative Survey Analysis.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the absence of a cure in the time of a pandemic, social distancing measures seem to be the most effective intervention to slow the spread of disease. Various simulation-based studies have been conducted to investigate the effectiveness of these measures. While those studies unanimously confirm the mitigating effect of social distancing on disease spread, the reported effectiveness varies from 10% to more than 90% reduction in the number of infections. This level of uncertainty is mostly due to the complex dynamics of epidemics and their time-variant parameters. However, real transactional data can reduce uncertainty and provide a less noisy picture of the effectiveness of social distancing.
objectiveThe aim of this paper was to integrate multiple transactional data sets (GPS mobility data from Google and Apple as well as disease statistics from the European Centre for Disease Prevention and Control) to study the role of social distancing policies in 26 countries and analyze the transmission rate of the coronavirus disease (COVID-19) pandemic over the course of 5 weeks.
methodsRelying on the susceptible-infected-recovered (SIR) model and official COVID-19 reports, we first calculated the weekly transmission rate (β) of COVID-19 in 26 countries for 5 consecutive weeks. Then, we integrated these data with the Google and Apple mobility data sets for the same time frame and used a machine learning approach to investigate the relationship between the mobility factors and β values.
resultsGradient boosted trees regression analysis showed that changes in mobility patterns resulting from social distancing policies explain approximately 47% of the variation in the disease transmission rates.
conclusionsConsistent with simulation-based studies, real cross-national transactional data confirms the effectiveness of social distancing interventions in slowing the spread of COVID-19. In addition to providing less noisy and more generalizable support for the idea of social distancing, we provide specific insights for public health policy makers regarding locations that should be given higher priority for enforcing social distancing measures.
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