Italian National Surveillance of Alcohol-Based Hand Rub Consumption in a Healthcare Setting-A Three-Year Analysis: 2020-2022.

Background/Objectives: Hand hygiene (HH) is pivotal in mitigating infectious disease transmission and enhancing public health outcomes. This study focuses on detailing the national surveillance system for alcohol-based hand rub (ABHR) consumption in healthcare facilities across Italy, presenting results from a comprehensive three-year evaluation period, from 2020 to 2022. It aims to delineate this surveillance system and report on ABHR consumption trends in various Regions/Autonomous Provinces (Rs/APs). Methods: ABHR consumption data, collected through the ABHR Italian national surveillance system, coordinated by the Istituto Superiore di Sanità (ISS), were analyzed. Statistical methods, e.g., the Mann-Whitney test, were used to assess trends in ABHR consumption, expressed in liters per 1000 patient days (L/1000PD). Results: The results show significant variation in ABHR consumption across Rs/APs and over the years studied. National median ABHR consumption decreased from 2020 to 2022, with a significant reduction from a median of 24.5 L/1000PD in 2020 to 20.4 L/1000PD in 2021 and 15.6 L/1000PD in 2022. Conclusions: The decline in ABHR consumption raises concerns about the ongoing adherence to HH practices in Italian healthcare settings. This underscores the essential role that systematic ABHR monitoring and improved surveillance play in enhancing HH compliance, suggesting that sustained and strategic efforts are fundamental to uphold high standards of hygiene and to effectively respond to fluctuating ABHR usage trends over time. Further research is needed to explore barriers to effective ABHR use and to develop targeted strategies to improve HH practices.

Seven Years of Culture Collection of Neisseria gonorrhoeae: Antimicrobial Resistance and Molecular Epidemiology.

The emergence of Neisseria gonorrhoeae isolates displaying resistance to antimicrobials, in particular to ceftriaxone monotherapy or ceftriaxone plus azithromycin, represents a global public health concern. This study aimed to analyze the trend of antimicrobial resistance in a 7-year isolate collection retrospective analysis in Italy. Molecular typing on a subsample of gonococci was also included. A total of 1,810 culture-positive gonorrhea cases, collected from 2013 to 2019, were investigated by antimicrobial susceptibility, using gradient diffusion method, and by the N. gonorrhoeae multiantigen sequence typing (NG-MAST). The majority of infections occurred among men with urogenital infections and 57.9% of male patients were men who have sex with men. Overall, the cefixime resistance remained stable during the time. An increase of azithromycin resistance was observed until 2018 (26.5%) with a slight decrease in the last year. In 2019, gonococci showing azithromycin minimum inhibitory concentration above the EUCAST epidemiological cutoff value (ECOFF) accounted for 9.9%. Ciprofloxacin resistance and penicillinase-producing N. gonorrhoeae (PPNG) percentages increased reaching 79.1% and 18.7% in 2019, respectively. The most common sequence types identified were 5,441, 1,407, 6,360, and 5,624. The predominant genogroup (G) was the 1,407; moreover, a new genogroup G13070 was also detected. A variation in the antimicrobial resistance rates and high genetic variability were observed in this study. The main phenotypic and genotypic characteristics of N. gonorrhoeae isolates were described to monitor the spread of drug-resistant gonorrhea.

Assessing COVID-19-Related Excess Mortality Using Multiple Approaches-Italy, 2020-2021.

