The impact of COVID-19 vaccination campaign on pediatric vaccine uptake based on parents' attitudes towards mandatory and recommended vaccination in Southern Italy.

INTRODUCTION: This study investigates the association between parental attitudes towards mandatory and recommended vaccines in the National Immunization Plan (NIP) of Italy and their acceptance of the COVID-19 vaccine in children aged 5-11 years. METHODS: Using data from approximately 42,000 children in Southern Italy, parental attitudes towards previous vaccinations were examined. Mandatory and recommended vaccinations were considered for the analysis, with the first shot of each schedule being considered relevant, regardless of when it was administered or whether the recommended number of doses was administered. A multivariate logistic regression was performed to analyze associations between the covariates of age, sex, adherence to mandatory vaccinations, number of recommended vaccinations, and COVID-19 vaccination. RESULTS: The COVID-19 vaccine acceptance rate was 50.7% in our sample. We revealed a strong association between parental attitudes towards previous vaccinations and the acceptance of the COVID-19 vaccine. Mandatory vaccinations under the NIP showed the highest acceptance rates, and among non-mandatory vaccines, the pneumococcal conjugate vaccine had the highest acceptance rate, potentially due to its co-administration with the hexavalent vaccine. The study identified a trend of lower COVID-19 vaccine coverage in younger children. CONCLUSIONS: The study underscores the importance of co-administration approaches and well-planned vaccination schedules in enhancing vaccine coverage. It suggests that integrating newer vaccines, like the COVID-19 vaccine, into established vaccination schedules could potentially increase acceptance and coverage. The findings highlight the urgency of addressing vaccine hesitancy, particularly in the pediatric population, to ensure high vaccination coverage and effective disease control. Further research is needed to explore the potential strategies to increase vaccine acceptance.

Pre-COVID-19-pandemic RSV epidemiology and clinical burden in pediatric primary care in Italy: a comparative analysis across two regions for the 2019/2020 season.

BACKGROUND: Respiratory syncytial virus (RSV) infection in children under 5 years have a significant clinical burden, also in primary care settings. This study investigates the epidemiology and burden of RSV in Italian children during the 2019/20 pre-pandemic winter season. METHODS: A prospective cohort study was conducted in two Italian regions. Children with Acute Respiratory Infection (ARI) visiting pediatricians were eligible. Nasopharyngeal swabs were collected and analyzed via multiplex PCR for RSV detection. A follow-up questionnaire after 14 days assessed disease burden, encompassing healthcare utilization and illness duration. Statistical analyses, including regression models, explored associations between variables such as RSV subtype and regional variations. RESULTS: Of 293 children with ARI, 41% (119) tested positive for RSV. Median illness duration for RSV-positive cases was 7 days; 6% required hospitalization (median stay: 7 days). Medication was prescribed to 95% (110/116) of RSV cases, with 31% (34/116) receiving antibiotics. RSV subtype B and regional factors predicted increased healthcare utilization. Children with shortness of breath experienced a 36% longer illness duration. CONCLUSIONS: This study highlights a significant clinical burden and healthcare utilization associated with RSV in pre-pandemic Italian primary care settings. Identified predictors, including RSV subtype and symptomatology, indicate the need for targeted interventions and resource allocation strategies. RSV epidemiology can guide public health strategies for the implementation of preventive measures.

RSV Disease Burden in Primary Care in Italy: A Multi-Region Pediatric Study, Winter Season 2022-2023.

INTRODUCTION: Human respiratory syncytial virus (RSV) is one of the most frequent causes of respiratory infections in children under 5 years of age, but its socioeconomic impact and burden in primary care settings is still little studied. METHODS: During the 2022/2023 winter season, 55 pediatricians from five Italian regions participated in our community-based study. They collected a nasal swab for RSV molecular test from 650 patients under the age of 5 with acute respiratory infections (ARIs) and performed a baseline questionnaire. The clinical and socioeconomic burden of RSV disease in primary care was evaluated by two follow-up questionnaires completed by the parents of positive children on Days 14 and 30. RESULTS: RSV laboratory-confirmed cases were 37.8% of the total recruited ARI cases, with RSV subtype B accounting for the majority (65.4%) of RSV-positive swabs. RSV-positive children were younger than RSV-negative ones (median 12.5 vs. 16.5 months). The mean duration of symptoms for all children infected by RSV was 11.47 ± 6.27 days. We did not observe substantial differences in clinical severity between the two RSV subtypes, but RSV-A positive patients required more additional pediatric examinations than RSV-B cases. The socioeconomic impact of RSV infection was considerable, causing 53% of children to be absent from school, 46% of parents to lose working days, and 25% of families to incur extra costs. CONCLUSIONS: Our findings describe a baseline of the RSV disease burden in primary care in Italy before the introduction of upcoming immunization strategies.

