Corrigendum: Time-Trends in Air Pollution Impact on Health in Italy, 1990-2019: An Analysis from the Global Burden of Disease Study 2019.

[This corrects the article DOI: 10.3389/ijph.2023.1605959.].

Injury Patterns and Gender in Italy.

Introduction: Globally, injuries pose significant public health challenges, with road traffic accidents in particular being responsible for considerable morbidity, mortality, and economic distress. Italy has been significantly impacted due to its high population density and frequency of road traffic and domestic incidents. Method: This study set out to investigate the incidence of self-reported road traffic and home and leisure accidents in the Italian general population. A particular emphasis was placed on exploring possible gender differences across varying age groups. The data was obtained from the European Health Interview Survey and a representative sample of the Italian population was analyzed. Results: The analysis revealed that regardless of age, women experienced a reduced risk of road traffic accidents compared to men. However, gender disparities in home-leisure accidents were observed to be age-dependent. Women under the age of 25 exhibited a lower likelihood of home-leisure accidents and serious accidents necessitating hospital admission in comparison to their male counterparts. In contrast, women aged 65 and above had an increased likelihood of home-leisure accidents as opposed to men in the same age category. Conclusions: The findings of this study highlight the importance of considering age and gender as significant factors in the occurrence of different types of accidents, offering insight into how injury rates vary between these demographic groups within Italy.

Analyzing the 20-year declining trend of hospital length-of-stay in European countries with different healthcare systems and reimbursement models.

The study aims to investigate the last 20-year (2000-2019) of hospital length of stay (LOS) trends and their association with different healthcare systems (HS) among 25 European countries. A panel dataset was created using secondary data from Eurostat and Global Burden of Disease study databases, with dependent and control variables aggregated at the national level over a period of 20 years. A time trend analysis was conducted using a weighted least squares model for panel data to investigate the association between LOS, HS models [National Health Service (NHS), National Health Insurance, Social Health Insurance (SHI), and Etatist Social Health Insurance], healthcare reimbursement schemes [Prospective Global Budget (PGB), Diagnosis Related Groups (DRG), and Procedure Service Payment (PSP)], and control variables. The study showed a reduction of average LOS from 9.20 days in 2000 to 7.24 in 2019. SHI was associated with a lower LOS compared to NHS (b = - 0.6327, p < 0.05). Both DRG (b = 1.2399, p < 0.05) and PSP (b = 1.1677, p < 0.05) reimbursement models were positively associated with LOS compared to PGB. Our results confirmed the downward trend of LOS in the last 20 years, its multifactorial nature, and the influence of the SHI model of HS. This could be due to the financial incentives present in fee-for-service payment models and the role of competition in creating a market for healthcare services. These results offer insight into the factors influencing healthcare utilization and can inform the design of more effective, efficient, and sustainable HS.

Stime dell'antibiotico-resistenza in Italia e in Europa occidentale nel 2019: un'analisi comparativa basata su MICROBE.

