COVID-19 cumulative incidence, intensive care, and mortality in Italian regions compared to selected European countries.
COVID-19 cumulative incidence, intensive care, and mortality in Italian regions compared to selected European countries.
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DOI：
10.1016/j.ijid.2020.10.070
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发表时间：
2021-01
期刊：
影响因子：
--
通讯作者：
Sebastiani G
中科院分区：
文献类型：
--
作者：
Olivieri A;Palù G;Sebastiani G
2019冠状病毒病（COVID-19）的高传染性和快速传播导致大量危重至严重危及生命的病例，需要紧急入院并在重症监护室（ICU）接受治疗。这一流行病对所有欧洲国家的卫生系统及其提供适当反应的能力是一个坚韧的考验。目前的工作旨在揭示意大利地区COVID-19发病率、ICU床位占用率、ICU多余面积和死亡率等参数之间的相关性。2020年3月1日至7月16日期间的公开数据使用多种数学和统计方法进行了分析。该分析定义了两个独立的意大利地区组。在这些组内考虑的检查变量是相互关联和相互依赖的。这两组地区具有相同的拟合模型（线性），将死亡率解释为累积发病率的函数，但其中一组的常数值较高，因此其特点是大流行病的高内在“强度”，在产生大量严重和危及生命的病例方面肯定发挥了主要作用。这些结果在欧洲得到了证实。其他因素可能影响死亡率并与发病率相关，如ICU饱和和过度。这些定量结果可以成为一个非常有用的工具，有助于在这一流行病反复出现，超过任何公共卫生系统的反应能力之前，制定预防措施和优化生物医学干预措施。
The high contagiousness and rapid spreading of the coronavirus disease 2019 (COVID-19) has caused a high number of critical to severe life-threatening cases, which required urgent hospital admission and treatment in intensive care units (ICUs). The pandemic has been a tough test for all European national health systems and their capability to provide an adequate reaction. The present work aims to reveal correlations between parameters such as COVID-19 incidence, ICU bed occupancy, ICU excess area, and mortality in Italian regions. Public data for the period of March 1 to July 16, 2020, were analyzed using several mathematical and statistical methods. The analysis defined two separate groups of Italian regions. The examined variables considered within these groups were interlinked and dependent on each other. The regions of the two groups shared the same kind of fitted model (linear) explaining mortality as a function of cumulative incidence, but with higher value of the constant in one group, so characterized by a high intrinsic “strength” of the pandemic, certainly playing a major role in the generation of a large number of severe and life-threatening cases. These results are confirmed at European level. Other factors may condition mortality and be linked to incidence, such as ICU saturation and excess. These quantitative results could be a very helpful tool to set up preventive measures and optimize biomedical interventions before the pandemic, in its recurrent waves, could overcome the reaction capacity of any public health system.
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DOI：
10.1038/nrmicro.2016.81
发表时间：
2016-08
期刊：
Nature reviews. Microbiology
影响因子：
--
作者：
de Wit E;van Doremalen N;Falzarano D;Munster VJ
通讯作者：
Munster VJ
DOI：
10.1073/pnas.6.6.275
发表时间：
1920-01-01
影响因子：
11.1
作者：
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通讯作者：
Reed, LJ
影响因子：
56.9
作者：
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通讯作者：
Lipsitch, Marc
影响因子：
3.7
作者：
WARD, JH
通讯作者：
WARD, JH
影响因子：
13.6
作者：
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通讯作者：
Riboli, Elio