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

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 MEASURESRates 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 (Ն80 years) had a higher risk of having severe or critical disease (proportion, 41.3%; risk ratio, 3.61 [95% CI,) 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 RELEVANCEA 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.

Multinational modeling of SARS-CoV-2 spreading dynamics: Insights on the heterogeneity of COVID-19 transmission and its potential healthcare burden

“…33 Preliminary data from China demonstrates that public health interventions including traffic restrictions, social distancing, home quarantine, and universal symptom survey can be temporally associated with a reduced effective reproduction number of SARS-CoV-2. 34 This fact is in agreement with our data, which shows that China experienced significant reductions in values; indicating a containment of the COVID-19 spread. Austria and South Korea are additional examples of appropriate public health measures, which have effectively curbed the total number of cases.…”

Survival-Convolution Models for Predicting COVID-19 Cases and Assessing Effects of Mitigation Strategies

“…For predicting daily new cases, our analyses suggest that the model estimated from 19,20 arrived at a similar conclusion, and their estimated R t closely matches with our estimates.…”

“…Summary Background Countries around the globe have implemented unprecedented mitigation measures to mitigate the coronavirus disease 2019 (COVID- 19) pandemic. We aim to predict COVID-19 cases and compare effectiveness of mitigation measures across countries to inform policy decision making.…”

Impact of non-pharmaceutical interventions on documented cases of COVID-19

“…NPIs have been linked to the spread of SARS-CoV-2 primarily within or from a single country [8][9][10][11][12][13][14][15][16][17][18][19] , mostly focusing on the novel coronavirus outbreak in China. The majority of findings are based on transmission models where epidemiological parameters are informed by previous studies or corroborated via simulation.…”