BACKGROUND: antimicrobial resistance (AMR) will cause 10 million deaths per year worldwide by 2050, with economic costs of up to 100 trillion dollars. Antibiotic resistance (ABR) constitutes the majority of this health threat. Globally, 1.27 million people died in 2019 as a direct result of ABR. One in 5 deaths occurred in children under five, and 6 bacterial pathogens accounted for more than 70% of ABR-associated deaths. OBJECTIVES: to compare ABR estimates in terms of death and disability-adjusted life-years (DALYs) in 2019 in Italy and in Western Europe (WE) by grading the infectious syndromes and the bacterial pathogens involved, with the aim to identify the most urgent healthcare needs in Italy. DESIGN: the estimates of the burden of ABR in 2019 in WE and Italy, extracted from the Measuring Infectious Causes and Resistance Outcomes for Burden Estimation (MICROBE) tool by the Institute for Health Metrics and Evaluation (IHME; Seattle, USA), reported deaths and DALYs associated with 33 bacterial pathogens across 12 infectious syndromes, as well as deaths and DALYs associated with and attributable to ABR for 23 bacteria and 86 pathogen-drug combinations. The comparison between WE and Italy was performed in steps. First, among the 12 groups of infectious syndromes from the Global Burden of Diseases (GBD) study 2019, the most impacting in terms of deaths and DALYs were ranked based on the magnitude of rates, and the corresponding ABR-associated burden was reported. Then, the burden of the leading pathogens (bacteria, viruses, fungi, and polymicrobial infections) for all infectious syndromes was compared between the two areas. Death and DALY rates associated with ABR were reported for each bacterium, together with the percentage of ABR-attributable burden. Although it is known that Italy is one of the WE countries with the largest share of elderly, crude rates were reported instead of age-standardized rates, in order to quantify the actual burden of ABR in the two areas. SETTING AND PARTICIPANTS: Italy and Western Europe. MAIN OUTCOMES MEASURES: death and DALYs rates per 100,000 inhabitants. RESULTS: the largest difference between ABR-associated death rates in the two areas was found for bloodstream infections (25.2 and 18.8 per 100,000 in Italy and WE, respectively), followed by peritoneal and abdominal infections (15.1 and 12.2 in Italy and WE, respectively). However, the percentages of deaths and DALYs attributable to ABR were always higher in Italy for all the infections considered. Regarding pathogens, Escherichia coli accounted for the greatest burden associated to ABR, in terms of both deaths and DALYs, in both areas. The highest ABR-attributable percentage of deaths was found for Acinetobacter baumannii (28.4% in WE and 31.9% in Italy), accounting also for the highest percentage of ABR-attributable DALYs (28.4% in WE and 31.7% in Italy). The pathogen-drug combination with the highest burden associated with AMR was Escherichia coli-Aminopenicillin, while the greatest AMR-attributable burden was found for Staphylococcus aureus-Methicillin (MRSA). On average, 55.4% of Escherichia coli was resistant to Aminopenicillin in WE, with Italy ranking third (67.6%). Nordic countries showed smaller values, with Sweden in last place (32.8%). The average percentage of MRSA in WE was 16%, with Italy exceeding it by more than 13 pointsConclusions: despite similar sepsis mortality rates in Italy and other WE countries, the proportion of ABR-associated and attributable deaths was higher in Italy. Targeted strategies aimed at reducing the circulation of bacteria and resistant microorganisms together with other interventions could lead to an overall reduction in deaths associated with ABR.

Factors Influencing the Healthcare Workers' Willingness to Receive the COVID-19 Booster Dose in Tuscany (Italy).

BACKGROUND: The World Health Organization has defined vaccine hesitancy as behavior influenced by several factors, including trust in the vaccine itself or its provider or the perceived need for vaccination. The aim of this study was to investigate the factors influencing the willingness to receive the COVID-19 vaccine among the employees and healthcare professionals of the Central Tuscany Local Health Authority (CT-LHA) in Italy. METHODS: From July to October 2022, a cross-sectional study was conducted. An online questionnaire was administered to 7000 employees of the CT-LHA. The questionnaire analyzed the factors that influenced receiving the booster dose of the COVID-19 vaccine. The sample was stratified by gender, age, type of occupation (healthcare or non-healthcare workers), and seniority. Incomplete questionnaires were excluded. A chi-squared test was performed through STATA. The significance level was set at 95%. RESULTS: Of the questionnaires administered, 1885 (26.9%) questionnaires were eligible for the study. In the previous vaccination campaign, the healthcare workers (HCWs) considered the vaccine used by CT-LHA as safe, in contrast to non-healthcare workers (N-HCWs), who considered it less secure (p < 0.05). The HCWs showed a higher propensity for vaccine safety to receive the booster dose than N-HCWs. N-HCWs appeared to be less affected by an updated booster dose than HCWs (p < 0.05). CONCLUSIONS: The factors studied appear to influence HCWs differently from N-HCWs. Both HCWs and N-HCWs would choose an upgraded mRNA vaccine for the booster dose.

