Lockdowns, Community Mobility Patterns, and COVID-19: A Retrospective Analysis of Data from 16 Countries
1
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
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.
Abstract
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.
참고문헌 (30)
- "Coronavirus disease (COVID-19) technical guidance: Infection prevention and control / WASH" (2020)[URL]
- Chu DK, "Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19 : a systematic review and meta-analysis", Lancet, 395(10242), pp.1973~1987 (2020)
- Lai S, "Effect of non-pharmaceutical interventions to contain COVID-19 in China", Nature, 585(7825), pp.410~413 (2020)
- Dore B, "Covid-19: collateral damage of lockdown in India", BMJ, 369, pp.m1711~ (2020)
- Lo KL, "Forecasting the trend of COVID-19 considering the impacts of public health interventions : an application of FGM and buffer level", J Healthc Inform Res, 5(4), pp.497~528 (2021)
- Chatterjee K, "Healthcare impact of COVID-19 epidemic in India : a stochastic mathematical model", Med J Armed Forces India, 76(2), pp.147~155 (2020)
- Ngonghala CN, "Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel coronavirus", Math Biosci, 325, pp.108364~ (2020)
- "COVID-19 community mobility report" (2022)[URL]
- Sun J, "Effects of social mobility and stringency measures on the COVID-19 outcomes : evidence from the United States", Front Public Health, 9, pp.779501~ (2021)
- Aravind Gandhi Periyasamy, "Population Mobility, Lockdowns, and COVID-19 Control: An Analysis Based on Google Location Data and Doubling Time from India", Healthcare Informatics Research, 27(4), pp.325~334 (2021), 대한의료정보학회
- Lu N, "Weathering COVID-19 storm : successful control measures of five Asian countries", Am J Infect Control, 48(7), pp.851~852 (2020)
- Yang X, "Does city lockdown prevent the spread of COVID-19? : new evidence from the synthetic control method", Glob Health Res Policy, 6(1), pp.20~ (2021)
- Muniz-Rodriguez K, "Doubling time of the COVID-19 epidemic by province, China", Emerg Infect Dis, 26(8), pp.1912~1914 (2020)
- Galvani AP, "Severe acute respiratory syndrome : temporal stability and geographic variation in case-fatality rates and doubling times", Emerg Infect Dis, 9(8), pp.991~994 (2003)
- Wallinga J, "How generation intervals shape the relationship between growth rates and reproductive numbers", Proc Biol Sci, 274(1609), pp.599~604 (2007)
- "COVID-19 government response tracker" (2022)[URL]
- Wold S, "Principal component analysis", Chemom Intell Lab Syst, 2(1-3), pp.37~52 (1987)
- Nelder JA, "Generalized linear models", J R Stat Soc Ser A, 135(3), pp.370~384 (1972)
- Bholowalia P, "EBK-means : a clustering technique based on elbow method and k-means in WSN", Int J Comput Appl, 105(9), pp.17~24 (2014)
- Tobias A, "Evaluation of the lockdowns for the SARSCoV-2 epidemic in Italy and Spain after one month follow up", Sci Total Environ, 725, pp.138539~ (2020)
- "Interplay of global multiscale human mobility, social distancing, government interventions, and COVID-19 dynamics" (2020)[URL]
- "Which country has flattened the curve for the coronavirus?" (2020)[URL]
- "The best global responses to COVID-19 pandemic, 1 year later" (2020)[URL]
- "What countries did right and wrong in responding to the pandemic" (2020)[URL]
- Carrasco-Escobar G, "Use of open mobile mapping tool to assess human mobility traceability in rural offline populations with contrasting malaria dynamics", PeerJ, 7, pp.e6298~ (2019)
- Wesolowski A, "Connecting mobility to infectious diseases : the promise and limits of mobile phone data", J Infect Dis, 214(suppl_4), pp.S414~S420 (2016)
- Badr HS, "Association between mobility patterns and COVID-19 transmission in the USA : a mathematical modelling study", Lancet Infect Dis, 20(11), pp.1247~1254 (2020)
- Voko Z, "The effect of social distance measures on COVID-19 epidemics in Europe : an interrupted time series analysis", Geroscience, 42(4), pp.1075~1082 (2020)
- Delen D, "No place like home : cross-national data analysis of the efficacy of social distancing during the COVID-19 pandemic", JMIR Public Health Surveill, 6(2), pp.e19862~ (2020)
- Espinoza B, "Mobility restrictions for the control of epidemics: when do they work?", PLoS One, 15(7), pp.e0235731~ (2020)