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BackgroundThe management of COVID-19 in Italian prisons triggered considerable concern at the beginning of the pandemic due to numerous riots which resulted in inmate deaths, damages and prison breaks. The aim of this study is to shed some light, through analysis of the infection and relevant disease parameters, on the period spanning from the second to the fourth wave of the outbreak in Italy’s prisons.MethodsReproductive number (Rt) and Hospitalisation were calculated through a Eulerian approach applied to differential equations derived from compartmental models. Comparison between trends was performed through paired t-test and linear regression analyses.ResultsThe infection trends (prevalence and Rt) show a high correlation between the prison population and the external community. Both the indices appear to be lagging 1 week in prison. The prisoners’ Rt values are not statistically different from those of the general population. The hospitalisation trend of inmates strongly correlates with the external population’s, with a delay of 2 weeks. The magnitude of hospitalisations in prison is less than in the external community for the period analysed.ConclusionsThe comparison with the external community revealed that in prison the infection prevalence was greater, although Rt values showed no significant difference, and the hospitalisation rate was lower. These results suggest that the consistent monitoring of inmates results in a higher infection prevalence while a wide vaccination campaign leads to a lower hospitalisation rate. All three indices demonstrate a lag of 1 or 2 weeks in prison. This delay could represent a useful time-window to strengthen planned countermeasures.

Background: Multiple Breath washout (MBW) represents an important tool to detect early a possible pulmonary exacerbation especially in Cystic Fibrosis (CF) disease. Lung clearance index (LCI) is the most commonly reported multiple breath washout (MBW) index and in the last years was used as management measure for evaluation. Our aim was to analyze clinical utility of LCI index variability in pulmonary exacerbation in CF. Methods: A single-center study was conducted at CF Unit of Bambino Gesù Children’s Hospital among hospitalized > 3 years patients for pulmonary exacerbations and treated with antibiotic intravenous treatment for 14 days. MBW and spirometry were evaluated within 72 hours of admission to hospital and at the end of hospitalization. Descriptive analysis was conducted and correlations between quantitative variables were investigated. Results: Fifty-seven patients (M22/F35) with an average age 18.56 (± 8.54) years were enrolled. LCI 2.5 was significantly reduced at the end of antibiotic treatment in both pediatric and adult populations with an average improvement of -6% in 37/57 patients. 26/57 are stable in LCI values. A significant elevation of +7.30% was found for FEV1%. 4/57 (7.02 %) had a significant deterioration in LCI values at the end of IV antibiotic treatment. A positive good correlation among LCI 2.5 and Scond (rho= +0.615, p=0.000) and LCI 2.5 and Sacin (rho=+0.649, p=0.000) and a negative strong correlation between FEV1% and LCI 2.5 were found in post treatment period. A better increase of LCI 2.5 in < 18 years (-10.27% vs -4.57%) than adult was noticed. Conclusions: LCI may have a role in the routine clinical care of CF patients as a good tool to assess response to intravenous antibiotic therapy.

Autism spectrum disorder (ASD) is a heterogeneous condition, characterized by complex genetic architectures and intertwined genetic/environmental interactions. Novel analysis approaches to disentangle its pathophysiology by computing large amounts of data are needed. We present an advanced machine learning technique, based on a clustering analysis on genotypical/phenotypical embedding spaces, to identify biological processes that might act as pathophysiological substrates for ASD. This technique was applied to the VariCarta database, which contained 187,794 variant events retrieved from 15,189 individuals with ASD. Nine clusters of ASD-related genes were identified. The 3 largest clusters included 68.6% of all individuals, consisting of 1455 (38.0%), 841 (21.9%), and 336 (8.7%) persons, respectively. Enrichment analysis was applied to isolate clinically relevant ASD-associated biological processes. Two of the identified clusters were characterized by individuals with an increased presence of variants linked to biological processes and cellular components, such as axon growth and guidance, synaptic membrane components, or transmission. The study also suggested other clusters with possible genotype–phenotype associations. Innovative methodologies, including machine learning, can improve our understanding of the underlying biological processes and gene variant networks that undergo the etiology and pathogenic mechanisms of ASD. Future work to ascertain the reproducibility of the presented methodology is warranted.