Regional and sex inequalities of avoidable mortality in Italy: A time trend analysis.

Objectives: This study provides a comprehensive analysis of avoidable mortality (AM), treatable mortality (TM), and preventable mortality (PM) across Italy, focusing on region- and gender-specific inequalities over a 14-year period. Study design: Time-trend analysis (2006-2019). Methods: The study was conducted using mortality data from the Italian Institute of Statistics to evaluate the extent and patterns of AM, TM, and PM in Italy. Biennial age-standardized mortality rates were calculated by gender and region using the joint OECD/Eurostat list. Results: The overall AM rates showed a large reduction from 2006/7 (221.0 per 100,000) to 2018/9 (166.4 per 100,000). Notably, females consistently displayed lower AM rates than males. Furthermore, both gender differences and the North-South gap of AM decreased during the period studied. The regions with the highest AM rates fluctuated throughout the study period. The highest percentage decrease in AM from 2006/7 to 2018/9, for both males (-41.3 %) and females (-34.2 %), was registered in the autonomous province of Trento, while the lowest reduction was observed in Molise for males (-17.4 %) and in Marche for females (-10.0 %). Conclusions: Remarkable gender and regional differences in AM between 2006 and 2019 have been recorded in Italy, although they have decreased over years. Continuous monitoring of AM and the implementation of region- and gender-specific interventions is essential to provide valuable insights for both policy and public health practice. This study contributes to the efforts to improve health equity between Italian regions.

Time-Trends in Air Pollution Impact on Health in Italy, 1990-2019: An Analysis From the Global Burden of Disease Study 2019.

Objectives: We explored temporal variations in disease burden of ambient particulate matter 2.5 µm or less in diameter (PM2.5) and ozone in Italy using estimates from the Global Burden of Disease Study 2019. Methods: We compared temporal changes and percent variations (95% Uncertainty Intervals [95% UI]) in rates of disability adjusted life years (DALYs), years of life lost, years lived with disability and mortality from 1990 to 2019, and variations in pollutant-attributable burden with those in the overall burden of each PM2.5- and ozone-related disease. Results: In 2019, 467,000 DALYs (95% UI: 371,000, 570,000) were attributable to PM2.5 and 39,600 (95% UI: 18,300, 61,500) to ozone. The crude DALY rate attributable to PM2.5 decreased by 47.9% (95% UI: 10.3, 65.4) from 1990 to 2019. For ozone, it declined by 37.0% (95% UI: 28.9, 44.5) during 1990-2010, but it increased by 44.8% (95% UI: 35.5, 56.3) during 2010-2019. Age-standardized rates declined more than crude ones. Conclusion: In Italy, the burden of ambient PM2.5 (but not of ozone) significantly decreased, even in concurrence with population ageing. Results suggest a positive impact of air quality regulations, fostering further regulatory efforts.

Identifying patient subgroups with different trends of patient-reported outcomes (PROMs) after elective knee arthroplasty.

BACKGROUND: Patient-reported outcome measures (PROMs) are increasingly being used to assess the effectiveness of elective total knee arthroplasty (TKA). However, little is known about how PROMs scores change over time in these patients. The aim of this study was to identify the trajectories of quality of life and joint functioning, and their associated demographic and clinical features in patients undergoing elective TKA. METHODS: A prospective, cohort study was conducted, in which PROMs questionnaires (Euro Quality 5 Dimensions 3L, EQ-5D-3L, and Knee injury and Osteoarthritis Outcome Score Patient Satisfaction, KOOS-PS) were administered to patients at a single center undergoing elective TKA before surgery, and at 6 and 12 months after surgery. Latent class growth mixture models were used to analyze the patterns of change in PROMs scores over time. Multinomial logistic regression was used to investigate the association between patient characteristics and PROMs trajectories. RESULTS: A total of 564 patients were included in the study. The analysis highlighted differential patterns of improvement after TKA. Three distinct PROMs trajectories were identified for each PROMs questionnaire, with one trajectory indicating the most favorable outcome. Female gender appears to be associated with a presentation to surgery with worse perceived quality of life and joint function than males, but also more rapid improvement after surgery. Having an ASA score greater than 3 is instead associated with a worse functional recovery after TKA. CONCLUSION: The results suggest three main PROMs trajectories in patients undergoing elective TKA. Most patients reported improved quality of life and joint functioning at 6 months, which then stabilized. However, other subgroups showed more varied trajectories. Further research is needed to confirm these findings and to explore the potential clinical implications of these results.

