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Showing content from https://pubmed.ncbi.nlm.nih.gov/32275295/ below:

Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China

. 2020 May 19;323(19):1915-1923. doi: 10.1001/jama.2020.6130. Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China Li Liu¹, Chaolong Wang¹, Huan Guo², Xingjie Hao¹, Qi Wang¹, Jiao Huang¹, Na He³, Hongjie Yu³, Xihong Lin^{4 5}, Sheng Wei¹, Tangchun Wu²

Affiliations

¹ Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
² Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
³ School of Public Health, Ministry of Education Key Laboratory of Public Health Safety, Fudan University, Shanghai, China.
⁴ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
⁵ Department of Statistics, Harvard University, Boston, Massachusetts.

PMID: 32275295
PMCID: PMC7149375
DOI: 10.1001/jama.2020.6130

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Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China

An Pan et al. JAMA. 2020.

. 2020 May 19;323(19):1915-1923. doi: 10.1001/jama.2020.6130. Authors An Pan¹, Li Liu¹, Chaolong Wang¹, Huan Guo², Xingjie Hao¹, Qi Wang¹, Jiao Huang¹, Na He³, Hongjie Yu³, Xihong Lin^{4 5}, Sheng Wei¹, Tangchun Wu² Affiliations

¹ Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
² Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
³ School of Public Health, Ministry of Education Key Laboratory of Public Health Safety, Fudan University, Shanghai, China.
⁴ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
⁵ Department of Statistics, Harvard University, Boston, Massachusetts.

PMID: 32275295
PMCID: PMC7149375
DOI: 10.1001/jama.2020.6130

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Abstract

Importance: Coronavirus disease 2019 (COVID-19) has become a pandemic, and it is unknown whether a combination of public health interventions can improve control of the outbreak.

Objective: To evaluate the association of public health interventions with the epidemiological features of the COVID-19 outbreak in Wuhan by 5 periods according to key events and interventions.

Design, setting, and participants: In this cohort study, individual-level data on 32 583 laboratory-confirmed COVID-19 cases reported between December 8, 2019, and March 8, 2020, were extracted from the municipal Notifiable Disease Report System, including patients' age, sex, residential location, occupation, and severity classification.

Exposures: Nonpharmaceutical public health interventions including cordons sanitaire, traffic restriction, social distancing, home confinement, centralized quarantine, and universal symptom survey.

Main outcomes and measures: Rates of laboratory-confirmed COVID-19 infections (defined as the number of cases per day per million people), across age, sex, and geographic locations were calculated across 5 periods: December 8 to January 9 (no intervention), January 10 to 22 (massive human movement due to the Chinese New Year holiday), January 23 to February 1 (cordons sanitaire, traffic restriction and home quarantine), February 2 to 16 (centralized quarantine and treatment), and February 17 to March 8 (universal symptom survey). The effective reproduction number of SARS-CoV-2 (an indicator of secondary transmission) was also calculated over the periods.

Results: Among 32 583 laboratory-confirmed COVID-19 cases, the median patient age was 56.7 years (range, 0-103; interquartile range, 43.4-66.8) and 16 817 (51.6%) were women. The daily confirmed case rate peaked in the third period and declined afterward across geographic regions and sex and age groups, except for children and adolescents, whose rate of confirmed cases continued to increase. The daily confirmed case rate over the whole period in local health care workers (130.5 per million people [95% CI, 123.9-137.2]) was higher than that in the general population (41.5 per million people [95% CI, 41.0-41.9]). The proportion of severe and critical cases decreased from 53.1% to 10.3% over the 5 periods. The severity risk increased with age: compared with those aged 20 to 39 years (proportion of severe and critical cases, 12.1%), elderly people (≥80 years) had a higher risk of having severe or critical disease (proportion, 41.3%; risk ratio, 3.61 [95% CI, 3.31-3.95]) while younger people (<20 years) had a lower risk (proportion, 4.1%; risk ratio, 0.47 [95% CI, 0.31-0.70]). The effective reproduction number fluctuated above 3.0 before January 26, decreased to below 1.0 after February 6, and decreased further to less than 0.3 after March 1.

