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At the beginning of 2023, the Italian former prime minister, the former health minister and 17 others including the current president of the Lombardy region were placed under investigation on suspicion of aggravated culpable epidemic in connection with the government's response at the start of the COVID-19 pandemic. The charges revolve around the failure by authorities to take adequate measures to prevent the spread of the virus in the Bergamo area, which experienced a significant excess of deaths during the initial outbreak. The aim of this paper is to analyse the pandemic data of Italy and the Lombardy region in the first 10 days of the pandemic, spanning from the 24th of February 2020 to the 4th of March 2020. The objective is to determine whether the use of early warning indicators could have facilitated the identification of a critical increase in infections. This identification, in turn, would have enabled the timely formulation of strategies for pandemic containment, thereby reducing the number of deaths. In conclusion, to translate our findings into practical guidelines, we propose a low-cost early warning method for infectious respiratory diseases with asymptomatic carriers. [ABSTRACT FROM AUTHOR]

The prediction of the evolution of epidemics plays an important role in limiting the transmissibility and the burdensome consequences of infectious diseases, which leads to the employment of mathematical modeling. In this paper, we propose a stochastic particle filtering extended SEIRS model with repeated vaccination and time-dependent parameters, aiming to efficiently describe the demanding dynamics of time-varying epidemics. The validity of our model is examined using daily records of COVID-19 in Italy for a period of 525 days, revealing a notable capacity to uncover the hidden dynamics of the pandemic. The main findings include the estimation of asymptomatic cases, which is a well-known feature of the current pandemic. Unlike other proposed models that employ extra compartments for asymptomatic cases, which force the estimation of this proportion and significantly increase the model's complexity, our approach leads to the evaluation of the hidden dynamics of COVID-19 without additional computational burden. Other findings that confirm the model's appropriateness and robustness are its parameter evolution and the estimation of more ICU-admitted cases compared to the official records during the most prevalent infection wave of January 2022, attributed to the intensified increase in admissions that may have led to full occupancy in ICUs. As the vast majority of datasets contain time series of total recovered and vaccinated cases, we propose a statistical algorithm to estimate the currently recovered and protected through vaccination cases. This necessity arises from the attenuation of antibodies after vaccination/infection and is necessary for long-time interval predictions. Finally, we not only present a novel stochastic epidemiological model and test its efficiency but also investigate its mathematical properties, such as the existence and stability of epidemic equilibria, giving new insights to the literature. The latter provides additional details concerning the system's long-term behavior, while the conclusions drawn from the R0 index provide perspectives on the severity and future of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Infectious disease epidemics are challenging for medical and public health practitioners. They require prompt treatment, but it is challenging to recognize and define epidemics in real time. Knowing the prediction of an infectious disease epidemic can evaluate and prevent the disease's impact. Mathematical models of epidemics that work in real time are important tools for preventing disease, and data-driven deep learning enables practical algorithms for identifying parameters in mathematical models. In this paper, the SIR model was reduced to a logistic differential equation involving a constant parameter and a time-dependent function. The time-dependent function leads to constant, rational, and birational models. These models use several constant parameters from the available data to predict the time and number of people reported to be infected with the COVID-19 Omicron variant. Two out of these three models, rational and birational, provide accurate predictions for countries that practice strict mitigation measures, but fail to provide accurate predictions for countries that practice partial mitigation measures. Therefore, we introduce a time-series model based on neural networks to predict the time and number of people reported to be infected with the COVID-19 Omicron variant in a given country that practices both partial and strict mitigation measures. A logistics-informed neural network algorithm was also introduced. This algorithm takes as input the daily and cumulative number of people who are reported to be infected with the COVID-19 Omicron variant in the given country. The algorithm helps determine the analytical solution involving several constant parameters for each model from the available data. The accuracy of these models is demonstrated using error metrics on Omicron variant data for Portugal, Italy, and China. Our findings demonstrate that the constant model could not accurately predict the daily or cumulative infections of the COVID-19 Omicron variant in the observed country because of the long series of existing data of the epidemics. However, the rational and birational models accurately predicted cumulative infections in countries adopting strict mitigation measures, but they fell short in predicting the daily infections. Furthermore, both models performed poorly in countries with partial mitigation measures. Notably, the time-series model stood out for its versatility, effectively predicting both daily and cumulative infections in countries irrespective of the stringency of their mitigation measures. [ABSTRACT FROM AUTHOR]

This paper has explored the impact of the Covid-19 pandemic on the Italian stock market at an industry level, analysing companies listed in the two major stock indexes: MIB 30 and STAR. Using daily firm-level stock prices (from December 2019, until October 31, 2020), we employed an event-study approach to analyse short-term stock market reactions, considering different pandemic windows period. Results showed that stocks reacted negatively to the announcement of the first case in the country, with deep reversal effects when the country was locked down. Monetary policy measures showed potential to ease stock markets: the announcement of Next Generation Agreement highlights the reversed role of Market Capitalization. Firm-specific variables were included in order to make inferences about firm characteristics that emerged as value drivers during the pandemic: in the first lockdown period, a greater company's capitalization ensured a greater resilience to the Covid-19 shock. Reversals at both an industry and a company level are observed. Results allow to understand how an outbreak of contagious disease affects stock returns in various sectors, helping investors to develop trading strategies to protect their wealth from future epidemics and providing inputs into the assessment of economic vulnerability to pandemic crises. [ABSTRACT FROM AUTHOR]

Highly contagious diseases, such as mumps, are a global concern as new epidemics continue to emerge, even in highly vaccinated populations. The risk of transmission and spread of these viruses is even higher for individuals who are more likely to be exposed, including healthcare workers (HCWs). In healthcare settings, both HCWs and patients are at risk of infection during the care process, potentially leading to nosocomial epidemic outbreaks. Mumps is often underestimated compared with measles and rubella, despite being milder and less likely to spread. In fact, the risk of complications following mumps infection is extremely high, especially if the disease occurs in adulthood. The measles–mumps–rubella (MMR) vaccine has been shown to be an excellent preventive measure. Unfortunately, the mumps component appears to be less effective in inducing immunity than those for measles and rubella (two-dose effectiveness of 85%, 95% and 97%, respectively). The main aim of our study was to investigate the prevalence of detectable mumps antibodies (serum IgG antibodies) in a cohort of Italian and foreign HCWs in relation to personal and occupational factors. We included in the study 468 subjects who underwent health surveillance at the Occupational Medicine Unit of the Tor Vergata Polyclinic in Rome during the period from January 2021 to March 2023. In our study, the proportion of HCWs found to be unprotected against mumps was very high (8.3%), and those found to be immune are below the WHO threshold for herd immunity (95%). From our data, it seems essential that all occupational health services carry out an accurate screening with a dose of anti-mumps antibodies to assess serological protection before starting a job, regardless of an individual's vaccination history. This approach is proving to be beneficial, accurate, as it allows all serologically non-immune individuals to be vaccinated in the workplace, including those who would be protected by their vaccination history but have lost the antibody response. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 pandemic has created unprecedented social, financial, and moral disruptions across the globe despite global efforts to reduce the transmission of the novel coronavirus. Currently, vaccinating populations against COVID-19 has emerged as the most sustainable strategy to help countries recover from the socioeconomic effects of COVID-19 while protecting public health. To meet vaccination targets, some countries have adopted policies that rely on varying levels of coercion. This paper analyses the ethical implications of coercive vaccination policies implemented in Singapore and Italy, which impose barriers to accessing healthcare on the unvaccinated. These two cases are compared to the vaccine mandate in New Zealand, which did not restrict access to healthcare for the unvaccinated. This analysis draws on key considerations from Kass' ethical framework for assessing public health intervention. This analysis is relevant to countries considering similar policies to increase vaccination uptake for infectious diseases. Since healthcare is a fundamental good, a critical question is whether imposing barriers to accessing healthcare services is an ethically justifiable consequence of the choice to remain unvaccinated. [ABSTRACT FROM AUTHOR]

