A compartmental model for smoking dynamics in Italy: a pipeline for inference, validation, and forecasting under hypothetical scenarios.

We propose a compartmental model for investigating smoking dynamics in an Italian region (Tuscany). Calibrating the model on local data from 1993 to 2019, we estimate the probabilities of starting and quitting smoking and the probability of smoking relapse. Then, we forecast the evolution of smoking prevalence until 2043 and assess the impact on mortality in terms of attributable deaths. We introduce elements of novelty with respect to previous studies in this field, including a formal definition of the equations governing the model dynamics and a flexible modelling of smoking probabilities based on cubic regression splines. We estimate model parameters by defining a two-step procedure and quantify the sampling variability via a parametric bootstrap. We propose the implementation of cross-validation on a rolling basis and variance-based Global Sensitivity Analysis to check the robustness of the results and support our findings. Our results suggest a decrease in smoking prevalence among males and stability among females, over the next two decades. We estimate that, in 2023, 18% of deaths among males and 8% among females are due to smoking. We test the use of the model in assessing the impact on smoking prevalence and mortality of different tobacco control policies, including the tobacco-free generation ban recently introduced in New Zealand.

[School-based screening strategies to prevent the spread of COVID-19 in school: a systematic review of the literature]. / Strategie di screening per contenere la diffusione del COVID-19 nella scuola: una revisione sistematica della letteratura.

OBJECTIVES: to describe studies that evaluated the screening programmes implemented in the school during the COVID-19 pandemic. DESIGN: a systematic literature review was conducted according to the PRISMA 2020 Guidelines. Studies published until December 2021 were included. The methodological quality of the studies was assessed with validated scales. Study selection, data extraction, and quality assessment were carried out by two authors independently. SETTING AND PARTICIPANTS: teachers and students belonging to schools of all levels, including universities. MAIN OUTCOMES MEASURES: a. transmission-related outcomes (such as the number or proportion of cases, cumulative frequency, incidence); b. feasibility/acceptability of the screening strategies; c. socioeconomic outcomes (such as testing cost, number of days spent in school, quarantine). RESULTS: after having removed duplicate articles, 2,822 records were retrieved. Thirty-six studies were included (15 used an observational design and 21 modelling study). Regarding the former, the methodological quality has been rated as high in 2 studies, intermediate in 6 and low in 2; in the remaining ones, it was not evaluated because only descriptive. Screenings were quite different in terms of school study population, types of tests used, methods of submission and analysis, and level of incidence in the community at the time of implementation. Outcome indicators were also varied, a heterogeneity that, on the one hand, did not allow for meta-analysis of results and, on the other, allowed for testing the performance of the screenings in very different settings. All of the field studies claim that the screenings reduced SARS-CoV-2 exposure and infection among children, adolescents, and college students, curbing at-school transmission and helping to reduce the number of closing school days. Studies that evaluated the cost of the intervention emphasized its cost-effectiveness, while those that focused on the acceptability of the instrument showed a preference among children, adolescents, and parents for minimally invasive, self-administered tests with high sensitivity and lower frequency of repetition. Simulation-based studies are mostly based on compartmental and agent-based models. Their quality is quite high methodologically, although uncertainty quantification and external validation, aimed at verifying the model ability to reproduce observed data, are lacking in many cases. The contexts to which the simulations refer are all school-based, although 7 studies consider residential situations, which are poorly suited to the Italian context. All simulation-based models indicate the importance of planning repeated testing on asymptomatic individuals to limit contagion. However, the costs of these procedures can be high unless assessments are spaced out or pool testing procedures are used. Obtaining high student adherence to the screening programme is extremely important to maximize results. CONCLUSIONS: school-based screenings, especially when combined with other preventive measures, have been important public health tools to contain infections during COVID-19 waves and to ensure children's and adolescents' right to education and to prevent the fallout in physical and mental health (with strong equity consequences) associated with school closures.

Perampanel in Brain Tumor-Related Epilepsy: A Systematic Review.

Brain tumor-related epilepsy (BTRE) is a common comorbidity in patients with brain neoplasms and it may be either the first symptom or develop after the tumor diagnosis. Increasing evidence suggests that brain tumors and BTRE share common pathophysiological mechanisms. Glutamatergic mechanisms can play a central role in promoting both primary brain tumor growth and epileptogenesis. Perampanel (PER), which acts as a selective antagonist of glutamate α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, may play a role both in the reduction in tumor growth and the control of epileptiform activity. This systematic review aimed to summarize the pre-clinical and clinical evidence about the antitumor properties, antiseizure effects and tolerability of PER in BTRE. Eight pre-clinical and eight clinical studies were identified. The currently available evidence suggests that PER can be an effective and generally well-tolerated therapeutic option in patients with BTRE. In vitro studies demonstrated promising antitumor activity of PER, while no role in slowing tumor progression has been demonstrated in rat models; clinical data on the potential antitumor activity of PER are scarce. Additional studies are needed to explore further the effects of PER on tumor progression and fully characterize its potentialities in patients with BTRE.

