[Integrated Surveillance in Italy: outputs and related activities]. / La sorveglianza integrata COVID-19 in Italia: output e attività correlate.

OBJECTIVES: to describe the integrated surveillance system of COVID-19 in Italy, to illustrate the outputs used to return epidemiological information on the spread of the epidemic to the competent public health bodies and to the Italian population, and to describe how the surveillance data contributes to the ongoing weekly regional monitoring and risk assessment system. METHODS: the COVID-19 integrated surveillance system is the result of a close and continuous collaboration between the Italian National Institute of Health (ISS), the Italian Ministry of Health, and the regional and local health authorities. Through a web platform, it collects individual data of laboratory confirmed cases of SARS-CoV-2 infection and gathers information on their residence, laboratory diagnosis, hospitalisation, clinical status, risk factors, and outcome. Results, for different levels of aggregation and risk categories, are published daily and weekly on the ISS website, and made available to national and regional public health authorities; these results contribute one of the information sources of the regional monitoring and risk assessment system. RESULTS: the COVID-19 integrated surveillance system monitors the space-time distribution of cases and their characteristics. Indicators used in the weekly regional monitoring and risk assessment system include process indicators on completeness and results indicators on weekly trends of newly diagnosed cases per Region. CONCLUSIONS: the outputs of the integrated surveillance system for COVID-19 provide timely information to health authorities and to the general population on the evolution of the epidemic in Italy. They also contribute to the continuous re-assessment of risk related to transmission and impact of the epidemic thus contributing to the management of COVID-19 in Italy.

Decline in reported measles cases in Italy in the COVID-19 era, January 2020 - July 2022: The need to prevent a resurgence upon lifting non-pharmaceutical pandemic measures.

From January 2020 to July 2022, 120 measles cases were reported to the Italian national surveillance system, of which 105 had symptom onset in 2020, nine in 2021 and six in the first seven months of 2022. This represents a sharp decline compared to the time period immediately preceding the COVID-19 pandemic, most likely due to the non-pharmaceutical interventions implemented to prevent SARS-CoV2 transmission. Of 105 cases reported in 2020, 103 acquired the infection before a national lockdown was instituted on 9 March 2020. Overall, one quarter of cases reported at least one complication. As non-pharmaceutical pandemic measures are being eased worldwide, and considering measles seasonality, infectiousness, and its potential severity, it is important that countries ensure high vaccination coverage and close immunity gaps, to avoid risk of future outbreaks.

Understanding the vaccine stance of Italian tweets and addressing language changes through the COVID-19 pandemic: Development and validation of a machine learning model.

Social media is increasingly being used to express opinions and attitudes toward vaccines. The vaccine stance of social media posts can be classified in almost real-time using machine learning. We describe the use of a Transformer-based machine learning model for analyzing vaccine stance of Italian tweets, and demonstrate the need to address changes over time in vaccine-related language, through periodic model retraining. Vaccine-related tweets were collected through a platform developed for the European Joint Action on Vaccination. Two datasets were collected, the first between November 2019 and June 2020, the second from April to September 2021. The tweets were manually categorized by three independent annotators. After cleaning, the total dataset consisted of 1,736 tweets with 3 categories (promotional, neutral, and discouraging). The manually classified tweets were used to train and test various machine learning models. The model that classified the data most similarly to humans was XLM-Roberta-large, a multilingual version of the Transformer-based model RoBERTa. The model hyper-parameters were tuned and then the model ran five times. The fine-tuned model with the best F-score over the validation dataset was selected. Running the selected fine-tuned model on just the first test dataset resulted in an accuracy of 72.8% (F-score 0.713). Using this model on the second test dataset resulted in a 10% drop in accuracy to 62.1% (F-score 0.617), indicating that the model recognized a difference in language between the datasets. On the combined test datasets the accuracy was 70.1% (F-score 0.689). Retraining the model using data from the first and second datasets increased the accuracy over the second test dataset to 71.3% (F-score 0.713), a 9% improvement from when using just the first dataset for training. The accuracy over the first test dataset remained the same at 72.8% (F-score 0.721). The accuracy over the combined test datasets was then 72.4% (F-score 0.720), a 2% improvement. Through fine-tuning a machine-learning model on task-specific data, the accuracy achieved in categorizing tweets was close to that expected by a single human annotator. Regular training of machine-learning models with recent data is advisable to maximize accuracy.