Introduction: Telemedicine and tele-monitoring represent an emerging-study area in several and chronic diseases. Tele-rehabilitation during Covid-19 disease became an essential tool to promote physical activity in total safety. Infact, for pwCF physical activity was fundamental not only for the respiratory program but also Aim: To evaluate the feasibility of home web-based program of home exercise training program in patients with cystic fibrosis during COVID-19 pandemic. Subjects and methods: 32 patients (12 M/ 20 F) age 20,52 (±9,3); FEV1 mean was 84,88% and Ph angle mean at T0 was 6,11 (sd 0,83). Results: Adherence average rate was 61,5 %. Satisfaction and utility scores were respectively 4.5 and 4.3(Likert Scale); about QoL the Body-domain had a statistically significant increase (pvalue Conclusion: Web-based rehabilitation could be a good tool but more studies are needed to confirm optimal values of adherence. Although data are based on a small sample size and longer periods of treatment are requested to analyze especially the physiological answer about heart rate and lung volumes.

Background: Mortality and causes of death are among the most important statistics used in assessing the effectiveness of a country’s health system. Several countries do not have information systems for collecting these data, and they must therefore be estimated from surveys. Objective: This study analyzes mortality data retrieved from official government databases in Iraqi Kurdistan to describe ten-year trends in natural causes of death. Methods: Data for natural causes of death, reported from 2009 to 2018, were extracted from the databases of the Registration Bureau of Births and Deaths and of the Forensic Medicine of the Province of Sulaymaniyah. A sample of 16,433 causes of death was analyzed. Results: Causes of death were coded according to the ICD-10 classification. Overall, cardiovascular diseases were the leading cause of mortality (52.6%), followed by neoplasms (17.7%), infectious and parasitic diseases (8.9%), and genitourinary diseases (6.3%). Neonatal conditions, congenital anomalies, and neurological conditions each accounted for less than 1% each. Numbers of natural deaths by cause and cause-specific mortality rates have been estimated for the entire Region of Iraqi Kurdistan. Comparisons with other sources suggest that there is a substantial amount of underreporting, especially in relation to deaths of infants and under-five children. Conclusion: Our findings confirm that the region is facing a burden of non-communicable diseases, coupled with high proportions of infectious diseases. However, the lack of effective vital statistics with combined under-reported data collection highlights the need for implementation of health monitoring systems. Advancements in generating high-quality data are essential in improving health and reducing preventable deaths. The establishment of a novel Health Information System is discussed.

Within the confinements of critical infrastructures, the COVID-19 pandemic is posing a series of challenges to Health Management. In the spotlight of highly contagious and quick spreading diseases within such enclosed facilities, whether it be a detention facility or otherwise, the health and safety of those living within its internment is paramount. This paper aims to highlight the specific challenges and the possible solutions to counteract this problem, starting from the lessons learnt from the Italian prison system case study. Following the general description of the available resources within the Italian prisons, the study aimed at specifically describing the first counteracting measures deployed by the Italian prison authorities during the first phase of the COVID-19 outbreak (February–July 2020). The aim was to propose an integrated plan capable of responding to a biological threat within the prisons. In particular, the study describes the actions and technical features that, in accordance with national and international legal frameworks and the relevant organisational bodies that run the Italian Prison Service, had been adopted in managing, right from the start, the COVID-19 pandemic until Summer 2020. Available information and data showed the ability of the prison administration to comply almost completely with WHO’s technical and human rights recommendations and also, in successfully handling prison emergencies both in terms of the sick and the deceased in line with the epidemiological framework of the general population. In addition, the paper proposes a draft of guidelines that should involve the National Health Service and the Prison Service that are aimed at supporting the local prison facilities with drawing up their own biological incident contingency plans. An approved, legal, standardised plan could increase the awareness of prison managers. It could even increase their self-confidence, in particular, with regard to cases of dispute and their ability to respond to them. In fact, it is valuable and forward-thinking to be able to demonstrate that every endeavour has been taken and that ‘certified’ best practices have been put in place in accordance with the national standards.