COVID-19 is the highly communicable disease which is being announced as pandemic by WHO. The disease has already impacted the economies of big nations like China, Italy, United states etc and now this disease is hitting our developing country i.e. India too. COVID-19 or Corona virus is human to human spread disease and thus social distancing is the only measure which everyone can take to minimize its spread. National lockdown is the measure taken by Government to create distance among people. But what will be the probable impact of this lockdown on different sectors of our country. This paper aims to analyze impact of COVID-19 on the educational sector of India. [ABSTRACT FROM AUTHOR]

The dynamics of human mobility have been known to play a critical role in the spread of infectious diseases like COVID-19. In this paper, we present a simple compact way to model the transmission of infectious disease through transportation networks using widely available aggregate mobility data in the form of a zone-level origin-destination (OD) travel flow matrix. A key feature of our model is that it not only captures the propagation of infection via direct connections between zones (first-order effects) as in most existing studies but also transmission effects that are due to subsequent interactions in the remainder of the system (higher-order effects). We demonstrate the importance of capturing higher-order effects in a simulation study. We then apply our model to study the first wave of COVID-19 infections in (i) Italy, and, (ii) the New York Tri-State area. We use daily data on mobility between Italian provinces (province-level OD data) and between Tri-State Area counties (county-level OD data), and daily reported caseloads at the same geographical levels. Our empirical results indicate substantial predictive power, particularly during the early stages of the outbreak. Our model forecasts at least 85% of the spatial variation in observed weekly COVID-19 cases. Most importantly, our model delivers crucial metrics to identify target areas for intervention. [ABSTRACT FROM AUTHOR]

Coronavirus disease 19 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus, which is responsible for the ongoing global pandemic. Stringent measures have been adopted to face the pandemic, such as complete lockdown, shutting down businesses and trade, as well as travel restrictions. Nevertheless, such solutions have had a tremendous economic impact. Although the use of recent vaccines seems to reduce the scale of the problem, the pandemic does not appear to finish soon. Therefore, having a forecasting model about the COVID-19 spread is of paramount importance to plan interventions and, then, to limit the economic and social damage. In this paper, we use Genetic Programming to evidence dependences of the SARS-CoV-2 spread from past data in a given Country. Namely, we analyze real data of the Campania Region, in Italy. The resulting models prove their effectiveness in forecasting the number of new positives 10/15 days before, with quite a high accuracy. The developed models have been integrated into the context of SVIMAC-19, an analytical-forecasting system for the containment, contrast, and monitoring of Covid-19 within the Campania Region. [ABSTRACT FROM AUTHOR]

We employ a new macroeconomic–epidemiological agent-based model to evaluate the "lives vs livelihoods" trade-off brought to the fore by coronavirus disease (Covid-19). An infectious disease spreads across the network of agents' social and economic contacts and feeds back on the economic dimension of the model through various channels such as employment and consumption demand. Under a lockdown (LD) scenario, the model is able to closely reproduce the epidemiological dynamics of the first wave of the Covid-19 epidemic in the Lombardy region of Italy. We find that, in the presence of non-pharmaceutical interventions, there is no trade-off between lives and macroeconomic losses as a stricter LD eventually leads to superior outcomes along both dimensions. We also evaluate the efficacy of various macroeconomic stabilization policies designed to counteract the downturn generated by the epidemic and LD measures. In an agent-based setting we gain additional insights on the way in which such policies impact not only on gross domestic product but also, for instance, on firms' defaults and relative prices. Liquidity support for firms, a short-time working scheme with compensation for workers, and direct transfer to households stand out as the most effective policy tools. [ABSTRACT FROM AUTHOR]

The present research aimed at understanding individuals' vaccination intentions and protective behaviours against COVID-19 through two different studies. In Study 1 (N = 213, 73% women; mean age = 24.03) the Protection Motivation Theory model was tested considering the fear of COVID-19 as a possible mediator between threat appraisal (in terms of both health and social life) and intentions to get vaccinated when the vaccination was not yet available. Study 2 (N = 1111, 68.9% women; mean age = 38.33) was conducted when the vaccine became available for the entire population. Through this study, by adopting the 5C model of vaccine hesitancy as a theoretical framework, we aimed to understand how people who got vaccinated and the ones who did not differed, considering fear of vaccination, personality and vaccination hesitancy. In Study 1, social limitations, perceived severity and COVID-19 perceived vulnerability were significantly and positively related to fear of COVID-19. Contrary to what we expected, fear of COVID-19 was not a significant predictor of vaccination intention, which was predicted by both response efficacy and self-efficacy. In Study 2, in line with previous studies, vaccine hesitancy was negatively related to vaccination. More specifically, the social-oriented dimension of collective responsibility was the strongest predictor of effective behaviour. Our findings provide insights into the complexity of vaccine acceptance and emphasise the need for targeted interventions to promote vaccination and mitigate the spread of infectious diseases. [ABSTRACT FROM AUTHOR]

European countries struggled to fight against the second and the third waves of the COVID-19 pandemic, as the Test-Trace-Isolate (TTI) strategy widely adopted over the summer and early fall 2020 failed to contain the spread of the disease effectively. This paper sheds light on the effectiveness of such a strategy in two European countries (Spain and Italy) by analysing data from June to December 2020, collected via a large-scale online citizen survey with 95,251 and 43,393 answers in Spain and Italy, respectively. Our analysis describes several weaknesses in each of the three pillars of the TTI strategy: Test, Trace, and Isolate. We find that 40% of respondents had to wait more than 48 hours to obtain coronavirus tests results, while literature has shown that a delay of more than one day might make tracing all cases inefficient. We also identify limitations in the manual contact tracing capabilities in both countries, as only 29% of respondents in close contact with a confirmed infected individual reported having been contact traced. Moreover, our analysis shows that more than 45% of respondents report being unable to self-isolate if needed. We also analyse the mitigation strategies deployed to contain the second wave of coronavirus. We find that these interventions were particularly effective in Italy, where close contacts were reduced by more than 20% in the general population. Finally, we analyse the participants' perceptions about the coronavirus risk associated with different daily activities. We observe that they are often gender- and age-dependent, and not aligned with the actual risk identified by the literature. This finding emphasises the importance of deploying public-health communication campaigns to debunk misconceptions about SARS-CoV-2. Overall, our work illustrates the value of online citizen surveys to quickly and efficiently collect large-scale population data to support and evaluate policy decisions to combat the spread of infectious diseases, such as coronavirus. [ABSTRACT FROM AUTHOR]

The importance of spatial networks in the spread of an epidemic is an essential aspect in modeling the dynamics of an infectious disease. Additionally, any realistic data-driven model must take into account the large uncertainty in the values reported by official sources such as the amount of infectious individuals. In this paper, we address the above aspects through a hyperbolic compartmental model on networks, in which nodes identify locations of interest such as cities or regions, and arcs represent the ensemble of main mobility paths. The model describes the spatial movement and interactions of a population partitioned, from an epidemiological point of view, on the basis of an extended compartmental structure and divided into commuters, moving on a suburban scale, and non-commuters, acting on an urban scale. Through a diffusive rescaling, the model allows us to recover classical diffusion equations related to commuting dynamics. The numerical solution of the resulting multiscale hyperbolic system with uncertainty is then tackled using a stochastic collocation approach in combination with a finite volume Implicit–Explicit (IMEX) method. The ability of the model to correctly describe the spatial heterogeneity underlying the spread of an epidemic in a realistic city network is confirmed with a study of the outbreak of COVID-19 in Italy and its spread in the Lombardy Region. [ABSTRACT FROM AUTHOR]

We discuss the probable presence of tuberculosis in non-adults of a medieval rural community in northern Italy with a biocultural perspective. Before birth, mother and child have a closely interconnected relationship, as suggested by the role of microchimerism on maternal health. To better understand maternal–child health and related stress factors, paleopathology has investigated the potential of this relationship in recent years. Diseases with environmental development factors such as infections depend on and are strongly affected by maternal control variables such as, for example, breastfeeding and the growth environment. This article presents ISZ2, the second possible case of childhood tuberculosis identified in northeastern Italy through recent paleopathological criteria. The subject is of primary importance as it not only represents a direct testimony of this infectious disease otherwise known only from historical sources, but also increases our knowledge on the state of health of infants in this area, which to date are scarcely analyzed. [ABSTRACT FROM AUTHOR]