How the Italian Twitter Conversation on Vaccines Changed During the First Phase of the Pandemic: A Mixed-Method Analysis.

In the context of the European Joint Action on Vaccination, we analyzed, through quantitative and qualitative methods, a random sample of vaccine-related tweets published in Italy between November 2019 and June 2020, with the aim of understanding how the Twitter conversation on vaccines changed during the first phase of the pandemic, compared to the pre-pandemic months. Tweets were analyzed by a multidisciplinary team in terms of kind of vaccine, vaccine stance, tone of voice, population target, mentioned source of information. Multiple correspondence analysis was used to identify variables associated with vaccine stance. We analyzed 2,473 tweets. 58.2% mentioned the COVID-19 vaccine. Most had a discouraging stance (38.1%), followed by promotional (32.5%), neutral (22%) and ambiguous (2.5%). The discouraging stance was the most represented before the pandemic (69.6%). In February and March 2020, discouraging tweets decreased intensely and promotional and neutral tweets dominated the conversation. Between April and June 2020, promotional tweets remained more represented (36.5%), followed by discouraging (30%) and neutral (24.3%). The tweets' tone of voice was mainly polemical/complaining, both for promotional and for discouraging tweets. The multiple correspondence analysis identified a definite profile for discouraging and neutral tweets, compared to promotional and ambiguous tweets. In conclusion, the emergence of SARS-CoV-2 caused a deep change in the vaccination discourse on Twitter in Italy, with an increase of promotional and ambiguous tweets. Systematic monitoring of Twitter and other social media, ideally combined with traditional surveys, would enable us to better understand Italian vaccine hesitancy and plan tailored, data-based communication strategies.

Effectiveness of an mRNA vaccine booster dose against SARS-CoV-2 infection and severe COVID-19 in persons aged ≥60 years and other high-risk groups during predominant circulation of the delta variant in Italy, 19 July to 12 December 2021.

BACKGROUND: Consolidated information on the effectiveness of COVID-19 booster vaccination in Europe are scarce. RESEARCH DESIGN AND METHODS: We assessed the effectiveness of a booster dose of an mRNA vaccine against any SARS-CoV-2 infection (symptomatic or asymptomatic) and severe COVID-19 (hospitalization or death) after over two months from administration among priority target groups (n = 18,524,568) during predominant circulation of the Delta variant in Italy (July-December 2021). RESULTS: Vaccine effectiveness (VE) against SARS-CoV-2 infection and, to a lesser extent, against severe COVID-19, among people ≥60 years and other high-risk groups (i.e. healthcare workers, residents in long-term-care facilities, and persons with comorbidities or immunocompromised), peaked in the time-interval 3-13 weeks (VE against infection = 67.2%, 95% confidence interval (CI): 62.5-71.3; VE against severe disease = 89.5%, 95% CI: 86.1-92.0) and then declined, waning 26 weeks after full primary vaccination (VE against infection = 12.2%, 95% CI: -4.7-26.4; VE against severe disease = 65.3%, 95% CI: 50.3-75.8). After 3-10 weeks from the administration of a booster dose, VE against infection and severe disease increased to 76.1% (95% CI: 70.4-80.7) and 93.0% (95% CI: 90.2-95.0), respectively. CONCLUSIONS: These results support the ongoing vaccination campaign in Italy, where the administration of a booster dose four months after completion of primary vaccination is recommended.