In recent decades, the increasing threats associated with Chemical and Radiological (CR) agents prompted the development of new tools to detect and collect samples without putting in danger first responders inside contaminated areas. A particularly promising branch of these technological developments relates to the integration of different detectors and sampling systems with Unmanned Aerial Vehicles (UAV). The adoption of this equipment may bring significant benefits for both military and civilian implementations. For instance, instrumented UAVs could be used in support of specialist military teams such as Sampling and Identification of Biological, Chemical and Radiological Agents (SIBCRA) team, tasked to perform sampling in contaminated areas, detecting the presence of CR substances in field and then confirming, collecting and evaluating the effective threats. Furthermore, instrumented UAVs may find dual-use application in the civil world in support of emergency teams during industrial accidents and in the monitoring activities of critical infrastructures. Small size drones equipped with different instruments for detection and collection of samples may enable, indeed, several applications, becoming a tool versatile and easy to use in different fields, and even featuring equipment normally utilized in manual operation. The authors hereby present the design of miniaturized sensors for a mission-oriented UAV application and the preliminary results from an experimental campaign performed in 2020.

The advancements in the field of robotics, specifically in the aerial robotics, combined with technological improvements of the capability of drones, have increased dramatically the use of these devices as a valuable tool in a wide range of applications. From civil to commercial and military area, the requirements in the emerging application for monitoring complex scenarios that are potentially dangerous for operators give rise to the need of a more powerful and sophisticated approach. This work aims at proposing the use of swarm drones to increase plume detection, tracking and source declaration for chemical releases. The several advantages which this technology may lead to this research and application fields are investigated, as well as the research and technological activities to be performed to make swarm drones efficient, reliable, and accurate.

Unconventional scenarios with hazardous radioactive levels are expected as consequences of accidents in the industrial sector of the nuclear energy production or following intentional releases of radioactive materials for terrorist purposes (dirty bombs, indoor contaminations, etc.). Nowadays, the need to balance the high standards of safety and security through an effective detection network is a matter of paramount importance. In this work, the authors’ challenge has been to design, realize and test a low-cost gamma detection and spectroscopy system which may be used in unmanned vehicles in general and/or drones with low payload capabilities. The designed platform may be used to carry out mapping or localization operations in order to reduce the risk factor for first responders or for the population affected by radiological and nuclear events. In this paper, the design process of a gamma ray detection and spectroscopy system based on affordable and commercially available technologies is presented along with the results of our ongoing characterization of the prototype.

The development of a tool to reduce the exposure of personnel in case of intentional or accidental toxic chemicals dispersion scenarios opens the field to new operational perspectives in the domain of operator safety and of critical infrastructure monitoring. The use of two sensors with different operating principles, metal oxide and photo-ionization detector, allows to confirm the presence of specific classes of chemicals in a contaminated area. All instruments are expected to be integrated into the payload of an unmanned aerial vehicle (UAV) and used for different purposes such as critical infrastructure surveillance focused on the volatile organic chemical and chemical warfare agents (CWA) detection and the post-incident of contamination level monitoring. In this paper, the authors presented the hardware set-up implemented and the test realized with CWAs simulants and will discuss the results obtained presenting advantages and disadvantages of this system in an application such as a UAV for the detection of chemical substances.

