Evidence map›Paper›PMID 33060093›Full record

ArticleBMJ open2020

Outbreak of COVID-19 and SARS in mainland China: a comparative study based on national surveillance data.

Lin Zhao, Dan Feng, Run-Ze Ye, Hai-Tao Wang, Yu-Hao Zhou, Jia-Te Wei, Sake J de Vlas, Xiao-Ming Cui, Na Jia, Chao-Nan Yin and 3 more

Abstract readComparative StudyMulticenter Study
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Lin ZhaoInstitute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.ORCID 0000-0003-0545-4194
Dan FengInstitution of Hospital Management, Medical Innovation Research Division, Chinese PLA General Hospital, Beijing, China.
Run-Ze YeInstitute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.
Hai-Tao WangInstitute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.
Yu-Hao ZhouState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Jia-Te WeiInstitute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.
Sake J de VlasDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Xiao-Ming CuiState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Na JiaState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Chao-Nan YinInstitute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.
Shi-Xue LiInstitute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.
Zhi-Qiang WangDepartment of Gastroenterology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China wzq301@263.net caowuchun@126.com.ORCID 0000-0003-3661-6061
Wu-Chun CaoState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China wzq301@263.net caowuchun@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare the epidemiological characteristics and transmission dynamics in relation to interventions against the COVID-19 and severe acute respiratory syndrome (SARS) outbreak in mainland China.

designComparative study based on a unique data set of COVID-19 and SARS.

settingOutbreak in mainland China.

participantsThe final database included 82 858 confirmed cases of COVID-19 and 5327 cases of SARS.

methodsWe brought together all existing data sources and integrated them into a comprehensive data set. Individual information on age, sex, occupation, residence location, date of illness onset, date of diagnosis and clinical outcome was extracted. Control measures deployed in mainland China were collected. We compared the epidemiological and spatial characteristics of COVID-19 and SARS. We estimated the effective reproduction number to explore differences in transmission dynamics and intervention effects.

resultsCompared with SARS, COVID-19 affected more extensive areas (1668 vs 230 counties) within a shorter time (101 vs 193 days) and had higher attack rate (61.8 vs 4.0 per million persons). The COVID-19 outbreak had only one epidemic peak and one epicentre (Hubei Province), while the SARS outbreak resulted in two peaks and two epicentres (Guangdong Province and Beijing). SARS-CoV-2 was more likely to infect older people (median age of 52 years), while SARS-CoV tended to infect young adults (median age of 34 years). The case fatality rate (CFR) of either disease increased with age, but the CFR of COVID-19 was significantly lower than that of SARS (5.6% vs 6.4%). The trajectory of effective reproduction number dynamically changed in relation to interventions, which fell below 1 within 2 months for COVID-19 and within 5.5 months for SARS.

conclusionsChina has taken more prompt and effective responses to combat COVID-19 by learning lessons from SARS, providing us with some epidemiological clues to control the ongoing COVID-19 pandemic worldwide.

Indexed as

BetacoronavirusPandemicsAdultChinaCoronavirus InfectionsCOVID-19Disease OutbreaksFemaleHumansIncidenceMaleMiddle AgedPneumonia, ViralPopulation SurveillanceSARS-CoV-2Survival Ratecovid-19epidemiologyinfectious diseases

Identifiers

PMID33060093
PMCPMC7565247

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.