Purpose: To develop recommendations for the management of acute hepatitis B by the Italian Society for the Study of Infectious and Tropical Diseases. Methods: Development of the recommendations divided into three levels of evidence according to the GRADE system: A (high), B (medium) and C (low experts opinion), together with three recommendation levels: 1 (strong), 2 (medium), 3 (weak). Results: The treatment with antivirals is in selected cases the mainstay of management of severe acute hepatitis, and should be started as a matter of urgency in order to prevent death. Conclusions: These recommendations are meant to provide the rationale and practical indications for the management of acute hepatitis B (AHB). [ABSTRACT FROM AUTHOR]

Evidences on the absence of risk of sexual transmission of HIV by persons living with HIV/AIDS (PLWHA) with undetectable plasma HIV-RNA (HIV-RNA <200 copies/ml) led to the worldwide campaign "U = U" (undetectable = untransmittable). The purpose of this study was to evaluate the perceived accuracy of this message among PLWHA, HIV-negative people having unprotected sex (PHUS) and infectious diseases' (ID) physicians in Italy. A nationwide survey has been conducted using three different anonymous questionnaires (for ID physicians, PLWHA and PHUS). A total of 1121 participants filled the questionnaires: 397 PLWHA; 90 physicians; 634 PHUS. Awareness of U = U message has been reported in 74%, 92% and 47% of PLWHA, ID physicians and PHUS, respectively. The perception of accuracy of the U = U message among those aware was reported as high in 80.4%, 79.5% and 67.3% of PLWHA, ID physicians and PHUS, respectively. Physicians perceived that 11% of PLWHA have a high rate of perception of U = U, whereas among PLWHA, only 34% reported definitive positive messages from physicians. Discrepancies between awareness and perception of accuracy of the message U = U in PLWHA and physicians have been found, suggesting still low confidence in the community regarding the message itself. [ABSTRACT FROM AUTHOR]

Despite its effectiveness in preventing invasive meningococcal disease (IMD), pediatric uptake of recombinant meningococcal vaccination for serogroup B meningitis (MenB) is low in Italy. This study aimed to investigate knowledge, attitudes, and practice (KAP) about IMD and the vaccine uptake for MenB from July to December 2019, in a sample collected from a series of local Facebook discussion groups from the provinces of Parma and Reggio Emilia (North-Eastern Italy; 337,104 registered users). A self-administered anonymous web-based questionnaire was used to collect demographics, knowledge status, perceived risk for contracting meningitis, attitude towards the utility of meningococcal vaccine, and willingness to receive/perform MenB vaccine in their offspring. In total, 541 parents returned a fully completed questionnaire (response rate of 1.6% of potential recipients), with a mean age of 39.2 years ± 6.3 (78.1% females). Meningococcal infection was identified as severe or highly severe by most participants (88.9%), while it was recognized as being frequent/highly frequent in the general population by 18.6% of respondents. The overall knowledge status was unsatisfactory (57.6% ± 33.6 of correct answers to the knowledge test). Even though 63.4% of participants were somewhat favorable to MenB/MenC vaccines, offspring's vaccination towards MenB was reported by only 38.7% of participants. In a binary logistic regression model, the male gender of respondents (adjusted odds ratio [aOR] 3.184, 95% confidence interval [95%CI] 1.772 to 5.721), living in a municipality >15,000 inhabitants (aOR 1.675, 95%CI 1.051 to 2.668), reporting a favorable attitude on meningococcus B vaccine (aOR 12.472, 95%CI 3.030 to 51.338), having been vaccinated against serogroup B (aOR 5.624, 95%CI 1.936 to 16.337) and/or serogroup C (aOR 2.652, 95%CI 1.442 to 4.872), and having previously vaccinated their offspring against serogroup C meningococcus (aOR 6.585, 95%CI 3.648 to 11.888) were characterized as positive effectors of offspring's vaccination. On the contrary, having a higher risk perception on vaccines was identified as the only negative effector (aOR 0.429, 95%CI 0.241 to 0.765). Our results hint towards extensive knowledge gaps on IMD and preventive interventions in the general population, suggesting that a positive attitude towards vaccines and vaccinations could be identified as the main effector also for MenB acceptance. Interventions in the general population aimed at improving confidence, compliance, and acknowledgment of the collective responsibility, as well as preventing actual constraints and the sharing of false beliefs on infectious diseases and their preventive measures, could therefore increase vaccination acceptance in both targeted individuals and their offspring. [ABSTRACT FROM AUTHOR]

Background: This cross-sectional survey aimed to determine the knowledge, attitudes, and behaviors regarding vaccinations among schoolteachers in Italy. Methods: Data were collected through an online questionnaire from September 2020 to May 2021 from a sample of schoolteachers in the Campania region of southern Italy. Results: Only 27% of the participants had good knowledge about the vaccinations recommended for schoolteachers. Females who had children, who were unsatisfied by their health status, and not needing additional information about vaccinations were more likely to have good knowledge. Moreover, 61.5% perceived that vaccinations are useful in preventing infectious diseases, and 44.5% agreed or strongly agreed that vaccinations should be mandatory for schoolteachers. The results of multivariate logistic regression showed that schoolteachers who perceived that vaccinations are useful in preventing infectious diseases, who considered the recommended vaccinations to be useful to protecting their own and their students' health, who believed that information received about vaccination was useful, and who needed additional information about vaccinations recommended for schoolteachers, were significantly more likely to agree or strongly agree that vaccinations should be mandatory for schoolteachers. Conclusions: These findings suggest the need for education strategies to ensure that schoolteachers are better informed about vaccinations recommended for their profession. [ABSTRACT FROM AUTHOR]

Discontinuation of antimicrobial stewardship programs (ASPs) and increased antibiotic use were described during SARS-CoV-2 pandemic. In order to measure COVID-19 impact on ASPs in a setting of high multidrug resistance organisms (MDRO) prevalence, a qualitative survey was designed. In July 2021, eighteen ID Units were asked to answer a questionnaire about their hospital characteristics, ASPs implementation status before the pandemic and impact of SARS-CoV-2 pandemic on ASPs after the 1st and 2nd pandemic waves in Italy. Nine ID centres (50%) reported a reduction of ASPs and in 7 cases (38.9%) these were suspended. After the early pandemic waves, the proportion of centres that restarted their ASPs was higher among the ID centres where antimicrobial stewardship was formally identified as a priority objective (9/11, 82%, vs 2/7, 28%). SARS-CoV-2 pandemic had a severe impact in ASPs in a region highly affected by COVID-19 and antimicrobial resistance but weaknesses related to the pre-existent ASPs might have played a role. [ABSTRACT FROM AUTHOR]

Tick-borne encephalitis (TBE), a human viral infectious disease caused by the tick-borne encephalitis virus (TBEV), is emerging in Italy, especially in the north-eastern area. No human cases of autochthonous TBE have been reported in Italy's central regions (such as Emilia-Romagna, Italy). However, here we describe the first human case of TBEV infection in this region, pointing to endemic transmission of TBEV, supporting the concept of circulation of TBEV and of the presence of a possible hot spot in the Serramazzoni region in the Emilian Apennines. [ABSTRACT FROM AUTHOR]

Background. The COVID-19 pandemic has drastically impacted many aspects of society and has indirectly produced various psychological consequences. This systematic review aimed to estimate the worldwide prevalence of posttraumatic stress disorder (PTSD) in children due to the COVID-19 pandemic, as well as to identify protective or risk factors contributing to child PTSD. Methods. We conducted a systematic literature search in the PubMed, ProQuest, PsycINFO, Embase, Web of Science, WanFang, CNKI, and VIP databases. We searched for studies published between January 1, 2020 and May 26, 2021, that reported the prevalence of child PTSD due to the COVID-19 pandemic, as well as factors contributing to child PTSD. Eighteen studies were included in our systematic review, of which 10 studies were included in the meta-analysis. Results. The estimated prevalence of child PTSD after the COVID-19 outbreak was 28.15% (95% CI: 19.46–36.84%, I 2 = 99.7%). In subgroup analyses for specific regions the estimated prevalence of post-pandemic child PTSD was 19.61% (95% CI: 11.23–27.98%) in China, 50.8% (95% CI: 34.12–67.49%) in the USA, and 50.08% in Italy (95% CI: 47.32–52.84%). Conclusions. Factors contributing to child PTSD were categorized into four aspects: personal factors, family factors, social factors and infectious diseases related factors. Based on this, we presented a new framework summarizing the occurrence and influence of the COVID-19 related child PTSD, which may contribute to a better understanding, prevention and development of interventions for child PTSD in forthcoming pandemics. [ABSTRACT FROM AUTHOR]