Genome sequencing has identified a large number of putative autism spectrum disorder (ASD) risk genes, revealing possible disrupted biological pathways, however, the genetic and environmental underpinnings of ASD remain mostly unanswered. The presented methodology aimed to identify genetically related clusters of ASD individuals. By using the VariCarta dataset, which contains data retrieved from 13,069 people with ASD, we compared patients pairwise to build &ldquo, patient similarity matrices&rdquo, Hierarchical-agglomerative-clustering and heatmapping were performed, followed by enrichment analysis (EA). We analyzed whole-genome sequencing retrieved from 2062 individuals, and isolated 11,609 genetic variants shared by at least two people. The analysis yielded three clusters, composed, respectively, by 574 (27.8%), 507 (24.6%), and 650 (31.5%) individuals. Overall, 4187 variants (36.1%) were common to the three clusters. The EA revealed that the biological processes related to the shared genetic variants were mainly involved in neuron projection guidance and morphogenesis, cell junctions, synapse assembly, and in observational, imitative, and vocal learning. The study highlighted genetic networks, which were more frequent in a sample of people with ASD, compared to the overall population. We suggest that itemizing not only single variants, but also gene networks, might support ASD etiopathology research. Future work on larger databases will have to ascertain the reproducibility of this methodology.

Background: Developments in gene-hunting techniques identified several ASD associated genes. The considerable significance of cluster analysis associated with gene network studies has led to reveal many disrupted key pathways in ASD, even if its genetic underpinnings remain a challenging task. This study aims to determine, through a novel data-driven approach, how networks of mutated genes impact biological processes underlying autism. Methods: We analyzed the VariCarta dataset, which presents more than 200,000 genomic variant events collected from 13,069 people with ASD. Firstly, we created a whole-genome and an exome sequencing subset. Then, for each subset we compared pairwise patients of each group to build “patient similarity matrices”. Hierarchical-agglomerative-clustering and heatmap were performed to identify clusters of patients with common occurrences of gene networks within these matrices. The subsequent enrichment analysis (EA) highlighted biological processes that might be impacted by the mutated genes of each subgroup. Results: Considering the whole-genome matrix, we identified three main genetic clusters of ASD patients, each one characterized by a network of shared genetic variants. We isolated 11,609 genetic variants shared by at least two subjects in each cluster; 4,187 of these variants (36.1%) were common to the three clusters. Only 331 patients (2.5%) shared none or very few mutated genes with anyone else. The EA highlighted common or cluster-specific biological processes related to the variants. Most of the common abnormal processes were involved in neuron projections guidance and morphogenesis, cell junctions and synapse assembly. Exome sequencing alone was not effectual in identifying ASD subgroups. Limitations: Caution is warranted when interpreting our results, as we did not compare them with a control group and did not verify if the identified subgroups where actually associated with different phenotypes. Future work will have to ascertain the strength and reproducibility of these results. Conclusions: Itemizing not just single mutated genes, but also gene networks and specific biological processes that characterize different ASD subpopulations might allow to better understand which networks of genetic variants play a major role in the etiopathology of ASD. The proposed methodology may represent a novel approach to help disentangle ASD complexity and an instrument to boost more focused genotype-phenotype studies.

The world has changed. The global crisis related to the reduction of energy fossil resources, the reduction of potable water resources and the war for the control of energy sources are part of the causes which can lead to an intentional CBRNe (Chemical, Biological, Radiological, Nuclear, and explosive) event together with the potential misuse of CBRNe agents, once considered to be solely the concern of the military, now needs to be considered also in the public domain. This kind of events could also be the consequence of an unintentional release of substances (i.e., an accident of a truck containing a Toxic Industrial Chemical), or of natural events like a tsunami or an earthquake. Thus, the high percentage of risk connected to their occurrence is clear. The aim of this paper is to analyze the CBRNe risk scenario and propose a standardized CBRNe joint approach for the establishment of “CBRNe technical tables” composed by cluster Entities from around Europe to manage the production of technologies, research, education and training activities in order to: (1) establish and maintain a roster of capabilities and facilities, and (2) organize to share expertise, and (3) plan to pool resources. The authors will show the results in the “Italian case study” as a potential pilot project analyzing the strengths and weaknesses to propose new ideas to improve it.