Case-Control Study on the Routes of Transmission of SARS-CoV-2 after the Third Pandemic Wave in Tuscany, Central Italy.

The emergence of hyper-transmissible SARS-CoV-2 variants that rapidly became prevalent throughout the world in 2022 made it clear that extensive vaccination campaigns cannot represent the sole measure to stop COVID-19. However, the effectiveness of control and mitigation strategies, such as the closure of non-essential businesses and services, is debated. To assess the individual behaviours mostly associated with SARS-CoV-2 infection, a questionnaire-based case-control study was carried out in Tuscany, Central Italy, from May to October 2021. At the testing sites, individuals were invited to answer an online questionnaire after being notified regarding the test result. The questionnaire collected information about test result, general characteristics of the respondents, and behaviours and places attended in the week prior to the test/symptoms onset. We analysed 440 questionnaires. Behavioural differences between positive and negative subjects were assessed through logistic regression models, adjusting for a fixed set of confounders. A ridge regression model was also specified. Attending nightclubs, open-air bars or restaurants and crowded clubs, outdoor sporting events, crowded public transportation, and working in healthcare were associated with an increased infection risk. A negative association with infection, besides face mask use, was observed for attending open-air shows and sporting events in indoor spaces, visiting and hosting friends, attending courses in indoor spaces, performing sport activities (both indoor and outdoor), attending private parties, religious ceremonies, libraries, and indoor restaurants. These results might suggest that during the study period people maintained a particularly responsible and prudent approach when engaging in everyday activities to avoid spreading the virus.

Combining and comparing regional SARS-CoV-2 epidemic dynamics in Italy: Bayesian meta-analysis of compartmental models and global sensitivity analysis.

During autumn 2020, Italy faced a second important SARS-CoV-2 epidemic wave. We explored the time pattern of the instantaneous reproductive number, R 0(t), and estimated the prevalence of infections by region from August to December calibrating SIRD models on COVID-19-related deaths, fixing at values from literature Infection Fatality Rate (IFR) and average infection duration. A Global Sensitivity Analysis (GSA) was performed on the regional SIRD models. Then, we used Bayesian meta-analysis and meta-regression to combine and compare the regional results and investigate their heterogeneity. The meta-analytic R 0(t) curves were similar in the Northern and Central regions, while a less peaked curve was estimated for the South. The maximum R 0(t) ranged from 2.15 (South) to 2.61 (North) with an increase following school reopening and a decline at the end of October. The predictive performance of the regional models, assessed through cross validation, was good, with a Mean Absolute Percentage Error of 7.2% and 10.9% when considering prediction horizons of 7 and 14 days, respectively. Average temperature, urbanization, characteristics of family medicine and healthcare system, economic dynamism, and use of public transport could partly explain the regional heterogeneity. The GSA indicated the robustness of the regional R 0(t) curves to different assumptions on IFR. The infectious period turned out to have a key role in determining the model results, but without compromising between-region comparisons.

Screening plans for SARS-CoV-2 based on sampling and rotation: An example in a European school setting.

Screening plans for prevention and containment of SARS-CoV-2 infection should take into account the epidemic context, the fact that undetected infected individuals may transmit the disease and that the infection spreads through outbreaks, creating clusters in the population. In this paper, we compare through simulations the performance of six screening plans based on poorly sensitive individual tests, in detecting infection outbreaks at the level of single classes in a typical European school context. The performance evaluation is done by simulating different epidemic dynamics within the class during the four weeks following the day of the initial infection. The plans have different costs in terms of number of individual tests required for the screening and are based on recurrent evaluations on all students or subgroups of students in rotation. Especially in scenarios where the rate of contagion is high, at an equal cost, testing half of the class in rotation every week appears to be better in terms of sensitivity than testing all students every two weeks. Similarly, testing one-fourth of the students every week is comparable with testing all students every two weeks, despite the first one is a much cheaper strategy. In conclusion, we show that in the presence of natural clusters in the population, testing subgroups of individuals belonging to the same cluster in rotation may have a better performance than testing all the individuals less frequently. The proposed simulations approach can be extended to evaluate more complex screening plans than those presented in the paper.

The first wave of the SARS-CoV-2 epidemic in Tuscany (Italy): A SI2R2D compartmental model with uncertainty evaluation.

With the aim of studying the spread of the SARS-CoV-2 infection in the Tuscany region of Italy during the first epidemic wave (February-June 2020), we define a compartmental model that accounts for both detected and undetected infections and assumes that only notified cases can die. We estimate the infection fatality rate, the case fatality rate, and the basic reproduction number, modeled as a time-varying function, by calibrating on the cumulative daily number of observed deaths and notified infected, after fixing to plausible values the other model parameters to assure identifiability. The confidence intervals are estimated by a parametric bootstrap procedure and a Global Sensitivity Analysis is performed to assess the sensitivity of the estimates to changes in the values of the fixed parameters. According to our results, the basic reproduction number drops from an initial value of 6.055 to 0 at the end of the national lockdown, then it grows again, but remaining under 1. At the beginning of the epidemic, the case and the infection fatality rates are estimated to be 13.1% and 2.3%, respectively. Among the parameters considered as fixed, the average time from infection to recovery for the not notified infected appears to be the most impacting one on the model estimates. The probability for an infected to be notified has a relevant impact on the infection fatality rate and on the shape of the epidemic curve. This stresses the need of collecting information on these parameters to better understand the phenomenon and get reliable predictions.