Psoriatic patients with latent tuberculosis infection and properly treated active tuberculosis need careful management when prescribing modern biological drugs. Although data and guidelines regarding tumour necrosis factor-α inhibitors advise caution and initiation of prophylactic therapy in patients with latent tuberculosis infection, the same indications do not seem to find equal force for interleukin (IL)-23 and IL-17 inhibitors. In order to evaluate the risk of reactivation in patients with latent tuberculosis infection or properly treated active tuberculosis, an observational retrospective study was conducted on the population referred to our centre at Dermatologic Clinic of University of Turin, Italy. In the last 10 years at the clinic 19 psoriatic patients were found to be at risk of tuberculosis reactivation: 10 patients were QuantiFERON-TB-positive at baseline, 2 became positive during treatment, 6 reported prior tuberculous infection, and 1 was QuantiFERON-TB-negative at baseline and developed disseminated tuberculosis during treatment with anti-tumour necrosis factor-α. Overall, 10.5% of this group of patients developed active tuberculosis; however, stratifying by biologic therapy, zero cases were observed among patients treated with anti-IL-17, -23, or -12/23 over a relatively long followup (48.1 months) A review of the available literature following our experience confirms the increased risk of tuberculosis reactivation with tumour necrosis factor-α inhibitors. Concerning anti-IL-23 and IL-17 drugs, available data showed high safety in patients at risk of tuberculosis reactivation. Screening of patients who should be taking IL-17 and IL-23 inhibitors is recommended for public health purposes. In case of a positive result with these therapies, consulting with an infectious diseases specialist is suggested in order to weigh up the risks and benefits of prophylactic treatment. [ABSTRACT FROM AUTHOR]

In this article, we describe the advances in the field of pediatrics that have been published in the Italian Journal of Pediatrics in 2020. We report progresses in understanding allergy, autoinflammatory disorders, critical care, endocrinology, genetics, infectious diseases, microbiota, neonatology, neurology, nutrition, orthopedics, respiratory tract illnesses, rheumatology in childhood. [ABSTRACT FROM AUTHOR]

A discrete-time deterministic epidemic model is proposed to better understand the contagious dynamics and the behaviour observed in the incidence of real infectious diseases. For this purpose, we analyse a SIRS model both in a random-mixing approach and in a small-world network formulation. The models include the basic parameters that characterize an epidemic: infection and recovery times, as well as mechanisms of contagion. Depending on the parameters, the random-mixing model has different types of behaviour of an epidemic: pathogen extinction; endemic infection; sustained oscillations and dynamic extinction. Spatial effects are included in our network-based approach, where each individual of a population is represented by a node of a small-world network. Our network-based approach includes rewiring connections to account for time-varying network structure, a consequence of the natural response to the emergence of an epidemic (e.g. avoiding contacts with infected individuals). Random and adaptive rewiring conditions are analysed and numerical simulation are made. A comparison of model predictions with the actual effects of COVID-19 infection on population that occurred in Italy and France is produced. Results of the time series of infected people show that our adaptive evolving networks represent effective strategies able to decrease the epidemic spreading. [ABSTRACT FROM AUTHOR]

For epidemics such as COVID-19, with a significant population having asymptomatic, untested infection, model predictions are often not compatible with data reported only for the cases confirmed by laboratory tests. Additionally, most compartmental models have instantaneous recovery from infection, contrary to observation. Tuning such models with observed data to obtain the unknown infection rate is an ill-posed problem. Here, we derive from the first principle an epidemiological model with delay between the newly infected (N) and recovered (R) populations. To overcome the challenge of incompatibility between model and case data, we solve for the ratios of the observed quantities and show that log(N(t)/R(t)) should follow a straight line. This simple prediction tool is accurate in hindcasts verified using data for China and Italy. In traditional epidemiology, an epidemic wanes when much of the population is infected so that 'herd immunity' is achieved. For a highly contagious and deadly disease, herd immunity is not a feasible goal without human intervention or vaccines. Even before the availability of vaccines, the epidemic was suppressed with social measures in China and South Korea with much less than 5% of the population infected. Effects of social behaviour should be and are incorporated in our model. [ABSTRACT FROM AUTHOR]

Background Since the beginning of the pandemic, the epidemiology of coronavirus disease 2019 (COVID-19) in Italy has been characterized by the occurrence of subnational outbreaks. The World Health Organization recommended building the capacity to rapidly control COVID-19 clusters of cases in order to avoid the spread of the disease. This study describes a subregional outbreak of COVID-19 that occurred in the Emilia Romagna region, Italy, and the intervention undertaken to successfully control it. Methods Cases of COVID-19 were defined by a positive reverse transcriptase polymerase chain reaction (RT-PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on nasopharyngeal swab. The outbreak involved the residential area of a small town, with ~10 500 inhabitants in an area of 9 km2. After the recognition of the outbreak, local health care authorities implemented strict quarantine and a rearrangement of health care services, consisting of closure of general practitioner outpatient clinics, telephone contact with all residents, activation of health care units to visit at-home patients with symptoms consistent with COVID-19, and a dedicated Infectious Diseases ambulatory unit at the nearest hospital. Results The outbreak lasted from February 24 to April 6, 2020, involving at least 170 people with a cumulative incidence of 160 cases/10 000 inhabitants; overall, 448 inhabitants of the municipality underwent at least 1 nasopharyngeal swab to detect SARS-CoV-2 (positivity rate, 38%). Ninety-three people presented symptoms before March 11 (pre-intervention period), and 77 presented symptoms during the postintervention period (March 11–April 6). Conclusions It was possible to control this COVID-19 outbreak by prompt recognition and implementation of a targeted local intervention. [ABSTRACT FROM AUTHOR]

People who use drugs are a key population in global HCV control. We evaluated the efficacy of an innovative model to eliminate HCV infection in a high‐risk population of PWUD in a service for substance use disorder (SUD). Between January 2018 and December 2018, we conducted a prospective, interventional, before and after study, based on audits performed by Infectious Diseases physicians in a SUD facility in Piedimonte Matese, in southern Italy, to improve the knowledge about HCV infection; a shared protocol for screening and linkage to care of patients was implemented. The pre‐intervention period was defined as January‐December 2017 and the post‐intervention period as January‐December 2018. The subjects followed up at SUD facility in the pre‐intervention and post‐intervention periods were 318 and 275, respectively. Compared with the pre‐intervention period, the number of anti‐HCV–positive subjects tested for HCV RNA was higher in the post‐intervention period (91% vs 27%, P <.0001), as was the number who started directly acting antivirals (DAAs). Of the 18 HCV RNA–positive subjects in the pre‐intervention period, only 3 (16.6%) started DAA, a percentage decisively lower than that observed after the start of the programme, 63 (84%) of 75 subjects (P <.0001), and all obtained SVR. The data were similar for people who inject drugs (PWID) and non‐PWID sub‐populations. The use of our innovative model with close interaction between the Infectious Disease Unit and the SUD facility determined a significant increase in HCV RNA testing, linkage to care and the start of DAA in the PWUD population. [ABSTRACT FROM AUTHOR]

Latent autoregressive models are useful time series models for the analysis of infectious disease data. Evaluation of the likelihood function of latent autoregressive models is intractable and its approximation through simulation-based methods appears as a standard practice. Although simulation methods may make the inferential problem feasible, they are often computationally intensive and the quality of the numerical approximation may be difficult to assess. We consider instead a weighted pairwise likelihood approach and explore several computational and methodological aspects including estimation of robust standard errors and the role of numerical integration. The suggested approach is illustrated using monthly data on invasive meningococcal disease infection in Greece and Italy. [ABSTRACT FROM AUTHOR]