Herein we report the fabrication and electrochemical characterization of a novel type of supercapacitor composed of laser-induced graphene (LIG) electrodes, achieved by the laser-writing of polyimide foils, and 1-Butyl-1-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide ionic liquid as electrolyte. This combination allows the development of a flexible microsupercapacitor suitable for harsh environment application. The influence of several parameters is evaluated with the aim of maximizing the performance of the flexible pouch-bag devices, such as the laser-writing conditions, type of electrode layout and amount of nitrogen-doping. Among them, the laser writing conditions are found to strongly influence the areal capacitance allowing to achieve about 4 mF cm−2, as measured from the galvanostatic charge-discharge measurement at 10 µA cm−2, with a maximum operating potential range of 3 V at 25 °C. In order to probe the potential application of such device, i) flexible pouch architecture and ii) high temperature measurements (considering harsh environment field) are investigated. This type of flexible device exhibits energy and power density as high as 4.5 µWh cm−2 and 90.5 µW cm−2, respectively, high cycling stability as well as acceptable coulombic efficiency above 97% demonstrating good stability even at high bending condition (1.25 cm of bending radius). The electrochemical measurements increasing temperature up to 100 °C reveal a 300% of rise in capacitance and 43% of increment in energy density at de-rated voltage. The obtained energy storage performance are comparable to the best data ever reported for a microsupercapacitor for high temperature application. Moreover, a de-rated voltage analysis (DVA) is proposed as a safe procedure to characterize an energy storage device in an extended temperature range without compromising the system performances.

With the aim to have risk mitigation for people and first responders, active remote sensing standoff detection is a fruitful technology, both in case of accidental (natural or incidental) or intentional dispersion in the environment of volatile chemical substances. Nowadays, several laser-based methodologies could be put in place to perform extensive areal monitoring. The present study regards the proposal for a new system architecture derived from the integration of a low-cost laser-based network of detectors for pollutants interfaced with a more sophisticated layout mounted on an unmanned aerial vehicle (UAV) able to identify the nature and the amount of a release. With this system set up, the drone will be activated by the alarm triggered by the laser-based network when anomalies are detected. The area will be explored by the drone with a more accurate set of sensors for identification to validate the detection of the network of Lidar systems and to sample the substance in the focus zone for subsequent analysis. In this work, methodologies and requirements for the standoff detection and the identification features chosen for this integrated system are described. The work aims at the definition of a new approach to the problem through the integration of different technologies and tools in the operative field experiments. Some preliminary results in support of the suitability of the integration hypothesis proposed are presented. This study gives rise to an integrated system to be furtherly tested in a real environment.

During the latest decades, an increasing of threats associated to Chemical, Biological, Radiological and Nuclear events (CBRNe) took place. For what regards break-out of chemical and radiological compounds, several episodes have occurred, such as unwanted industrial leakage, intentional use of chemical weapons by non-state actors or smuggling of nuclear material, that, by materializing a global threat, have conducted to casualties the actors involved, inter alia fire brigades and military first responders. Concerning the equipment provided to these operators, huge progresses have been done in portable detectors, now able to employ numerous different working principles and technologies. Nonetheless, especially during the survey phase after a CBRN release, the operators enter in a potentially contaminated area without knowing type and amount of the contamination, running the risk of losses during the reconnaissance. On the other hand, nowadays we are witnessing a worldwide spread development of Unmanned Aerial Vehicles (UAV), with countless uses in different fields. They have founded fruitful implementation across civil and military ground in aerial photography, express shipping, gathering information during disaster management, thermal sensor drones for search and rescue operations, geographic mapping of inaccessible locations, severe weather forecasting. What if we could send one or more of these flying platforms equipped with CBRN sensors, geo-localized, able to collect samples and to detect in real time a contamination. Subsequently, once the CBRN incident occurrence is confirmed, after the analysis of collected samples is likely to determine the chemical compound or the radiation emitter involved and the level of contamination. If all this is made feasible, we will be able to minimize or completely avoid the exposure of personnel, moreover it will be determined the exact position of the hotspot and better supported the choice of personal protective equipment to be used to enter in the hazard area. Finally, time will be saved by an early UAV survey, while waiting to obtain the safety permissions for entry in the area.