Evaluating hepatitis C cascade of care surveillance system in Tuscany, Italy, through a population retrospective data-linkage study, 2015-2021.

This comprehensive retrospective data-linkage study aimed at evaluating the impact of Direct-Acting Antivirals (DAAs) on Hepatitis C Virus (HCV) testing, treatment trends, and access to care in Tuscany over six years following their introduction. Utilizing administrative healthcare records, our work reveals a substantial increase in HCV tests in 2017, attributed to the decision to provide universal access to treatment. However, despite efforts to eradicate chronic HCV through a government-led plan, the target of treating 6,221 patients annually was not met, and services contracted after 2018, exacerbated by the COVID-19 pandemic. Key findings indicate a higher prevalence of HCV screening among females in the 33-53 age group, influenced by pregnancy-related recommendations, while diagnostic tests and treatment uptake were more common among males. Problematic substance users constituted a significant proportion of those tested and treated, emphasizing their priority in HCV screening. Our paper underscores the need for decentralized HCV models and alternative testing strategies, such as point-of-care assays, especially in populations accessing harm reduction services, communities, and prisons. The study acknowledges limitations in relying solely on administrative records, advocating for improved data access and timely linkages to accurately monitor HCV care cascades and inform regional plans. Despite challenges, the paper demonstrates the value of administrative record linkages in understanding the access to care pathway for hard-to-reach populations. The findings emphasize the importance of the national HCV elimination strategy and the need for enhanced data collection to assess progress accurately, providing insights for future regional and national interventions.

Waning intra-season vaccine effectiveness against influenza A(H3N2) underlines the need for more durable protection.

BACKGROUND: The question of whether influenza vaccine effectiveness (VE) wanes over the winter season is still open and some contradictory findings have been reported. This study investigated the possible decline in protection provided by the available influenza vaccines. RESEARCH DESIGN AND METHODS: An individual-level pooled analysis of six test-negative case-control studies conducted in Italy between the 2018/2019 and 2022/2023 seasons was performed. Multivariable logistic regression analyses were performed to estimate weekly change in the odds of testing positive for influenza 14 days after vaccination. RESULTS: Of 6490 patients included, 1633 tested positive for influenza. Each week that had elapsed since vaccination was associated with an increase in the odds of testing positive for any influenza (4.9%; 95% CI: 2.0-8.0%) and for A(H3N2) (6.5%; 95% CI: 2.9-10.3%). This decline in VE was, however, significant only in children and older adults. A similar increase in the odds of testing positive was seen when the dataset was restricted to vaccinees only. Conversely, VE waning was less evident for A(H1N1)pdm09 or B strains. CONCLUSIONS: Significant waning of VE, especially against influenza A(H3N2), may be one of the factors associated with suboptimal end-of-season VE. Next-generation vaccines should provide more durable protection against A(H3N2).

Innovative Techniques for Infection Control and Surveillance in Hospital Settings and Long-Term Care Facilities: A Scoping Review.

Healthcare-associated infections (HAIs) pose significant challenges in healthcare systems, with preventable surveillance playing a crucial role. Traditional surveillance, although effective, is resource-intensive. The development of new technologies, such as artificial intelligence (AI), can support traditional surveillance in analysing an increasing amount of health data or meeting patient needs. We conducted a scoping review, following the PRISMA-ScR guideline, searching for studies of new digital technologies applied to the surveillance, control, and prevention of HAIs in hospitals and LTCFs published from 2018 to 4 November 2023. The literature search yielded 1292 articles. After title/abstract screening and full-text screening, 43 articles were included. The mean study duration was 43.7 months. Surgical site infections (SSIs) were the most-investigated HAI and machine learning was the most-applied technology. Three main themes emerged from the thematic analysis: patient empowerment, workload reduction and cost reduction, and improved sensitivity and personalization. Comparative analysis between new technologies and traditional methods showed different population types, with machine learning methods examining larger populations for AI algorithm training. While digital tools show promise in HAI surveillance, especially for SSIs, challenges persist in resource distribution and interdisciplinary integration in healthcare settings, highlighting the need for ongoing development and implementation strategies.

