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KMID : 1100520220280020160
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Healthcare Informatics Research
2022 Volume.28 No. 2 p.160 ~ p.169
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Lockdowns, Community Mobility Patterns, and COVID-19: A Retrospective Analysis of Data from 16 Countries
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Venkatesh U
P Aravind Gandhi
Ara Tasnim
Rahman Md Mahabubur
Kishore Jugal
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Abstract
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Objectives: During the coronavirus disease 2019 (COVID-19) pandemic, countries around the world framed specific lawsand imposed varying degrees of lockdowns to ensure the maintenance of physical distancing. Understanding changes in temporaland spatial mobility patterns may provide insights into the dynamics of this infectious disease. Therefore, we assessedthe efficacy of lockdown measures in 16 countries worldwide by analyzing the relationship between community mobility patternsand the doubling time of COVID-19.
Methods: We performed a retrospective record-based analysis of population-leveldata on the doubling time for COVID-19 and community mobility. The doubling time for COVID-19 was calculated basedon the laboratory-confirmed cases reported daily over the study period (from February 15 to May 2, 2020). Principal componentanalysis (PCA) of six mobility pattern-related variables was conducted. To explain the magnitude of the effect of mobilityon the doubling time, a finite linear distributed lag model was fitted. The k-means clustering approach was employed toidentify countries with similar patterns in the significant co-efficient of the mobility index, with the optimal number of clustersderived using Elbow’s method.
Results: The countries analyzed had reduced mobility in commercial and social places.
Reduced mobility had a significant and favorable association with the doubling time of COVID-19?specifically, the greaterthe mobility reduction, the longer the time taken for the COVID-19 cases to double.
Conclusions: COVID-19 lockdownsachieved the immediate objective of mobility reduction in countries with a high burden of cases.
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KEYWORD
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COVID-19, Spatio-Temporal Analysis, Geographic Information Systems, Information Technology, Infectious Disease Transmission
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