Epidemiological and clinical characteristics of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among healthcare workers in Hubei Province, China.

OBJECTIVE: To evaluate the epidemiological and clinical characteristics of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among healthcare workers (HCWs) in Hubei Province, China. DESIGN: Retrospective cohort study. SETTING: Hubei Provincial Center for Disease Control and Prevention. PARTICIPANTS: The participants in this study are cases identified by epidemiological investigation in Hubei Province, as of February 27, 2020, and were followed until March 7, 2020. In total, 1,989 HCWs and 41,137 other occupational cases were included for analysis. METHODS: We used descriptive statistics to summarize patient characteristics. RESULTS: Of 1,989 laboratory-confirmed HCWs, 297 (14.93%) had severe or critical cases, 73 (3.67%) had asymptomatic infections, and 18 died of coronavirus disease 2019 (COVID-19). The case fatality rate was 0.9%. The proportion of severe or critical cases decreased from the beginning to the end of the outbreak (from 21.29% to 3.52%), and the proportion of asymptomatic cases increased from 0.0% to 47.18%. Nearly half of HCWs with confirmed COVID-19 reported no known contact with COVID-19 patients (969, 48.72%). Fever and cough were the most common symptoms at disease onset in both HCWs and other occupational cases; however, HCWs had higher rates of fatigue (30.90% vs 25.02%; P < .001) and myalgia (19.15% vs 13.43%; P < .001). Additionally, compared with other occupational groups, HCWs were associated with a lower risk of death after adjustment for potential confounders (odd ratio [OR], 0.50; 95% confidence interval [CI], 0.30-0.79). CONCLUSIONS: Compared with COVID-19 cases in other occupational groups, HCWs with COVID-19 have half the risk of death, although they have been shown to have higher rates of fatigue and myalgia.

Effect of public health interventions on COVID-19 cases: an observational study.

BACKGROUND: As the epidemic of COVID-19 is gradually controlled in China, a summary of epidemiological characteristics and interventions may help control its global spread. METHODS: Data for COVID-19 cases in Hubei Province (capital, Wuhan) was extracted until 7 March 2020. The spatiotemporal distribution of the epidemic in four periods (before 10 January, 10-22 January, 23 January-6 February and 7 February-7 March) was evaluated, and the impacts of interventions were observed. RESULTS: Among 67 706 COVID-19 cases, 52 111 (76.97%) were aged 30-69 years old, and 34 680 (51.22%) were women. The average daily attack rates (95% CI) were 0.5 (0.3 to 0.7), 14.2 (13.2 to 15.1), 45.7 (44.0 to 47.5) and 8.6 (7.8 to 9.3) cases per 106 people in four periods, and the harmonic means (95% CI) of doubling times were 4.28 (4.01 to 4.55), 3.87 (3.78 to 3.98), 5.40 (4.83 to 6.05) and 45.56 (39.70 to 52.80) days. Compared with the first period, daily attack rates rose rapidly in the second period. In the third period, 14 days after 23 January, the daily average attack rate in and outside Wuhan declined by 33.8% and 48.0%; the doubling times increased by 95.0% and 133.2%. In the four periods, 14 days after 7 February, the daily average attack rate in and outside Wuhan decreased by 79.1% and 95.2%; the doubling times increased by 79.2% and 152.0%. CONCLUSIONS: The public health interventions were associated with a reduction in COVID-19 cases in Hubei Province, especially in districts outside of Wuhan.

Spatiotemporal analysis of COVID-19 outbreaks in Wuhan, China.

Few study has revealed spatial transmission characteristics of COVID-19 in Wuhan, China. We aimed to analyze the spatiotemporal spread of COVID-19 in Wuhan and its influence factors. Information of 32,682 COVID-19 cases reported through March 18 were extracted from the national infectious disease surveillance system. Geographic information system methods were applied to analysis transmission of COVID-19 and its influence factors in different periods. We found decrease in effective reproduction number (Rt) and COVID-19 related indicators through taking a series of effective public health measures including restricting traffic, centralized quarantine and strict stay-at home policy. The distribution of COVID-19 cases number in Wuhan showed obvious global aggregation and local aggregation. In addition, the analysis at streets-level suggested population density and the number of hospitals were associated with COVID-19 cases number. The epidemic situation showed obvious global and local spatial aggregations. High population density with larger number of hospitals may account for the aggregations. The epidemic in Wuhan was under control in a short time after strong quarantine measures and restrictions on movement of residents were implanted.

[Impact of Pollutant Emission Reduction on Air Quality During the COVID-19 Pandemic Control in Early 2020 Based on RAMS-CMAQ].

In this work, the relationships between air quality and pollutant emissions were investigated during the COVID-19 pandemic in Shandong Province. During the quarantine period (from January 24 to February 7, 2020), the concentrations of atmospheric pollutants decreased significantly relative to the period before controls were imposed (from January 15 to 23, 2020). Specifically, except for an increase in the concentration of O3, concentrations of PM10, PM2.5, NO2, SO2, and CO decreased for 72.6 µg·m-3 (45.86%), 47.4 µg·m-3(41.24%), 25.6 µg·m-3 (58.00%), 3.0 µg·m-3 (17.71%), and 0.5 mg·m-3 (31.40%), respectively. RAMS-CMAQ simulation showed that meteorological diffusion had an essential role in improving air quality. Influenced by meteorological factors, emissions of PM10, PM2.5, NO2, SO2, and CO were reduced 26.04%, 33.03%, 28.35%, 43.27%, and 23.29%, respectively. Furthermore, the concentrations of PM10, PM2.5, NO2, SO2, and CO were reduced by 19.82%, 8.21%, 29.65%, -25.56%, and 8.12%, respectively, due to pollution emissions reductions during the quarantine period. O3 concentrations increased by 20.51% during quarantine, caused by both meteorological factors (10.47%) and human activities (10.04%). These results indicate that primary pollutants were more sensitive to emissions reductions; however, secondary pollutants demonstrated a lagged response the emissions reduction and were significantly affected by meteorological factors. The linear relationship between ozone and the emissions reduction was not significant, and was inverse overall. Further investigation are now required on the impact of emissions reduction on ozone pollution control.