Exploring the Possible Use of AI Chatbots in Public Health Education: Feasibility Study.

BACKGROUND: Artificial intelligence (AI) is a rapidly developing field with the potential to transform various aspects of health care and public health, including medical training. During the "Hygiene and Public Health" course for fifth-year medical students, a practical training session was conducted on vaccination using AI chatbots as an educational supportive tool. Before receiving specific training on vaccination, the students were given a web-based test extracted from the Italian National Medical Residency Test. After completing the test, a critical correction of each question was performed assisted by AI chatbots. OBJECTIVE: The main aim of this study was to identify whether AI chatbots can be considered educational support tools for training in public health. The secondary objective was to assess the performance of different AI chatbots on complex multiple-choice medical questions in the Italian language. METHODS: A test composed of 15 multiple-choice questions on vaccination was extracted from the Italian National Medical Residency Test using targeted keywords and administered to medical students via Google Forms and to different AI chatbot models (Bing Chat, ChatGPT, Chatsonic, Google Bard, and YouChat). The correction of the test was conducted in the classroom, focusing on the critical evaluation of the explanations provided by the chatbot. A Mann-Whitney U test was conducted to compare the performances of medical students and AI chatbots. Student feedback was collected anonymously at the end of the training experience. RESULTS: In total, 36 medical students and 5 AI chatbot models completed the test. The students achieved an average score of 8.22 (SD 2.65) out of 15, while the AI chatbots scored an average of 12.22 (SD 2.77). The results indicated a statistically significant difference in performance between the 2 groups (U=49.5, P<.001), with a large effect size (r=0.69). When divided by question type (direct, scenario-based, and negative), significant differences were observed in direct (P<.001) and scenario-based (P<.001) questions, but not in negative questions (P=.48). The students reported a high level of satisfaction (7.9/10) with the educational experience, expressing a strong desire to repeat the experience (7.6/10). CONCLUSIONS: This study demonstrated the efficacy of AI chatbots in answering complex medical questions related to vaccination and providing valuable educational support. Their performance significantly surpassed that of medical students in direct and scenario-based questions. The responsible and critical use of AI chatbots can enhance medical education, making it an essential aspect to integrate into the educational system.

Vaccine hesitancy and knowledge regarding maternal immunization among reproductive age women in central Italy: a cross sectional study.

Background: Vaccination in pregnancy offers protection to the mother and the newborn. In Italy, influenza, pertussis, and COVID-19 vaccinations are recommended in pregnancy, but vaccination coverage is still far from the National Immunization Plan goals. We aimed to assess knowledge and attitude on maternal immunization in two groups of Italian women, in pregnancy and in reproductive age (non pregnant). Methods: A cross sectional study on Italian childbearing age women gathering information on their knowledge on maternal immunization and attitudes to receiving influenza and pertussis vaccines in pregnancy was carried out at the University of Rome Tor Vergata, between September 2019 and February 2020. Logistic and multinomial regressions were chosen as statistical tests for our analysis. Results: 1,031 women participated in the survey by answering the questionnaire. Out of these, 553 (53.6%) women were pregnant, and 478 (46.4%) were in the reproductive age. 37% (204/553) of pregnant women and 41% (198/476) of non pregnant women are aware of the existence of an immunization plan for pregnant women in Italy. The group with age between 20 and 30, for both pregnant women and women in the reproductive age, has a better knowledge of vaccination in pregnancy. Working status is a variable associated with more awareness about vaccination during pregnancy only for pregnant women (OR = 2.34, p < 0.00001). Educational status, trimester of pregnancy and knowledge on the topic are associated with vaccine hesitancy in our multivariate analysis for pregnant women. In the reproductive age group women who had a previous pregnancy are more likely to be hesitant towards vaccination in pregnancy, on the other hand the one with a higher knowledge and educational status are more likely to get vaccinated. Conclusions: The study highlights the persistent vaccine hesitancy among Italian women of reproductive age and pregnant women. Despite healthcare providers being identified as a reliable source of information, their recommendations alone are insufficient to overcome vaccine hesitancy. Factors such as employment status, educational level, pregnancy trimester, and knowledge about vaccinations during pregnancy influence vaccine hesitancy. Tailored educational interventions and communication campaigns targeting these areas can help reduce vaccine hesitancy and promote maternal immunization.

