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Purpose Violence against health-care workers represents a public health issue that affects individuals, organizations and may have legal consequences. In Italy, workplace violence (WPV) constitutes a “sentinel event”, defined as a particularly serious, potentially avoidable adverse event, which may result in death or serious harm to health-care workers, and which leads to a loss of public confidence in the health-care system. In 2007, the Italian Ministry of Health issued Recommendation No. 8, “Preventing acts of violence against health workers”, inviting each Italian Hospital to develop procedures and guidelines for dealing with and preventing acts of aggression. This study aimed at investigating the appropriateness of the procedures and guidelines developed by the Italian hospitals. Design/methodology/approach Procedures on preventing violence against health-care workers published by 29 Italian Hospitals between 2007 and 2020 were collected retrospectively via Web searches and further evaluated according to their compliance with the 2007 Italian ministerial recommendations. Findings A total of 9 documents out of 29 were fully compliant with the 2007 Ministerial Recommendation, 18 were partially compliant, while 2 were totally non-compliant. A total of 24 documents explicitly addressed the management of verbal and physical aggression, whereas 20 set appropriate training on de-escalation techniques for nurses and medical staff. Psychological support was fully considered in 11 procedures, partially considered in 14, while not included at all in 4. Originality/value Public procedures on preventing violence against health-care workers in Italian hospitals are scarcely compliant with the Ministerial Recommendations. The absence of specific instructions to address the needs at territorial level and the lack of support provided to health-care workers is a weak point in the effective management of WPV.

Coronavirus disease (COVID-19) caused by the SARS-CoV-2 virus continues to afflict many countries around the world. The resurgence of COVID-19 cases and deaths in many countries shows a complacency in adhering to preventive guidelines. Consequently, vaccination continues to be a crucial intervention to reduce the effects of this pandemic. This study investigated the impact of preventive measures and COVID-19 vaccination on the infection, medication, and hospitalization. A cross-sectional online survey was conducted between 23 December 2021 and 12 March 2022 in Algeria. To evaluate the effectiveness of strategies aimed at avoiding and minimizing SARS-CoV-2 infection and severity, a questionnaire was created and validated. Descriptive statistics and logistic regression analyses were computed to identify associations between dependent and independent variables. Variables with a p-value of < 0.05 were considered statistically significant. Our results indicated that out of 2294 answers received, only 16% of our sample was vaccinated, and more than 60% did not apply preventive guidelines. As a result, 45% were infected with SARS-CoV-2, 75% took treatment (even preventive), and 9% were hospitalized. The logistic regression showed that the impact of preventive measures on the unvaccinated is statistically not significant (OR: 0.764, 95% CI = 0. 555–1.052; p = 0.09). However, this relationship changes significantly for people who are vaccinated (OR: 0.108, 95% CI = 0.047–0.248; p < 0.0001). Our results also demonstrated that the impact of protective measures on non-vaccinated individuals is statistically significant in reducing the need to receive anti-COVID-19 treatments (OR: 0.447, 95% CI = 0.321–0.623; p < 0.0001). Furthermore, the results showed that the impact of preventive measures on the non-vaccinated population is also statistically significant in reducing the risk of hospitalization (OR: 0.211, 95% CI = 0.081–0.548; p < 0.0001). Moreover, vaccinated individuals who neglect preventive measures must take the COVID-19 medication at a rate of 3.77 times (OR: 3.77) higher than those who follow preventive measures and are vaccinated. In short, our findings demonstrate the importance of combining preventive measures and vaccination in order to fight against the pandemic. Therefore, we advise the Ministry of Health and relevant authorities to put more effort into enhancing public knowledge about the COVID-19 infection and vaccination through education and awareness initiatives. Parallel to implementing vaccination as additional preventive strategy, behavioral change initiatives must be improved to encourage adherence to COVID-19 prevention recommendations.

In this study, we aimed to investigate the relative vaccine effectiveness (rVE) of the MF59-adjuvanted trivalent (aTIV) and non-adjuvanted quadrivalent (QIVe) egg-based standard-dose vaccines against severe laboratory-confirmed influenza.This test-negative case-control study was conducted in a hospital setting during four recent Italian influenza seasons (from 2018/19 to 2021/22). The clinical outcome was severe acute respiratory infection (SARI) with laboratory confirmation diagnosed among subjects aged ≥65 years. rVE of aTIV versus QIVe was estimated through propensity score matching followed by logistic regression.The influenza virus circulated to a significant extent only during the 2018/19 and 2019/20 seasons. The final population included 512 vaccinated older adults, of which 83 were cases and 429 were test-negative controls. aTIV and QIVe users differed substantially from the point of view of several baseline characteristics. The propensity score adjusted rVE of aTIV vs QIVe was 59.2% (95% CI: 14.6%, 80.5%), 54.7% (95% CI: -28.7%, 84.0%) and 56.9% (95% CI: -7.8%, 82.8%) against any influenza, A(H1N1)pdm09 and A(H3N2), respectively.aTIV was more effective than QIVe in preventing laboratory-confirmed SARI. The benefits of aTIV may be obscured by confounding indication.

Handwritten text recognition systems interpret the scanned script images as text composed of letters. In this paper, efficient offline methods using fuzzy degrees, as well as interval fuzzy degrees of type-2, are proposed to recognize letters beforehand decomposed into strokes. For such strokes, the first stage methods are used to create a set of hypotheses as to whether a group of strokes matches letter or digit patterns. Subsequently, the second-stage methods are employed to select the most promising set of hypotheses with the use of fuzzy degrees. In a primary version of the second-stage system, standard fuzzy memberships are used to measure compatibility between strokes and character patterns. As an extension of the system thus created, interval type-2 fuzzy degrees are employed to perform a selection of hypotheses that fit multiple handwriting typefaces.

