Determinants of workplace safety towards SARS-Cov-2 and combating COVID-19 among non-healthcare workers in Hong Kong, Nanjing and Wuhan, China.

There has been no validated tool to assess workplace infection control towards SARS-Cov-2 in non-healthcare industries. In this first year survey during 07/2020-04/2021, 6684 workers were recruited from varied non-healthcare settings of Hong Kong, Nanjing and Wuhan of China and responded standard questionnaires containing information of prevention measures and policies implemented by companies and personal preventive behaviour towards infection control. All participants were randomly stratified into two sub-samples as training and validation sample. Workplace safety index towards SARS-Cov-2 (WSI-SC2) was developed and validated using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). We identified 14 manifest variables in WSI-SC2, with three sub-indices named "Workplace infection control measures and prevention", "Company occupational safety and health management and commitment" and "Worker's personal preventive behavior and awareness towards infectious control". WSI-SC2 obtained a good internal consistency reliability (Cronbach's alpha coefficients ranged: 0.76-0.91), good composite reliability (composite reliability ranged: 0.70-0.95) and satisfactory fit of the model (GFI = 0.95; SRMR = 0.05; RMSEA = 0.07). We further performed stratified analysis according to cities, and the index remained stable. Workers with higher scores of WSI-SC2 were more likely to uptake COVID-19 test. This multi-city large study developed a novel and validated tool that could horizontally measure the workplace safety towards SARS-Cov-2 in non-healthcare workers.

Association of current income and reduction in income during the COVID-19 pandemic with anxiety and depression among non-healthcare workers.

BACKGROUND: Many workers experienced income reduction during the coronavirus disease 2019 (COVID-19) pandemic, which may link to adverse mental health. AIMS: This study aimed to examine the association of current income and reduction in income during COVID-19 with anxiety and depression levels among non-healthcare workers. METHODS: This is a multi-city cross-sectional study. We used standardized questionnaires to collect information. We regrouped the current income and income reduction during COVID-19 according to the tertile and median value of each specific city. Depression, Anxiety and Stress Scales-21 item short version (DASS-21) was used to assess anxiety and depression levels. We performed multinomial logistic regression to examine the association of current and reduced income with anxiety and depression. Path models were developed to outline the potential modification/indirect effect of subsidies from government. RESULTS: Large income reduction and low current income were significantly associated with more anxiety/depression symptoms. Path analysis showed that government subsidies could not significantly alleviate the impact of reduced income on anxiety/depression. CONCLUSION: Our findings showed that large income reduction and low current income were independently associated with anxiety/depression, while these symptoms may not be ameliorated by one-off government funds. This study suggests the need for long-term policies (e.g. developing sustained economic growth policies) to mitigate negative impacts of the COVID-19.

Global COVID-19 Pandemic Waves: Limited Lessons Learned Worldwide over the Past Year.

The occurrence of coronavirus disease 2019 (COVID-19) was followed by a small burst of cases around the world; afterward, due to a series of emergency non-pharmaceutical interventions (NPIs), the increasing number of confirmed cases slowed down in many countries. However, the lifting of control measures by the government and the public's loosening of precautionary behaviors led to a sudden increase in cases, arousing deep concern across the globe. arousing deep concern across the globe. This study evaluates the situation of the COVID-19 pandemic in countries and territories worldwide from January 2020 to February 2021. According to the time-varying reproduction number (R(t)) of each country or territory, the results show that almost half of the countries and territories in the world have never controlled the epidemic. Among the countries and territories that had once contained the occurrence, nearly half failed to maintain their prevention and control, causing the COVID-19 pandemic to rebound across the world-resulting in even higher waves in half of the rebounding countries or territories. This work also proposes and uses a time-varying country-level transmission risk score (CTRS), which takes into account both R(t) and daily new cases, to demonstrate country-level or territory-level transmission potential and trends. Time-varying hierarchical clustering of time-varying CTRS values was used to successfully reveal the countries and territories that contributed to the recent aggravation of the global pandemic in the last quarter of 2020 and the beginning of 2021, and to identify countries and territories with an increasing risk of COVID-19 transmission in the near future. Furthermore, a regression analysis indicated that the introduction and relaxation of NPIs, including workplace closure policies and stay-at-home requirements, appear to be associated with recent global transmission changes. In conclusion, a systematic evaluation of the global COVID-19 pandemic over the past year indicates that the world is now in an unexpected situation, with limited lessons learned. Summarizing the lessons learned could help in designing effective public responses for constraining future waves of COVID-19 worldwide.