Assessing vaccine hesitancy and health literacy using a new Italian vaccine confidence index and a modified Italian medical term recognition test: A cross-sectional survey on Italian parents.

The decline in children's vaccination coverage and the resurgence of preventable infectious diseases draw attention to parents' vaccine hesitancy. Our study introduces two validated tools to independently assess vaccine hesitancy and health literacy among parents with school-age children. We developed a Vaccine Confidence Index (VCI) from 10 Likert items, exploring their relationships through exploratory and confirmatory factor analyses. We modified the IMETER (Italian medical term recognition test) to measure health literacy. We assessed the internal consistency of the modified IMETER and the 10 Likert items using Cronbach's alpha test (α) and McDonald's omega total coefficient (ω) with good results (ω = 0.92, α = 0.90; ω = 0.87, α = 0.82 respectively). We used these tools within a questionnaire conducted on 743 parents recruited from pediatric clinic waiting rooms in Italy, collecting demographic data, information sources on vaccines and vaccine-preventable diseases knowledge. The VCI resulting from factor analyses consisted of six items on a ten-point Likert scale, reflecting the ratio of positive to negative items. The survey revealed significant variations in the VCI according to individual features such as education, use of social networks, or Health institutions as sources of information. Multivariate logistic regression identified an association between vaccine intention and the VCI. Health literacy was functional for 91.2% of participants, but knowledge about vaccine-preventable diseases was generally low. The VCI showed no significant association with health literacy and vaccine-preventable diseases knowledge. The VCI and the modified IMETER effectively assess vaccination attitude and health literacy, offering valuable public health tools for tailoring vaccination campaigns to hesitant population subgroups.

Investigating Resistance to Carbapenems in Enterobacterales: A Descriptive Epidemiological Study of 2021 Screening in an Italian Teaching Hospital.

Antimicrobial resistance (AMR) presents a growing threat to global healthcare. This descriptive epidemiological study investigates the prevalence and characteristics of Enterobacterales with AMR factors in a tertiary teaching hospital in Italy over the course of the year 2021. In 2021, the prevalence of colonisation by Enterobacterales with AMR factors in patients was 1.08%. During the observation period, a total of 8834 rectal swabs were performed, with 1453 testing positive. A total of 5639 rectal swabs were performed according to a hospital procedure for the active screening of MDRO colonisation at the time of admission. Of these, 679 were positive for microorganisms under surveillance, and 74 patients were colonised with Enterobacterales, predominantly Klebsiella pneumoniae and Escherichia coli. Antibiotic resistance factors were observed in 61 of these 74 patients (82.43%) of these patients, with NDM and KPC being the most frequent resistance factors. A statistically significant trend in positive swabs was observed across different ward categories (surgery, ICUs, and medical wards). Regarding specific trends, the rate of positive admission screening in medical and surgical wards was higher than in ICU wards. The results highlight the ease with which Enterobacterales develops resistance across different ward categories. The findings underscore the need for adjusted screening protocols and tailored infection prevention strategies in various care settings.

Performance comparison between heterologous and homologous COVID19 vaccine schedules on Omicron variant incidence: A real-world retrospective cohort study in Southern Italy.