A Nonparametric Bayesian Approach to the Rare Type Match Problem.

The "rare type match problem" is the situation in which, in a criminal case, the suspect's DNA profile, matching the DNA profile of the crime stain, is not in the database of reference. Ideally, the evaluation of this observed match in the light of the two competing hypotheses (the crime stain has been left by the suspect or by another person) should be based on the calculation of the likelihood ratio and depends on the population proportions of the DNA profiles that are unknown. We propose a Bayesian nonparametric method that uses a two-parameter Poisson Dirichlet distribution as a prior over the ranked population proportions and discards the information about the names of the different DNA profiles. This model is validated using data coming from European Y-STR DNA profiles, and the calculation of the likelihood ratio becomes quite simple thanks to an Empirical Bayes approach for which we provided a motivation.

Targeted re-sequencing for early diagnosis of genetic causes of childhood epilepsy: the Italian experience from the 'beyond epilepsy' project.

BACKGROUND: Childhood epilepsies are a heterogeneous group of conditions differing in diagnostic criteria, management, and outcome. Late-infantile neuronal ceroid lipofuscinosis type 2 (CLN2) is a neurodegenerative condition caused by biallelic TPP1 variants. This disorder presents with subtle and relatively non-specific symptoms, mimicking those observed in more common paediatric epilepsies and followed by rapid psychomotor deterioration and drug-resistant epilepsy. A prompt diagnosis is essential to adopt appropriate treatment and disease management strategies. METHODS: This is a prospective, multicentre study on the efficiency of targeted re-sequencing in the early identification of the genetic causes of childhood epilepsy, with particular regard to CLN2. After phenotypic characterization, a 283-gene Next Generation Sequencing panel was performed in 21 Italian children with neurodevelopmental abnormalities, aged between 24 and 60 months, experiencing first unprovoked seizure after 2 years of age. RESULTS: The average age at enrolment was 39.9 months, with a mean age at seizure onset of 30.9 months and a mean time interval between seizure onset and targeted resequencing of 9 months. Genetic confirmation was achieved in 4 out of 21 patients, with a diagnostic yield of 19%. In one case, the homozygous splice acceptor variant c.509-1G > C in TPP1 was identified, leading to a CLN2 diagnosis. Three pathogenic variants in MECP2 were also detected in three patients, including the frameshift variant c.1157_1186delinsA (p.Leu386Hisfs*9) in a girl with negative single gene sequencing. Variants of unknown significance (VUS) were found in 11 out of 21 (52.4%) individuals, whereas no clinically significant variants were observed in the remaining 6 subjects. CONCLUSIONS: Our findings support the efficacy of target re-sequencing in the identification of the genetic causes of childhood epilepsy and suggest that this technique might prove successful in the early detection of CLN2 as well as other neurodevelopmental conditions.

[Analysis and future scenarios of the SARS-CoV-2 epidemic in Tuscany Region (Central Italy)]. / Analisi e previsioni dell'epidemia da SARS-CoV-2 in Toscana.

OBJECTIVES: about two months after the end of the lockdown imposed for the containment of the SARS-CoV-2 epidemic, the contagion dynamics in the Tuscany Region (Central Italy) have been assessed from the beginning of the emergency to the end of June through a compartmental model, and future medium-long term projections have been produced. DATA AND METHODS: this study used a SIRD model in which the infection reproduction number R0 varied over time, according to a piecewise constant function. The fatality parameter and the time from contagion to infection resolution (death or recovery) were fixed to ensure parameter identifiability, and the model was calibrated on the Covid-19 deaths notified from March 9th to June 30th 2020. The uncertainty around the estimates was quantified through parametric bootstrap. Finally, the resulting model was used to produce medium-long term projections of the epidemic dynamics. RESULTS: the date of the first infection in Tuscany was estimated as February 21st 2020. The value of R0(t) ranged from 7.78 (95%CI 7.55-7.89), at the beginning of the outbreak, to a value very close to 0 between April 27th and May 17th. Finally, R0(t) rose, reaching an average of 0.66 (0.32, 0.88) between May 18th and June 30th. At the epidemic peak, estimated at the beginning of April, the notified infected people circulating in the region were just 22% of those predicted by the model. According to the estimated SIRD, under the hypothetical scenario that R0(t) slightly exceeds 1 from the beginning of October 2020, a new wave of contagion could arise by next spring. CONCLUSIONS: the estimated trend of R0(t) is suggestive of a strong effect of the lockdown in Tuscany and of a mild increase of the contagion potentially attributable to the easing of the containment measures. Medium-long term projections unequivocally indicate that the danger of a new epidemic wave has not been averted.