Nowadays, Chemical-Biological-Radiological-Nuclear-explosive (CBRNe) risks are one of the world's main safety concerns. The radiological disasters of Fukushima and Chernobyl, the chemical events of Seveso or the release of Sarin in the Tokyo Subway, the biological emergencies such as the H1N1 flu or the recent Ebola outbreak, and recent news about the availability of non-conventional weapons acquired by fundamentalist organisations represent evidence of potential future threats. CBRNe risks are a real and global threat. The University of Rome, Tor Vergata, in collaboration with the most important Italian and international bodies working in the field of CBRNe safety and security, and supported by the North Atlantic Treaty Organisation and the Organisation for the Prohibition of Chemical Weapons, organises International Masters Courses on the Protection against CBRNe events. Within this framework, a Table-Top Exercise was planned, in collaboration with the Italian Ministry of Interior and Ministry o...

Tabletop exercises (TTXs) are discussion-based, emergency management exercises, involving key personnel discussing hypothetical scenarios in an informal setting. With the aim of identifying strengths and shortfalls, and achieving changes in the approach to a particular situation, TTXs can be productively exploited for gap analysis (i.e., data collected from a TTX allows an effective comparison between actual performance and optimal/expected ones). In order to ease the process of collecting and analyzing meaningful data from TTXs, in this paper the design of a supporting software system is proposed, which is based on previous efforts on the GATE tool (gap analysis for TTX evaluation). The proposed system aims at enhancing modularity, flexibility, usability, and customizability. Moreover, a model-driven framework for TTX simulation is introduced, as a first step toward new opportunities as what-if analysis in an emergency simulation, personnel training through simulation, or even automated scenario generation.

The training process of the international master courses in “protection against CBRNe events” requires that knowledge of the issues is well addressed and the roles and behaviours that individual stakeholders have, during an emergency management, are trained and verified through exercises. The pattern of these command postexercises is best known as tabletop exercise (TTX). The TTX model used during the master courses has been developed by the Department of Firefighters, Public Rescue and Civil Defence, based on a CBRNe civil defence scenario, with the purpose of providing an operational tool to complete a training session. Tor Vergata researchers have developed a tool called GATE (Gap Analysis for TTX Evaluation) to analyse the results of these exercises and to improve the performances of TTX participants. The purpose of this work is, therefore, to demonstrate how the proposed exercise model (TTX) can also be applied to the exercises for command posts on external emergency plans that companies at “risk of major accident” (by the “Seveso III” Directive) must perform. Moreover, this work describes how the tool GATE can be adapted to allow the evaluation of this specific type of exercise.

Nowadays the intentional diffusion in air (both in open and confined environments) of chemical contaminants is a dramatic source of risk for the public health worldwide. The needs of a high-tech networks composed by software, diagnostics, decision support systems and cyber security tools are urging all the stakeholders (military, public, research & academic entities) to create innovative solutions to face this problem and improve both safety and security. The Quantum Electronics and Plasma Physics (QEP) Research Group of the University of Rome Tor Vergata is working since the 1960s on the development of laser-based technologies for the stand-off detection of contaminants in the air. Up to now, four demonstrators have been developed (two LIDAR-based and two DIAL-based) and have been used in experimental campaigns during all 2015. These systems and technologies can be used together to create an innovative solution to the problem of public safety and security: the creation of a network composed by detection systems: A low cost LIDAR based system has been tested in an urban area to detect pollutants coming from urban traffic, in this paper the authors show the results obtained in the city of Crotone (south of Italy). This system can be used as a first alarm and can be coupled with an identification system to investigate the nature of the threat. A laboratory dial based system has been used in order to create a database of absorption spectra of chemical substances that could be release in atmosphere, these spectra can be considered as the fingerprints of the substances that have to be identified. In order to create the database absorption measurements in cell, at different conditions, are in progress and the first results are presented in this paper.

