Carla Ancona, Lorenzo Richiardi, Dolores Catelan, Federica Asta, Valeria Belleudi, Alice Bernasconi, Simone Giannini, Tancredi Lo Presti, Giovenale Moirano, Sara Tunesi
{"title":"[Position paper. The role of epidemiology in urban health].","authors":"Carla Ancona, Lorenzo Richiardi, Dolores Catelan, Federica Asta, Valeria Belleudi, Alice Bernasconi, Simone Giannini, Tancredi Lo Presti, Giovenale Moirano, Sara Tunesi","doi":"10.19191/EP26.3.A1055.052","DOIUrl":"https://doi.org/10.19191/EP26.3.A1055.052","url":null,"abstract":"","PeriodicalId":50511,"journal":{"name":"Epidemiologia & Prevenzione","volume":"50 3","pages":"226-227"},"PeriodicalIF":0.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148438840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Redistribution of garbage codes to underlying causes of death: a systematic analysis on Italian data based on the Global Burden of Disease Study 2023.","authors":"","doi":"10.19191/EP26.3.A1056.064","DOIUrl":"10.19191/EP26.3.A1056.064","url":null,"abstract":"<p><strong>Objectives: </strong>to describe the garbage codes (GCs) identified in the Global Burden of Disease Study (GBD) 2023 and their redistribution to underlying causes of death in Italy in 2021. Specifically, the study aims to: 1. compare temporal trends in the proportion of GCs in Italy with those of other Western European countries with similar population sizes; 2. identify the most frequent GC packages, analyze their geographic distribution, and determine the causes to which they are reassigned; 3. examine the relationship between the proportion of GCs and contextual factors related to death certification, including the type of certifier, place of death, and requests for autopsy.</p><p><strong>Design: </strong>descriptive epidemiological study based on GBD 2023 estimates.</p><p><strong>Setting and participants: </strong>the analysis focuses on the Italian population in 2021, stratified by 21 subnational units, including 19 regions and 2 autonomous provinces.</p><p><strong>Main outcome measures: </strong>total number of deaths; number of GCs, defined as deaths attributed to causes that do not represent underlying causes of death; percentage of GCs, calculated as the number of GCs divided by total deaths and multiplied by 100.</p><p><strong>Results: </strong>the proportion of GCs in Italy gradually decreased over time, from 34.6% in 1990 to 28.8% in 2021. In 2021, the three most frequent GC packages at the national level were 'unspecified type of stroke' (4.28% of total deaths), 'unspecified type of diabetes' (2.44%), and 'heart failure, right or left' (2.38%). In the same year, the proportion of GCs was positively correlated with the share of deaths occurring at home (r 0.71; p <0.001), with missing data on the type of certifying physician (r 0.54, p=0.020), on place of death (r 0.77, p <0.001), and on autopsy requests (r 0.76, p <0.001).</p><p><strong>Conclusions: </strong>misreporting of causes of death arises from multiple mechanisms, reflecting errors of different nature and severity, with important implications for public health policies and health information systems. While redistribution methods are essential to produce comparable and policy-relevant estimates, improving data quality at the source remains a critical priority.</p>","PeriodicalId":50511,"journal":{"name":"Epidemiologia & Prevenzione","volume":"50 3","pages":"241-249"},"PeriodicalIF":0.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148437952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giuseppe Campagna, Annalisa Amato, Benedetta Salvucci, Fabio Majo, Gianluca Ferrari, Marco Cipolli, Benedetta Fabrizi, Armando Magrelli, Daniela Pierannunzio, Giovanni Taccetti, Antonio Guarini, Rita Padoan, Marco Salvatore
{"title":"[Italian Cystic Fibrosis Registry (ICFR). Report 2023-2024].","authors":"Giuseppe Campagna, Annalisa Amato, Benedetta Salvucci, Fabio Majo, Gianluca Ferrari, Marco Cipolli, Benedetta Fabrizi, Armando Magrelli, Daniela Pierannunzio, Giovanni Taccetti, Antonio Guarini, Rita Padoan, Marco Salvatore","doi":"10.19191/EP26.3S1.A1051.057","DOIUrl":"10.19191/EP26.3S1.A1051.057","url":null,"abstract":"<p><strong>Introduction: </strong>Italian Cystic Fibrosis Registry (ICFR) collects data of people with cystic fibrosis through the collaboration with Italian CF referral and support Centres (Italian law 548/93). It aims at analysing medium and long-term clinical and epidemiological trends, identifying healthcare needs at regional and national levels, contributing to healthcare programs and resource allocation (sharing the population of FC centres with the Ministry of Health). Finally, the RIFC shares some of its data with the Italian Medicines Agency (Agenzia Italiana del Farmaco, AIFA) to better define the number of people with cystic fibrosis with early access to specific treatments with innovative therapies. Moreover, ICFR data are shared with the European CF Patients' Registry (ECFSPs' Registry) to contribute to the estimation of the European incidence of the pathology and to bridge knowledge gaps on specific topics as well as to the adoption of common strategies for the standardized collection of data on people with cystic fibrosis.