INTRODUCTION: Excess mortality (EM) is a valid indicator of COVID-19's impact on public health. Several studies regarding the estimation of EM have been conducted in Italy, and some of them have shown conflicting values. We focused on three estimation models and compared their results with respect to the same target population, which allowed us to highlight their strengths and limitations. METHODS: We selected three estimation models: model 1 (Maruotti et al.) is a Negative-Binomial GLMM with seasonal patterns; model 2 (Dorrucci et al.) is a Negative Binomial GLM epidemiological approach; and model 3 (Scortichini et al.) is a quasi-Poisson GLM time-series approach with temperature distributions. We extended the time windows of the original models until December 2021, computing various EM estimates to allow for comparisons. RESULTS: We compared the results with our benchmark, the ISS-ISTAT official estimates. Model 1 was the most consistent, model 2 was almost identical, and model 3 differed from the two. Model 1 was the most stable towards changes in the baseline years, while model 2 had a lower cross-validation RMSE. DISCUSSION: Presently, an unambiguous explanation of EM in Italy is not possible. We provide a range that we consider sound, given the high variability associated with the use of different models. However, all three models accurately represented the spatiotemporal trends of the pandemic waves in Italy.

Characteristics of COVID-19 cases in Italy from a sex/gender perspective.

INTRODUCTION: Coronavirus disease 19 (COVID-19) is an infectious disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). To date, few data on clinical features and risk factors for disease severity and death by gender are available. AIM: The current study aims to describe from a sex/gender perspective the characteristics of the SARS-CoV-2 cases occurred in the Italian population from February 2020 until October 2021. METHOD AND RESULTS: We used routinely collected data retrieved from the Italian National Surveillance System. The highest number of cases occurred among women between 40 and 59 years, followed by men in the same age groups. The proportion of deaths due to COVID-19 was higher in men (56.46%) compared to women (43.54%). Most of the observed deaths occurred in the elderly. Considering the age groups, the clinical outcomes differed between women and men in particular in cases over 80 years of age; with serious or critical conditions more frequent in men than in women. CONCLUSIONS: Our data clearly demonstrate a similar number of cases in women and men, but with more severe disease and outcome in men, thus confirming the importance to analyse the impact of sex and gender in new and emerging diseases.

Prevalence and risk factors for hepatitis E virus infection in blood donors: a nationwide survey in Italy, 2017 to 2019.

BackgroundIn high-income countries, hepatitis E virus (HEV) infection is mainly a zoonosis. However, it is also transfusion-transmissible and some countries, but not Italy, have introduced HEV screening for blood donations.AimWe assessed HEV infection prevalence and risk factors in a nationwide sample of Italian blood donors.MethodsWe selected 107 blood establishments (BE) distributed in the 20 Italian regions by a stratified two-stage design and invited them to participate in the study. Donors were tested for anti-HEV IgG and IgM and HEV RNA. Sociodemographic data and risk factors were collected through a questionnaire.ResultsOverall, 60 BE from 60 provinces in 19 Italian regions joined the study. We assessed HEV markers in 7,172 blood donors, of whom 6,235 completed the questionnaire. Overall crude and adjusted anti-HEV IgG prevalences were 8.3% and 5.5%, respectively. Overall anti-HEV IgM prevalence was 0.5%, while no blood donor was HEV RNA-positive. Anti-HEV IgG prevalence varied widely among regions (range: 1.3%-27.20%) and hyperendemic prevalences (> 40%) were detected in some provinces in two regions. Older age (AOR = 1.81; 95% CI: 1.36-2.41), foreign nationality (AOR = 2.77; 95% CI: 1.06-7.24), eating raw pork liver sausages (AOR = 2.23; 95% CI: 1.55-3.20) and raw homemade sausages (AOR = 3.63; 95% CI: 2.50-5.24) were independent infection predictors.ConclusionItalian blood donors showed a low to moderate HEV seroprevalence. High levels in some regions and/or provinces were mainly attributable to eating habits. Prevention should include avoiding consumption of raw or undercooked meat and safe production of commercial pork products.

A population-based cohort approach to assess excess mortality due to the spread of COVID-19 in Italy, January-May 2020.