Comprehensive estimation for the length and dispersion of COVID-19 incubation period: a systematic review and meta-analysis.

PURPOSE: To estimate the central tendency and dispersion for incubation period of COVID-19 and, in turn, assess the effect of a certain length of quarantine for close contacts in active monitoring. METHODS: Literature related to SARS-CoV-2 and COVID-19 was searched through April 26, 2020. Quality was assessed according to Agency for Healthcare Research and Quality guidelines. Log-normal distribution for the incubation period was assumed to estimate the parameters for each study. Incubation period median and dispersion were estimated, and distribution was simulated. RESULTS: Fifty-six studies encompassing 4095 cases were included in this meta-analysis. The estimated median incubation period for general transmissions was 5.8 days [95% confidence interval (95% CI): 5.3, 6.2]. Incubation period was significantly longer for asymptomatic transmissions (median: 7.7 days; 95% CI 6.3, 9.4) than for general transmissions (P = 0.0408). Median and dispersion were higher for SARS-CoV-2 incubation compared to other viral respiratory infections. Furthermore, about 12 in 10,000 contacts in active monitoring would develop symptoms after 14 days, or below 1 in 10,000 for asymptomatic transmissions. Meta-regression suggested that each 10-year increase in age resulted in an average 16% increment in length of median incubation (incubation period ratio, 1.16, 95% CI 1.01, 1.32; P = 0.0250). CONCLUSION: This study estimated the median and dispersion of the SARS-CoV-2 incubation period more precisely. A 14-day quarantine period is sufficient to trace and identify symptomatic infections.

Comparative Characterization and Risk Stratification of Asymptomatic and Presymptomatic Patients With COVID-19.

The identification of asymptomatic, non-severe presymptomatic, and severe presymptomatic coronavirus disease 2019 (COVID-19) in patients may help optimize risk-stratified clinical management and improve prognosis. This single-center case series from Wuhan Huoshenshan Hospital, China, included 2,980 patients with COVID-19 who were hospitalized between February 4, 2020 and April 10, 2020. Patients were diagnosed as asymptomatic (n = 39), presymptomatic (n = 34), and symptomatic (n = 2,907) upon admission. This study provided an overview of asymptomatic, presymptomatic, and symptomatic COVID-19 patients, including detection, demographics, clinical characteristics, and outcomes. Upon admission, there was no significant difference in clinical symptoms and CT image between asymptomatic and presymptomatic patients for diagnosis reference. The mean area under the receiver operating characteristic curve (AUC) of the differential diagnosis model to discriminate presymptomatic patients from asymptomatic patients was 0.89 (95% CI, 0.81-0.98). Importantly, the severe and non-severe presymptomatic patients can be further stratified (AUC = 0.82). In conclusion, the two-step risk-stratification model based on 10 laboratory indicators can distinguish among asymptomatic, severe presymptomatic, and non-severe presymptomatic COVID-19 patients on admission. Moreover, single-cell data analyses revealed that the CD8+T cell exhaustion correlated to the progression of COVID-19.

Antibody seroprevalence in the epicenter Wuhan, Hubei, and six selected provinces after containment of the first epidemic wave of COVID-19 in China.