Background: Tdap and flu immunization in pregnancy has been proven to be both effective and safe. Despite this, the vaccination rate in pregnant women is low in Italy. The COVID-19 pandemic has focused the attention of public opinion on communicable diseases, underlining the importance of primary prevention measures such as vaccination. We conducted a survey to investigate the behavior of pregnant women during the COVID-19 pandemic regarding maternal immunization to identify the reasons for vaccine hesitancy in order to overcome them. The new challenge is COVID-19 vaccination in pregnancy, and preliminary data show hesitancy towards it. Our analysis may be useful to improve immunization in the pregnant population, including through the COVID-19 vaccine. Methods: A targeted survey was performed in Italy including 520 women who experienced in the first trimester of pregnancy, prior to the novel coronavirus spread, the 2019–2020 influenza vaccination campaign and the Tdap vaccine recommendation in the third trimester during the COVID pandemic. They represent a unique model to investigate if the new coronavirus outbreak might have changed attitudes towards vaccination in pregnancy in the same patients. Data were collected from a self-completed paper questionnaire. Descriptive statistics were calculated and percentages were compared using the chi-2 test or Fisher's exact test. Results: We obtained data from 195 of the 520 women who gave birth during the inclusion period; 325 cases declined to participate in the survey. A total of 8.7% (17 cases) performed flu vaccination in the first trimester of pregnancy (pre-COVID era), 50.8% (99 cases) accepted Tdap immunization during their third trimester of gestation (COVID-19 pandemic) and 6.7% (13 cases) received both vaccines during pregnancy. For both the flu and Tdap shots, pregnant patients were more likely to accept the vaccines if they were recommended by a healthcare provider, whereas the main reason not to be vaccinated was the lack of such a recommendation. Conclusions: Our survey shows that the COVID-19 experience, which has raised awareness as to the role of vaccines in preventable diseases, may positively change attitudes toward immunization in pregnancy. Vaccination must be recommended to all pregnant women and organized during routine prenatal care as an important element for the prevention of communicable diseases. Vaccination hesitancy can be minimized through consistent recommendation to all pregnant women offered by obstetric staff during routine prenatal care. This approach is likely to be effective in terms of building trust in flu and Tdpa immunization among pregnant women, as well as to avoid unjustified hesitancy towards the more recent COVID-19 vaccines. [ABSTRACT FROM AUTHOR]

Objective: To report mode of delivery and immediate neonatal outcome in women infected with COVID-19.Design: Retrospective study.Setting: Twelve hospitals in northern Italy.Participants: Pregnant women with COVID-19-confirmed infection who delivered.Exposure: COVID 19 infection in pregnancy.Methods: SARS-CoV-2-infected women who were admitted and delivered from 1 to 20 March 2020 were eligible. Data were collected from the clinical records using a standardised questionnaire on maternal general characteristics, any medical or obstetric co-morbidity, course of pregnancy, clinical signs and symptoms, treatment of COVID 19 infection, mode of delivery, neonatal data and breastfeeding.Main Outcome and Measures: Data on mode of delivery and neonatal outcome.Results: In all, 42 women with COVID-19 delivered at the participating centres; 24 (57.1%, 95% CI 41.0-72.3) delivered vaginally. An elective caesarean section was performed in 18/42 (42.9%, 95% CI 27.7-59.0) cases: in eight cases the indication was unrelated to COVID-19 infection. Pneumonia was diagnosed in 19/42 (45.2%, 95% CI 29.8-61.3) cases: of these, 7/19 (36.8%, 95% CI 16.3-61.6) required oxygen support and 4/19 (21.1%, 95% CI 6.1-45.6) were admitted to a critical care unit. Two women with COVID-19 breastfed without a mask because infection was diagnosed in the postpartum period: their newborns tested positive for SARS-Cov-2 infection. In one case, a newborn had a positive test after a vaginal operative delivery.Conclusions: Although postpartum infection cannot be excluded with 100% certainty, these findings suggest that vaginal delivery is associated with a low risk of intrapartum SARS-Cov-2 transmission to the newborn.Tweetable Abstract: This study suggests that vaginal delivery may be associated with a low risk of intrapartum SARS-Cov-2 transmission to the newborn. [ABSTRACT FROM AUTHOR]

Infectious diseases are a common cause of death in young dogs. Several factors are thought to predispose young dogs to microbiological infections. Identifying the cause of death is often a challenge, and broad diagnostic analysis is often needed. Here, we aimed to determine the infectious causes of death in young dogs aged up to 1 year, examining how it relates to age (under and over 6 months), lifestyle (owned versus ownerless), breed (purebred and crossbreed), and gender. A retrospective study was conducted in a 3-year period (2015–2017) on 138 dead dogs that had undergone necropsy and microbiological diagnostics. Enteritis and pneumonia were the most commonly observed lesions. Polymicrobism was more prevalent (62.3%) than single-agent infections and associated with a higher rate of generalised lesions. Ownerless dogs showed over a three-fold higher predisposition to viral coinfections than owned dogs. Above all, canine parvovirus was the most prevalent agent (77.5%), followed by canine coronavirus (31.1%) and canine adenovirus (23.9%); ownerless pups had a higher predisposition to these viruses. Escherichia coli (23.9%), Clostridium perfringens type A (18.1%), and Enterococcus spp. (8.7%) were the most commonly identified bacteria, which mostly involved in coinfections. A lower prevalence of CDV and Clostridium perfringens type A was observed in puppies under 6 months of age. In conclusion, this study is the first comprehensive survey on a wide panel of microbiological agents related to necropsy lesions. It lays the groundwork for future studies attempting to understand the circulation of infectious agents in a determined area. [ABSTRACT FROM AUTHOR]

In this work, we aim to determine the main factors driving self-initiated behavioral changes during the seasonal flu. To this end, we designed and deployed a questionnaire via Influweb, a Web platform for participatory surveillance in Italy, during the 2017 − 18 and 2018 − 19 seasons. We collected 599 surveys completed by 434 users. The data provide socio-demographic information, level of concerns about the flu, past experience with illnesses, and the type of behavioral changes voluntarily implemented by each participant. We describe each response with a set of features and divide them in three target categories. These describe those that report i) no (26%), ii) only moderately (36%), iii) significant (38%) changes in behaviors. In these settings, we adopt machine learning algorithms to investigate the extent to which target variables can be predicted by looking only at the set of features. Notably, 66% of the samples in the category describing more significant changes in behaviors are correctly classified through Gradient Boosted Trees. Furthermore, we investigate the importance of each feature in the classification task and uncover complex relationships between individuals' characteristics and their attitude towards behavioral change. We find that intensity, recency of past illnesses, perceived susceptibility to and perceived severity of an infection are the most significant features in the classification task and are associated to significant changes in behaviors. Overall, the research contributes to the small set of empirical studies devoted to the data-driven characterization of behavioral changes induced by infectious diseases. Author summary: Human behavior and infectious diseases are linked by a feedback loop. While individuals might change their behavior as a response to an epidemic, such changes might influence the spreading itself. So far, our understanding and characterization of behavioral changes induced by diseases has been strongly limited by the lack of empirical data. As result, the vast majority of research has been focused on theoretical, what if, scenarios. In this work, we collected a unique dataset comprised of 599 surveys submitted by 434 users to the participatory surveillance platform Influweb over the 2017 − 18 and 2018 − 19 flu seasons. The data provide socio-demographic information, level of concerns about the flu, past experience with illnesses, and the type of self-initiated behavioral changes implemented by each participant. Our analysis, conducted adopting machine learning algorithms, show that both past experience of illness and personal beliefs about the disease are fundamental drivers of behavioral change. These findings are in good agreement with the constructs of the Health Belief Model and provide, to the best of our knowledge, the first data driven characterization of behavioral changes during the seasonal flu. [ABSTRACT FROM AUTHOR]

