Inferring a cause-effect relationship between lockdown restrictions and COVID-19 pandemic trend during the first wave

被引:2
|
作者
Megna, Rosario [1 ]
机构
[1] CNR, Inst Biostruct & Bioimaging, Via Tommaso de Amicis, I-80145 Naples, Italy
关键词
COVID-19; SARS-CoV-2; Lockdown; Modelling; Health policy; Public health; IMPACT; INTERVENTIONS; OUTBREAK; HEALTH; POLICY;
D O I
10.1016/j.healthpol.2021.09.008
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
The large number of infected persons due to the COVID-19 pandemic and the need of hospital care for many of them induced the majority of world governments to implement lockdown measures. We devel-oped an analytical model to evaluate the trend of the SARS-CoV-2 pandemic. This model was applied to the first four months of the epidemiological data of the most affected countries in Europe and Russia, in order to evaluate the effect of the lockdown on the epidemic curves during the first wave. According to our model, the difference between the beginning of the lockdown and the slope change of the curve representing the daily distribution of counts was: Germany and Spain 6 days, France 7 days, the United Kingdom 9 days, Italy 21 days, and Russia 30 days. On the basis of these results, we infer a possible cause-effect relationship between the lockdown imposed in countries taken into account and the curve representing the daily distribution of new cases. Lockdown measures imposed by governments slowed the spread of the pandemic and reduced the number of infected persons. In economic terms, the damage was considerable, with entire production sectors in crisis. On the other hand, the effort s and innovations implemented to produce vaccines and effective treatments against the pandemic could be applied also in other fields of public health. (c) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码:1441 / 1447
页数:7
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