</p><p><strong>Objectives: </strong>The objective of this report is to provide updated data from ICFR for the years 2023 and 2024. It is essential to consider that the analyses and specific studies carried out refer to a limited number of variables collected in the Registry, and that the selection of the topics covered in the chapters of this report was agreed by the scientific committee of the ICFR.</p><p><strong>Study design: </strong>The analyses and results presented in this report pertain to people with cystic fibrosis currently under care Italian National Referral Centres (CRR) and Support Centres (SS) for Cystic Fibrosis and Paediatric Hospital 'Bambino Gesù' (OPBG). Data are collected using web-based software adopted by almost all participating centres, except for the centres in Verona (which also includes the data from Treviso and Rovereto) and Messina, where data collection is carried out using a different software. The submitted data are then subject to both quantitative and qualitative quality control (QC) procedures, aimed at verifying the consistency and continuity of the information previously transmitted and shared with the European CF Registry.</p><p><strong>Setting and participants: </strong>In the two-year period 2023-2024, 28 and 27 CF Centres, respectively, submitted their data to ICFR. However, the information from the two CF centres in Sardinia is still partial, since the data provided is limited to a small number of people with cystic fibrosis from 2023.</p><p><strong>Results: </strong>The results section provides a comprehensive overview of various aspects of CF epidemiology and people with cystic fibrosis characteristics. 1. Demography: in 2023 and 2024, 6,127 and 6,182 people with cystic fibrosis were, respectively, included in the ICFR (median ages of 24.1 and 24.9 years). On average, 52.2% of people with cystic fibrosis are male, and most of the population (65.3%) is older than 18 year","PeriodicalId":50511,"journal":{"name":"Epidemiologia & Prevenzione","volume":"50 3 S1","pages":"1-46"},"PeriodicalIF":0.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148347290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maria Teresa Greco, Eliana Gabellini, Luca Cavalieri d'Oro, Anna Clara Fanetti, Maria Letizia Gambino, Cinzia Gasparotti, Simona Dalle Carbonare, Marco Villa, Alberto Zucchi, Antonio Giampiero Russo
{"title":"[Multicenter experience of the Lombardy Health Protection Agencies (ATS) in the application of an algorithm to estimate disability prevalence and profiles based on routine administrative data: from data sharing to regional-level analysis].","authors":"Maria Teresa Greco, Eliana Gabellini, Luca Cavalieri d'Oro, Anna Clara Fanetti, Maria Letizia Gambino, Cinzia Gasparotti, Simona Dalle Carbonare, Marco Villa, Alberto Zucchi, Antonio Giampiero Russo","doi":"10.19191/EP26.3.A1017.058","DOIUrl":"10.19191/EP26.3.A1017.058","url":null,"abstract":"<p><strong>Objectives: </strong>to apply, at the regional level, the algorithm developed by the Health Protection Agency (ATS) of the Metropolitan City of Milan to identify people with disabilities through the integration of routinely collected health and social care databases; to produce annual prevalence estimates and describe their territorial distribution (across ATS jurisdictions and districts), as well as the main classification characteristics according to the International Classification of Functioning, Disability and Health (ICF-2018), a framework that characterizes an individual's health status through the coding of body functions and structures, activities, and participation.</p><p><strong>Design: </strong>retrospective observational study based on administrative data.</p><p><strong>Setting and participants: </strong>residents in Lombardy Region (Northern Italy), which is divided into 8 ATSs and 86 districts, during the period 2018-2024.</p><p><strong>Main outcome measures: </strong>annual period prevalence of disability; sex differences; contribution of data flows; ICF-2018 classification combinations.</p><p><strong>Results: </strong>in 2024, 1,083,538 people with disability were identified (10.8% of the regional population). Prevalence ranged across ATSs from 9.6% to 16.9%, and across districts from 6.3% to 19.8%. The largest overall contributions came from outpatient claims (28-SAN), hospital discharge records (SDO), exemption registries, and major prosthetics, with heterogeneity across ATSs. The most frequent ICF-2018 combination was \"Structures of the nervous system/Mental functions\" identified exclusively in healthcare flows.</p><p><strong>Conclusions: </strong>integrating healthcare and sociohealthcare flows within a shared ICF framework enables comparable small-area disability estimates to support integrated planning. Clinical validation and systematic monitoring of data quality are needed to strengthen the algorithm use.</p>","PeriodicalId":50511,"journal":{"name":"Epidemiologia & Prevenzione","volume":"50 3","pages":"250-260"},"PeriodicalIF":0.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148273803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Flavia Mayer, Maria Laura Fazio, Maria Cutillo, Giorgia Stendardo, Stefania Spila Alegiani, Gianluca Trifirò, Marco Massari
