ArticleEpidemiology and infection2020
Community movement and COVID-19: a global study using Google's Community Mobility Reports.
Article in Epidemiology and infection, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
50 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Global Experiences of Community Responses to COVID-19: A Systematic Literature Review.Frontiers in public health · 2022Pooled it
- Digital Phenotyping of Lifestyle Profiles and Mental Well-Being in German Adults: Prospective Longitudinal Cohort Study.Journal of medical Internet research · 2026Article
- Article
- Explaining COVID-19 dynamics through user activity data from digital platforms with Yandex's self-isolation index as a case study.Scientific reports · 2025Article
- A graph-theoretic framework for integrating mobility data into mathematical epidemic models.Infectious Disease Modelling · 2025Article
- The day-of-the-week effect is resilient to routine change.Memory & cognition · 2025Article
- Rapid human movement and dengue transmission in Bangladesh: a spatial and temporal analysis based on different policy measures of COVID-19 pandemic and Eid festival.Infectious diseases of poverty · 2024Article
- Predicting Covid-19 pandemic waves with biologically and behaviorally informed universal differential equations.Heliyon · 2024Article
- Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review.JMIR public health and surveillance · 2024Article
- Understanding Risk Factors for Suicide Among Older People in Rural China: A Systematic Review.Innovation in aging · 2024Review
- The effects of policy changes and human mobility on the COVID-19 epidemic in the Dominican Republic, 2020-2021.Preventive medicine reports · 2023Article
- Interregional mobility in different age groups is associated with COVID-19 transmission in the Taipei metropolitan area, Taiwan.Scientific reports · 2023Article
- Checkpoint Travel Numbers as a Proxy Variable in Population-Based Studies During the COVID-19 Pandemic: Validation Study.JMIR public health and surveillance · 2023Article
- COVID-19-associated income loss and job loss: Evidence from Indonesia.Journal of Asian economics · 2023Article
- Leisure mobility changes during the COVID-19 pandemic - An analysis of survey and mobile phone data in Sweden.Research in transportation business & management · 2023Article
- Concentration and size distribution of atmospheric particles in southern Italy during COVID-19 lockdown period.Atmospheric environment (Oxford, England : 1994) · 2023Article
- Geographic Variations in Human Mobility Patterns during the First Six Months of the COVID-19 Pandemic in California.Applied sciences (Basel, Switzerland) · 2023Article
- Replacing discontinued Big Tech mobility reports: a penetration-based analysis.Scientific reports · 2023Article
- Efficient social distancing during the COVID-19 pandemic: Integrating economic and public health considerations.European journal of operational research · 2023Article
- A data-driven framework to assess population dynamics during novel coronavirus outbreaks: A case study on Xiamen Island, China.PloS one · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Google's 'Community Mobility Reports' (CMR) detail changes in activity and mobility occurring in response to COVID-19. They thus offer the unique opportunity to examine the relationship between mobility and disease incidence. The objective was to examine whether an association between COVID-19-confirmed case numbers and levels of mobility was apparent, and if so then to examine whether such data enhance disease modelling and prediction. CMR data for countries worldwide were cross-correlated with corresponding COVID-19-confirmed case numbers. Models were fitted to explain case numbers of each country's epidemic. Models using numerical date, contemporaneous and distributed lag CMR data were contrasted using Bayesian Information Criteria. Noticeable were negative correlations between CMR data and case incidence for prominent industrialised countries of Western Europe and the North Americas. Continent-wide examination found a negative correlation for all continents with the exception of South America. When modelling, CMR-expanded models proved superior to the model without CMR. The predictions made with the distributed lag model significantly outperformed all other models. The observed relationship between CMR data and case incidence, and its ability to enhance model quality and prediction suggests data related to community mobility could prove of use in future COVID-19 modelling.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.