Background COVID-19, a viral respiratory disease first reported in December 2019, quickly became a threat to global public health. Further understanding of the epidemiology of the SARS-CoV-2 virus and the risk perception of the community may better inform targeted interventions to reduce the impact and spread of COVID-19. Objective In this study, we aimed to examine the association between chronic diseases and serious outcomes following COVID-19 infection, and to explore its influence on people’s self-perception of risk for worse COVID-19 outcomes. Methods This study draws data from two databases: (1) the nationwide database of all confirmed COVID-19 cases in Portugal, extracted on April 28, 2020 (n=20,293); and (2) the community-based COVID-19 Barometer survey, which contains data on health status, perceptions, and behaviors during the first wave of COVID-19 (n=171,087). We assessed the association between relevant chronic diseases (ie, respiratory, cardiovascular, and renal diseases; diabetes; and cancer) and death and intensive care unit (ICU) admission following COVID-19 infection. We identified determinants of self-perception of risk for severe COVID-19 outcomes using logistic regression models. Results Respiratory, cardiovascular, and renal diseases were associated with mortality and ICU admission among patients hospitalized due to COVID-19 infection (odds ratio [OR] 1.48, 95% CI 1.11-1.98; OR 3.39, 95% CI 1.80-6.40; and OR 2.25, 95% CI 1.66-3.06, respectively). Diabetes and cancer were associated with serious outcomes only when considering the full sample of COVID-19–infected cases in the country (OR 1.30, 95% CI 1.03-1.64; and OR 1.40, 95% CI 1.03-1.89, respectively). Older age and male sex were both associated with mortality and ICU admission. The perception of risk for severe COVID-19 disease in the study population was 23.9% (n=40,890). This was markedly higher for older adults (n=5235, 46.4%), those with at least one chronic disease (n=17,647, 51.6%), or those in both of these categories (n=3212, 67.7%). All included diseases were associated with self-perceptions of high risk in this population. Conclusions Our results demonstrate the association between some prevalent chronic diseases and increased risk of worse COVID-19 outcomes. It also brings forth a greater understanding of the community’s risk perceptions of serious COVID-19 disease. Hence, this study may aid health authorities to better adapt measures to the real needs of the population and to identify vulnerable individuals requiring further education and awareness of preventive measures.

BackgroundResearch evaluating enforcement and compliance with smoking partial bans is rather scarce, especially in countries with relative weak tobacco control policies, such as Portugal. There is also scarce evidence on specific high risk groups such as vehicle workers. In January 2008, Portugal implemented a partial ban, followed by poor enforcement. The purpose of this study was to explore the effectiveness of a partial smoking ban in a pro-smoking environment, specifically transportation by taxi in the city of Lisbon. Ban effectiveness was generally defined by ban awareness and support, compliance and enforcement.MethodsExploratory cross-sectional study; purposive sampling in selected Lisbon streets. Structured interviews were conducted by trained researchers while using taxi services (January 2009-December 2010). Participants: 250 taxi drivers (98.8% participation rate). Chi-square, McNemar, Man Whitney tests and multiple logistic regression were performed.ResultsOf the participants, 249 were male; median age was 53.0 years; 43.6% were current smokers. Most participants (82.8%) approved comprehensive bans; 84.8% reported that clients still asked to smoke in their taxis; 16.8% allowed clients to smoke. Prior to the ban this value was 76.9% (p < 0.001). The major reason for not allowing smoking was the legal ban and associated fines (71.2%). Of the smokers, 66.1% admitted smoking in their taxi. Stale smoke smells were detected in 37.6% of the cars. None of the taxi drivers did ever receive a fine for non-compliance. Heavy smoking, night-shift and allowing smoking prior the ban predicted non-compliance.ConclusionsDespite the strong ban support observed, high smoking prevalence and poor enforcement contribute to low compliance. The findings also suggest low compliance among night-shift and vehicle workers. This study clearly demonstrates that a partial and poorly-enforced ban is vulnerable to breaches, and highlights the need for clear and strong policies.

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Background: One month after the first COVID-19 infection was recorded, Portugal counted 18,051 cases and 599 deaths from COVID-19. To understand the overall impact on mortality of the pandemic of COVID-19, we estimated the excess mortality registered in Portugal during the first month of the epidemic, from March 16 until April 14 using two different methods. Methods: We compared the observed and expected daily deaths (historical average number from daily death registrations in the past 10 years) and used 2 standard deviations confidence limit for all-cause mortality by age and specific mortality cause, considering the last 6 years. An adapted Auto Regressive Integrated Moving Average (ARIMA) model was also tested to validate the estimated number of all-cause deaths during the study period. Results: Between March 16 and April 14, there was an excess of 1255 all-cause deaths, 14% more than expected. The number of daily deaths often surpassed the 2 standard deviations confidence limit. The excess mortality occurred mostly in people aged 75+. Forty-nine percent (49%) of the estimated excess deaths were registered as due to COVID-19, the other 51% registered as other natural causes. Conclusion: Even though Portugal took early containment measures against COVID-19, and the population complied massively with those measures, there was significant excess mortality during the first month of the pandemic, mostly among people aged 75+. Only half of the excess mortality was registered as directly due do COVID-19.