Epidemiological characteristics and transmission dynamics of paediatric cases with coronavirus disease 2019 in Hubei province, China.

AIM: This study aimed to identify the epidemiological characteristics and transmission dynamics of paediatric cases. METHODS: Information on 1369 paediatric cases with COVID-19 from 8 December 2019 to 7 March 2020 in Hubei province was extracted from the National Infectious Disease Surveillance System. The analysis included epidemic curves, temporal-spatial distribution, clinical classification and interval times between onset and diagnosis. RESULTS: Among 1369 paediatric cases, the median age was 9 years and 58.2% of them were males. The proportion of severe and critical cases in children was lower than that in adults and the proportion of asymptomatic cases in children was five times greater than for adult cases. The first paediatric case was reported on 2 January 2020, and the daily number of new paediatric cases remained high from 1 February through to 22 February. The epidemiological curve of paediatric cases lagged behind that of adults by 19 days, and the first spike of the epidemic curve in senior high school students occurred 1 week earlier than in other paediatric groups. The proportion of clustered cases among children was about twice that for adults. The median of the interval in paediatric cases between onset and diagnosis, isolation and notification were 3, 0 and 3 days, respectively, and all of those were significantly shorter than in adults. CONCLUSIONS: The epidemic curve of child cases lagged behind that of adult cases by 19 days, and the major form of transmission observed was in clusters.

Epidemiological characteristics and the entire evolution of coronavirus disease 2019 in Wuhan, China.

BACKGROUND: Coronavirus Disease 2019 (COVID-19) spread rapidly around the world. We aimed to describe the epidemiological characteristics and the entire evolution of COVID-19 in Wuhan, and to evaluate the effect of non-pharmaceutical intervention by the government. METHODS: The information of COVID-19 cases until Mar 18, 2020 in Wuhan were collected from the national infectious disease surveillance system in Hubei province. RESULTS: A total of 49,973 confirmed cases were reported until Mar 18, 2020 in Wuhan. Among whom, 2496 cases died and the overall mortality was 5.0%. Most confirmed cases (25,619, 51.3%) occurred during Jan 23 to Feb 4, with a spike on Feb 1 (new cases, 3374). The number of daily new cases started to decrease steadily on Feb 19 (new cases, 301) and decreased greatly on Mar 1 (new cases, 57). However, the mortality and the proportion of severe and critical cases has been decreasing over time, with the lowest of 2.0 and 10.1% during Feb 16 to Mar 18, 2020, respectively. The percentage of severe and critical cases among all cases was 19.6%, and the percentage of critical and dead cases aged over 60 was 70.1 and 82.0%, respectively. CONCLUSION: The number of new cases has dropped significantly after the government taking the isolation of four types of personnel and the community containment for 14 days. Our results indicate that the mortality and proportion of severe and critical cases gradually decreased over time, and critical and dead cases are more incline to be older individuals.

Predictive Model and Risk Factors for Case Fatality of COVID-19: A Cohort of 21,392 Cases in Hubei, China.

An increasing number of patients are being killed by coronavirus disease 2019 (COVID-19), however, risk factors for the fatality of COVID-19 remain unclear. A total of 21,392 COVID-19 cases were recruited in the Hubei Province of China between December 2019 and February 2020, and followed up until March 18, 2020. We adopted Cox regression models to investigate the risk factors for case fatality and predicted the death probability under specific combinations of key predictors. Among the 21,392 patients, 1,020 (4.77%) died of COVID-19. Multivariable analyses showed that factors, including age (≥60 versus <45 years, hazard ratio [HR] = 7.32; 95% confidence interval [CI], 5.42, 9.89), sex (male versus female, HR = 1.31; 95% CI, 1.15, 1.50), severity of the disease (critical versus mild, HR = 39.98; 95% CI, 29.52, 48.86), comorbidity (HR = 1.40; 95% CI, 1.23, 1.60), highest body temperature (>39°C versus <39°C, HR = 1.28; 95% CI, 1.09, 1.49), white blood cell counts (>10 × 109/L versus (4-10) × 109/L, HR = 1.69; 95% CI, 1.35, 2.13), and lymphocyte counts (<0.8 × 109/L versus (0.8-4) × 109/L, HR = 1.26; 95% CI, 1.06, 1.50) were significantly associated with case fatality of COVID-19 patients. Individuals of an older age, who were male, with comorbidities, and had a critical illness had the highest death probability, with 21%, 36%, 46%, and 54% within 1-4 weeks after the symptom onset. Risk factors, including demographic characteristics, clinical symptoms, and laboratory factors were confirmed to be important determinants of fatality of COVID-19. Our predictive model can provide scientific evidence for a more rational, evidence-driven allocation of scarce medical resources to reduce the fatality of COVID-19.