Health visitors (HVs) and environmental health officers (EHOs) are the healthcare workers (HCWs) who, in the Italian National Health Service, mainly operate in the prevention departments of local health authorities, guaranteeing the territorial activities specifically declared with the respective professional profiles. During the SARS-CoV-2 pandemic, it was necessary to reallocate all HCWs supporting Hygiene and Public Health Services involved on the front lines of the emergency, in order to perform preventive activities and to take immediate action to fight the spread of the virus. By means of an IT survey consisting of three sections, this study investigated how 960 HVs and EHOs dealt with this reallocation, with the shifting in service assignment, and with the perceived level of fatigue and pressure, through the application of skills acquired from university training. The synergy among the preventive health professions, the ability to work in a multi-professional team, and the complementary training of HCWs represent the main strengths for overcoming future public health challenges, aimed at protecting human health.

In real-world approximation problems, precise input data are economically expensive. Therefore, fuzzy methods devoted to uncertain data are in the focus of current research. Consequently, a method based on fuzzy-rough sets for fuzzification of inputs in a rule-based fuzzy system is discussed in this paper. A triangular membership function is applied to describe the nature of imprecision in data. Firstly, triangular fuzzy partitions are introduced to approximate common antecedent fuzzy rule sets. As a consequence of the proposed method, we obtain a structure of a general (non-interval) type-2 fuzzy logic system in which secondary membership functions are cropped triangular. Then, the possibility of applying so-called regular triangular norms is discussed. Finally, an experimental system constructed on precise data, which is then transformed and verified for uncertain data, is provided to demonstrate its basic properties.

Hemiplegic migraine (HM) is a clinically and genetically heterogeneous condition with attacks of headache and motor weakness which may be associated with impaired consciousness, cerebellar ataxia and intellectual disability. Motor symptoms usually last

Background: It is a well-known fact that the information obtained from a survey can be used in a healthcare organizational analysis; however, it is very difficult to compare the different results found in the literature to each other, even through the use of metanalysis, as the methodology is often not consistent. Methods: Data from a survey analyzing the organizational and managerial responses adopted in pathology-specific clinical pathways (CPs) during the first two waves of the COVID-19 pandemic were used for constructing a decisional matrix, a tool called SPRIS system, consisting of four different sheets. The first sheet reports the results of the survey and, using a streetlight color system, identifies strengths and weaknesses; the second one, by assigning a priority score, establishes the priority of intervention on each of the strengths and weaknesses identified; the third sheet reports the subjective items of the questionnaire in order to identify threats and opportunities and their probability of happening; in the last sheet, a SWOT Analysis is used to calculate the performance index of the whole organization. Results: The SPRIS system, applied to data concerning the adaptation of four CPs to the COVID-19 pandemic, showed that, whereas all the CPs had a good performance index, some concerns remained unsolved and need be addressed. Conclusions: The SPRIS system showed to be an easily constructed tool that is able to give an overview of the organization analyzed by the survey and to produce an index that can be used in a direct quality comparison between different services or organizations.

Background and ObjectiveNonthyroidal Illness Syndrome (NTIS) occurs in approximately 70% of patients admitted to Intensive Care Units (ICU)s and has been associated with increased risk of death. Whether patients with NTIS should receive treatment with thyroid hormones (TH)s is still debated. Since many interventional randomized clinical trials (IRCT)s were not conclusive, current guidelines do not recommend treatment for these patients. In this review, we analyze the reasons why TH treatment did not furnish convincing results regarding possible beneficial effects in reported IRCTs.MethodsWe performed a review of the metanalyses focused on NTIS in critically ill patients. After a careful selection, we extracted data from four metanalyses, performed in different clinical conditions and diseases. In particular, we analyzed the type of TH supplementation, the route of administration, the dosages and duration of treatment and the outcomes chosen to evaluate the results.ResultsWe observed a marked heterogeneity among the IRCTs, in terms of type of TH supplementation, route of administration, dosages and duration of treatment. We also found great variability in the primary outcomes, such as prevention of neurological alterations, reduction of oxygen requirements, restoration of endocrinological and clinical parameters and reduction of mortality.ConclusionsNTIS is a frequent finding in critical ill patients. Despite several available IRCTs, it is still unclear whether NTIS should be treated or not. New primary endpoints should be identified to adequately validate the efficacy of TH treatment and to obtain a clear answer to the question raised some years ago.

Background: The FLURESP project is a public health research funded by the European Commission, with the objective to design a methodological framework to assess and compare the cost-effectiveness of existing public health measures against human influenza pandemics in four target countries: France, Italy, Poland and Romania. This article presents the results relevant to the Italian health system using a dataset specifically collected for this purpose. As most of interventions against human influenza are relavant against other respiratory diseases pandemics, potential interests in COVID-19 are discussed.Methods: Eight public health measures against human influenza pandemics pandemic were selected to be also relevant to other respiratory virus pandemics such as COVID 19: 1) individual (hand washing, using masks), 2) border control (quarantine, fever screening, border closure), 3) community infection (school closure, class dismissal, social distancing, limitation of public transport), 4) reduction of secondary infections (implementation of antibiotic therapy guidelines), 5) pneumococcal vaccination for at-risk people, 6) development of Intensive Care Unit (ICU) capacity, 7) implementation of life support equipments in ICU and 8) screening interventions (virus testing).The outcome "achieving a mortality reduction of higher or equal to 40%” has been selected as a meaningful effectiveness criteria from the public health perspective. Cost distributions have been taken into account according to the Italian health system using a uniform distribution. Results: In the frame of the major pandemic event observed in Italy in 2020, the most cost-effective strategies are “reduction of secondary infections” and “implementation of life support equipment in ICU”. The least cost-effective option during a major pandemic event is screening interventions.Conclusions: A number of intervention strategies against human influenza pandemics appears relevant against respiratory virus pandemics in general such as the COVID-19 pandemic. These pandemics are imposing a substantial economic burden in Italy, confirming the interest of considering the cost-effectiveness of public health measures to enlighten decision making.

