Evidence map›Paper›PMID 32409826›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2021

Case Fatality Risk of the First Pandemic Wave of Coronavirus Disease 2019 (COVID-19) in China.

Xiaowei Deng, Juan Yang, Wei Wang, Xiling Wang, Jiaxin Zhou, Zhiyuan Chen, Jing Li, Yinzi Chen, Han Yan, Juanjuan Zhang and 12 more

Abstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. VIBES: A multiscale modeling approach integrating within-host and between-hosts dynamics in epidemics.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. The importance of playing the long game when it comes to pandemic surveillance.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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  8. Hereditary colorectal cancer syndromes and the COVID-19 pandemic: results from a survey conducted in patients enrolled in a dedicated registry.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors.

Xiaowei DengSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Juan YangSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Wei WangSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Xiling WangSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Jiaxin ZhouSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Zhiyuan ChenSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Jing LiSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Yinzi ChenSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Han YanSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Juanjuan ZhangSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Yongli ZhangSavaid Medical School, University of Chinese Academy of Sciences, Beijing, China.
Yan WangSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Qi QiuSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Hui GongSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Xianglin WeiSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Lili WangSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Kaiyuan SunDivision of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, USA.
Peng WuWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China.
Marco AjelliBruno Kessler Foundation, Trento, Italy.
Benjamin J CowlingWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China.
Cecile ViboudDivision of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, USA.
Hongjie YuSchool of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.

Funding

National Science and Technology Major Project 2018ZX10201001-010National Science Fund for Distinguished Young Scholars 81525023
6 · The paper itself

Abstract

backgroundTo assess the case fatality risk (CFR) of COVID-19 in mainland China, stratified by region and clinical category, and estimate key time-to-event intervals.

methodsWe collected individual information and aggregated data on COVID-19 cases from publicly available official sources from 29 December 2019 to 17 April 2020. We accounted for right-censoring to estimate the CFR and explored the risk factors for mortality. We fitted Weibull, gamma, and log-normal distributions to time-to-event data using maximum-likelihood estimation.

resultsWe analyzed 82 719 laboratory-confirmed cases reported in mainland China, including 4632 deaths and 77 029 discharges. The estimated CFR was 5.65% (95% confidence interval [CI], 5.50-5.81%) nationally, with the highest estimate in Wuhan (7.71%) and lowest in provinces outside Hubei (0.86%). The fatality risk among critical patients was 3.6 times that of all patients and 0.8-10.3-fold higher than that of mild-to-severe patients. Older age (odds ratio [OR], 1.14 per year; 95% CI, 1.11-1.16) and being male (OR, 1.83; 95% CI, 1.10-3.04) were risk factors for mortality. The times from symptom onset to first healthcare consultation, to laboratory confirmation, and to hospitalization were consistently longer for deceased patients than for those who recovered.

conclusionsOur CFR estimates based on laboratory-confirmed cases ascertained in mainland China suggest that COVID-19 is more severe than the 2009 H1N1 influenza pandemic in hospitalized patients, particularly in Wuhan. Our study provides a comprehensive picture of the severity of the first wave of the pandemic in China. Our estimates can help inform models and the global response to COVID-19.

Indexed as

COVID-19Influenza A Virus, H1N1 SubtypeAgedChinaHospitalizationHumansMaleSARS-CoV-2case fatality riskChinacoronavirus disease 2019severe acute respiratory syndrome coronavirus 2

Identifiers

PMID32409826
PMCPMC7239217

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