ArticleHealthcare informatics research2021
Population Mobility, Lockdowns, and COVID-19 Control: An Analysis Based on Google Location Data and Doubling Time from India.
Article in Healthcare informatics research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Comparing lagged impacts of mobility changes and environmental factors on COVID-19 waves in rural and urban India: A Bayesian spatiotemporal modelling study.PLOS global public health · 2025Article
- Relationship between GPS-based community mobility data and orthopedic trauma admissions during the COVID-19 pandemic in Austria: a multicenter analysis.Wiener klinische Wochenschrift · 2024Article
- Effects of meteorological factors and air pollutants on the incidence of COVID-19 in South Korea.Environmental research · 2022Article
- Lockdowns, Community Mobility Patterns, and COVID-19: A Retrospective Analysis of Data from 16 Countries.Healthcare informatics research · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesPhysical distancing is a control measure against coronavirus disease 2019 (COVID-19). Lockdowns are a strategy to enforce physical distancing in urban areas, but they are drastic measures. Therefore, we assessed the effectiveness of the lockdown measures taken in the world's second-most populous country, India, by exploring their relationship with community mobility patterns and the doubling time of COVID-19.
methodsWe conducted a retrospective analysis based on community mobility patterns, the stringency index of lockdown measures, and the doubling time of COVID-19 cases in India between February 15 and April 26, 2020. Pearson correlation coefficients were calculated between the stringency index, community mobility patterns, and the doubling time of COVID-19 cases. Multiple linear regression was applied to predict the doubling time of COVID-19.
resultsCommunity mobility drastically fell after the lockdown was instituted. The doubling time of COVID-19 cases was negatively correlated with population mobility patterns in outdoor areas (r = -0.45 to -0.58). The stringency index and outdoor mobility patterns were also negatively correlated (r = -0.89 to -0.95). Population mobility patterns (R2 = 0.67) were found to predict the doubling time of COVID-19, and the model's predictive power increased when the stringency index was also added (R2 = 0.73).
conclusionsLockdown measures could effectively ensure physical distancing and reduce short-term case spikes in India. Therefore, lockdown measures may be considered for tailored implementation on an intermittent basis, whenever COVID-19 cases are predicted to exceed the health care system's capacity to manage.
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