Healthc Inform Res.  2021 Oct;27(4):325-334. 10.4258/hir.2021.27.4.325.

Population Mobility, Lockdowns, and COVID-19 Control: An Analysis Based on Google Location Data and Doubling Time from India

• Periyasamy AG
• Venkatesh U

• KMID: 2522214
• DOI: http://doi.org/10.4258/hir.2021.27.4.325

Abstract

Objectives
Physical 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.
Methods
We 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.
Results
Community 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).
Conclusions
Lockdown 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.

Keyword

COVID-19, Spatio-Temporal Analysis, Geographic Information Systems, Information Technology, Infectious Disease Transmission

Figure

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  Figure 1 Distribution of changes in mobility patterns between February 15 and April 26, 2020.

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  Figure 2 Spatial distribution map showing mean changes from baseline in the mobility pattern between March 24 and April 26, 2020 across the states of India.

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  Figure 3 Statewise mean percentage changes in (A) retail and recreation and (B) grocery and pharmacy mobility patterns during the lockdown compared to baseline.

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  Figure 4 Statewise mean percentage changes in (A) park and (B) transit station mobility patterns during the lockdown compared to baseline.

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  Figure 5 Statewise mean percentage changes in (A) workplace and (B) residential mobility patterns during the lockdown compared to baseline.

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  Figure 6 Variation of community mobility patterns with changes in the stringency index.

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  Figure 7 Distribution of doubling time and the stringency index from February 15 to April 26, 2020.

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  Figure 8 Correlation matrix of changes in mobility patterns between various place categories in India.

Reference

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