An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak. Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI. The early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96-2.55) to 3.58 (95%CI: 2.89-4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0. The mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks.

The ongoing coronavirus disease 2019 (COVID-19) outbreak, emerged in Wuhan, China in the end of 2019, has claimed more than 2600 lives as of 24 February 2020 and posed a huge threat to global public health. The Chinese government has implemented control measures including setting up special hospitals and travel restriction to mitigate the spread. We propose conceptual models for the COVID-19 outbreak in Wuhan with the consideration of individual behavioural reaction and governmental actions, e.g., holiday extension, travel restriction, hospitalisation and quarantine. We employe the estimates of these two key components from the 1918 influenza pandemic in London, United Kingdom, incorporated zoonotic introductions and the emigration, and then compute future trends and the reporting ratio. The model is concise in structure, and it successfully captures the course of the COVID-19 outbreak, and thus sheds light on understanding the trends of the outbreak.

Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R₀, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R₀. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403–540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18–25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R₀ of 2019-nCoV at 2.56 (95% CI: 2.49–2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation.

Background: The mental health consequences of the coronavirus disease (COVID-19) pandemic, community-wide interventions, and social media use during a pandemic are unclear. The first and most draconian interventions have been implemented in Wuhan, China, and these countermeasures have been increasingly deployed by countries around the world. Objective: The aim of this study was to examine risk factors, including the use of social media, for probable anxiety and depression in the community and among health professionals in the epicenter, Wuhan, China. Methods: We conducted an online survey via WeChat, the most widely used social media platform in China, which was administered to 1577 community-based adults and 214 health professionals in Wuhan. Probable anxiety and probable depression were assessed by the validated Generalized Anxiety Disorder-2 (cutoff ≥3) and Patient Health Questionnaire-2 (cutoff ≥3), respectively. A multivariable logistic regression analysis was used to examine factors associated with probable anxiety and probable depression. Results: Of the 1577 community-based adults, about one-fifth of respondents reported probable anxiety (n=376, 23.84%, 95% CI 21.8-26.0) and probable depression (n=303, 19.21%, 95% CI 17.3-21.2). Similarly, of the 214 health professionals, about one-fifth of surveyed health professionals reported probable anxiety (n=47, 22.0%, 95% CI 16.6-28.1) or probable depression (n=41, 19.2%, 95% CI 14.1-25.1). Around one-third of community-based adults and health professionals spent ≥2 hours daily on COVID-19 news via social media. Close contact with individuals with COVID-19 and spending ≥2 hours daily on COVID-19 news via social media were associated with probable anxiety and depression in community-based adults. Social support was associated with less probable anxiety and depression in both health professionals and community-based adults. Conclusions: The internet could be harnessed for telemedicine and restoring daily routines, yet caution is warranted toward spending excessive time searching for COVID-19 news on social media given the infodemic and emotional contagion through online social networks. Online platforms may be used to monitor the toll of the pandemic on mental health.

Quality of life (QOL) is an important component in assessing people’s health. Environmental quality can influence people’s QOL in the physical health, psychological, social relationships and environment domains. QOL in the four domains, overall QOL and general heath of residents living in the Kowloon Peninsula of Hong Kong were assessed. The association between satisfaction with the neighborhood environment and QOL, and health-related behaviors which mediated the effect were investigated. A sample of 317 residents completed a questionnaire which comprised the WHOQOL-BREF (Hong Kong version) to assess QOL, the International Physical Activity Questionnaire (IPAQ) to study physical activities, and questions on satisfaction with the neighborhood environment, health-related behaviors and socio-demographics. One-way ANOVA and linear regression were used to study the associations between environmental satisfaction and QOL in the four domains, overall QOL and general health, followed by assessing the relationships between environmental satisfaction and the potential health-related behavior mediators with regression tests. Mediation analysis was conducted using multiple linear regressions to study the effects of environmental satisfaction on QOL in the four domains, overall QOL and general health, as well as the potential mediating roles played by various health-related behaviors. A P-value of < 0.05 was considered as statistically significant. The residents had a relatively higher physical health mean score of 70.83 ± 12.69, and a lower environmental mean score of 61.98 ± 13.76. Moderate satisfaction with the neighborhood environment had a significant relationship with QOL in the psychological domain (β = 0.170, P = 0.006), however, this effect was partially mediated by the non-smoking behavior of the residents (β = 0.143, P = 0.022). Our residents had lower QOL in the physical health and psychological domains but similar QOL in the social relationships and environmental domains compared to other countries. Only QOL in the psychological domain could be predicted by the satisfaction with the neighborhood environment, and non-smoking status was a partial mediator of the effect of moderate environmental satisfaction on QOL in the psychological domain. Refrain from smoking seems to be able to lower the influence of neighborhood environment on people’s QOL in the psychological domain to a certain extent.

Background: The ongoing pandemic of coronavirus disease 2019 (COVID-19) has caused serious concerns about its potential adverse effects on pregnancy. There are limited data on maternal and neonatal outcomes of pregnant women with COVID-19 pneumonia.Methods: We conducted a case-control study to compare clinical characteristics and maternal and neonatal outcomes of pregnant women with and without COVID-19 pneumonia.Results: During the period 24 January–29 February 2020, there were 16 pregnant women with confirmed COVID-19 pneumonia and 18 suspected cases who were admitted to labor in the third trimester. Two had vaginal delivery and the rest were cesarean delivery. Few patients presented respiratory symptoms (fever and cough) on admission, but most had typical chest computed tomographic images of COVID-19 pneumonia. Compared to the controls, patients with COVID-19 pneumonia had lower counts of white blood cells (WBCs), neutrophils, C-reactive protein (CRP), and alanine aminotransferase on admission. Increased levels of WBCs, neutrophils, eosinophils, and CRP were found in postpartum blood tests of pneumonia patients. Three (18.8%) of the mothers with confirmed COVID-19 pneumonia and 3 (16.7%) with suspected COVID-19 pneumonia had preterm delivery due to maternal complications, which were significantly higher than in the control group. None experienced respiratory failure during their hospital stay. COVID-19 infection was not found in the newborns, and none developed severe neonatal complications.Conclusions: Severe maternal and neonatal complications were not observed in pregnant women with COVID-19 pneumonia who had vaginal or cesarean delivery. Mild respiratory symptoms of pregnant women with COVID-19 pneumonia highlight the need of effective screening on admission.