Estimating age-specific COVID-19 fatality risk and time to death by comparing population diagnosis and death patterns: Australian data

被引:39
作者
Marschner, Ian C. [1 ]
机构
[1] Univ Sydney, Natl Hlth & Med Res Council, Clin Trials Ctr, Trials Ctr, Sydney, NSW 2006, Australia
关键词
Age-specific incidence; Case fatality; COVID-19; Deconvolution; Mortality; Surveillance data; INCUBATION PERIOD; AIDS EPIDEMIC; SEVERITY;
D O I
10.1186/s12874-021-01314-w
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
Background Mortality is a key component of the natural history of COVID-19 infection. Surveillance data on COVID-19 deaths and case diagnoses are widely available in the public domain, but they are not used to model time to death because they typically do not link diagnosis and death at an individual level. This paper demonstrates that by comparing the unlinked patterns of new diagnoses and deaths over age and time, age-specific mortality and time to death may be estimated using a statistical method called deconvolution. Methods Age-specific data were analysed on 816 deaths among 6235 cases over age 50 years in Victoria, Australia, from the period January through December 2020. Deconvolution was applied assuming logistic dependence of case fatality risk (CFR) on age and a gamma time to death distribution. Non-parametric deconvolution analyses stratified into separate age groups were used to assess the model assumptions. Results It was found that age-specific CFR rose from 2.9% at age 65 years (95% CI:2.2 - 3.5) to 40.0% at age 95 years (CI: 36.6 - 43.6). The estimated mean time between diagnosis and death was 18.1 days (CI: 16.9 - 19.3) and showed no evidence of varying by age (heterogeneity P = 0.97). The estimated 90% percentile of time to death was 33.3 days (CI: 30.4 - 36.3; heterogeneity P = 0.85). The final age-specific model provided a good fit to the observed age-stratified mortality patterns. Conclusions Deconvolution was demonstrated to be a powerful analysis method that could be applied to extensive data sources worldwide. Such analyses can inform transmission dynamics models and CFR assessment in emerging outbreaks. Based on these Australian data it is concluded that death from COVID-19 occurs within three weeks of diagnosis on average but takes five weeks in 10% of fatal cases. Fatality risk is negligible in the young but rises above 40% in the elderly, while time to death does not seem to vary by age.
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页数:10
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共 32 条
  • [1] [Anonymous], 1994, AIDS Epidemiology: A Quantitative Approach. Monographs in Epidemiology and Biostatistics
  • [3] INCUBATION PERIOD OF AIDS IN SAN-FRANCISCO
    BACCHETTI, P
    MOSS, AR
    [J]. NATURE, 1989, 338 (6212) : 251 - 253
  • [4] Practical methods for competing risks data: A review
    Bakoyannis, Giorgos
    Touloumi, Giota
    [J]. STATISTICAL METHODS IN MEDICAL RESEARCH, 2012, 21 (03) : 257 - 272
  • [5] Real estimates of mortality following COVID-19 infection
    Baud, David
    Qi, Xiaolong
    Nielsen-Saines, Karin
    Musso, Didier
    Pomar, Leo
    Favre, Guillaume
    [J]. LANCET INFECTIOUS DISEASES, 2020, 20 (07) : 773 - 773
  • [6] The probability of the 6-week lockdown in Victoria (commencing 9 July 2020) achieving elimination of community transmission ofSARS-CoV-2
    Blakely, Tony
    Thompson, Jason
    Carvalho, Natalie
    Bablani, Laxman
    Wilson, Nick
    Stevenson, Mark
    [J]. MEDICAL JOURNAL OF AUSTRALIA, 2020, 213 (08) : 349 - +
  • [7] RECONSTRUCTION AND FUTURE-TRENDS OF THE AIDS EPIDEMIC IN THE UNITED-STATES
    BROOKMEYER, R
    [J]. SCIENCE, 1991, 253 (5015) : 37 - 42
  • [8] Coronavirus (COVID-19) in Australia, COVID 19 DEATHS AUST
  • [9] Case Fatality Risk of the First Pandemic Wave of Coronavirus Disease 2019 (COVID-19) in China
    Deng, Xiaowei
    Yang, Juan
    Wang, Wei
    Wang, Xiling
    Zhou, Jiaxin
    Chen, Zhiyuan
    Li, Jing
    Chen, Yinzi
    Yan, Han
    Zhang, Juanjuan
    Zhang, Yongli
    Wang, Yan
    Qiu, Qi
    Gong, Hui
    Wei, Xianglin
    Wang, Lili
    Sun, Kaiyuan
    Wu, Peng
    Ajelli, Marco
    Cowling, Benjamin J.
    Viboud, Cecile
    Yu, Hongjie
    [J]. CLINICAL INFECTIOUS DISEASES, 2021, 73 (01) : E79 - E85
  • [10] Donoghoe MW, **DATA OBJECT**