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.

Background— The association between secondhand smoke (SHS) and risk of peripheral arterial disease (PAD) and stroke remains uncertain. Methods and Results— We examined the relationship between SHS and cardiovascular diseases, particularly PAD and stroke, in Chinese women who never smoked from a population-based cross-sectional study in Beijing, China. SHS exposure was defined as exposure to another person’s tobacco smoke at home or in the workplace. Cardiovascular disease events included coronary heart disease, stroke, and PAD. PAD was defined by signs of intermittent claudication as measured by the World Health Organization Rose questionnaire and an ankle-brachial index of <0.90. Among 1209 women who never smoked, 39.5% were exposed to SHS at home or in workplaces. Those individuals who were exposed to SHS had a significantly higher risk of coronary heart disease (adjusted odds ratio [OR], 1.69; 95% CI, 1.31 to 2.18) and ischemic stroke (OR, 1.56; 95% CI, 1.03 to 2.35) than those never exposed to SHS after adjustment for 13 potential risk factors. The adjusted ORs of PAD defined by intermittent claudication, by ankle-brachial index <0.90, and by either intermittent claudication or ankle-brachial index <0.90 were 1.87 (95% CI, 1.30 to 2.68), 1.47 (95% CI, 1.07 to 2.03), and 1.67 (95% CI, 1.23 to 2.16), respectively. Dose-response relationships were found between SHS exposure amount (cigarettes per day) and duration (minutes per day) and increasing prevalence of coronary heart disease, ischemic stroke, and PAD. Conclusions— In China, SHS exposure in women is highly prevalent. In addition to being a risk factor for coronary heart disease, SHS should be considered an important risk factor for ischemic stroke and PAD in nonsmoking women.

The proportion of the world population aged 60 years or over is expected to increase from 12% in 2013 to 21% in 2050. This increase will represent more than 2 billion elderly individuals, including 400 million people aged 80 years or older and 3.4 million centenarians in 2050.¹ The population of individuals of advanced ages, including near-centenarians and centenarians, has become the fastest-growing segment of the population.² This growth has led to considerable concern about the social and economic burden of disease and disability in this age group, for the oldest old are vulnerable to multiple age-related chronic conditions and disabilities and are at a high risk of...

Previous studies have evaluated the effectiveness of interventions aimed at screen time reduction, but the results have been inconsistent. We therefore conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) to summarize the accumulating evidence of the impact of interventions targeting screen time reduction on body mass index (BMI) reduction and screen time reduction. The PubMed, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) databases were searched for RCTs on the effect of interventions targeting screen time reduction. The primary and secondary outcomes were the mean difference between the treatment and control groups in the changes in BMI and changes in screen viewing time. A random effects model was used to calculate the pooled mean differences. Fourteen trials including 2238 participants were assessed. The pooled analysis suggested that interventions targeting screen time reduction had a significant effect on BMI reduction (-0.15 kg/m, P < 0.001, I = 0) and on screen time reduction (-4.63 h/w, P = 0.003, I = 94.6%). Subgroup analysis showed that a significant effect of screen time reduction was observed in studies in which the duration of intervention was <7 months and that the types of interventions in those studies were health promotion curricula or counseling. Interventions for screen time reduction might be effective in reducing screen time and preventing excess weight. Further rigorous investigations with larger samples and longer follow-up periods are still needed to evaluate the efficacy of screen time reduction both in children and in adults.