Human cytomegalovirus (HCMV) infections are among the most common complications arising in transplant patients, elevating the risk of various complications including loss of graft and death. HCMV infections are also responsible for more congenital infections worldwide than any other agent. Congenital HCMV (cCMV) infections are the leading nongenetic cause of sensorineural hearing loss and a source of significant neurological disabilities in children. While there is overlap in the clinical and laboratory approaches to diagnosis of HCMV infections in these settings, the management, follow-up, treatment, and diagnostic strategies differ considerably. As yet, no country has implemented a universal screening program for cCMV. Here, we summarize the issues, limitations, and application of diagnostic strategies for transplant recipients and congenital infection, including examples of screening programs for congenital HCMV that have been implemented at several centers in Japan, Italy, and the United States. [ABSTRACT FROM AUTHOR]

Objectives: To describe: (i) factors associated with rapid and delayed ART initiation; (ii) rates of 12 week virological response; and (iii) virologically controlled retention in care by 1 year from ART initiation according to timing of start in a real-life setting.Methods: All individuals in the Icona cohort diagnosed with HIV in 2016-17 who initiated ART were grouped according to the time between HIV diagnosis and ART initiation: Group 1, ≤7 days; Group 2, 8-14 days; Group 3, 15-30 days; Group 4, 31-120 days; and Group 5, >120 days. Multivariable logistic regression models were used to identify factors associated with: (i) the probability of rapid (Group 1) and very delayed (Group 5) ART initiation; (ii) the 12 week virological response (by a modified snapshot algorithm); and (iii) the probability of retention in care at 1 year (on ART with HIV-RNA <50 copies/mL).Results: A total of 1247 individuals were included [82 (6.6%) in Group 1, 115 (9.2%) in Group 2, 267 (21.4%) in Group 3, 641 (51.4%) in Group 4 and 142 (11.4%) in Group 5]. Main predictors of rapid ART start (Group 1) were low CD4 cell count and high HIV-RNA at first contact with the infectious diseases centre. There was no association between probability of virological response and timing of ART initiation. Overall, 90% of individuals remained on ART after 1 year, 91% with undetectable HIV-RNA. Participants of Italian nationality, those with higher CD4 cell count and lower HIV-RNA at ART initiation were more likely to be retained in care after 1 year.Conclusions: In our high-income observational setting, we did not observe differences in the 1 year rate of virological response and retention in care according to timing of ART initiation. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to develop a spending predictor model to evaluate the direct costs associated with the management of ABSSSIs from the National health-care provider's perspective of Italy, Romania, and Spain. Methodology: A decision-analytic model was developed to evaluate the diagnostic and clinical pathways of hospitalized ABSSSI patients based on scientific guidelines and real-world data. A Standard of Care (SoC) scenario was compared with a dalbavancin scenario in which the patients could be discharged early. The epidemiological and cost parameters were extrapolated from national administrative databases (i.e., hospital information system). A probabilistic sensitivity analysis (PSA) and one-way sensitivity analysis (OWA) were performed. Results: Overall, the model estimated an average annual number of patients with ABSSSIs of approximately 50,000 in Italy, Spain, and Romania. On average, the introduction of dalbavancin reduced the length of stay by 3.3 days per ABSSSI patient. From an economic perspective, dalbavancin did not incur any additional cost from the National Healthcare perspective, and the results were consistent among the countries. The PSA and OWA demonstrated the robustness of these results. Conclusion: This model represents a useful tool for policymakers by providing information regarding the economic and organizational consequences of an early discharge approach in ABSSSI management. [ABSTRACT FROM AUTHOR]

Hepatitis C virus (HCV) infection is now considered a systemic disease due to the occurrence of extra-hepatic manifestations. Among these, the renal involvement is frequent. HCV infection, in fact, is strongly associated with proteinuria and chronic kidney disease (CKD) and negatively affects the prognosis of renal patients. In the last few years, availability of more specific and effective drugs against HCV has dramatically changed the clinical course of this disease. These drugs may provide further advantages in the CKD population as a whole by reducing progression of renal disease, mortality rate and by increasing the survival of graft in renal transplant recipients. The strict pathogenetic and prognostic link between HCV infection and CKD requires an ongoing relationship among the healthcare professionals involved in the treatment of both HCV infection and CKD. Therefore, Scientific Societies involved in the care of this high-risk population in Italy have organized a joint expert panel. The aim of the panel is to produce a position statement that can be used in daily clinical practice for the management of HCV infected patients across the whole spectrum of renal disease, from the conservative phase to renal replacement treatments (dialysis and transplantation). Sharing specific evidence-based expertise of different professional healthcare is the first step to obtain a common ground of knowledge on which to instate a model for multidisciplinary management of this high-risk population. Statements cover seven areas including epidemiology of CKD, HCV-induced glomerular damage, HCV-related renal risk, staging of liver disease in patients with CKD, prevention of transmission of HCV in hemodialysis units, treatment of HCV infection and management of HCV in kidney transplantation. [ABSTRACT FROM AUTHOR]

Background Since 2008 Italy has been the destination of the 'central Mediterranean route', used by migrants to reach Europe. The aim of this study is to describe demographic characteristics and health problems of migrants at the time of arrival on the Italian coasts, focussing on dermatological and infectious diseases. Methods Cross-sectional study of data routinely collected (n = 6, 188) by the National Institute for Health Migration and Poverty (INMP) in the centres for migrants of Lampedusa and Trapani-Milo (2015–16). Logistic models were performed to identify factors associated with scabies, varicella and the occurrence of two or more not related diagnosis. Results The average age was 21.6 years; 83.5% of the patients were males. The most frequent countries of origin were Eritrea, Nigeria, and Somalia. The most frequent diagnosis was scabies (58% of patients), skin infections, pediculosis and dermatitis; respiratory infections and varicella were the most represented infectious diseases. The diagnosis of scabies was more probable among Somalis (OR: 11.60) and Eritreans (OR: 10.05); the diagnosis of varicella was more probable among Ghanaians (OR: 13.58) and Nigerians (OR: 9.79). Somalis (OR: 4.10) and Eritreans (OR: 3.32) were the patients more likely to receive two or more diagnosis. Conclusions The majority of the diseases affecting migrants is in most cases, related to the migration experience and is likely not to represent a major threat for public health. Up-to-date information regarding the burden of diseases is needed in order to identify the health needs of incoming migrants and to arrange the appropriate response in terms of health services provision. [ABSTRACT FROM AUTHOR]

We conducted a second National survey in all Italian Infectious Disease clinics to assess the number of people diagnosed and linked to care and, among these, the number of people on antiretroviral therapy and viral load suppressed. In 2014, 100,049 (0.16 per 100 residents) people diagnosed and linked to care were estimated, corresponding to an increase of 6.3% compared to the survey conducted in 2012. Among people diagnosed and linked to care, 91.9% were on antiretroviral therapy (increase of 11.4% compared to 2012), and among these, 87.7% were viral load suppressed. Overall, the majority were males (72.1%), Italians (82.7%), aged 25-49 years (45.6%); the most common HIV mode of transmission was reported to be in heterosexual contact (37.9%) and men who had sex with men (31.3%); 8.8% had less than 350 CD4 cells/μL, 82.4% had VL <50 copies and 22.9% had a CDC stage C. In conclusion, the number of people diagnosed and linked to care was increasing. The vast majority of them was receiving ART but the percentage of people still with a detectable viral load was lower than the 90-90-90 WHO target. [ABSTRACT FROM AUTHOR]