{"title":"[Comparing synthetic data generation methods in pharmacoepidemiology: reconciling reproducibility with privacy protection].","authors":"Flavia Mayer, Maria Laura Fazio, Maria Cutillo, Giorgia Stendardo, Stefania Spila Alegiani, Gianluca Trifirò, Marco Massari","doi":"10.19191/EP26.3.A992.059","DOIUrl":"https://doi.org/10.19191/EP26.3.A992.059","url":null,"abstract":"<p><strong>Background: </strong>the use of real-world (RW) data has become an integral part of pharmacoepidemiological research and regulatory assessment. However, access to individual-level data, especially for purposes other than the original ones (secondary use), is often restricted by legal and ethical constraints related to privacy protection. In this context, generating synthetic data, defined as artificially generated data that reproduce the statistical properties and relationships of real data without containing information traceable to real individuals, offers an innovative opportunity to balance privacy protection with the need to generate RW evidence to support regulatory decision-making.</p><p><strong>Objectives: </strong>to compare two methods of generating tabular synthetic data: synthpop, based on transparent and interpretable inferential methodologies, and Conditional Tabular-Generative Adversarial Networks (CT-GANs), which leverage deep learning approaches to reproduce complex multivariate distributions. The focus is on evaluating the ability of both approaches to preserve the statistical structure of real data and reduce the risk of disclosure/re-identification.</p><p><strong>Design: </strong>comparative study of two synthetic data generation methods.</p><p><strong>Setting and participants: </strong>a large anonymized RW dataset including 42,926 patients hospitalized for COVID-19 in Italy during the early phase of the pandemic. The dataset was obtained through record linkage of administrative databases and the COVID-19 registry using the TheShinISS tool.</p><p><strong>Main outcome measures: </strong>synthetic versions of the original dataset were generated using both synthpop and CT-GAN methods. Real and synthetic data were compared using three type of measures: 1. general utility measures (univariate, bivariate, and global), including comparison of variable distributions using plots, descriptive statistics, standardized mean differences (SMD), and Propensity Score Mean Squared Error; 2. specific utility measures, assessing the similarity of associations estimates from univariate and multivariable Cox models by evaluating the overlap of 95% confidence intervals (CI) of hazard ratios (HR), and comparison of Kaplan-Meier curves using the log-rank test; 3. disclosure (re-identification) measures, estimating the risk of identity and attribute disclosure using dedicated metrics (Unique in Original - UiO, replicated Uniques - repU, Disclosive in Original - Dorig, Disclosive in Synthetic Correct Original - DiSCO).</p><p><strong>Results: </strong>in terms of general utility, results confirmed the superiority of synthpop over CT-GAN, with more than half of the variables exceeding the acceptable SMD threshold. Moreover, synthpop showed higher specific utility than CT-GAN, with a median overlap of 95%CI of HR of 75% (interquartile range, IQR: 66%-95%) compared with 0% (IQR: 0%-6%) for CT-GAN. Concerning disclosure measures, although the or","PeriodicalId":50511,"journal":{"name":"Epidemiologia & Prevenzione","volume":"50 3","pages":"279-289"},"PeriodicalIF":0.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148438822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Humanitarian System at a Crossroads: Change or become irrelevant? The Report of the Johns Hopkins Center for Humanitarian Health - Lancet on Health, Conflicts, and Forced Displacement.","authors":"Sandro Colombo","doi":"10.19191/EP26.3.A1073.065","DOIUrl":"10.19191/EP26.3.A1073.065","url":null,"abstract":"<p><p>Humanitarian action in the health sector has played a crucial role in mitigating the impact of crises - conflicts, famines, and natural disasters - on morbidity and mortality, while also highlighting structural and operational limitations. This contribution reviews the evolution of humanitarian system reforms, from the initiatives following