BACKGROUND: China implemented containment measures to stop SARS-CoV-2 transmission in response to the COVID-19 epidemic. After the first epidemic wave, we conducted population-based serological surveys to determine extent of infection, risk factors for infection, and neutralization antibody levels to assess the real infections in the random sampled population. METHODS: We used a multistage, stratified cluster random sampling strategy to conduct serological surveys in three areas - Wuhan, Hubei Province outside Wuhan, and six provinces selected on COVID-19 incidence and containment strategy. Participants were consenting individuals >1 year old who resided in the survey area >14 days during the epidemic. Provinces screened sera for SARS-CoV-2-specific IgM, IgG, and total antibody by two lateral flow immunoassays and one magnetic chemiluminescence enzyme immunoassay; positive samples were verified by micro-neutralization assay. FINDINGS: We enrolled 34,857 participants (overall response rate, 92%); 427 were positive by micro-neutralization assay. Wuhan had the highest weighted seroprevalence (4•43%, 95% confidence interval [95%CI]=3•48%-5•62%), followed by Hubei-ex-Wuhan (0•44%, 95%CI=0•26%-0•76%), and the other provinces (<0•1%). Living in Wuhan (adjusted odds ratio aOR=13•70, 95%CI= 7•91-23•75), contact with COVID-19 patients (aOR=7•35, 95%CI=5•05-10•69), and age over 40 (aOR=1•36, 95%CI=1•07-1•72) were significantly associated with SARS-CoV-2 infection. Among seropositives, 101 (24%) reported symptoms and had higher geometric mean neutralizing antibody titers than among the 326 (76%) without symptoms (30±2•4 vs 15±2•1, p<0•001). INTERPRETATION: The low overall extent of infection and steep gradient of seropositivity from Wuhan to the outer provinces provide evidence supporting the success of containment of the first wave of COVID-19 in China. SARS-CoV-2 infection was largely asymptomatic, emphasizing the importance of active case finding and physical distancing. Virtually the entire population of China remains susceptible to SARS-CoV-2; vaccination will be needed for long-term protection. FUNDING: This study was supported by the Ministry of Science and Technology (2020YFC0846900) and the National Natural Science Foundation of China (82041026, 82041027, 82041028, 82041029, 82041030, 82041032, 82041033).

Estimating the time interval between transmission generations and the presymptomatic period by contact tracing surveillance data from 31 provinces in the mainland of China

The global pandemic of 2019 coronavirus disease (COVID-19) is a great assault to public health. Presymptomatic transmission cannot be controlled with measures designed for symptomatic persons, such as isolation. This study aimed to estimate the interval of the transmission generation (TG) and the presymptomatic period of COVID-19, and compare the fitting effects of TG and serial interval (SI) based on the SEIHR model incorporating the surveillance data of 3453 cases in 31 provinces. These data were allocated into three distributions and the value of AIC presented that the Weibull distribution fitted well. The mean of TG was 5.2 days (95% CI: 4.6-5.8). The mean of the presymptomatic period was 2.4 days (95% CI: 1.5-3.2). The dynamic model using TG as the generation time performed well. Eight provinces exhibited a basic reproduction number from 2.16 to 3.14. Measures should be taken to control presymptomatic transmission in the COVID-19 pandemic.

Pre-diagnostic circulating concentrations of insulin-like growth factor-1 and risk of COVID-19 mortality: results from UK Biobank.

Coronavirus disease 2019 (COVID-19) deteriorates suddenly primarily due to excessive inflammatory injury, and insulin-like growth factor-1 (IGF-1) is implicated in endocrine control of the immune system. However, the effect of IGF-1 levels on COVID-19 prognosis remains unknown. Using UK Biobank resource, we investigated the association between circulating IGF-1 concentrations and mortality risk (available death data updated on 07 Sep 2020) among COVID-19 patients who had pre-diagnostic serum IGF-1 measurements at baseline (2006-2010). Unconditional logistic regression was performed to estimate the odds ratio (OR) and 95% confidence intervals (CIs) of mortality. Among 1670 COVID-19 patients, 415 deaths occurred due to COVID-19. Compared to the lowest quartile of IGF-1 concentrations, the highest quartile was associated with a 41% lower risk of mortality (OR = 0.59, 95% CI 0.41-0.86, P-trend = 0.01). In the continuous model, per 1-standard deviation increment in log-transformed IGF-1 was associated with a 15% reduction in the risk (intraclass correlation coefficients corrected OR = 0.85, 95% CI 0.73-0.99). The association was largely consistent in the various stratified and sensitivity analyses. In conclusion, our data suggest that higher IGF-1 concentrations are associated with a lower risk of COVID-19 mortality. Further studies are required to determine whether and how targeting IGF-1 pathway might improve COVID-19 prognosis.