Background: Healthcare workers (HCWs) are at higher risk than the general population of contracting tuberculosis (TB). Moreover, although subjects with latent TB infection (LTBI) are asymptomatic and are not infectious, they may eventually develop active disease. Thus, a fundamental tool of TB control programs for HCWs is the screening and treatment of LTBI. Methods: From January 2014 to January 2015, hospital personnel at Azienda Ospedaliera Universitaria, Naples, Italy, were screened for TB. To this end, a tuberculin skin test (TST) was administered as an initial examination, unless when contraindicated, in which case the QuantiFERON® TB-Gold (QFT) assay was performed. Moreover, QFT was carried out on all TST-positive cases to confirm the initial result. Results: Of 628 personnel asked to participate, 28 (4.5%) denied consent, 533 were administered TST as the baseline examination, and 67 were tested only with QFT. In the TST group, 73 (13.2%) individuals were found positive, 418 (78.4%) were negative, and 42 (7.9%) were absent for the reading window; QFT confirmed the result in 39 (53.4%) TST-positive individuals. In the QFT-only group, 44 (65.7%) individuals were found positive. All TST- and/or QFT-positive subjects were referred for chest X-ray and examination by an infectious diseases specialist. None were found to have active TB, and were thus diagnosed with LTBI. Conclusions: Although Italy is a low-incidence country regarding TB, our findings suggest that the prevalence of LTBI in HCWs may be relatively high. As a result, active screening for TB and LTBI is needed for these workers. [ABSTRACT FROM AUTHOR]

Background: Emerging and re-emerging infectious diseases such as Zika, SARS, ncovid19 and Pertussis, pose a compelling challenge for epidemiologists due to their significant impact on global public health. In this context, computational models and computer simulations are one of the available research tools that epidemiologists can exploit to better understand the spreading characteristics of these diseases and to decide on vaccination policies, human interaction controls, and other social measures to counter, mitigate or simply delay the spread of the infectious diseases. Nevertheless, the construction of mathematical models for these diseases and their solutions remain a challenging tasks due to the fact that little effort has been devoted to the definition of a general framework easily accessible even by researchers without advanced modelling and mathematical skills. Results: In this paper we describe a new general modeling framework to study epidemiological systems, whose novelties and strengths are: (1) the use of a graphical formalism to simplify the model creation phase; (2) the implementation of an R package providing a friendly interface to access the analysis techniques implemented in the framework; (3) a high level of portability and reproducibility granted by the containerization of all analysis techniques implemented in the framework; (4) a well-defined schema and related infrastructure to allow users to easily integrate their own analysis workflow in the framework. Then, the effectiveness of this framework is showed through a case of study in which we investigate the pertussis epidemiology in Italy. Conclusions: We propose a new general modeling framework for the analysis of epidemiological systems, which exploits Petri Net graphical formalism, R environment, and Docker containerization to derive a tool easily accessible by any researcher even without advanced mathematical and computational skills. Moreover, the framework was implemented following the guidelines defined by Reproducible Bioinformatics Project so it guarantees reproducible analysis and makes simple the developed of new user-defined workflows. [ABSTRACT FROM AUTHOR]

Honeybee health can be compromised not only by infectious and infesting diseases, but also by the acute or chronic action of certain pesticides. In recent years, there have been numerous reports of colony mortality by Italian beekeepers, but the investigations of these losses have been inconsistent, both in relation to the type of personnel involved (beekeepers, official veterinarians, members of the police force, etc.) and the procedures utilized. It was therefore deemed necessary to draw up national guidelines with the aim of standardizing sampling active ties. In this paper, we present the results of a survey carried out in Italy from 2015 to 2019, following these guidelines. Residues of 150 pesticides in 696 samples were analyzed by LC-MS/MS and GC-MS/MS. On average, 50% of the honeybee samples were positive for one or more pesticides with an average of 2 different pesticides per sample and a maximum of seven active ingredients, some of which had been banned in Europe or were not authorized in Italy. Insecticides were the most frequently detected, mainly belonging to the pyrethroid group (49%, above all tau-fluvalinate), followed by organophosphates (chlorpyrifos, 18%) and neonicotinoids (imidacloprid, 7%). This work provides further evidence of the possible relationship between complex pesticide exposure and honeybee mortality and/or depopulation of hives. [ABSTRACT FROM AUTHOR]

Background: Prisoners constitute a high-risk population, particularly for infectious diseases. The aim of this study was to estimate the level of infectious risk in the prisons of five different European countries by measuring to what extent the prison system adheres to WHO/UNODC recommendations.Methods: Following the methodology used in a previous French survey, a postal/electronic questionnaire was sent to all prisons in Austria, Belgium, Denmark and Italy to collect data on the availability of several recommended HIV-HCV prevention interventions and HBV vaccination for prisoners. A score was built to compare adherence to WHO/UNODC recommendations (considered a proxy of environmental infectious risk) in those 4 countries. It ranged from 0 (no adherence) to 12 (full adherence). A second score (0 to 9) was built to include data from a previous French survey, thereby creating a 5-country comparison.Results: A majority of prisons answered in Austria (100 %), France (66 %) and Denmark (58 %), half in Belgium (50 %) and few in Italy (17 %), representing 100, 74, 89, 47 and 23 % coverage of the prison populations, respectively. Availability of prevention measures was low, with median adherence scores ranging from 3.5 to 4.5 at the national level. These results were confirmed when using the second score which included France in the inter-country comparison. Overall, the adherence score was inversely associated with prison overpopulation rates (p = 0.08).Conclusions: Using a score of adherence to WHO/UNODC recommendations, the estimated environmental infectious risk remains extremely high in the prisons of the 5 European countries assessed. Public health strategies should be adjusted to comply with the principle of equivalence of care and prevention with the general community. [ABSTRACT FROM AUTHOR]

Objective. The aim of this study was to develop and validate an algorithm to assist the attribution of neuropsychiatric (NP) events to underlying disease in SLE patients. Methods. Phase 1 identified and categorized candidate items to be included in the algorithm for the attribution of an NP event to SLE and their relative weights through a literature-informed consensus-driven process. Using a retrospective training cohort of SLE, phase 2 validated items selected in phase 1 and refined weights through a data-driven process, fitting items as independent variables and expert evaluation (clinical judgement) as reference standard in logistic models. Phase 3 consisted of a validation process using an external multicentre retrospective SLE cohort. Results. Phase 1 identified four different items: timing of the NP event, type of event, confounding factors and favouring factors. The training and validating cohorts included 228 and 221 patients, respectively. Each patient experienced at least one NP event characterized using the ACR case definition. In these samples, items selected in phase 1 showed good performance in discriminating patients with NPSLE: the area under the receiver operating characteristic curve using dichotomous outcomes was 0.87 in the training set and 0.82 in the validating set. Relevant cut-offs of the validated score identify events with a positive predictive value of 100% (95% CI 93.2, 100) and 86.3% (95% CI 76.2, 93.2) in the training and validating cohorts, respectively. Conclusion. A new algorithm based on a probability score was developed and validated to determine the relationship between NP events and SLE. [ABSTRACT FROM AUTHOR]

The aim of this population-based study was to assess the incidence rates of infectious diseases in native- (Italian) and foreign-born (immigrants) populations in a North Italy area, in 2006-2010. Crude, age-specific incidence rates (IRs) and age-standardised rate ratios (SRRs) between foreign- and native-born subjects and their 95 % confidence intervals (95 % CI) were estimated. A total of 32,554 cases of infectious diseases were found (9.9 % in foreign-born subjects). The highest SRRs between foreign- and nativeborn subjects were found for tuberculosis (SRR = 27.1; 95 % CI 21.3-34.3), malaria (SRR = 21.1; 14.6-30.4), scabies (SRR = 8.5; 7.6-9.4), AIDS (SRR = 2.5; 1.8-3.4) and viral hepatitis B (SRR = 3.3; 2.1-5.2). The highest IR was found for AIDS in people from the Americas (IR = 4.57; 95 % CI 2.2-8.4), for malaria and tuberculosis in people from Africa (IR = 13.89; 11.6-16.5 and IR = 11.87; 9.8-14.3 respectively). Therefore immigrants are at a higher risk of acquiring some common infectious diseases compared to the native population in Western European countries. [ABSTRACT FROM AUTHOR]