SUMMARYMathematical modelling is an important tool for understanding the dynamics of the spread of infectious diseases, which could be the result of a natural outbreak or of the intentional release of pathogenic biological agents. Decision makers and policymakers responsible for strategies to contain disease, prevent epidemics and fight possible bioterrorism attacks, need accurate computational tools, based on mathematical modelling, for preventing or even managing these complex situations. In this article, we tested the validity, and demonstrate the reliability, of an open-source software, the Spatio-Temporal Epidemiological Modeler (STEM), designed to help scientists and public health officials to evaluate and create models of emerging infectious diseases, analysing three real cases of Ebola haemorrhagic fever (EHF) outbreaks: Uganda (2000), Gabon (2001) and Guinea (2014). We discuss the cases analysed through the simulation results obtained with STEM in order to demonstrate the capability of this software in helping decision makers plan interventions in case of biological emergencies.

A Table Top Exercise (TTX) gap analysis tool was developed with the aim to provide a complete, systematic and objective evaluation of TTXs organized in safety and security fields. A TTX consists in a discussion-based emergency management exercise, organized in a simulated emergency scenario, involving groups of players who are subjected to a set of solicitations (‘injects’), in order to evaluate their emergency response abilities. This kind of exercise is devoted to identify strengths and shortfalls and to propose potential and promising changes in the approach to a particular situation. In order to manage the TTX derived data collection and analysis, a gap analysis tool would be very useful and functional at identifying the ’gap’ between them and specific areas and actions for improvement, consisting the gap analysis in a comparison between actual performances and optimal/expected ones. In this context, a TTX gap analysis tool was designed, with the objective to provide an evaluation of Team players’ competences and performances and TTX organization and structure. The influence of both the players’ expertise and the reaction time (difference between expected time and time necessary to actually complete the injects) on the final evaluation of the inject responses was also taken into account.

CFD (Computational Fluid Dynamics) simulations are widely used nowadays to predict the behaviour of fluids in pure research and in industrial applications. This approach makes it possible to get quantitatively meaningful results, often in good agreement with the experimental ones. The aim of this paper is to show how CFD calculations can help to understand the time evolution of two possible CBRNe (Chemical-Biological-Radiological-Nuclear-explosive) events: (1) hazardous dust mobilization due to the interaction between a jet of air and a metallic powder in case of a LOVA (Loss Of Vacuum Accidents) that is one of the possible accidents that can occur in experimental nuclear fusion plants; (2) toxic gas release in atmosphere. The scenario analysed in the paper has consequences similar to those expected in case of a release of dangerous substances (chemical or radioactive) in enclosed or open environment during nonconventional events (like accidents or man-made or natural disasters).

Among the potential biological agents suitable as a weapon, Ebola virus represents a major concern. Classified by the CDC as a category A biological agent, Ebola virus causes severe hemorrhagic fever, characterized by high case-fatality rate; to date, no vaccine or approved therapy is available. The EVD epidemic, which broke out in West Africa since the late 2013, has got the issue of the possible use of Ebola virus as biological warfare agent (BWA) to come to the fore once again. In fact, due to its high case-fatality rate, population currently associates this pathogen to a real and tangible threat. Therefore, its use as biological agent by terrorist groups with offensive purpose could have serious repercussions from a psychosocial point of view as well as on closely sanitary level. In this paper, after an initial study of the main characteristics of Ebola virus, its potential as a BWA was evaluated. Furthermore, given the spread of the epidemic in West Africa in 2014 and 2015, the potential dissemination of the virus from an urban setting was evaluated. Finally, it was considered the actual possibility to use this agent as BWA in different scenarios, and the potential effects on one or more nation's stability.