the failures observed in Rwanda, Darfur, Haiti, and Pakistan to the more recent strategies for renewal. Particular attention is given to the report of the Johns Hopkins-Lancet Commission on Health, Conflicts, and Forced Displacement (2026), which proposes a profound transformation of humanitarian architecture and governance, centred on strengthening the role of affected communities, increasing emphasis on accountability and monitoring of humanitarian law violations, achieving more equitable funding, and ensuring effective safeguarding of the right to health.The current convergence of protracted conflicts, attacks against civilians, personnel, and health infrastructures, forced displacements, and drastic reductions in funding has brought the humanitarian system to the brink of collapse. In this context, marked by increasing humanitarian needs, the Commission's recommendations, while not new, provide a platform to promote a structural change in the humanitarian system, oriented towards greater equity and the transfer of resources and decision-making responsibilities to the local level.</p>","PeriodicalId":50511,"journal":{"name":"Epidemiologia & Prevenzione","volume":"50 3","pages":"307-310"},"PeriodicalIF":0.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148438253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"[PSA screening: reflections from a layman].","authors":"Marco Geddes da Filicaia","doi":"10.19191/EP26.3.A1061.066","DOIUrl":"https://doi.org/10.19191/EP26.3.A1061.066","url":null,"abstract":"","PeriodicalId":50511,"journal":{"name":"Epidemiologia & Prevenzione","volume":"50 3","pages":"214-216"},"PeriodicalIF":0.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148438804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giulia Maddaleni, Elisa Betti, Erika Del Prete, Giuseppe Diegoli, Priscilla Sassoli de Bianchi, Debora Canuti, Francesca Sanseverino, Patrizia Falini, Francesca Battisti, Paola Mantellini
{"title":"The lived experience of cancer screening healthcare workers during the COVID-19 pandemic: an Italian multiregional survey.","authors":"Giulia Maddaleni, Elisa Betti, Erika Del Prete, Giuseppe Diegoli, Priscilla Sassoli de Bianchi, Debora Canuti, Francesca Sanseverino, Patrizia Falini, Francesca Battisti, Paola Mantellini","doi":"10.19191/EP26.3.A978.056","DOIUrl":"10.19191/EP26.3.A978.056","url":null,"abstract":"<p><strong>Objectives: </strong>to explore the experiences and training needs of healthcare workers involved in cancer screening programmes in Italy during the COVID-19 pandemic.</p><p><strong>Design: </strong>an anonymous questionnaire was developed by the Institute for Cancer Research, Prevention, and Clinical Network (ISPRO) of Florence (Italy), distributed using Google Forms between May and June 2023. Responses were collected using 5-point Likert scales, multiple-choice questions, and open-ended prompts. Descriptive analyses were performed using Stata/SE version 16.1 for quantitative data; thematic analysis was applied to open-ended questions.</p><p><strong>Setting and participants: </strong>the Italian Ministry of Health's CCM 2021 multiregional programme aimed to develop a training programme for cancer screening professionals to address COVID-19-related issues and maintain a high level of preparedness. This exploratory survey guided the design of the training programme which targeted cancer screening workers in 3 Regions: Toscana, Emilia-Romagna, and Basilicata.</p><p><strong>Main outcome measures: </strong>the questionnaire comprised 36 items in 3 sections: experiences during the pandemic, organizational support, and sociodemographic characteristics.</p><p><strong>Results: </strong>the responses were 317. Participants were predominantly female (82.3%), mostly from Emilia-Romagna (65.0%) and Toscana (33.1%). The most frequently reported negative consequence concerned psychological well-being (63.1%), yet only 3.5% of the participants received psychological counselling, and nearly half (49.8%) reported no organizational support. However, teamwork and collaboration among colleagues were generally high (87.1%); 65.9% reported developing new competencies. Many opposed suspending first-level screening in future emergencies (46.1%) and strongly supported reaffirming screening importance within healthcare (89.3%) and society (92.8%). A structured pandemic plan was considered the most valuable measure (63.1%).</p><p><strong>Conclusions: </strong>enhancing cancer screening programme resilience requires a systems-level approach integrating psychological support and proactive governance. Future policies should use these insights to safeguard users and professionals.</p>","PeriodicalId":50511,"journal":{"name":"Epidemiologia & Prevenzione","volume":"50 3","pages":"270-278"},"PeriodicalIF":0.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148438606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}