Background: Multidrug-resistant tuberculosis (MDR-TB) requires lengthy use of second-line drugs, burdened by many side effects. Hepatitis C virus (HCV) chronic infection increases risk of drug-induced liver injury (DILI) in these patients. Data on MDR-TB patients with concurrent HCV chronic infection treated at the same time with second-line antitubercular drugs and new direct-acting antivirals (DAAs) are lacking. We evaluate if treating at the same time HCV infection and pulmonary MDR-TB is feasible and effective.Cases Presentation: In this study, we described two cases of patients with pulmonary MDR-TB and concurrent HCV chronic infection cured with DAAs at a Tertiary Infectious Diseases Hospital in Italy. During antitubercular treatment, both patients experienced a DILI before treating HCV infection. After DAAs liver enzymes normalized and HCV RNA was undetectable. Then antitubercular regimen was started according to the institutional protocol, drawn up following WHO MDR-TB guidelines. It was completed without further liver side effects and patients were declared cured from both HCV infection and MDR-TB.Conclusions: We suggest to consider treatment of chronic hepatitis C with DAAs as a useful intervention for reintroduction of second-line antitubercular agents in those patients who developed DILI, reducing the risk of treatment interruption when re-exposed to these drugs. [ABSTRACT FROM AUTHOR]

Background: Pigs play a key epidemiologic role in the ecology of influenza A viruses (IAVs) emerging from animal hosts and transmitted to humans. Between 2008 and 2010, we investigated the health risk of occupational exposure to swine influenza viruses (SIVs) in Italy, during the emergence and spread of the 2009 H1N1 pandemic (H1N1pdm) virus. Methodology/Principal Findings: Serum samples from 123 swine workers (SWs) and 379 control subjects (Cs), not exposed to pig herds, were tested by haemagglutination inhibition (HI) assay against selected SIVs belonging to H1N1 (swH1N1), H1N2 (swH1N2) and H3N2 (swH3N2) subtypes circulating in the study area. Potential cross-reactivity between swine and human IAVs was evaluated by testing sera against recent, pandemic and seasonal, human influenza viruses (H1N1 and H3N2 antigenic subtypes). Samples tested against swH1N1 and H1N1pdm viruses were categorized into sera collected before (n. 84 SWs; n. 234 Cs) and after (n. 39 SWs; n. 145 Cs) the pandemic peak. HI-antibody titers ≥10 were considered positive. In both pre-pandemic and post-pandemic peak subperiods, SWs showed significantly higher swH1N1 seroprevalences when compared with Cs (52.4% vs. 4.7% and 59% vs. 9.7%, respectively). Comparable HI results were obtained against H1N1pdm antigen (58.3% vs. 7.7% and 59% vs. 31.7%, respectively). No differences were found between HI seroreactivity detected in SWs and Cs against swH1N2 (33.3% vs. 40.4%) and swH3N2 (51.2 vs. 55.4%) viruses. These findings indicate the occurrence of swH1N1 transmission from pigs to Italian SWs. Conclusion/Significance: A significant increase of H1N1pdm seroprevalences occurred in the post-pandemic peak subperiod in the Cs (p<0.001) whereas SWs showed no differences between the two subperiods, suggesting a possible occurrence of cross-protective immunity related to previous swH1N1 infections. These data underline the importance of risk assessment and occupational health surveillance activities aimed at early detection and control of SIVs with pandemic potential in humans. [ABSTRACT FROM AUTHOR]

Background: Tuberculosis (TB) surveillance systems have some pitfalls outside of a National Tuberculosis Program and lack of efficient surveillance hampers accurate epidemiological quantification of TB burden. In the present study we assessed the quality of surveillance at the University Hospital in Pisa (UHP), Italy, and TB incidence rates over a ten year period (1999-2008). Methods: Assessment of underreporting was done by record-linkage from two sources: databases of TB diagnoses performed in the UHP and the Italian Infectious Disease Surveillance (IIDS) system. Two different databases were examined: a) TB diagnoses reported in the Hospital Discharge Records (HDR) from three Units of UHP (Respiratory Pathophysiology, Pulmonology and Infectious Diseases Units) (TB database A); b) TB diagnoses reported in HDR of all Units of UHP plus TB positive cases obtained by the Laboratory Register (LR) of UHP (TB database B). For the TB database A, the accuracy of TB diagnosis in HDR was assessed by direct examination of the Clinical Record Forms of the cases. For the TB database B, clinical and population data were described, as well as the trend of incidence and underreporting over 10 yrs. Results: In the first study 293 patients were found: 80 patients (27%) with a confirmed TB diagnosis were underreported, 39 of them were microbiologically confirmed. Underreporting was related to age (Reported vs Non Reported, mean age: 49.27 ± 20 vs 55 ± 19, p<0.005 ), diagnosis (smear positive vs negative cases 18.7 vs 81.2%, p = 0.001), microbiological confirmation (49% vs 51%, p<0.05), X-ray findings (cavitary vs non-cavitary cases: 12.5 vs 87.5%, p = 0.001) but not to nationality. In the second study, 666 patients were found. Mean underreporting rate was 69.4% and decreased over time (68% in 1999, 48% in 2008). Newly diagnosed TB cases were also found to decrease in number whereas immigration rate increased. Underreporting was related to nationality (Immigrants vs Italians: 18% vs 68%, p<0.001), diagnosis (microbiological confirmation: 25% vs 75%, p<0.01), kind of hospital regimen (hospitalized patients vs Day Hospital: 70% vs 16%, p<0.001), and position of TB code in the HDR (TB code in first position vs in the following position: 39,5% vs 45% p<0.001). Conclusions: TB is underreported in Pisa, particularly in older patients and those without microbiological confirmation. The TB code in first position of HDR seems fairly accurate in confirming TB diagnosis. [ABSTRACT FROM AUTHOR]

BackgroundThe study aims to explore, using indirect ecological measures of exposure, the role of viral infections in the development of anorexia nervosa (AN).MethodThe cohort of participants consisted of all female subjects born in the Veneto region in the period between 1970 and 1984, and residing in the urban and suburban area of Padua (27 682 female subjects in an area of 424 km2). The main outcome measure was the diagnosis of AN resulting from the Public Mental Health Database, the Register of Hospital Admissions, and the Register of the Eating Disorders Unit (n=402, 1.4%). The number of cases of rubella, chickenpox, influenza and measles was ascertained for each month for the 15-year period.ResultsExposures during the sixth month of pregnancy to the peaks of chickenpox [odds ratio (OR) 1.6, 95% confidence interval (CI) 1.2–2.0] and rubella infections (OR 1.5, 95% CI 1.1–2.0) were significantly associated with an increased risk of developing AN, even after controlling for socio-economic status, urbanization and month of birth. We found weak evidence of a season-of-birth bias.ConclusionsIn utero exposure to viral infection could be a risk factor for developing AN. We need further epidemiological and serological studies to confirm this hypothesis. [ABSTRACT FROM PUBLISHER]

Background: The tiger mosquito (Aedes albopictus), vector of several emerging diseases, is expanding into more northerly latitudes as well as into higher altitudes in northern Italy. Changes in the pattern of distribution of the tiger mosquito may affect the potential spread of infectious diseases transmitted by this species in Europe. Therefore, predicting suitable areas of future establishment and spread is essential for planning early prevention and control strategies. Methodology/Principal Findings: To identify the areas currently most suitable for the occurrence of the tiger mosquito in the Province of Trento, we combined field entomological observations with analyses of satellite temperature data (MODIS Land Surface Temperature: LST) and human population data. We determine threshold conditions for the survival of overwintering eggs and for adult survival using both January mean temperatures and annual mean temperatures. We show that the 0°C LST threshold for January mean temperatures and the 11°C threshold for annual mean temperatures provide the best predictors for identifying the areas that could potentially support populations of this mosquito. In fact, human population density and distance to human settlements appear to be less important variables affecting mosquito distribution in this area. Finally, we evaluated the future establishment and spread of this species in relation to predicted climate warming by considering the A2 scenario for 2050 statistically downscaled at regional level in which winter and annual temperatures increase by 1.5 and 1°C, respectively. Conclusions/Significance: MODIS satellite LST data are useful for accurately predicting potential areas of tiger mosquito distribution and for revealing the range limits of this species in mountainous areas, predictions which could be extended to an European scale. We show that the observed trend of increasing temperatures due to climate change could facilitate further invasion of Ae. albopictus into new areas. [ABSTRACT FROM AUTHOR]