Basic reproduction number and predicted trends of coronavirus disease 2019 epidemic in the mainland of China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a serious epidemic around the world, but it has been effectively controlled in the mainland of China. The Chinese government limited the migration of people almost from all walks of life. Medical workers have rushed into Hubei province to fight against the epidemic. Any activity that can increase infection is prohibited. The aim of this study was to confirm that timely lockdown, large-scale case-screening and other control measures proposed by the Chinese government were effective to contain the spread of the virus in the mainland of China. METHODS: Based on disease transmission-related parameters, this study was designed to predict the trend of COVID-19 epidemic in the mainland of China and provide theoretical basis for current prevention and control. An SEIQR epidemiological model incorporating asymptomatic transmission, short term immunity and imperfect isolation was constructed to evaluate the transmission dynamics of COVID-19 inside and outside of Hubei province. With COVID-19 cases confirmed by the National Health Commission (NHC), the optimal parameters of the model were set by calculating the minimum Chi-square value. RESULTS: Before the migration to and from Wuhan was cut off, the basic reproduction number in China was 5.6015. From 23 January to 26 January 2020, the basic reproduction number in China was 6.6037. From 27 January to 11 February 2020, the basic reproduction number outside Hubei province dropped below 1, but that in Hubei province remained 3.7732. Because of stricter controlling measures, especially after the initiation of the large-scale case-screening, the epidemic rampancy in Hubei has also been contained. The average basic reproduction number in Hubei province was 3.4094 as of 25 February 2020. We estimated the cumulative number of confirmed cases nationwide was 82 186, and 69 230 in Hubei province on 9 April 2020. CONCLUSIONS: The lockdown of Hubei province significantly reduced the basic reproduction number. The large-scale case-screening also showed the effectiveness in the epidemic control. This study provided experiences that could be replicated in other countries suffering from the epidemic. Although the epidemic is subsiding in China, the controlling efforts should not be terminated before May.

Spatial statistical analysis of Coronavirus Disease 2019 (Covid-19) in China.

The cluster of pneumonia cases linked to coronavirus disease 2019 (Covid-19), first reported in China in late December 2019 raised global concern, particularly as the cumulative number of cases reported between 10 January and 5 March 2020 reached 80,711. In order to better understand the spread of this new virus, we characterized the spatial patterns of Covid-19 cumulative cases using ArcGIS v.10.4.1 based on spatial autocorrelation and cluster analysis using Global Moran's I (Moran, 1950), Local Moran's I and Getis-Ord General G (Ord and Getis, 2001). Up to 5 March 2020, Hubei Province, the origin of the Covid-19 epidemic, had reported 67,592 Covid-19 cases, while the confirmed cases in the surrounding provinces Guangdong, Henan, Zhejiang and Hunan were 1351, 1272, 1215 and 1018, respectively. The top five regions with respect to incidence were the following provinces: Hubei (11.423/10,000), Zhejiang (0.212/10,000), Jiangxi (0.201/10,000), Beijing (0.196/10,000) and Chongqing (0.186/10,000). Global Moran's I analysis results showed that the incidence of Covid-19 is not negatively correlated in space (p=0.407413>0.05) and the High-Low cluster analysis demonstrated that there were no high-value incidence clusters (p=0.076098>0.05), while Local Moran's I analysis indicated that Hubei is the only province with High-Low aggregation (p<0.0001).