AIMS: To assess the impact of the COVID-19 pandemic on all-cause mortality in Italy during the first wave of the epidemic, taking into consideration the geographical heterogeneity of the spread of COVID-19. METHODS: This study is a retrospective, population-based cohort study using national statistics throughout Italy. Survival analysis was applied to data aggregated by day of death, age groups, sex, and Italian administrative units (107 provinces). We applied Cox models to estimate the relative hazards (RH) of excess mortality, comparing all-cause deaths in 2020 with the expected deaths from all causes in the same time period. The RH of excess deaths was estimated in areas with a high, moderate, and low spread of COVID-19. We reported the estimate also restricting the analysis to the period of March-April 2020 (first peak of the epidemic). RESULTS: The study population consisted of 57,204,501 individuals living in Italy as of January 1, 2020. The number of excess deaths was 36,445, which accounts for 13.4% of excess mortalities from all causes during January-May 2020 (i.e., RH = 1.134; 95% confidence interval (CI): 1.129-1.140). In the macro-area with a relatively higher spread of COVID-19 (i.e., incidence rate, IR): 450-1,610 cases per 100,000 residents), the RH of excess deaths was 1.375 (95% CI: 1.364-1.386). In the area with a relatively moderate spread of COVID-19 (i.e., IR: 150-449 cases) it was 1.049 (95% CI: 1.038-1.060). In the area with a relatively lower spread of COVID-19 (i.e., IR: 30-149 cases), it was 0.967 (95% CI: 0.959-0.976). Between March and April (peak months of the first wave of the epidemic in Italy), we estimated an excess mortality from all causes of 43.5%. The RH of all-cause mortality for increments of 500 cases per 100,000 residents was 1.352 (95% CI: 1.346-1.359), corresponding to an increase of about 35%. CONCLUSIONS: Our analysis, making use of a population-based cohort model, estimated all-cause excess mortality in Italy taking account of both time period and of COVID-19 geographical spread. The study highlights the importance of a temporal/geographic framework in analyzing the risk of COVID-19-epidemy related mortality.

Excess Mortality in Italy During the COVID-19 Pandemic: Assessing the Differences Between the First and the Second Wave, Year 2020.

COVID-19 dramatically influenced mortality worldwide, in Italy as well, the first European country to experience the Sars-Cov2 epidemic. Many countries reported a two-wave pattern of COVID-19 deaths; however, studies comparing the two waves are limited. The objective of the study was to compare all-cause excess mortality between the two waves that occurred during the year 2020 using nationwide data. All-cause excess mortalities were estimated using negative binomial models with time modeled by quadratic splines. The models were also applied to estimate all-cause excess deaths "not directly attributable to COVD-19", i.e., without a previous COVID-19 diagnosis. During the first wave (25th February-31st May), we estimated 52,437 excess deaths (95% CI: 49,213-55,863) and 50,979 (95% CI: 50,333-51,425) during the second phase (10th October-31st December), corresponding to percentage 34.8% (95% CI: 33.8%-35.8%) in the second wave and 31.0% (95%CI: 27.2%-35.4%) in the first. During both waves, all-cause excess deaths percentages were higher in northern regions (59.1% during the first and 42.2% in the second wave), with a significant increase in the rest of Italy (from 6.7% to 27.1%) during the second wave. Males and those aged 80 or over were the most hit groups with an increase in both during the second wave. Excess deaths not directly attributable to COVID-19 decreased during the second phase with respect to the first phase, from 10.8% (95% CI: 9.5%-12.4%) to 7.7% (95% CI: 7.5%-7.9%), respectively. The percentage increase in excess deaths from all causes suggests in Italy a different impact of the SARS-CoV-2 virus during the second wave in 2020. The decrease in excess deaths not directly attributable to COVID-19 may indicate an improvement in the preparedness of the Italian health care services during this second wave, in the detection of COVID-19 diagnoses and/or clinical practice toward the other severe diseases.

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.

Impact of a Nationwide Lockdown on SARS-CoV-2 Transmissibility, Italy.

On March 11, 2020, Italy imposed a national lockdown to curtail the spread of severe acute respiratory syndrome coronavirus 2. We estimate that, 14 days after lockdown, the net reproduction number had dropped below 1 and remained stable at ¼0.76 (95% CI 0.67-0.85) in all regions for >3 of the following weeks.