Effectiveness of mRNA vaccines and waning of protection against SARS-CoV-2 infection and severe covid-19 during predominant circulation of the delta variant in Italy: retrospective cohort study.

OBJECTIVES: To estimate the effectiveness of mRNA vaccines against SARS-CoV-2 infection and severe covid-19 at different time after vaccination. DESIGN: Retrospective cohort study. SETTING: Italy, 27 December 2020 to 7 November 2021. PARTICIPANTS: 33 250 344 people aged ≥16 years who received a first dose of BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) vaccine and did not have a previous diagnosis of SARS-CoV-2 infection. MAIN OUTCOME MEASURES: SARS-CoV-2 infection and severe covid-19 (admission to hospital or death). Data were divided by weekly time intervals after vaccination. Incidence rate ratios at different time intervals were estimated by multilevel negative binomial models with robust variance estimator. Sex, age group, brand of vaccine, priority risk category, and regional weekly incidence in the general population were included as covariates. Geographic region was included as a random effect. Adjusted vaccine effectiveness was calculated as (1-IRR)×100, where IRR=incidence rate ratio, with the time interval 0-14 days after the first dose of vaccine as the reference. RESULTS: During the epidemic phase when the delta variant was the predominant strain of the SARS-CoV-2 virus, vaccine effectiveness against SARS-CoV-2 infection significantly decreased (P<0.001) from 82% (95% confidence interval 80% to 84%) at 3-4 weeks after the second dose of vaccine to 33% (27% to 39%) at 27-30 weeks after the second dose. In the same time intervals, vaccine effectiveness against severe covid-19 also decreased (P<0.001), although to a lesser extent, from 96% (95% to 97%) to 80% (76% to 83%). High risk people (vaccine effectiveness -6%, -28% to 12%), those aged ≥80 years (11%, -15% to 31%), and those aged 60-79 years (2%, -11% to 14%) did not seem to be protected against infection at 27-30 weeks after the second dose of vaccine. CONCLUSIONS: The results support the vaccination campaigns targeting high risk people, those aged ≥60 years, and healthcare workers to receive a booster dose of vaccine six months after the primary vaccination cycle. The results also suggest that timing the booster dose earlier than six months after the primary vaccination cycle and extending the offer of the booster dose to the wider eligible population might be warranted.

Are vaccine shortages a relevant public health issue in Europe? Results from a survey conducted in the framework of the EU Joint Action on Vaccination.

National immunisation programmes require an adequate supply of vaccines to function properly but many countries, globally and in Europe, have reported vaccine shortages. A comprehensive view of vaccine shortages and stockouts in the EU/EEA is missing in the published literature. This study was conducted in the framework of the European Joint Action on Vaccination (EU-JAV). Twenty-eight countries, including 20 EU-JAV consortium member states and an additional 8 EU/EEA countries, were invited to participate in a survey aimed at collecting information on vaccine shortages and stock-outs experienced from 2016 to 2019, their main causes, actions taken, and other aspects of vaccine supply. Twenty-one countries completed the survey (response rate 75%), of which 19 reported at least one shortage/stock-out event. Overall, 115 events were reported, 28 of which led to a change in the national immunisation programme. The most frequently involved vaccines were DT- and dT-containing combination vaccines, hepatitis B, hepatitis A, and BCG vaccines. The median duration of shortages/stock-outs was five months (range <1 month-39 months). Interruption in supply and global shortage were the most frequently indicated causes. Only about half of countries reported having an immunization supply chain improvement plan. Similarly, only about half of countries had recommendations or procedures in place to address shortages/stockouts. The survey also identified the occurrence of shortages/stockouts of other biological products (e.g. diphtheria antitoxin in 12 countries). Public health strategies to assure a stable and adequate vaccine supply for immunization programmes require coordinated actions from all stakeholders, harmonized definitions, strengthening of reporting and monitoring systems, the presence of an immunization supply chain improvement plan in all countries, and procedures or recommendations in place regarding the use of alternative vaccines or vaccination schedules in case of shortages/stockouts.

