论文标题
定量评估资源优化和ICU入学政策对COVID-19死亡率的影响
Quantitative assessment of the effects of resource optimization and ICU admission policy on COVID-19 mortalities
论文作者
论文摘要
显然，提高强化单位（ICU）的能力并优先考虑接受和治疗年轻患者将减少199例死亡人数，但是对这些措施的定量评估仍然不足。我们开发了一个全面的非马克维亚国家过渡模型，该模型通过准确预测两个震中的每日死亡人数来验证：中国武汉和意大利伦巴第。该模型在各种情况下都可以预测COVID-19死亡。例如，如果给年轻患者的治疗优先级，武汉和伦巴第的死亡人数将分别降低10.4 \％和6.7 \％。该策略取决于流行量表，在人口结构较年轻的国家中更有效。对来自中国，韩国，意大利和西班牙的数据分析表明，人均ICU医疗资源较少的国家应在大流行的早期实施这一策略，以减少死亡率。
It is evident that increasing the intensive-care-unit (ICU) capacity and giving priority to admitting and treating younger patients will reduce the number of COVID-19 deaths, but a quantitative assessment of these measures has remained inadequate. We develop a comprehensive, non-Markovian state transition model, which is validated through accurate prediction of the daily death toll for two epicenters: Wuhan, China and Lombardy, Italy. The model enables prediction of COVID-19 deaths in various scenarios. For example, if treatment priorities had been given to younger patients, the death toll in Wuhan and Lombardy would have been reduced by 10.4\% and 6.7\%, respectively. The strategy depends on the epidemic scale and is more effective in countries with a younger population structure. Analyses of data from China, South Korea, Italy, and Spain suggest that countries with less per capita ICU medical resources should implement this strategy in the early stage of the pandemic to reduce mortalities.