A step-by-step researcher's guide to the use of an AI-based transformer in epidemiology: an exploratory analysis of ChatGPT using the STROBE checklist for observational studies.

Objective: This study aims at investigating how AI-based transformers can support researchers in designing and conducting an epidemiological study. To accomplish this, we used ChatGPT to reformulate the STROBE recommendations into a list of questions to be answered by the transformer itself. We then qualitatively evaluated the coherence and relevance of the transformer's outputs. Study design: Descriptive study. Methods: We first chose a study to be used as a basis for the simulation. We then used ChatGPT to transform each STROBE checklist's item into specific prompts. Each answer to the respective prompt was evaluated by independent researchers in terms of coherence and relevance. Results: The mean scores assigned to each prompt were heterogeneous. On average, for the coherence domain, the overall mean score was 3.6 out of 5.0, and for relevance it was 3.3 out of 5.0. The lowest scores were assigned to items belonging to the Methods section of the checklist. Conclusions: ChatGPT can be considered as a valuable support for researchers in conducting an epidemiological study, following internationally recognized guidelines and standards. It is crucial for the users to have knowledge on the subject and a critical mindset when evaluating the outputs. The potential benefits of AI in scientific research and publishing are undeniable, but it is crucial to address the risks, and the ethical and legal consequences associated with its use.

Changes in private health service utilisation and access to the Italian National Health Service between 2006 and 2019: a cross-sectional comparative study.

OBJECTIVES: Previous research highlighted that in the early 2000s a significant share of the Italian population used and paid out of pocket for private healthcare services even when they could potentially have received the same treatments from the National Health Service (NHS). The decrease in public investments in healthcare and the increase in health needs due to the population ageing may have modified the use of private health services and equity of access to the Italian NHS. This study aims to investigate the change in the prevalence of individuals who have fully paid out of pocket for accessing healthcare services in Italy between 2006 and 2019 and the main reasons behind this choice. DESIGN: Cross-sectional comparative study. PARTICIPANTS AND COMPARISON: Two representative samples of the Italian population were collected in 2006 and 2019. OUTCOME MEASURES: Prevalence of access to fully paid out-of-pocket private health services; type of service of the last fully paid out-of-pocket access; main reasons for the last fully paid out-of-pocket access. RESULTS: We found an increase in the prevalence of people who declared having fully paid out of pocket at least one access to health services during their lifetime from 79.0% in 2006 to 91.9% in 2019 (adjusted OR 2.66; 95% CI 1.98 to 3.58). 'To avoid waiting times' was the main reason and it was significantly more frequent in 2019 compared with 2006 (adjusted OR 1.75; 95% CI 1.45 to 2.11). CONCLUSIONS: This comparative study, conducted the year before the outbreak of the COVID-19 pandemic, highlighted an increase in the prevalence of Italian residents who have fully paid out of pocket for access to health services to overcome long waiting times. Our findings may indicate a reduced access and possible worsening of the equity of access to the public and universalistic Italian NHS between 2006 and 2019.

Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review.