As the COVID19 pandemic progresses, there is an increasing need to evaluate the performance of vaccine strategies. This study investigated the vaccine schedule performance of heterologous vaccination compared to homologous vaccination in preventing Omicron SARS-CoV2 infection in the adult population. This retrospective cohort study utilized data from the Infections Regional Information System and the Apulia Regional Vaccine Registry to identify individuals who received a booster dose of one of 14 different COVID19 vaccination schedules between September 2021 and August 2022 in the province of Lecce, Southern Italy. The standardized cumulative incidence of SARS-CoV2 infection after the booster dose was assessed and the risk of infection between subgroups of heterologous and homologous vaccination schedules was compared using the Cochran-Mantel-Haenszel test. A total of 469,069 subjects were included in the study. The standardized incidence of SARS-CoV2 infection varied greatly among different vaccine schedules, with the highest and lowest being AZ-AZ-BNT (34.7 %) and MOD-MOD-BNT (18.9 %), respectively, and some heterologous schedules performing better than homologous ones. The risk of SARS-CoV2 infection was significantly lower in individuals who received specific heterologous vaccination schedules compared to homologous vaccination schedules, the best performing being MOD-MOD-BNT with a common odd ratio of 0.661 (IC. 95 % [0.620-0.704]). This study provides evidence that heterologous vaccination schedules may be more effective in preventing Omicron SARS-CoV2 infection compared to homologous vaccination schedules, highlighting how the vaccine product, rather than the platform, is involved in the different protection provided by heterologous vaccination.

Population-level benefits of increasing influenza vaccination uptake among Italian older adults: results from a granular panel model.

Background: The impact of seasonal influenza vaccination (SIV) on mortality is still controversial; some studies have claimed that increasing vaccination coverage rates is beneficial, while others have found no significant association. This study aimed to construct a granular longitudinal dataset of local VCRs and assess their effect on pneumonia- and influenza-related (P&I) mortality among Italian adults aged ≥ 65 years. Methods: NUTS-3 (nomenclature of territorial units for statistics) level data on SIV coverage were collected via a survey of local data holders. Fixed- and random-effects panel regression modeling, when adjusted for potential confounders, was performed to assess the association between local SIV coverage rates and P&I mortality in older adults. Results: A total of 1,144 local VCRs from 2003 to 2019 were ascertained. In the fully adjusted fixed-effects model, each 1% increase in vaccination coverage was associated (P < 0.001) with a 0.6% (95% CI: 0.3-0.9%) average over-time decrease in P&I mortality. With an annual average of 9,293 P&I deaths in Italy, this model suggested that 56 deaths could have been avoided each year by increasing SIV coverage by 1%. The random-effects model produced similar results. The base-case results were robust in a sensitivity analysis. Conclusion: Over the last two decades, Italian jurisdictions with higher SIV uptake had, on average, fewer P&I deaths among older adults. Local policy-makers should implement effective strategies to increase SIV coverage in the Italian senior population.

Brand-specific estimates of influenza vaccine effectiveness for the 2021-2022 season in Europe: results from the DRIVE multi-stakeholder study platform.

Introduction: Development of Robust and Innovative Vaccine Effectiveness (DRIVE) was a European public-private partnership (PPP) that aimed to provide annual, brand-specific estimates of influenza vaccine effectiveness (IVE) for regulatory and public health purposes. DRIVE was launched in 2017 under the umbrella of the Innovative Medicines Initiative (IMI) and conducted IVE studies from its pilot season in 2017-2018 to its final season in 2021-2022. Methods: In 2021-2022, DRIVE conducted four primary care-based test-negative design (TND) studies (Austria, Italy, Iceland, and England; involving >1,000 general practitioners), nine hospital-based TND studies (France, Iceland, Italy, Romania, and Spain, for a total of 21 hospitals), and one population-based cohort study in Finland. In the TND studies, patients with influenza-like illness (primary care) or severe acute respiratory infection (hospital) were enrolled, and laboratory tested for influenza using RT-PCR. Study contributor-specific IVE was calculated using logistic regression, adjusting for age, sex, and calendar time, and pooled by meta-analysis. Results: In 2021-2022, pooled confounder-adjusted influenza vaccine effectiveness (IVE) estimates against laboratory-confirmed influenza (LCI) overall and per type and subtype/lineage was produced, albeit with wide confidence intervals (CI). The limited circulation of influenza in Europe did not allow the network to reach the optimal sample size to produce precise IVE estimates for all the brands included. The most significant IVE estimates were 76% (95% CI 23%-93%) for any vaccine and 81% (22%-95%) for Vaxigrip Tetra in adults ≥65 years old and 64% (25%-83%) for Fluenz Tetra in children (TND primary care setting), 85% (12%-97%) for any vaccine in adults 18-64 years (TND hospital setting), and 38% (1%-62%) in children 6 months-6 years (population-based cohort, mixed setting). Discussion: Over five seasons, DRIVE collected data on >35,000 patients, more than 60 variables, and 13 influenza vaccines. DRIVE demonstrated that estimating brand-specific IVE across Europe is possible, but achieving sufficient sample size to obtain precise estimates for all relevant stratifications remains a challenge. Finally, DRIVE's network of study contributors and lessons learned have greatly contributed to the development of the COVID-19 vaccine effectiveness platform COVIDRIVE.