Vaccine Procurement: A Conceptual Framework Based on Literature Review.

Ensuring timely access to affordable vaccines has been acknowledged as a global public health priority, as also recently testified by the debate sparked during the COVID-19 pandemic. Effective vaccine procurement strategies are essential to reach this goal. Nevertheless, this is still a neglected research topic. A narrative literature review on vaccine procurement was conducted, by retrieving articles from four academic databases (PubMed/MEDLINE, Scopus, Embase, WebOfScience), 'grey' literature reports, and institutional websites. The aim was to clarify key concepts and definitions relating to vaccine procurement, describe main vaccine procurement methods, and identify knowledge gaps and future perspectives. A theoretical conceptual framework was developed of the key factors involved in vaccine procurement, which include quality and safety of the product, forecasting and budgeting, procurement legislation, financial sustainability, and plurality of manufacture, contracting, investment in training, storage and service delivery, monitoring and evaluation. This information can be useful to support policymakers during planning, implementation, and evaluation of regional and national vaccine procurement strategies and policies.

Initial impact of SARS-Cov-2 vaccination on healthcare workers in Italy- Update on the 28th of March 2021.

In Italy, the COVID-19 vaccination campaign started in December 2020 with the vaccination of healthcare workers (HCW). To analyse the real-life impact that vaccination is having on this population group, we measured the association between week of diagnosis and HCW status using log-binomial regression. By the week 22-28 March, we observed a 74% reduction (PPR 0.26; 95% CI 0.22-0.29) in the proportion of cases reported as HCW and 81% reduction in the proportion of symptomatic cases reported as HCW, compared with the week with the lowest proportion of cases among HCWs prior to the vaccination campaign (31 August-7 September). The reduction, both in relative and absolute terms, of COVID-19 cases in HCWs that started around 30 days after the start of the vaccination campaign suggest that COVID-19 vaccines are being effective in preventing infection in this group.

Risk of SARS-CoV-2 infection and subsequent hospital admission and death at different time intervals since first dose of COVID-19 vaccine administration, Italy, 27 December 2020 to mid-April 2021.

To assess the real-world impact of vaccines on COVID-19 related outcomes, we analysed data from over 7 million recipients of at least one COVID-19 vaccine dose in Italy. Taking 0-14 days post-first dose as reference, the SARS-CoV-2 infection risk subsequently decreased, reaching a reduction by 78% (incidence rate ratios (IRR): 0.22; 95% CI: 0.21-0.24) 43-49 days post-first dose. Similarly, hospitalisation and death risks decreased, with 89% (IRR: 0.11; 95% CI: 0.09-0.15) and 93% (IRR: 0.07; 95% CI: 0.04-0.11) reductions 36-42 days post-first dose. Our results support ongoing vaccination campaigns.

Epidemiological characteristics of COVID-19 cases in non-Italian nationals notified to the Italian surveillance system.

BACKGROUND: International literature suggests that disadvantaged groups are at higher risk of morbidity and mortality from SARS-CoV-2 infection due to poorer living/working conditions and barriers to healthcare access. Yet, to date, there is no evidence of this disproportionate impact on non-national individuals, including economic migrants, short-term travellers and refugees. METHODS: We analyzed data from the Italian surveillance system of all COVID-19 laboratory-confirmed cases tested positive from the beginning of the outbreak (20th of February) to the 19th of July 2020. We used multilevel negative-binomial regression models to compare the case fatality and the rate of admission to hospital and intensive care unit (ICU) between Italian and non-Italian nationals. The analysis was adjusted for differences in demographic characteristics, pre-existing comorbidities, and period of diagnosis. RESULTS: We analyzed 213 180 COVID-19 cases, including 15 974 (7.5%) non-Italian nationals. We found that, compared to Italian cases, non-Italian cases were diagnosed at a later date and were more likely to be hospitalized {[adjusted rate ratio (ARR)=1.39, 95% confidence interval (CI): 1.33-1.44]} and admitted to ICU (ARR=1.19, 95% CI: 1.07-1.32), with differences being more pronounced in those coming from countries with lower human development index (HDI). We also observed an increased risk of death in non-Italian cases from low-HDI countries (ARR=1.32, 95% CI: 1.01-1.75). CONCLUSIONS: A delayed diagnosis in non-Italian cases could explain their worse outcomes compared to Italian cases. Ensuring early access to diagnosis and treatment to non-Italians could facilitate the control of SARS-CoV-2 transmission and improve health outcomes in all people living in Italy, regardless of nationality.

