Health information-seeking behavior provides a variety of benefits, such as reducing knowledge gaps and educating individuals outside the medical office. This study aimed at evaluating if different sources used to gather information on COVID-19 could affect the willingness to undergo dental appointments. An anonymous survey was posted on social media. The 1003 respondents used several channels of communication, clearly distinguishing reliable from unreliable ones. Multiple logistic regression estimated the effect of different information channels on the probability of being strongly influenced by COVID-19 in accessing upcoming dental appointments. Newspapers were the most-used channel of information (61.2%), blogs and forums the least used (11.2%). Overall, the more an individual was informed, the higher was the risk of missing upcoming dental care appointments (OR 2.05, CI 1.45–2.90, p < 0.001). The two most reliable channels of communication were identified in journals/websites of medicine and healthcare professionals. Women proved to be more active in gathering information and relying on less secure but more personal channels, such as social media and friends and family, thus having an increased risk of being influenced by COVID-19 information regarding upcoming dental care appointments (OR 3.62, CI 0.85–15.52, p < 0.1 and OR 1.60, CI 1.00–2.58, p < 0.1, respectively). Social media should have a greater presence on the side of medical service providers to avoid distortions of information and fake news that ultimately cause fear among citizens and compromise their health. Healthcare professionals and institutions should adapt their communication channels based on the audience they want to address to optimize the education and information of the final users.

A measure for portfolio risk management is proposed by extending the Markowitz mean-variance approach to include the left-hand tail effects of asset returns. Two risk dimensions are captured: asset covariance risk along risk in left-hand tail similarity and volatility. The key ingredient is an informative set on the left-hand tail distributions of asset returns obtained by an adaptive clustering procedure. This set allows a left tail similarity and left tail volatility to be defined, thereby providing a definition for the left-tail-covariance-like matrix. The convex combination of the two covariance matrices generates a “two-dimensional” risk that, when applied to portfolio selection, provides a measure of its systemic vulnerability due to the asset centrality. This is done by simply associating a suitable node-weighted network with the portfolio. Higher values of this risk indicate an asset allocation suffering from too much exposure to volatile assets whose return dynamics behave too similarly in left-hand tail distributions and/or co-movements, as well as being too connected to each other. Minimizing these combined risks reduces losses and increases profits, with a low variability in the profit and loss distribution. The portfolio selection compares favorably with some competing approaches. An empirical analysis is made using exchange traded fund prices over the period January 2006–February 2018.

This paper aims to examine the impact of the Covid-19 pandemic on multidimensional poverty in Italy and its provinces by comparing household poverty levels before and after the outbreak. To capture the multidimensionality of poverty, we analyze various dimensions, including economic well-being, health status, education, neighborhood quality, and subjective well-being. The empirical analysis relies on micro-data from Istat’s aspects of daily life (AVQ) survey, covering the years 2018–2021. As the survey’s direct estimates are reliable only at the regional level (NUTS 2), we apply small area estimation techniques to produce accurate estimates of provincial (NUTS 3) deprivation incidences. Subsequently, we aggregate the deprivation headcounts across the elementary indicators using penalized power mean composite indicators. The empirical findings indicate that overall multidimensional poverty worsened in most of the Italian provinces, particularly during the second year of the pandemic, with higher levels persisting in southern areas. The various dimensions of poverty exhibited different trends, with education, subjective well-being, and health emerging as the most negatively affected in numerous provinces.

In this work we analyze the vulnerability of people aged 50+ living in 11 European Countries, taking into account for two aspects: a physical-economic dimension and a social one. Data come from the Survey of Health, Ageing, and Retirement in Europe (SHARE) and refer to the Covid-19 period, that is 2019-2020. Results show a geographical path of vulnerability: Mediterranean Countries register the higher vulnerability, especially in the Economic-Health domain.

In recent years, there has been growing attention to evaluating well-being at local level. Along this line, since 2013, the Italian Institute of Statistics (ISTAT) annually releases a dashboard of indicators to measure the so-called Equitable and Sustainable Well-Being (BES) for Italy, its Macro-area (NUTS-1) and regions (NUTS-2). More recently, the ISTAT provides BES indicators at local level (NUTS-3), related the 107 Italian provinces and metropolitan cities. The aim of the paper is to provide a more in-depth analysis of territorial inequalities and divergences across the Italian provinces. Specifically, the paper represents the first attempt to synthetize the main domain of BES (economic, social and environmental among others) through the parameters underlying the Beta distribution of the multidimensional well-being. The parameters - mode and concentration- associated with the Beta distribution and used as a proxy of territorial disparities identify a high degree of heterogeneity not only between the Northern and Southern Italian provinces, but also among adjacent provinces.

Recent studies have attempted to measure differences in lifestyle quality across the world. This paper contributes to this strand of literature by extending the indicator introduced in Milevsky (2020), i.e., “longevity-risk-adjusted global age” (LRaG age), to deal with the new short-term mortality fluctuation data series freely available from the Human Mortality Database. The new weekly data on mortality allow measuring weekly biological age. The weekly differences between biological and chronological ages across countries were used to assess country resilience to the COVID-19 pandemic in terms of excess mortality and health expenditure. Countries with a biological age lower than the chronological age had a lower excess mortality in 2020–2021 and a lower health expenditure, thus indicating some resilience to the shock of COVID-19.