The FLURESP European commission project: cost-effectiveness assessment of ten public health measures against influenza in Italy: is there an interest in COVID-19 pandemic?

BACKGROUND: The FLURESP project is a public health research funded by the European Commission, with the objective to design a methodological framework to assess the cost-effectiveness of existing public health measures against human influenza pandemics. A dataset has been specifically collected in the frame of the Italian health system. As most of interventions against human influenza are relavant against other respiratory diseases pandemics, potential interests in COVID-19 are discussed. METHODS: Ten public health measures against human influenza pandemics pandemic were selected to be also relevant to other respiratory virus pandemics such as COVID 19: individual (hand washing, using masks), border control (quarantine, fever screening, border closure), community infection (school closure, class dismissal, social distancing, limitation of public transport), reduction of secondary infections (implementation of antibiotic therapy guidelines), pneumococcal vaccination for at-risk people, development of Intensive Care Unit (ICU) capacity, implementation of life support equipments in ICU, screening interventions, vaccination programs targeting health professional and targeting general population. RESULTS: Using mortality reduction as effectiveness criteria, the most cost-effective strategies are "reduction of secondary infections" and "implementation of life support equipment in ICU". The least cost-effective option whatever the level of pandemic events are screening interventions and mass vaccination. CONCLUSIONS: A number of intervention strategies against human influenza pandemics appears relevant against every respiratory virus, including the COVID-19 event. Measures against pandemics should be considered according to their expected effectiveness but also their costs for the society because they impose substantial burden to the population, confirming the interest of considering cost-effectiveness of public health measures to enlighten decision making.

ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health.

Large Language Models (LLMs) have recently gathered attention with the release of ChatGPT, a user-centered chatbot released by OpenAI. In this perspective article, we retrace the evolution of LLMs to understand the revolution brought by ChatGPT in the artificial intelligence (AI) field. The opportunities offered by LLMs in supporting scientific research are multiple and various models have already been tested in Natural Language Processing (NLP) tasks in this domain. The impact of ChatGPT has been huge for the general public and the research community, with many authors using the chatbot to write part of their articles and some papers even listing ChatGPT as an author. Alarming ethical and practical challenges emerge from the use of LLMs, particularly in the medical field for the potential impact on public health. Infodemic is a trending topic in public health and the ability of LLMs to rapidly produce vast amounts of text could leverage misinformation spread at an unprecedented scale, this could create an "AI-driven infodemic," a novel public health threat. Policies to contrast this phenomenon need to be rapidly elaborated, the inability to accurately detect artificial-intelligence-produced text is an unresolved issue.

An Example of Neuro-Glial Commitment and Differentiation of Muse Stem Cells Obtained from Patients with IQSEC2-Related Neural Disorder: A Possible New Cell-Based Disease Model.

Although adult stem cells may be useful for studying tissue-specific diseases, they cannot be used as a general model for investigating human illnesses given their limited differentiation potential. Multilineage-differentiating stress-enduring (Muse) stem cells, a SSEA3(+) cell population isolated from mesenchymal stromal cells, fat, and skin fibroblasts, may be able to overcome that restriction. The Muse cells present in fibroblast cultures obtained from biopsies of patients' skin may be differentiated into cells of interest for analyzing diseases. We isolated Muse stem cells from patients with an intellectual disability (ID) and mutations in the IQSEC2 gene (i.e., BRAG1 gene) and induced in vitro neuroglial differentiation to study cell commitment and the differentiation of neural lineages. The neuroglial differentiation of Muse cells revealed that IQSEC2 mutations may alter the self-renewal and lineage specification of stem cells. We observed a decrease in the percentage of SOX2 (+) neural stem cells and neural progenitors (i.e., SOX2+ and NESTIN+) in cultures obtained from Muse cells with the mutated IQSEC2 gene. The alteration in the number of stem cells and progenitors produced a bias toward the astrocytes' differentiation. Our research demonstrates that Muse stem cells may represent a new cell-based disease model.