In the last decades, there has been a huge increase in the consumption of both Energy Drinks (EDs) and alcohol and, concurrently, these two trends generated the additional practice of mixing ED with alcohol, known as Alcohol mixed with Energy Drink (AmED). One of the most important group of AmED consumers is represented by young. Indeed, the study population of the researches in this field are mainly represented by college students and the results evidence a great range of negative consequences for health. The purpose of the systematic review was to explore the prevalence of AmED consumption among undergraduate students, together with motivations to their use, adverse effects and health-related behaviors associated to AmEDs use. The review was conducted according to the PRISMA Statement and PubMed, Scopus and Web of Science were interrogated. 42 articles, published from 2008 to 2021, were included in the review. An overall prevalence rate of 37% was estimated for AmEDs use in undergraduates, with geographical differences. Although a decrease in consumption was observed throughout the studied period, a continuous monitoring on this phenomenon is needed for identifying those risk groups that could develop risky behaviors related to AmEDs consumption and provide them targeted educational interventions.

Restriction measures imposed during the COVID-19 pandemic led to changes in people’s lives and behaviors. The aim of this paper is to assess the changes occurred in physical activity (PA), sleep, social and cultural activities and personal relationships of Italian adults during the pandemic and to evaluate the use of web-based resources to continue these activities. To this purpose, a cross-sectional study using a web-based questionnaire was carried out and both descriptive and regression analysis was performed. On a total of 1831 participants (61% females, age 18–93 years), the majority reported a decrease in PA, sleep, social and cultural activities and personal relationships, since the beginning of the pandemic. Sleep was notably affected by the use of new technologies. The regression analysis demonstrated that the use of web-based media for doing exercise was associated with being younger than 50 years and female; having a chronic condition was inversely related with the use of web resources for social and cultural activities and to maintain relationships; being employed was negatively related with the use of web media for continuing personal relationships and cultural activities; and being vaccinated against COVID-19 was positively associated with the use of the web for personal relationships. These findings confirm that the COVID-19 pandemic notably affected the daily life of Italian adults. Our results suggest that the use of technology to deal with these changes seems to be related with certain sociodemographic and health-related characteristics. These findings can be useful to identify those characteristics that can help people in copying with daily life modifications due to restriction measures.

In the course of 2022, an epidemic of monkeypox (MPX) arose worldwide. In order to assess the level of knowledge of the Italian adults regarding the new emerging disease, its prevention and their level of worrying and the acceptance of a possible vaccination, a web questionnaire was spread nationwide. A total of 1352 individuals (mean age 54.5 ± 13.4, 52.4% males) completed the questionnaire. Only 26. 7% of the sample were aware of the burden of the epidemic at the moment of the investigation; 47.1% were not able to identify the transmission route, nor the main symptoms (48.9%); and 54.2% were hesitant toward a possible MPXV vaccination, mainly because of a lack of confident in vaccines (38.5%). A low level of worrying about the disease was registered (mean score 2.3 ± 1.2 on a 5-point scale). In the regression analysis performed considering MPX knowledge as outcome, a lower level of knowledge was associated with higher age (OR 1.378, CI95% 0.998–1.904), working or studying in a nonhealthcare setting (OR 0.046, CI95% 0.033–0.066), being single (OR 0.624, CI95% 0.455–0.856) and having mass media as the main source of information (OR 0.332, CI95% 0.158–0.696). These findings indicate as of the time of this investigation, the communication about the MPXV epidemic was not effective in determining a good level of knowledge about the disease and its transmission among Italian adults. This highlights the need to improve risk communication strategies.

The paper presents research on a specific approach to the issue of computed tomography with an incomplete data set. The case of incomplete information is quite common, for example when examining objects of large size or difficult to access. Algorithms devoted to this type of problems can be used to detect anomalies in coal seams that pose a threat to the life of miners. The most dangerous example of such an anomaly may be a compressed gas tank, which expands rapidly during exploitation, at the same time ejecting rock fragments, which are a real threat to the working crew. The approach presented in the paper is an improvement of the previous idea, in which the detected objects were represented by sequences of points. These points represent rectangles, which were characterized by sequences of their parameters. This time, instead of sequences in the representation, there are sets of objects, which allow for the elimination of duplicates. As a result, the reconstruction is faster. The algorithm presented in the paper solves the inverse problem of finding the minimum of the objective function. Heuristic algorithms are suitable for solving this type of tasks. The following heuristic algorithms are described, tested and compared: Aquila Optimizer (AQ), Firefly Algorithm (FA), Whale Optimization Algorithm (WOA), Butterfly Optimization Algorithm (BOA) and Dynamic Butterfly Optimization Algorithm (DBOA). The research showed that the best algorithm for this type of problem turned out to be DBOA.

Tattooing and piercing may lead to health complications. The present multicenter cross-sectional study aimed to assess awareness and knowledge of health risks related to body art and to identify their possible determinants among a large sample of undergraduates in Italy. A web-based questionnaire collecting information on socio-demographic characteristics, awareness, knowledge, and some potential predictors was administered to undergraduates attending twelve Italian universities. The level of knowledge was expressed as the number of correct answers (0–11 for tattooing, 0–14 for piercing). A total of 2985 participants (mean age 23.15 ± 3.99, 73.9% F) participated in the study. Although 95.4% of the respondents were aware of possible health consequences of body art, a low level of specific knowledge was registered for both tattooing (mean number of correct answers 5.38 ± 2.39) and piercing (5.93 ± 3.12) consequences. Lower knowledge was associated with the attendance of non-life science course and with lower duration of academic education for both tattoo and piercing. Lower knowledge of tattooing risks was related with commuter status, while lower knowledge of piercing risks was associated with lower father’s education. These findings highlight the need to enhance information campaigns targeted to youths to increase their awareness of possible health risk of body art.