OBJECTIVES: In this systematic review we aimed at assessing how artificial intelligence (AI), including machine learning (ML) techniques have been deployed to predict, diagnose, and treat chronic kidney disease (CKD). We systematically reviewed the available evidence on these innovative techniques to improve CKD diagnosis and patient management. METHODS: We included English language studies retrieved from PubMed. The review is therefore to be classified as a "rapid review", since it includes one database only, and has language restrictions; the novelty and importance of the issue make missing relevant papers unlikely. We extracted 16 variables, including: main aim, studied population, data source, sample size, problem type (regression, classification), predictors used, and performance metrics. We followed the Preferred Reporting Items for Systematic Reviews (PRISMA) approach; all main steps were done in duplicate. RESULTS: From a total of 648 studies initially retrieved, 68 articles met the inclusion criteria. Models, as reported by authors, performed well, but the reported metrics were not homogeneous across articles and therefore direct comparison was not feasible. The most common aim was prediction of prognosis, followed by diagnosis of CKD. Algorithm generalizability, and testing on diverse populations was rarely taken into account. Furthermore, the clinical evaluation and validation of the models/algorithms was perused; only a fraction of the included studies, 6 out of 68, were performed in a clinical context. CONCLUSIONS: Machine learning is a promising tool for the prediction of risk, diagnosis, and therapy management for CKD patients. Nonetheless, future work is needed to address the interpretability, generalizability, and fairness of the models to ensure the safe application of such technologies in routine clinical practice.

Trust in science, medicine and medical providers and its relations to vaccine beliefs: A latent class analysis.

AIM: People may differ in their vaccine-related beliefs (i.e. efficacy, safety, purpose), with a host of factors influencing these differences. This can produce homogeneous groups of individuals who share certain beliefs, attitudes and opinions not only towards vaccines but science and medicine in general. This study aims to characterise distinct subgroups and identify ideal targets for tailored public health interventions to reinforce favourable vaccine beliefs. METHODS: Latent class analysis was used to derive unique profiles using the 2019 Gallup survey of 140 countries. We modelled a composite of vaccine beliefs and regressed this on class membership and relevant covariates. RESULTS: Patterns of item endorsement indicated a well-fitting five-class model, with classes distinguished based on whether individuals sought personal knowledge about science, medicine and health; trusted science and scientists; and reported confidence in the health care system. The lowest levels of vaccine beliefs were reported by a class lacking trust and confidence and the highest levels were reported by a class endorsing trust, confidence and desiring medical and scientific knowledge. Country-level income was moderately related to class membership, and vaccine beliefs were higher in lower-income countries. CONCLUSIONS: Findings suggest that public health campaigns can focus on improving trust in science and medical providers. Efforts to improve vaccination rates can only be achieved when individuals trust science, view the work of scientists as beneficial and hold favourable views towards health care providers. Individuals will then accrue the necessary wisdom to make good health care decisions that affect not only themselves but also their fellow citizens.

Biased, wrong and counterfeited evidences published during the COVID-19 pandemic, a systematic review of retracted COVID-19 papers.

In 2020 COVID-19 led to an unprecedented stream of papers being submitted to journals. Scientists and physicians all around the globe were in need for information about this new disease. In this climate, many articles were accepted after extremely fast peer-reviews to provide the scientific community with the latest discoveries and knowledge. Unfortunately, this also led to articles retraction due to authors' misconduct or errors in methodology and/or conclusions. The aim of this study is to investigate the number and characteristics of retracted papers, and to explore the main causes that led to retraction. We conducted a systematic review on retracted articles, using PubMed as data source. Our inclusion criteria were the following: English-language retracted articles that reported original data, results, opinions or hypotheses on COVID-19 and Sars-CoV-2. Twenty-seven retracted articles were identified, mainly reporting observational studies and opinion pieces. Many articles published during the first year of the pandemic have been retracted, mainly due to the authors' scientific misconduct. Duplications, plagiarism, frauds and absence of consent, were the main reasons for retractions. In modern medicine, researchers are required to publish frequently, and, especially during situations like the COVID-19 pandemic, when articles were rapidly published, gaps in peer-reviews system and in the path to scientific publication arose.

