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The effect of social distance measures on COVID-19 epidemics in Europe: an interrupted time series analysis.
Geroscience. 2020 08; 42(4):1075-1082.G

Abstract

Following the introduction of unprecedented "stay-at-home" national policies, the COVID-19 pandemic recently started declining in Europe. Our research aims were to characterize the changepoint in the flow of the COVID-19 epidemic in each European country and to evaluate the association of the level of social distancing with the observed decline in the national epidemics. Interrupted time series analyses were conducted in 28 European countries. Social distance index was calculated based on Google Community Mobility Reports. Changepoints were estimated by threshold regression, national findings were analyzed by Poisson regression, and the effect of social distancing in mixed effects Poisson regression model. Our findings identified the most probable changepoints in 28 European countries. Before changepoint, incidence of new COVID-19 cases grew by 24% per day on average. From the changepoint, this growth rate was reduced to 0.9%, 0.3% increase, and to 0.7% and 1.7% decrease by increasing social distancing quartiles. The beneficial effect of higher social distance quartiles (i.e., turning the increase into decline) was statistically significant for the fourth quartile. Notably, many countries in lower quartiles also achieved a flat epidemic curve. In these countries, other plausible COVID-19 containment measures could contribute to controlling the first wave of the disease. The association of social distance quartiles with viral spread could also be hindered by local bottlenecks in infection control. Our results allow for moderate optimism related to the gradual lifting of social distance measures in the general population, and call for specific attention to the protection of focal micro-societies enriching high-risk elderly subjects, including nursing homes and chronic care facilities.

Authors+Show Affiliations

Center for Health Technology Assessment, Semmelweis University, Budapest, Hungary. voko.zoltan@semmelweis-univ.hu. Syreon Research Institute, Budapest, Hungary. voko.zoltan@semmelweis-univ.hu.Syreon Research Institute, Budapest, Hungary.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32529592

Citation

Vokó, Zoltán, and János György Pitter. "The Effect of Social Distance Measures On COVID-19 Epidemics in Europe: an Interrupted Time Series Analysis." GeroScience, vol. 42, no. 4, 2020, pp. 1075-1082.
Vokó Z, Pitter JG. The effect of social distance measures on COVID-19 epidemics in Europe: an interrupted time series analysis. Geroscience. 2020;42(4):1075-1082.
Vokó, Z., & Pitter, J. G. (2020). The effect of social distance measures on COVID-19 epidemics in Europe: an interrupted time series analysis. GeroScience, 42(4), 1075-1082. https://doi.org/10.1007/s11357-020-00205-0
Vokó Z, Pitter JG. The Effect of Social Distance Measures On COVID-19 Epidemics in Europe: an Interrupted Time Series Analysis. Geroscience. 2020;42(4):1075-1082. PubMed PMID: 32529592.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - The effect of social distance measures on COVID-19 epidemics in Europe: an interrupted time series analysis. AU - Vokó,Zoltán, AU - Pitter,János György, Y1 - 2020/06/11/ PY - 2020/05/14/received PY - 2020/05/18/accepted PY - 2020/6/13/pubmed PY - 2020/8/18/medline PY - 2020/6/13/entrez KW - COVID-19 KW - Europe KW - Google community mobility reports KW - Interrupted time series analysis KW - Social distance SP - 1075 EP - 1082 JF - GeroScience JO - Geroscience VL - 42 IS - 4 N2 - Following the introduction of unprecedented "stay-at-home" national policies, the COVID-19 pandemic recently started declining in Europe. Our research aims were to characterize the changepoint in the flow of the COVID-19 epidemic in each European country and to evaluate the association of the level of social distancing with the observed decline in the national epidemics. Interrupted time series analyses were conducted in 28 European countries. Social distance index was calculated based on Google Community Mobility Reports. Changepoints were estimated by threshold regression, national findings were analyzed by Poisson regression, and the effect of social distancing in mixed effects Poisson regression model. Our findings identified the most probable changepoints in 28 European countries. Before changepoint, incidence of new COVID-19 cases grew by 24% per day on average. From the changepoint, this growth rate was reduced to 0.9%, 0.3% increase, and to 0.7% and 1.7% decrease by increasing social distancing quartiles. The beneficial effect of higher social distance quartiles (i.e., turning the increase into decline) was statistically significant for the fourth quartile. Notably, many countries in lower quartiles also achieved a flat epidemic curve. In these countries, other plausible COVID-19 containment measures could contribute to controlling the first wave of the disease. The association of social distance quartiles with viral spread could also be hindered by local bottlenecks in infection control. Our results allow for moderate optimism related to the gradual lifting of social distance measures in the general population, and call for specific attention to the protection of focal micro-societies enriching high-risk elderly subjects, including nursing homes and chronic care facilities. SN - 2509-2723 UR - https://www.unboundmedicine.com/medline/citation/32529592/The_effect_of_social_distance_measures_on_COVID_19_epidemics_in_Europe:_an_interrupted_time_series_analysis_ L2 - https://doi.org/10.1007/s11357-020-00205-0 DB - PRIME DP - Unbound Medicine ER -