Ras gene family members play a relevant role in cancer, especially when they are mutated. However, they may play additional roles in other conditions beside cancer. We performed gene expression analysis using the NanoString PanCancer IO 360 panel in the peripheral blood mononuclear cell (PBMC) of six COVID-19 patients and we found that H-Ras gene was significantly upregulated, while both K-Ras and N-Ras genes were downregulated. In particular, H-Ras gene upregulation was more evident in COVID-19 patients with a more severe disease. We compared our results with those obtained by analyzing two different and independent datasets, including a total of 53 COVID-19 patients, in which the gene expression analysis was performed using the Immunology_V2 panel. Comparative analysis of the H-Ras gene expression in these patients confirmed our preliminary results. In both of them, in fact, we were able to confirm the upregulation of the expression of the H-Ras gene. The exact role of this specific upregulation of the H-Ras gene in response to SARS-CoV-2 infection and its possible role in cancer still remains to be elucidated. In conclusion, H-Ras gene participates to the host immune response to SARS-CoV-2 virus infection, especially in patients affected by the most severe form of the COVID-19.

Background Low T3 syndrome is frequent in patients admitted to intensive care units for critical illness and pneumonia. It has been reported also in patients with COVID-19, Hodgkin disease and chronic lymphocytic leukemia. We analyzed the clinical relevance of Low T3 syndrome in COVID-19 patients and, in particular, in those with associated hematological malignancies. Methods Sixty-two consecutive patients, hospitalized during the first wave of SARS-CoV-2 outbreak in Sant’Andrea University Hospital in Rome, were subdivided in 38 patients (Group A), showing low levels of FT3, and in 24 patients (Group B), with normal FT3 serum values. During the acute phase of the disease, we measured serum, radiologic and clinical disease severity markers and scores, in search of possible correlations with FT3 serum values. In addition, in 6 COVID-19 patients, 4 with Low T3 syndrome, including 2 with a hematological malignancy, and 2 with normal FT3 values, we performed, high-dimensional single-cell analysis by mass cytometry, multiplex cytokine assay and gene expression profiling in peripheral blood mononuclear cells (PBMC). Results Low FT3 serum values were correlated with increased Absolute Neutrophil Count, NLR and dNLR ratios and with reduced total count of CD3+, CD4+ and CD8+ T cells. Low FT3 values correlated also with increased levels of inflammation, tissue damage and coagulation serum markers as well as with SOFA, LIPI and TSS scores. The CyTOF analysis demonstrated reduction of the effector memory and terminal effector subtypes of the CD4+ T lymphocytes. Multiplex cytokine assay indicates that mainly IL-6, IP-10 and MCAF changes are associated with FT3 serum levels, particularly in patients with coexistent hematological malignancies. Gene expression analysis using Nanostring identified four genes differently expressed involved in host immune response, namely CD38, CD79B, IFIT3 and NLRP3. Conclusions Our study demonstrates that low FT3 serum levels are associated with severe COVID-19. Our multi-omics approach suggests that T3 is involved in the immune response in COVID-19 and coexistent hematological malignancy and new possible T3 target genes in these patients have been identified.

COVID-19 causes acute respiratory illness in humans. The direct consequence of the spread of the virus is the need to find appropriate and effective solutions to reduce its spread. Similar to other countries, the pandemic has spread in Algeria, with noticeable variation in mortality and infection rates between regions. We aimed to estimate the proportion of people who died or became infected with SARS-CoV-2 in each provinces using a Bayesian approach. The estimation parameters were determined using a binomial distribution along with an a priori distribution, and the results had a high degree of accuracy. The Bayesian model was applied during the third wave (1 January–15 August 2021), in all Algerian’s provinces. For spatial analysis of duration, geographical maps were used. Our findings show that Tissemsilt, Ain Defla, Illizi, El Taref, and Ghardaia (Mean = 0.001) are the least affected provinces in terms of COVID-19 mortality. The results also indicate that Tizi Ouzou (Mean = 0.0694), Boumerdes (Mean = 0.0520), Annaba (Mean = 0.0483), Tipaza (Mean = 0.0524), and Tebessa (Mean = 0.0264) are more susceptible to infection, as they were ranked in terms of the level of corona infections among the 48 provinces of the country. Their susceptibility seems mainly due to the population density in these provinces. Additionally, it was observed that northeast Algeria, where the population is concentrated, has the highest infection rate. Factors affecting mortality due to COVID-19 do not necessarily depend on the spread of the pandemic. The proposed Bayesian model resulted in being useful for monitoring the pandemic to estimate and compare the risks between provinces. This statistical inference can provide a reasonable basis for describing future pandemics in other world geographical areas.

Medication errors are defined as “any preventable event that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the health care professional, patient, or consumer.” Such errors account for 30 to 50 percent of all errors in health care. The literature is replete with systematic reviews of medication errors, with a considerable number of studies focusing on systems and strategies to prevent errors in intensive care units, where these errors occur more frequently; however, to date, there appears to be no study that encapsulates and analyzes the various strategies. The aim of this study is to identify the main strategies and interventions for preventing medication errors in intensive care units through an umbrella review. The search was conducted on the following databases: PubMed, CINAHL, PsycInfo, Embase, and Scopus; it was completed in November 2020. Seven systematic reviews were included in this review, with a total of 47 studies selected. All reviews aimed to evaluate the effectiveness of a single intervention or a combination of interventions and strategies to prevent and reduce medication errors. Analysis of the results that emerged identified two macro-areas for the prevention of medication errors: systems and processes. In addition, the findings highlight the importance of adopting an integrated system of interventions in order to protect the system from harm and contain the negative consequences of errors.

