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Surface rupturing data from the historical earthquakes is used for obtaining empirical regression parameters for fault displacement hazard assessment. This paper represents an additional compilation and analysis effort, extending the first version of the SUrface Ruptures due to Earthquake (SURE) database. This new release contains slip measurements and mapped surface rupture traces of 50 surface rupturing earthquakes of reverse, normal, and strike-slip kinematics occurred all over the world between 1872 and 2019. As a novelty, a ranking scheme of the rupture features is applied to all the traces and slip measurements in the database. Fault ranking introduces geology as a primary analysis tool and allows the end user to obtain regression parameters suitable for the specific geological conditions at the site of interest. SURE 2.0 dataset consists of a table containing the background information about each earthquake, a table containing the slip measurement data of each event, and a joint shapefile containing all the surface rupture traces of the events in the database.
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We integrate an epidemiological model, augmented with contact and mobility analyses, with a two-sector macroeconomic model, to assess the economic costs of labor supply disruptions in a pandemic. The model is designed to capture key characteristics of the U.S. input-output tables with a core sector that produces intermediate inputs not easily replaceable by the other sectors, possibly subject to minimum-scale requirements. Using epidemiological and mobility data to inform our exercises, we show that the reduction in labor services due to the observed social distancing (spontaneous and mandatory) could explain up to 6-8 percentage points of the roughly 12% U.S. GDP contraction in the second quarter of 2020. We show that public measures designed to protect workers in core industries and occupations with tasks that cannot be performed from home, can flatten the epidemiological curve at reduced economic costs-and contain vulnerabilities to supply disruptions, namely a new surge of infections. Using state-level data for the United States, we provide econometric evidence that spontaneous social distancing was no less costly than mandated social distancing.
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OBJECTIVE: Elderly heart failure patients are at high risk of events. Available studies and systematic reviews suggest that elderly patients benefit from disease management programmes (DMPs). However, important questions remain open, including the optimal follow-up intensity and duration and whether such interventions are cost-effective during long-term follow-up and in different healthcare systems. The aim of this study was to determine the long-term efficacy of a hybrid DMP in consecutive older outpatients. METHODS: Intervention consisted in combined hospital-based (cardiologists and nurse-coordinators from two heart failure clinics) and home-based (patient's general practitioner visits) care. The components of the DMP were the following: discharge planning, education, therapy optimisation, improved communication, early attention to signs and symptoms. Intensive follow-up was based on scheduled hospital visits (starting within 14 days of discharge), nurse's phone call and home general practitioner visits. RESULTS: A group of 173 patients aged > or =70 years (mean age 77 +/- 6 years, 48% women) was randomly assigned to DMP (n = 86) or usual care (n = 87). At 2-year follow-up, a 36% reduction in all-cause death and heart failure hospital admissions was observed in DMP vs. usual care. All-cause and heart failure admissions as well as the length of hospital stay were also reduced. DMP patients reported, compared to baseline, significant improvements in functional status, quality of life and beta-blocker prescription rate. The intervention was cost-effective with a mean saving of euro 982.04 per patient enrolled. CONCLUSIONS: A hybrid DMP for elderly heart failure patients improves outcomes and is cost-effective over a long-term follow-up.