The Ebola virus epidemic burst in West Africa in late 2013, started in Guinea, reached in a few months an alarming diffusion, actually involving several countries (Liberia, Sierra Leone, Nigeria, Senegal, and Mali). Guinea and Liberia, the first nations affected by the outbreak, have put in place measures to contain the spread, supported by international organizations; then they were followed by the other nations affected. In the present EVD outbreak, the geographical spread of the virus has followed a new route: the achievement of large urban areas at an early stage of the epidemic has led to an unprecedented diffusion, featuring the largest outbreak of EVD of all time. This has caused significant concerns all over the world: the potential reaching of far countries from endemic areas, mainly through fast transports, induced several countries to issue information documents and health supervision for individuals going to or coming from the areas at risk. In this paper the geographical spread of the epidemic was analyzed, assessing the sequential appearance of cases by geographic area, considering the increase in cases and mortality according to affected nations. The measures implemented by each government and international organizations to contain the outbreak, and their effectiveness, were also evaluated.

Dust resuspension inside the vacuum vessel is one of the key security issues of the new-generation tokamaks (such as ITER or DEMO). It is well known that a fusion device generates dusts due to plasma–surface interactions, which cause a significant erosion of plasma facing components. Consequently, operators will have to manage several hundreds of kilograms of beryllium and tungsten dusts inside the VV. According to the reference categories, two main accidental situations lead to dusts re-suspension: loss of vacuum accidents (LOVA – air flow due to a rupture of a penetration line) and loss of coolant accidents (LOCA – fluid flashing due to a rupture of a coolant system pipe). The authors have gained a strong experience in the field of dust resuspension by virtue of the studies on the STARDUST facility, whose limitations, however, prevent from completing further analysis. These are, in particular, a reduced field of view to track the dust with optical techniques, the impossibility to replicate a LOVA from the upper port as well as any kind of LOCA. To overcome these problems, the authors have designed several new layouts of the facility. Numerical simulations to test the mechanical resistance together with a deep analysis of advantages and limitations have been performed for each layout. The authors will present the proposals for the new facility, the numerical results of the simulations and a comparison between the layouts analyzed. A new experimental facility will be then described to reproduce dust re-suspension due to both LOVA and LOCA consequences.

The putative spread after the outbreak of the haemorrhagic fever epidemic caused by Ebola virus in West Africa, in the early months of 2014, puts the spotlight on the management of biological risks involving air transportation. Ebola virus is a highly pathogenic agent, causing a haemorrhagic fever defined Ebola HF, characterized by a high fatality. This virus is generally considered to be self-limiting in terms of diffusion; its lethality is in fact so high as to prevent the exit from rural areas where outbreaks generally occur. However, when the virus comes from rural areas and reaches urban places, it is important to assess the risk of spreading even in areas far from the outbreak of origin. Therefore, the development or strengthening of strategies and plans to take action with timely and effective response in order to reduce the consequences of public health emergencies is paramount. During Ebola virus outbreak in West Africa in 2014, World Health Organization focused attention on many airports, stops of main flights coming from Africa; the aviation, due to its nature, has the potential to help boost the global spread of transmissible diseases, since air travel allow to reach the most remote locations in hours. The management of biological emergencies during ordinary operations of airlines and airports represents a real constraint in the event of contrast epidemic situations or endemic outbreaks. An effective response plan should include a careful assessment of the risks and the establishment of procedures to carry on board of aircrafts or on the ground. To ensure that this complex system works correctly, a broad and effective cooperation between the different actors involved is required. On the international level, several documents and recommendations relating to the management of contagious diseases in aeronautical environment have been produced by authoritative agencies. In this paper, after an overview on the international response to public health emergencies in the aviation environment, the attention is focused on emergency response to the Ebola virus crisis in 2014, including an evaluation of the potential dispersion of the pathogen.