The restriction measures adopted to control the COVID-19 pandemic had significant consequences on individuals’ lifestyles. This study is aimed at assessing the amount and type of habitual physical activity (PA) in older adults during the advanced phase of the pandemic and their possible relationships with sociodemographic aspects. A questionnaire that included sociodemographic characteristics and the Physical Activity Scale for the Elderly (PASE) was administered online to elderly subjects living in the Apulia region, South Italy. A sample of 939 participants (57.1% F; mean age 75.9 ± 6.3) was obtained. In total, 68.8% of female respondents reported a decrease in PA during the pandemic, while 55.1% of men maintained their previous levels (

Starting from 2013, the number of unvaccinated people alarmingly increased in Italy, therefore, in 2017 a new Vaccine National Plan was approved. Healthcare workers (HCWs), especially public health professionals (PHPs, i.e., workers in in the sector of hygiene and preventive medicine), have an important role in informing and promoting vaccinations. In this context, the Italian Study Group of Hospital Hygiene of the Italian Society of Hygiene, Preventive Medicine and Public Health (GISIO-SItI) conducted a national survey to assess knowledge, attitude, and practices towards recommended vaccinations among PHPs. The survey was conducted during October 2019 with an anonymous questionnaire distributed to PHPs attending the 52&deg, SItI National Congress. Overall, 57.1% of operators answered correctly to all seven recommended vaccinations, 12.8% reported to be vaccinated for all seven recommended vaccinations, while 30% were naturally immunized. A higher immunization coverage was reported for anti-hepatitis B (88.9%) and measles (86.1%), and 81.3% of the participants reported being offered the influenza vaccination during the 2018/2019 season. The majority of our sample indicated that hepatitis B (95%) and influenza (93.7%) were the recommended vaccines for HCWs, while less was known regarding varicella, pertussis, diphtheria, and tetanus boosters every 10 years. PHPs who were vaccinated (or who intended to be vaccinated) were more likely to recommend vaccinations to their patients and provided a reassuring example to those hesitant patients. Finally, this is the first study that identified good algorithms (using the techniques of machine learning as Random Forest and Deep Learning) to predict the knowledge of PHPs regarding recommended vaccinations with possible applications in other national and international contexts.

Background. Health literacy is a fundamental ability that allows individuals to manage their health. This study was aimed to assess health literacy and lifestyles among healthcare undergraduates in comparison to students attending other degree courses from two Italian universities. Methods. The Health Literacy Assessment Tool (HLAT-8) and the Newest Vital Sign (NVS) were used to assess health literacy. Demographic and anthropometric data, adherence to Mediterranean diet, physical activity levels and smoking habit were assessed in the enrolled sample to highlight possible associations. Results. Adequate health literacy scores were registered in the sample (27.4±4.4 HLAT-8; 4.2±1.8 NVS), with higher values among healthcare students (pp

Background: Suicide is a severe public health problem, in 2008 the Italian ministerial recommendation n° 4 on the management of suicide defined key areas for the identification of suicidal risk in ...

The uncontrolled spread of the coronavirus disease 2019 (COVID-19) has called for unprecedented measures, to the extent that the Italian government has imposed a quarantine on the entire country. Quarantine has a huge impact and can cause considerable psychological strain. The present study aims to establish the prevalence of psychiatric symptoms and identify risk and protective factors for psychological distress in the general population. An online survey was administered from 18&ndash, 22 March 2020 to 2766 participants. Multivariate ordinal logistic regression models were constructed to examine the associations between sociodemographic variables, personality traits, depression, anxiety, and stress. Female gender, negative affect, and detachment were associated with higher levels of depression, anxiety, and stress. Having an acquaintance infected was associated with increased levels of both depression and stress, whereas a history of stressful situations and medical problems was associated with higher levels of depression and anxiety. Finally, those with a family member infected and young person who had to work outside their domicile presented higher levels of anxiety and stress, respectively. This epidemiological picture is an important benchmark for identifying persons at greater risk of suffering from psychological distress and the results are useful for tailoring psychological interventions targeting the post-traumatic nature of the distress.

Awareness of the importance of the microbial contamination of air and surfaces has increased significantly during the COVID-19 pandemic. The aim of this study was to evaluate the presence of bacteria and fungi in the air and on surfaces within some critical areas of large supermarkets with and without an ozonation system. Surveys were conducted in four supermarkets belonging to the same commercial chain of an Apulian city in June 2021, of which two (A and B) were equipped with an ozonation system, and two (C and D) did not have any air-diffused remediation treatment. There was a statistically significant difference in the total bacterial count (TBC) and total fungal count (TFC) in the air between A/B and C/D supermarkets (p = 0.0042 and p = 0.0002, respectively). Regarding surfaces, a statistically significant difference in TBC emerged between A/B and C/D supermarkets (p = 0.0101). To the best of our knowledge, this is the first study evaluating the effect of ozone on commercial structures in Italy. Future investigations, supported by a multidisciplinary approach, will make it possible to deepen the knowledge on this method of sanitation, in light of any other epidemic/pandemic waves.

Over the last few years, the phenomenon of fake news has become an important issue, especially during the worldwide COVID-19 pandemic, and also a serious risk for the public health. Due to the huge amount of information that is produced by the social media such as Facebook and Twitter it is becoming difficult to check the produced contents manually. This study proposes an automatic fake news detection system that supports or disproves the dubious claims while returning a set of documents from verified sources. The system is composed of multiple modules and it makes use of different techniques from machine learning, deep learning and natural language processing. Such techniques are used for the selection of relevant documents, to find among those, the ones that are similar to the tested claim and their stances. The proposed system will be used to check medical news and, in particular, the trustworthiness of posts related to the COVID-19 pandemic, vaccine and cure.

In this paper a novel training technique is proposed to offer an efficient solution for neural network training in non-trivial and critical applications such as the diagnosis of health threatening illness. The presented technique aims to enhance the generalization capability of a neural network while preserving its sensitivity and precision. The implemented method has been devised in order to slowly increase, during training, the generalization capabilities of a Radial Basis Probabilistic Neural Network classifier, as well as preventing it from over-generalization and the consequent lack of resulting classification performances. The developed method was tested on Electrocardiograms. These latter are generally considered non-trivial both due to the difficulty to recognize some anomalous heart activities, and due to the intermittent nature of abnormal beat occurrences. The implemented training method obtained satisfactory performances, sensitivity and precision while showing high generalization capabilities.

The letter presents a novel iterative methodology for the design of FIR filters based on an approximation of the desired filter frequency response using a Gabor system generated by the Gaussian function. The proposed method exhibits simplicity of implementation, comparable to that of window-based design methods and ensures accuracy in the fulfillment of design requirements, comparable to the one achieved by the Parks–McClellans method. Furthermore, two other advantages of this method are: closed-form formula for the tap coefficients of the filter and the smooth, monotonically decreasing behavior of the frequency response from dc to infinite frequency.