Conclusions and relevance: A series of multifaceted public health interventions was temporally associated with improved control of the COVID-19 outbreak in Wuhan, China. These findings may inform public health policy in other countries and regions.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Yu reported receiving grants from the National Natural Science Foundation of China, the Program of Shanghai Academic/Technology Research Leader, and the National Science and Technology Major Project of China during the conduct of the study; grants from Sanofi Pasteur, GlaxoSmithKline, Yichang HEC Changjiang Pharmaceutical Company, and bioMérieux Diagnostic Product (Shanghai) outside the submitted work. No other disclosures were reported.

Figures
Figure 1.. The Epidemic Curve, Key Events…

Figure 1.. The Epidemic Curve, Key Events and Features, and Public Health Interventions Across the…
Figure 1.. The Epidemic Curve, Key Events and Features, and Public Health Interventions Across the 5 Periods During the COVID-19 Outbreak in Wuhan, China

The epidemic curve is shown as the number of incident cases each day by the symptom onset date. Details of the key events, features of the situation, and public health interventions across the 5 periods are further described in the eMethods in the Supplement. Chunyun is a period of significant travel in China with extremely high traffic load around the Chinese Lunar New Year. Cordons sanitaire restrict movement of people outside of a defined area.

Figure 2.. The Geographic Distribution of Daily…

Figure 2.. The Geographic Distribution of Daily Rates of COVID-19 Cases Across the 5 Periods…
Figure 2.. The Geographic Distribution of Daily Rates of COVID-19 Cases Across the 5 Periods in Wuhan, China

The daily rate of cases is expressed as number of laboratory-confirmed cases per day per million people, grouped by each of the 13 districts of the city of Wuhan. COVID-19 indicates coronavirus disease 2019.

Figure 3.. Daily Rates of Cases in…

Figure 3.. Daily Rates of Cases in Different Groups and Proportion of Severity Categories Across…
Figure 3.. Daily Rates of Cases in Different Groups and Proportion of Severity Categories Across the 5 Periods in Wuhan, China

The exact values for the daily rates of cases in panels A-C in different groups across the 5 periods are shown in eTable 2 in the Supplement. The clinical severity in panel D was defined according to the 7 editions of the Interim Diagnosis and Treatment of 2019 Novel Coronavirus Pneumonia, and details are shown in the eMethods in the Supplement. Error bars indicate 95% CIs.

Figure 4.. The Effective Reproduction Number (…

Figure 4.. The Effective Reproduction Number ( R _t ) Estimates Based on Laboratory-Confirmed Coronavirus…
Figure 4.. The Effective Reproduction Number (R_t) Estimates Based on Laboratory-Confirmed Coronavirus Disease 2019 (COVID-19) Cases in Wuhan, China

The effective reproduction number R_t is defined as the mean number of secondary cases generated by a typical primary case at time t in a population, calculated for the whole period over a 5-day moving average. Results are shown since January 1, 2020, given the limited number of diagnosed cases and limited diagnosis capacity in December 2019. The darkened horizontal line indicates R_t = 1, below which sustained transmission is unlikely so long as antitransmission measures are sustained, indicating that the outbreak is under control. The 95% credible intervals (CrIs) are presented as gray shading. Daily estimates of R_t with 95% CrIs are shown in eTable 3 in the Supplement.

Comment in

Public Health Interventions for COVID-19: Emerging Evidence and Implications for an Evolving Public Health Crisis.
Hartley DM, Perencevich EN. Hartley DM, et al. JAMA. 2020 May 19;323(19):1908-1909. doi: 10.1001/jama.2020.5910. JAMA. 2020. PMID: 32275299 No abstract available.
Gastrointestinal symptoms associated with severity of coronavirus disease 2019 (COVID-19): a pooled analysis.
Henry BM, de Oliveira MHS, Benoit J, Lippi G. Henry BM, et al. Intern Emerg Med. 2020 Aug;15(5):857-859. doi: 10.1007/s11739-020-02329-9. Epub 2020 Apr 17. Intern Emerg Med. 2020. PMID: 32303970 Free PMC article. No abstract available.
Seropositive Prevalence of Antibodies Against SARS-CoV-2 in Wuhan, China.
Liu A, Li Y, Wan Z, Wang W, Lei X, Lv Y. Liu A, et al. JAMA Netw Open. 2020 Oct 1;3(10):e2025717. doi: 10.1001/jamanetworkopen.2020.25717. JAMA Netw Open. 2020. PMID: 33095246 Free PMC article.