Suchergebnisse

Abstract. An operative methodology for rainfall thresholds definition is illustrated, in order to provide at critical river section optimal flood warnings. Threshold overcoming could produce a critical situation in river sites exposed to alluvial risk and trigger the prevention and emergency system alert. The procedure for the definition of critical rainfall threshold values is based both on the quantitative precipitation observed and the hydrological response of the basin. Thresholds values specify the precipitation amount for a given duration that generates a critical discharge in a given cross section and are estimated by hydrological modelling for several scenarios (e.g.: modifying the soil moisture conditions). Some preliminary results, in terms of reliability analysis (presence of false alarms and missed alarms, evaluated using indicators like hit rate and false alarm rate) for the case study of Mignone River are presented.

Abstract. Hydrological models are the basis of operational flood-forecasting systems. The accuracy of these models is strongly dependent on the quality and quantity of the input information represented by rainfall height. Finer space-time rainfall resolution results in more accurate hazard forecasting. In this framework, an optimum raingauge network is essential in predicting flood events. This paper develops an entropy-based approach to evaluate the maximum information content achievable by a rainfall network for different sampling time intervals. The procedure is based on the determination of the coefficients of transferred and nontransferred information and on the relative isoinformation contours. The nontransferred information value achieved by the whole network is strictly dependent on the sampling time intervals considered. An empirical curve is defined, to assess the objective of the research: the nontransferred information value is plotted versus the associated sampling time on a semi-log scale. The curve has a linear trend. In this paper, the methodology is applied to the high-density raingauge network of the urban area of Rome.

Abstract. Flash flood events are floods characterised by a very rapid response of basins to storms, often resulting in loss of life and property damage. Due to the specific space-time scale of this type of flood, the lead time available for triggering civil protection measures is typically short. Rainfall threshold values specify the amount of precipitation for a given duration that generates a critical discharge in a given river cross section. If the threshold values are exceeded, it can produce a critical situation in river sites exposed to alluvial risk. It is therefore possible to directly compare the observed or forecasted precipitation with critical reference values, without running online real-time forecasting systems. The focus of this study is the Mignone River basin, located in Central Italy. The critical rainfall threshold values are evaluated by minimising a utility function based on the informative entropy concept and by using a simulation approach based on radar data. The study concludes with a system performance analysis, in terms of correctly issued warnings, false alarms and missed alarms.

Background: This prospective, multicentre, observational INVIDIa-2 study is investigating the clinical efficacy of influenza vaccination in advanced-cancer patients receiving immune-checkpoint inhibitors (ICIs), enrolled in 82 Italian centres, from October 2019 to January 2020. The primary endpoint was the incidence of influenza-like illness (ILI) until 30 April 2020. All the ILI episodes, laboratory tests, complications, hospitalizations and pneumonitis were recorded. Therefore, the study prospectively recorded all the COVID-19 ILI events. Patients and methods: Patients were included in this non-prespecified COVID-19 analysis, if alive on 31 January 2020, when the Italian government declared the national emergency. The prevalence of confirmed COVID-19 cases was detected as ILI episode with laboratory confirmation of SARS-CoV-2. Cases with clinical-radiological diagnosis of COVID-19 (COVID-like ILIs), were also reported. Results: Out of 1257 enrolled patients, 955 matched the inclusion criteria for this unplanned analysis. From 31 January to 30 April 2020, 66 patients had ILI: 9 of 955 cases were confirmed COVID-19 ILIs, with prevalence of 0.9% [95% confidence interval (CI): 0.3–2.4], a hospitalization rate of 100% and a mortality rate of 77.8%. Including 5 COVID-like ILIs, the overall COVID-19 prevalence was 1.5% (95% CI: 0.5–3.1), with 100% hospitalization and 64% mortality. The presence of elderly, males and comorbidities was significantly higher among patients vaccinated against influenza versus unvaccinated (p = 0.009, p < 0.0001, p < 0.0001). Overall COVID-19 prevalence was 1.2% for vaccinated (six of 482 cases, all confirmed) and 1.7% for unvaccinated (8 of 473, 3 confirmed COVID-19 and 5 COVID-like), p = 0.52. The difference remained non-significant, considering confirmed COVID-19 only (p = 0.33). Conclusion: COVID-19 has a meaningful clinical impact on the cancer-patient population receiving ICIs, with high prevalence, hospitalization and an alarming mortality rate among symptomatic cases. ...