Epidemiological characteristics of COVID-19 cases and estimates of the reproductive numbers 1 month into the epidemic, Italy, 28 January to 31 March 2020.

BackgroundOn 20 February 2020, a locally acquired coronavirus disease (COVID-19) case was detected in Lombardy, Italy. This was the first signal of ongoing transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the country. The number of cases in Italy increased rapidly and the country became the first in Europe to experience a SARS-CoV-2 outbreak.AimOur aim was to describe the epidemiology and transmission dynamics of the first COVID-19 cases in Italy amid ongoing control measures.MethodsWe analysed all RT-PCR-confirmed COVID-19 cases reported to the national integrated surveillance system until 31 March 2020. We provide a descriptive epidemiological summary and estimate the basic and net reproductive numbers by region.ResultsOf the 98,716 cases of COVID-19 analysed, 9,512 were healthcare workers. Of the 10,943 reported COVID-19-associated deaths (crude case fatality ratio: 11.1%) 49.5% occurred in cases older than 80 years. Male sex and age were independent risk factors for COVID-19 death. Estimates of R0 varied between 2.50 (95% confidence interval (CI): 2.18-2.83) in Tuscany and 3.00 (95% CI: 2.68-3.33) in Lazio. The net reproduction number Rt in northern regions started decreasing immediately after the first detection.ConclusionThe COVID-19 outbreak in Italy showed a clustering onset similar to the one in Wuhan, China. R0 at 2.96 in Lombardy combined with delayed detection explains the high case load and rapid geographical spread. Overall, Rt in Italian regions showed early signs of decrease, with large diversity in incidence, supporting the importance of combined non-pharmacological control measures.

COVID-19 Disease Severity Risk Factors for Pediatric Patients in Italy.

OBJECTIVES: To describe the epidemiological and clinical characteristics of coronavirus disease (COVID-19) pediatric patients aged <18 years in Italy. METHODS: Data from the national case-based surveillance system of confirmed COVID-19 infections until May 8, 2020, were analyzed. Demographic and clinical characteristics of subjects were summarized by age groups (0-1, 2-6, 7-12, 13-18 years), and risk factors for disease severity were evaluated by using a multilevel (clustered by region) multivariable logistic regression model. Furthermore, a comparison among children, adults, and elderly was performed. RESULTS: Pediatric patients (3836) accounted for 1.8% of total infections (216 305); the median age was 11 years, 51.4% were male, 13.3% were hospitalized, and 5.4% presented underlying medical conditions. The disease was mild in 32.4% of cases and severe in 4.3%, particularly in children ≤6 years old (10.8%); among 511 hospitalized patients, 3.5% were admitted in ICU, and 4 deaths occurred. Lower risk of disease severity was associated with increasing age and calendar time, whereas a higher risk was associated with preexisting underlying medical conditions (odds ratio = 2.80, 95% confidence interval = 1.74-4.48). Hospitalization rate, admission in ICU, disease severity, and days from symptoms onset to recovery significantly increased with age among children, adults and elderly. CONCLUSIONS: Data suggest that pediatric cases of COVID-19 are less severe than adults; however, age ≤1 year and the presence of underlying conditions represent severity risk factors. A better understanding of the infection in children may give important insights into disease pathogenesis, health care practices, and public health policies.