Implementation of Clinical Diagnostic Criteria and Universal Symptom Survey Contributed to Lower Magnitude and Faster Resolution of the COVID-19 Epidemic in Wuhan.

The majority of cases infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China centered in the city of Wuhan. Despite a rapid increase in the number of cases and deaths due to the coronavirus disease 2019 (COVID-19), the epidemic was stemmed via a combination of epidemic mitigation and control measures. This study evaluates how the implementation of clinical diagnostics and universal symptom surveys contributed to epidemic control in Wuhan. We extended the susceptibles-exposed-infectious-removed (SEIR) transmission dynamics model by considering three quarantined compartments (SEIR+Q). The SEIR+Q dynamics model was fitted using the daily reported number of confirmed infections and unconfirmed cases by clinical diagnostic criteria up to February 14, 2020, in Wuhan. Applying the model to carry forward the pre-February 14 trend in Wuhan, the number of daily new diagnosed cases would be expected to drop below 100 by March 25, below 10 by April 29, and reach 0 by May 31, 2020. The observed case counts after February 14 demonstrated that the daily new cases fell below 100 by March 6, below 10 by March 11, and reached 0 by March 18, respectively, 19, 49, and 74 d earlier than model predictions. By March 30, the observed number of cumulative confirmed cases was 50 006, which was 19 951 cases fewer than the predicted count. Effective reproductive number R(t) analysis using observed frequencies showed a remarkable decline after the implementation of clinical diagnostic criteria and universal symptom surveys, which was significantly below the R(t) curve estimated by the model assuming that the pre-February 14 trend was carried forward. In conclusion, the proposed SEIR+Q dynamics model was a good fit for the epidemic data in Wuhan and explained the large increase in the number of infections during February 12-14, 2020. The implementation of clinical diagnostic criteria and universal symptom surveys contributed to a contraction in both the magnitude and the duration of the epidemic in Wuhan.

Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing, China.

Previous studies have showed clinical characteristics of patients with the 2019 novel coronavirus disease (COVID-19) and the evidence of person-to-person transmission. Limited data are available for asymptomatic infections. This study aims to present the clinical characteristics of 24 cases with asymptomatic infection screened from close contacts and to show the transmission potential of asymptomatic COVID-19 virus carriers. Epidemiological investigations were conducted among all close contacts of COVID-19 patients (or suspected patients) in Nanjing, Jiangsu Province, China, from Jan 28 to Feb 9, 2020, both in clinic and in community. Asymptomatic carriers were laboratory-confirmed positive for the COVID-19 virus by testing the nucleic acid of the pharyngeal swab samples. Their clinical records, laboratory assessments, and chest CT scans were reviewed. As a result, none of the 24 asymptomatic cases presented any obvious symptoms while nucleic acid screening. Five cases (20.8%) developed symptoms (fever, cough, fatigue, etc.) during hospitalization. Twelve (50.0%) cases showed typical CT images of ground-glass chest and 5 (20.8%) presented stripe shadowing in the lungs. The remaining 7 (29.2%) cases showed normal CT image and had no symptoms during hospitalization. These 7 cases were younger (median age: 14.0 years; P=0.012) than the rest. None of the 24 cases developed severe COVID-19 pneumonia or died. The median communicable period, defined as the interval from the first day of positive nucleic acid tests to the first day of continuous negative tests, was 9.5 days (up to 21 days among the 24 asymptomatic cases). Through epidemiological investigation, we observed a typical asymptomatic transmission to the cohabiting family members, which even caused severe COVID-19 pneumonia. Overall, the asymptomatic carriers identified from close contacts were prone to be mildly ill during hospitalization. However, the communicable period could be up to three weeks and the communicated patients could develop severe illness. These results highlighted the importance of close contact tracing and longitudinally surveillance via virus nucleic acid tests. Further isolation recommendation and continuous nucleic acid tests may also be recommended to the patients discharged.