特定年龄的新冠病毒病病死率的逻辑模型。
A logistic model for age-specific COVID-19 case-fatality rates.
作者信息
Gao Xiang, Dong Qunfeng
机构信息
Department of Medicine, Stritch School of Medicine, Loyola University Chicago, Maywood, Illinois, USA.
Center for Biomedical Informatics, Stritch School of Medicine, Loyola University Chicago, Maywood, Illinois, USA.
出版信息
JAMIA Open. 2020 Apr 13;3(2):151-153. doi: 10.1093/jamiaopen/ooaa025. eCollection 2020 Jul.
To develop a mathematical model to characterize age-specific case-fatality rates (CFR) of COVID-19. Based on 2 large-scale Chinese and Italian CFR data, a logistic model was derived to provide quantitative insight on the dynamics between CFR and age. We inferred that CFR increased faster in Italy than in China, as well as in females over males. In addition, while CFR increased with age, the rate of growth eventually slowed down, with a predicted theoretical upper limit for males (32%), females (21%), and the general population (23%). Our logistic model provided quantitative insight on the dynamics of CFR.
建立一个数学模型来描述新冠病毒病（COVID-19）的年龄特异性病死率（CFR）。基于两项大规模的中国和意大利CFR数据，推导了一个逻辑模型，以提供关于CFR与年龄之间动态关系的定量见解。我们推断，意大利的CFR增长速度比中国快，女性的CFR增长速度也高于男性。此外，虽然CFR随年龄增长而增加，但增长速度最终会放缓，预测男性的理论上限为32%，女性为21%，总体人群为23%。我们的逻辑模型提供了关于CFR动态关系的定量见解。
Zotero 插件