The impact of the SARS-CoV-2 pandemic on cause-specific mortality patterns: a systematic literature review.

Background: Understanding the effects of the COVID-19 pandemic on cause-specific mortality should be a priority, as this metric allows for a detailed analysis of the true burden of the pandemic. The aim of this systematic literature review is to estimate the impact of the pandemic on different causes of death, providing a quantitative and qualitative analysis of the phenomenon. Methods: We searched MEDLINE, Scopus, and ProQuest for studies that reported cause-specific mortality during the COVID-19 pandemic, extracting relevant data. Results: A total of 2413 articles were retrieved, and after screening 22 were selected for data extraction. Cause-specific mortality results were reported using different units of measurement. The most frequently analyzed cause of death was cardiovascular diseases (n = 16), followed by cancer (n = 14) and diabetes (n = 11). We reported heterogeneous patterns of cause-specific mortality, except for suicide and road accident. Conclusions: Evidence on non-COVID-19 cause-specific deaths is not exhaustive. Reliable scientific evidence is needed by policymakers to make the best decisions in an unprecedented and extremely uncertain historical period. We advocate for the urgent need to find an international consensus to define reliable methodological approaches to establish the true burden of the COVID-19 pandemic on non-COVID-19 mortality. Supplementary Information: The online version contains supplementary material available at 10.1007/s10389-022-01755-7.

Patient reported outcomes measures (PROMs) trajectories after elective hip arthroplasty: a latent class and growth mixture analysis.

BACKGROUND: Patient-reported outcome measures (PROMs) are an extensively used tool to assess and improve the quality of healthcare services. PROMs can be related to individual demographic and clinical characteristics in patients undergoing hip arthroplasty (HA). The aim of this study is to identify distinct subgroups of patients with unique trajectories of PROMS scores and to determine patients' features associated with these subgroups. METHODS: We conducted a prospective, cohort study in which PROMs questionnaires (Euro Quality 5 Dimensions 3L, EQ-5D-3L, Euro-Quality-Visual-Analytic-Score, EQ-VAS, Hip disability and Osteoarthritis Outcome Score, HOOS-PS) were administered to patients undergoing elective HA pre-operatively, and at 6 and 12 months after surgery. For each measure, latent class growth analysis and growth mixture models were used to identify subgroups of patients with distinct trajectories of scores. Demografic and clinical predictors of the latent classes in growth mixture model were identified using a 3-step approach. RESULTS: We found three distinct trajectories for each PROM score. These trajectories indicated a response heterogeneity to the HA among the patients (n = 991). Patient's gender, ASA score, and obesity were significantly associated with different PROMs trajectories. CONCLUSIONS: We identified three distinct trajectories for each of the three PROMs indicators. Several demographic and clinical characteristics are associated with the different trajectories of PROMs at 6 and 12 months after HA and could be used to identify groups of patients with different outcomes following HA surgery. These findings underline the importance of patient-centered care, supporting the usefulness of integrating PROMs data alongside routinely collected healthcare records for guiding clinical care and maximizing patients' positive outcomes. TRIAL REGISTRATION: Protocol version (1.0) and trial registration data are available on the platform www. CLINICALTRIAL: gov with the identifier NCT03790267, posted on December 31, 2018.

Tackling diabetes as a team: co-designing healthcare interventions to engage couples living with type 1 diabetes.

