Background: Coronavirus Disease 2019 (COVID-19) is currently a global public health threat. Outside of China, Italy is one of the countries suffering the most with the COVID-19 epidemic. It is important to predict the epidemic trend of the COVID-19 epidemic in Italy to help develop public health strategies. Methods: We used time-series data of COVID-19 from Jan 22 2020 to Apr 02 2020. An infectious disease dynamic extended susceptible-infected-removed (eSIR) model, which covers the effects of different intervention measures in dissimilar periods, was applied to estimate the epidemic trend in Italy. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credible interval (CI). Hunan, with a similar total population number to Italy, was used as a comparative item. Results: In the eSIR model, we estimated that the mean of basic reproductive number for COVID-19 was 4.34 (95% CI, 3.04-6.00) in Italy and 3.16 (95% CI, 1.73-5.25) in Hunan. There would be a total of 182 051 infected cases (95%CI:116 114-274 378) under the current country blockade and the endpoint would be Aug 05 in Italy. Conclusion: Italy's current strict measures can efficaciously prevent the further spread of COVID-19 and should be maintained. Necessary strict public health measures should be implemented as soon as possible in other European countries with a high number of COVID-19 cases. The most effective strategy needs to be confirmed in further studies.

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Background: The discipline of anaesthesiology in China has undergone historical changes and development during the past century. However, nationwide comprehensive data on the current status of each hospital department providing anaesthesia care has been lacking since the discipline was first established in China. This information is essential for effective regulation of healthcare policies by both the professional associations and the government health ministry. Therefore, a nationwide survey was set up in 2018 to investigate the current status of Chinese anaesthesiology. This paper reports the findings of the survey. Methods: We performed a cross-sectional nationwide census survey of the current status of each hospital department providing anaesthesia care in 31 provinces across the Chinese mainland. The content of the survey included general information of the department, the hospital level and scale, the volume of the anaesthesiology department, the characteristics of anaesthesiologists, and the caseload of the anaesthesiology departments. Face-to-face interviews were performed by trained interviewers. The Chinese Anaesthesiology Department Tracking Database (CADTD) was established during the survey. Data quality control was undertaken by the investigation committee throughout the survey process. Findings: The nationwide census survey was completed by 11,432 hospital departments providing anaesthesia care throughout mainland China from June 1, 2018 to June 30, 2019. Among the 11,432 departments, 4591 (40 • 16%) belonged to specialised hospitals, while 6841 (59 • 84%) were affiliated to general hospitals. The proportion of independent anaesthesiology departments was 45 • 15% in mainland China. There was a total of 92,726 anaesthesiologists, or 6 • 7 per 10 0,0 0 0 of the population. Regions with better economic conditions had more anaesthesiologists per 10 0,0 0 0 of the population. From 2015 to 2017, the workload of anaesthesiologists has increased by 10%. Interpretation: The discipline of anaesthesiology in China has entered a rapid development phase. However, the current status of anaesthesiology is not well defined, which makes it difficult to meet the needs of the increasing Chinese healthcare demand. The evidence from this survey offers valuable information for policy makers and anaesthesiology associations to monitor the development of the discipline and regulate healthcare policies effectively.

Background: As evidence on depression and health-related quality of life (HRQoL) among the oldest-old is currently limited, this study aimed to re-examine the association between depression and HRQoL among centenarians. Methods:We analyzed cross-sectional data from the China Hainan Centenarian Cohort Study (CHCCS). The 15-item Geriatric Depression Scale (GDS-15) and three-level EuroQol five-dimensions (EQ-5D-3L) were used to evaluate depression and HRQoL, respectively. Poor health states were defined as EQ-5D index <0.665. Based on their GDS-15 score, individuals were categorized into three stages of depression: major depressive disorder (MDD; score ≥10), minor depressive disorder (MnDD; score between 6 and 9), and normal (score ≤5). Based on sex and comorbidity stratification, multivariable logistic regression was used to calculate the risk of poor health state in different levels of depression. We also used restricted cubic splines with a knot at 5 points (GDS-15) to flexibly model the association of GDS-15 scores with poor health states.Results: Totally, 1,002 participants were included in this study for analysis. Participants' median age was 102 years, and 82.04% were female. The median EQ-5D index was 0.68 (range: −0.149-1), and the mean VAS and GDS-15 scores were 61.60 (range: 0-100), and 5.23 (range: 0-15), respectively. Centenarians with MnDD and MDD accounted for 38.12 and 9.98%, respectively. While those with poor health states accounted for 45.11%. For every 1-point increase in GDS-15, the risk of poor health state increased by 20% (P < 0.001) after an adjustment for age, gender, ethnicity, marital status, education, residence type, smoking, drinking, weekly exercise, body mass index category, serum albumin, 25-hydroxyvitamin D, C-reactive protein, and comorbidities. MnDD and MDD were independent risk factors for poor health state (MnDD, OR = 2.76, P < 0.001; MDD, OR = 3.14, P < 0.001). The association was more prominent in centenarians without comorbidity.Conclusions: This study demonstrated a negative association between depression and HRQoL in Chinese centenarians, especially in centenarians without comorbidity. Large-scale prospective studies are needed to corroborate our findings and provide more information about the causal inference and internal mechanisms of this association.