Clinical pathways (CPs) are multidisciplinary clinical governance tools necessary for the care management of the patients, whose aim is to outline the best practicable path within a health organization related to an illness or to a complex clinical situation. The COVID-19 pandemic emergency has created the need for an organizational renewal of care pathways based on the principles of “primary health care” recommended by the WHO. In Italy, the Hospitals and Local Health Authorities (ASL) have tried to guarantee the continuity of non-deferrable treatments and the maximum safety of both patients and health professionals. This study analyzes the organizational and managerial responses adopted in pathology-specific care pathways to assess how CPs as diagnostic tools responded to the COVID-19 pandemic in the first two waves. Twenty-four referents of Operational Units (UU OO) from Hospitals (AO) and Local Health Authorities (ASL) of the Lazio Region (Central Italy) that apply four different CPs responded to a survey, which analyzes the managerial and organizational responses of CPs in regard to different contexts. Results show that the structural and organizational adjustments of the CPs have made it possible to maintain an adequate level of care for specific treatment processes, with some common critical aspects that require improvement actions. The adjustments found could be useful for dealing with new outbreaks and/or new epidemics in order to try to mitigate the potential negative impact, especially on the most vulnerable patient categories.

Rainfall estimation based on the impact of rain on electromagnetic waves is a novel methodology that has had notable advancements during the last few years. Many studies conducted on this topic in the past considered only the electromagnetic waves with frequencies greater than 10 GHz since the rainfall impact on the electromagnetic wave attenuation is reduced at lower frequencies. Over the last few years, some authors have demonstrated that there can be a non-negligible attenuation even on the signals received on a global system for mobile communications mobile terminal in presence of rain. In this paper, we propose a new classification method based on a probabilistic neural network to obtain an accurate classification between four rainfall intensities (no rain, weak rain, moderate rain, and heavy rain). The innovative rainfall classification method is based on three received signal level (RSL) local features of the 4G/LTE: the instantaneous RSL, the average RSL value, and its variance calculated by using a sliding window. The proposed method exhibits good performance, obtaining an overall correct classification rate of 96.7%. Almost all papers on this topic present in the literature focus on electromagnetic waves with frequencies greater than 10 GHz, in which the rain impact is more relevant, according to the rain attenuation model. However, only the 4G/LTE signal has such widespread geographic coverage, so the proposed classification method can provide noticeable improvements in the creation of rainfall maps with higher spatial resolution.

In energy generation systems including a photovoltaic park, fluctuations are the norm: both production and demand levels can vary on hourly basis. Hence, energy management and dispatching systems have to cope with the possibility of inadequate production while satisfying as much as possible user demands. We put forward a management solution that models the behaviour of each production plant and consumption device, and determines energy allocation. For this, gathered data are wavelet transformed to let us retain only the useful characteristics of data on both large and small scales of the signal. Models are handled by several neural networks which perform predictions in advance of 48-h, with a granularity of half an hour. Moreover, according to realtime user demands, the management solution determines energy flows between production plants and consumption devices. Therefore, while in some cases it might be necessary to postpone the activation of some consumption devices, in others we can take advantage of a production surplus. Thanks to the proposed solution proper actuators can be programmed beforehand to improve the fairness to users, and use peaks of energy production, thus reducing green energy shortage, and extra costs.

In Italy, at the end of 2020, a voluntary immunization plan against COVID-19 was introduced, involving elderly among the first target categories. The aim of this study was to assess, through an online questionnaire, the acceptance of COVID-19 vaccination in a sample of older adults from southern Italy. Of a total of 1041 respondents (41.7% males, mean age 76.6 ± 6.5), 965 (92.7%) were vaccinated or willing to be vaccinated against COVID-19, although less than half of the sample was favorable to vaccinations and agreed with mandatory immunization. Acceptance of COVID-19 vaccination was found to be positively related with higher educational level (OR = 1.875, CI95% = 1.113–3.161, p = 0.018) and having social/mass media as a main source of information (OR = 2.415 CI95% = 1.358–4.296, p = 0.003). On the contrary, an inverse relationship was found between acceptance of COVID-19 vaccination and having fulfilled the questionnaire after the introduction of green pass (OR = 0.218, CI95% = 0.129–0.369, p &lt, 0.001). Therefore, although this evidence needs to be further confirmed, it is possible to agree with previous studies reporting that compulsory measures, such as green pass implementation, must be accompanied by effective education and information strategies of the target population.

In Italy, wine production is considered a sector of excellence, where the wines’ appreciable sensory features are favored by environmental factors, including weather and climate conditions, which benefit territories with a specific vocation. The whole chain involves many economic and agri-food sector operators, and requires an in-depth assessment of specific risks for identifying critical points, keeping the entire production process under control, and ensuring product traceability. This article describes the results of a pilot study conducted in the Prosecco DOCG (Designations of Controlled and Guaranteed Origin) area, concerning the detection of residues of plant protection products in fifty wine bottles. Although considerably below the maximum residue levels, all the samples tested were positive, ranging from two to five active substances detected in each sample. In addition to the provisions of the European Community legislation, this paper critically evaluates some best practices models that are already used by the Wine Federations of Italy, with the aim of identifying advantages of and areas for improvement in production methods, applicable to raw materials reception, rasping, storage, and bottling phases, in order to guarantee product safety and quality.