AIMS: Couples living with Type 1 diabetes: co-designing interventions to support them. METHODS: This is a qualitative study comprising two phases. Phase I represents the exploratory phase, consisting of semi-structured interviews with persons with Type 1 diabetes (N = 16) and partners (N = 6). In the second phase, co-design principles guided workshops with healthcare professionals, persons with Type 1 diabetes, and partners (N = 7) to facilitate discussion of the key themes identified and solutions to engage couples living with Type 1 diabetes in diabetes care. RESULT: The key themes identified from phase I as priorities to target in future interventions were: (i) Emotional impact of diabetes and (ii) Partners' involvement. Priority (i) captures the impact the emotional burden of diabetes management produces within couples' relationship. Priority (ii) captures the request from partners to be more involved in diabetes management. Characteristics of the interventions suggested during the co-design phase II focused on engaging patients and partners via a counseling point in healthcare settings and tailored help for couples' psychological support needs. CONCLUSIONS: Couples value pro-active intervention and support from their diabetes team or primary care for both the partners to live well with Type 1 diabetes.

Variations of the quality of care during the COVID-19 pandemic affected the mortality rate of non-COVID-19 patients with hip fracture.

INTRODUCTION: As COVID-19 roared through the world, governments worldwide enforced containment measures that affected various treatment pathways, including those for hip fractures (HFs). This study aimed to measure process and outcome indicators related to the quality of care provided to non-COVID-19 elderly patients affected by HF in Emilia-Romagna, a region of Italy severely hit by the pandemic. METHODS: We collected the hospital discharge records of all patients admitted to the hospitals of Emilia-Romagna with a diagnosis of HF from January to May in the years 2019 (pre-pandemic period) and 2020 (pandemic period). We analyzed surgery rate, surgery delays, length of hospital stay, timely rehabilitation, and 30-day mortality for each HF patient. We evaluated monthly data (2020 vs. 2019) with the chi-square and t-test, where appropriate. Logistic regression was used to investigate the differences in 30-day mortality. RESULTS: Our study included 5379 patients with HF. In April and May 2020, there was a significant increase in the proportion of HF patients that did not undergo timely surgery. In March 2020, we found a significant increase in mortality (OR = 2.22). Male sex (OR = 1.92), age ≥90 years (OR = 4.33), surgery after 48 hours (OR = 3.08) and not receiving surgery (OR = 6.19) were significantly associated with increased mortality. After adjusting for the aforementioned factors, patients hospitalized in March 2020 still suffered higher mortality (OR = 2.21). CONCLUSIONS: There was a reduction in the overall quality of care provided to non-COVID-19 elderly patients affected by HF, whose mortality increased in March 2020. Patients' characteristics and variations in processes of care partially explained this increase. Policymakers and professionals involved in the management of COVID-19 patients should be aware of the needs of patients with other health needs, which should be carefully investigated and included in future emergency preparedness and response plans.

The impact of health policies and vaccine rollout on the COVID-19 pandemic waves in Italy.

Background: Over the course of the COVID-19 pandemic in Italy, different response measures were taken to contain the spread of the virus. These include a variety of non-pharmaceutical interventions and a mass vaccination campaign. While not definitive, epidemiological measures provide some indication of the impact of such measures on the dynamics of the pandemic and lessons to better prepare for future emergencies. Objective: To describe the impact of vaccine rollout and health policies on the evolution of the COVID-19 pandemic in Italy from March 2020 to October 2021 using a set of epidemiological indicators. Methods: We performed a time-trend analysis of new confirmed COVID-19 cases, patients in hospital, and deaths. Using line charts, we informally assessed the relationship of these indicators with the immunization campaign and other health policies. Daily aggregate data were gathered from GitHub repositories of certified data from Italy's Government and Civil Protection. Results: The immunization coverage increased starting in March 2021, with a parallel decrease in COVID-19 infections, hospitalizations, and deaths. Despite different implementation approaches, the vaccine coverage growth rate had a similar pattern across regions. A comprehensive approach including measures such as requiring face masks and a "Green Pass" to enter indoor places also helped contain the pandemic. Conclusions: The vaccine rollout had a major effect on COVID-19 in Italy, especially on hospitalizations and deaths. Before the vaccine was available, however, other non-pharmaceutical interventions also helped to contain the spread of the virus and mitigate its effect on the population.