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KMID : 1100520210270040325
Healthcare Informatics Research
2021 Volume.27 No. 4 p.325 ~ p.334
Population Mobility, Lockdowns, and COVID-19 Control: An Analysis Based on Google Location Data and Doubling Time from India
Periyasamy Aravind Gandhi

Venkatesh U.
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
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