Data transmission is the most critical operation for mobile sensors networks in term of energy waste. Particularly in pervasive healthcare sensors network it is paramount to preserve the quality of service also by means of energy saving policies. Communication and data transmission are among the most critical operation for such devises in term of energy waste. In this paper we present a novel approach to increase battery life-span by means of shorter transmission due to data compression. On the other hand, since this latter operation has a non-neglectable energy cost, we developed a compression efficiency estimator based on the evaluation of the absolute and relative entropy. Such algorithm provides us with a fast mean for the evaluation of data compressibility. Since mobile wireless sensor networks are prone to battery discharge-related problems, such an evaluation can be used to improve the electrical efficiency of data communication. In facts the developed technique, due to its independence from the string or file length, is extremely robust both for small and big data files, as well as to evaluate whether or not to compress data before transmission. Since the proposed solution provides a quantitative analysis of the source's entropy and the related statistics, it has been implemented as a preprocessing step before transmission. A dynamic threshold defines whether or not to invoke a compression subroutine. Such a subroutine should be expected to greatly reduce the transmission length. On the other hand a data compression algorithm should be used only when the energy gain of the reduced transmission time is presumably greater than the energy used to run the compression software. In this paper we developed an automatic evaluation system in order to optimize the data transmission in mobile sensor networks, by compressing data only when this action is presumed to be energetically efficient. We tested the proposed algorithm by using the Canterbury Corpus as well as standard pictorial data as benchmark test. The implemented system has been proven to be time-inexpensive with respect to a compression algorithm. Finally the computational complexity of the proposed approach is virtually neglectable with respect to the compression and transmission routines themselves.

Background: Low T3 syndrome is a frequent finding in critical illness The prevalence and clinical relevance of the Low T3 syndrome in coronavirus infections ha

Background The aim of the study was to explore lifestyle of undergraduate students in southern Italy and to investigate their determinants. Methods An anonymous, web-based questionnaire investigating weight and its perception, smoking and alcohol use, achievement of recommended levels of physical activity and time spent daily in screen-based sedentary behaviors was administered to students attending two universities in southern Italy. Age, gender, city, type of degree course attended, occupational status and residential status were considered as possible demographic determinants. Results The majority of the participants reported a normal weight (71.2%), were non-smokers (66.6%), occasional alcohol consumers (60.5%) and insufficiently active (62.6%), with a reported mean screen time exceeding 2 h per day. Gender, city, type of degree course and occupational status were found to be associated with lifestyle by regression analysis. Normal weight, overweight and obese students were generally properly aware of their weight condition; however, weight misperceptions were registered among normal and underweight undergraduates. Conclusions This study highlighted some critical issues regarding lifestyles of university students that suggest the need for health promotion interventions targeted mainly on physical activity.

Legionella is the causative agent of Legionnaires' disease, a flu-like illness normally acquired following inhalation or aspiration of contaminated water aerosols. Our recent studies revealed that climatic parameters can increase the number of reported cases of community-acquired Legionnaires' disease. Here, we evaluated the presence of Legionella in water networks and the distribution of Legionnaires' disease cases associated with touristic-recreational facilities in the Apulia region (southern Italy) during the period 2001–2017 using geostatistical and climatic analyses. Geostatistical analysis data revealed that the area with the highest concentration of Legionella in water systems also had the greatest number of cases of Legionnaires' disease associated with touristic-recreational facilities. Climatic analysis showed that higher daily temperature excursion (difference between maximum and minimum temperature) on the day of sampling was more often associated with Legionella-positive samples than Legionella-negative samples. In addition, our data highlighted an increased risk of Legionnaires’ disease with increases in precipitation and average temperature and with decreases in daily temperature excursion (difference between maximum and minimum temperature over the course of 24 h in the days of incubation period of disease) and minimum temperature. Healthcare professionals should be aware of this phenomenon and be particularly vigilant for cases of community-acquired pneumonia during such climatic conditions and among the tourist population. The innovative geo-statistical approach used in this study could be applied in other contexts when evaluating the effects of climatic conditions on the incidence of Legionella infections.

Background The FLURESP project is a public health project funded by the European Commission with the objective to design a methodological approach in order to compare the cost-effectiveness of existing public health measures against human influenza pandemics in four target countries: France, Italy, Poland and Romania. This article presents the results relevant to the French health system using a data set specifically collected for this purpose. Methods Eighteen public health interventions against human influenza pandemics were selected. Additionally, two public-health criteria were considered: 'achieving mortality reduction ≥40%' and 'achieving morbidity reduction ≥30%'. Costs and effectiveness data sources include existing reports, publications and expert opinions. Cost distributions were taken into account using a uniform distribution, according to the French health system. Results Using reduction of mortality as an effectiveness criterion, the most cost-effective options was 'implementation of new equipment of Extracorporeal membrane oxygenation (ECMO) equipment'. Targeting vaccination to health professionals appeared more cost-effective than vaccination programs targeting at risk populations. Concerning antiviral distribution programs, curative programs appeared more cost-effective than preventive programs. Using reduction of morbidity as effectiveness criterion, the most cost-effective option was 'implementation of new equipment ECMO'. Vaccination programs targeting the general population appeared more cost-effective than both vaccination programs of health professionals or at-risk populations. Curative antiviral programs appeared more cost-effective than preventive distribution programs, whatever the pandemic scenario. Conclusion Intervention strategies against human influenza pandemics impose a substantial economic burden, suggesting a need to develop public-health cost-effectiveness assessments across countries.

Background Legionella is an intracellular microorganism living in natural and artificial aquatic environments. Although its transmission to humans is linked to the inhalation of contaminated aerosols, there is no validated air sampling method for the control and prevention of the disease. The aim of the present study was to provide more information on the distribution of Legionella spp. in indoor environments and to determine whether the same Legionella strains are isolated from air and water samples. Methods Ten healthcare facilities located in seven regions of Italy were enrolled. The serological typing of Legionella spp. from water samples and the surrounding air by active and passive sampling was assessed using polyvalent and monovalent antisera. Subsequently, the strains identified as Legionella pneumophila ( Lpn ) underwent molecular typing by sequence-based typing (SBT) using seven genes ( flaA , pilE , asd , mip , mompS , proA , and neuA ). The allelic profile number was assigned using the European Working Group for Legionella Infections–SBT database. Results Lpn serogroup 6 was the most prevalent serogroup; it was found simultaneously in the air and water samples of three different healthcare facilities. In the remaining seven hospitals, Lpn serogroups 1, 6, 7, 9, and 12 were isolated exclusively from water samples. The molecular investigation showed that Lpn strains in the water and air samples of each positive healthcare facility had the same allelic profile. Strains, identified as sequence types (STs) 728 and ST 1638+ST 1324, were isolated in two respective healthcare facilities, and a new strain, identified as ST 1989, was obtained in one healthcare facility. Conclusion The application of the SBT method allowed to verify the homology among Legionella strains from water samples and the surrounding air. The results showed that the same Lpn strains were present in the air and water samples, and a new Legionella strain was identified.

(1) Background: Health workers (HWs) are at high risk of acquiring SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) infections. Therefore, health authorities further recommend screening strategies for SARS-CoV-2 infection in exposed or high-risk HWs. Nevertheless, to date, the best/optimal method to screen HWs for SARS-CoV-2 infection is still under debate, and data on the prevalence of SARS-CoV-2 infection in HWs are still scarce. The present study aims to assess the SARS-CoV-2 infection rate amongst HWs in a teaching hospital in Central Italy and the diagnostic performance of SARS-CoV-2 serology (index test) in comparison with the SARS-CoV-2 RNA PCR assay (reference standard). (2) Methods: A cross-sectional study on the retrospective data of HWs tested for SARS-CoV-2 by RNA-RT-PCR on nasopharyngeal swabs and by an IgM/IgG serology assay on venous blood samples, irrespective of exposure and/or symptoms, was carried out. (3) Results: A total of 2057 HWs (median age 46, 19&ndash, 69 years, females 60.2%) were assessed by the RNA RT-PCR assay and 58 (2.7%) tested positive for SARS-CoV-2 infection. Compared with negative HWs, SARS-CoV-2-positives were younger (mean age 41.7 versus 45.2, p &lt, 0.01, 50% versus 31% under or equal to 40 years old, p &lt, 0.002) and had a shorter duration of employment (64 versus 125 months, p = 0.02). Exposure to SARS-CoV-2 was more frequent in positive HWs than in negatives (55.2% versus 27.5%, p &lt, 0.0001). In 44.8% of positive HWs, no exposure was traced. None of the positive HWs had a fatal outcome, none of them had acute respiratory distress syndrome, and only one required hospitalization for mild/moderate pneumonia. In 1084 (51.2%) HWs, nasopharyngeal swabs and an IgM/IgG serology assay were performed. With regard to IgM serology, sensitivity was 0% at a specificity of 98.99% (positive predictive value, PPV 0%, negative predictive value, NPV 99.2%). Concerning IgG serology and irrespective of the time interval between nasopharyngeal swab and serology, sensitivity was 50% at a specificity of 99.1% (PPV 28.6%, NPV 99.6%). IgG serology showed a higher diagnostic performance when performed at least two weeks after testing SARS-CoV-2-positive at the RNA RT-PCR assay by a nasopharyngeal swab. (4) Conclusions: Our experience in Central Italy demonstrated a low prevalence of SARS-CoV-2 infection amongst HWs, but higher than in the general population. Nearly half of the positive HWs reported no previous exposure to SARS-CoV-2-infected subjects and were diagnosed thanks to the proactive screening strategy implemented. IgG serology seems useful when performed at least two weeks after an RNA RT-PCR assay. IgM serology does not seem to be a useful test for the diagnosis of active SARS-CoV-2 infection. High awareness of SARS-CoV-2 infection is mandatory for all people, but especially for HWs, irrespective of symptoms, to safeguard their health and that of patients.

Legionellae are opportunistic bacteria that cause various conditions after exposure to contaminated aerosols, ranging from a serious type of pneumonia to a mild case of an influenza-like illness. Despite the risks of exposure, little is known about the occurrence of Legionella in natural environments and, even though studies have shown that there is a potential risk of transmission via inhalation, it does not have to be detected in groundwater that is used for irrigation. The culture methods traditionally used to detect Legionella have several limits that can be partly solved by applying molecular techniques. Samples from 177 wells in Apulia, Southern Italy, were collected twice, in winter and in summer, and analyzed. When compared with the guidelines, 145 (81.9%) of the sampled wells were suitable for irrigation use. The culture-based method highlighted the presence of different species and serogroups of Legionella in 31 (21.2%) of the 145 wells that were shown to be suitable for irrigation use. A greater number of wells returned positive results for Legionella in summer than in winter (p = 0.023), and the median concentrations were mostly higher in summer (500 CFU/L) than in winter (300 CFU/L). The median temperature in the Legionella positive well waters was significantly higher than that in the negative ones, both in winter and in summer (p Using molecular techniques, Legionella non-pneumophila was found in 37 of the 114 wells earlier detected as suitable for irrigation use but negative for Legionella by the culture-based methods. The distribution of Legionella differ significantly in porous aquifers compared to the karst-fissured ones both with quantitative polymerase chain reaction (qPCR) (p = 0.0004) and viable cells by propidium monoazide (PMA-qPCR) (p = 0.0000). Legionella concentrations were weakly correlated with temperature of water both with qPCR (ρ = 0.47, p = 0.0033) and PMA-qPCR (ρ = 0.41, p = 0.0126). Our data suggest that water that aerosolizes when sprinkled on plants represents a potential source of Legionellosis, with a higher risk from exposure in summer. On a practical level, this finding is important for workers (farmers and gardeners) who are in contact with waters used for irrigation.

In this paper, air pollutants concentrations for NO2, NO, NOx and PM10 in a single monitoring station are predicted using the data coming from other different monitoring stations located nearby. A cascade feed forward neural network based modeling is proposed. The main aim is to provide a methodology leading to the introduction of virtual monitoring station points consistent with the actual stations located in the city of Catania in Italy

Large software systems need to be modified to remain useful. Changes can be more easily performed when their design has been carefully documented. This paper presents an approach to quickly find design patterns that have been implemented into a software system. The devised solution greatly reduces the performed checks by organising the search for a design pattern as tree traversals, where candidate classes are carefully positioned into trees. By automatically tagging classes with design pattern roles we make it easier for developers to reason with large software systems. Our approach can provide documentation that lets developers understand the role each class is playing, assess the quality of the code, have assistance for refactoring and enhancing the functionalities of the software system.