Giovanni Rezza

Background: Healthcare-associated infections (HAIs) and antimicrobial resistance are major burdens in tertiary care hospitals. Repeated point prevalence surveys (PPSs) offer a pragmatic approach to monitor temporal changes and guide infection prevention. Objectives: Characterize healthcare-associated infections (HAI) prevalence trends, microbiological profiles, antimicrobial resistance (AMR) patterns, and risk factors to refine prevention strategies and hospital policy. Methods: Four annual cross-sectional PPSs were conducted between 2022 and 2025 using the standardized ECDC protocol. Data from all eligible inpatients present at 08:00 on survey days were collected through systematic medical record review. Multivariable logistic regression was used to identify factors independently associated with HAI, with additional sensitivity analyses evaluating invasive device burden and hospital ward type. Results: Across the surveys, 3314 patients were included. Overall HAI prevalence was 11.3%. Infections were most frequent in intensive care units (31.2%), followed by medical (14.6%) and surgical (14.2%) wards. Bloodstream infections (25.7%) and lower respiratory tract infections (19.8%) were the most common. Multivariable analysis identified invasive device exposure as the strongest predictor, with central venous and urinary catheters showing robust independent associations and a clear dose–response relationship according to the number of devices. Pathogens were predominantly Gram-positive cocci (40.5%) and Enterobacterales (30.8%), with Klebsiella pneumoniae being the most frequent isolate (13.0%). Notably, 57.6% of K. pneumoniae isolates were resistant to third-generation cephalosporins. All tested Acinetobacter baumannii isolates were resistant to carbapenems. Conclusions: This repeated PPS reveals a persistently high HAI burden, associated with invasive device exposure and resistant pathogens. Because of the repeated cross-sectional design, causal inference cannot be established. Hospital-wide device stewardship and integrated surveillance are essential for guiding targeted prevention measures, refining antimicrobial policies, and adapting local responses to evolving resistance profiles.

Andes virus (ANDV) is the only hantavirus with well-documented evidence of person-to-person transmission. However, key parameters related to transmission timing, viral shedding, exposure contexts, and public health management remain incompletely defined. We conducted a systematic review in accordance with PRISMA 2020. MEDLINE/PubMed, Scopus, and Web of Science were searched from database inception up to 14 May 2026. Eligible studies reported epidemiological, virological, clinical, or public health data relevant to ANDV infection, person-to-person transmission, viral shedding, and/or outbreak control. Thirty-three studies, including 17,204 individuals, 2221 laboratory-confirmed ANDV cases, and 135 documented secondary cases, were included. Person-to-person transmission was identified as a primary or co-occurring route in 20 papers. The median incubation period among ANDV cases was 20.8 days, and the median serial interval was 21.8 days (upper bounds near 40 days). Secondary attack rates were higher among sexual and other close contacts. ANDV RNA was consistently detected in blood and occasionally in saliva, respiratory secretions, urine, breast milk, and semen, although RNA detection alone does not necessarily imply infectious virus. Rare reports of culture-confirmed isolation of replication-competent virus support the biological plausibility of transmission via close mucosal or respiratory exposure. Unlike other hantaviruses, Andes virus can spread person to person through close contact, supporting prolonged monitoring and risk-stratified follow-up of high-risk contacts based on ANDV-specific epidemiological evidence. Possible recommendations, including post-discharge counselling regarding possible sexual transmission, remain provisional and require further evidence. Preparedness activities against outbreaks should also be implemented in non-endemic regions, while future research should prioritize prospective contact studies, standardized virological sampling, and genomic confirmation.

Background: Early differentiation of mosquito-borne viral infections from other causes of acute febrile illness remains challenging, particularly in endemic and resource-limited settings. Artificial intelligence (AI) models have been proposed to improve early diagnosis, but their incremental value over conventional approaches is unclear. Methods: We conducted a systematic review and meta-analysis of comparative studies evaluating AI/machine learning models versus conventional approaches (clinical assessment, laboratory-based pathways, or traditional statistical models) for early detection of mosquito-borne viral infections. PubMed, Embase, and Scopus were searched through August 2025. Paired performance metrics were synthesized using fixed- and random-effects models. Outcomes included AUC, sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV). Risk of bias was assessed using PROBAST. Results: Thirteen studies met inclusion criteria. Under random-effects models, AI improved sensitivity (ES = 2.64, p = 0.028), specificity (ES = 5.55, p < 0.001), accuracy (ES = 3.19, p < 0.001), and NPV (ES = 13.84, p < 0.001). No consistent advantage was observed for AUC, and PPV findings were inconsistent. Substantial heterogeneity was present across outcomes (I² = 100%). Most studies relied on internal validation, and PROBAST identified high risk of bias in the analysis domain in over half. Conclusions: AI-based models may enhance threshold-dependent performance metrics, supporting their use as adjunctive decision-support tools for early triage and case exclusion, while external validation and implementation-focused research remain essential.

Pandemics are large-scale outbreaks of an infectious disease that greatly increase morbidity and mortality at the global level, usually causing significant economic, social, political, and health-care disruption

Background/Objectives: Maintaining high childhood vaccination coverage is essential to prevent outbreaks of vaccine-preventable diseases. In Italy, Law No. 119/2017 introduced mandatory childhood immunizations, leading to significant improvements. However, the COVID-19 pandemic disrupted routine services, potentially jeopardizing these gains. This study aimed to evaluate national and regional trends in vaccine coverage across three phases: post-mandate (2015–2016 vs. 2017–2019), pandemic (2017–2019 vs. 2020–2021), and post-pandemic recovery (2020–2021 vs. 2022–2023). Methods: National and regional administrative data on vaccination coverage at 24 months of age were obtained from the Italian Ministry of Health. Temporal trends were analyzed using Joinpoint regression to estimate annual percent changes (APCs), and absolute changes in coverage (Δ) were calculated across defined periods. Pearson correlation coefficients were used to assess associations between baseline coverage and subsequent changes. Results: After the 2017 mandate, coverage increased significantly for varicella (APC = +28.6%), MenB (+22.6%), and measles (+3.4%). Regionally, varicella coverage rose by up to +58.4% in Emilia-Romagna and measles by +11.1% in Campania. During the pandemic, coverage declined for polio (−2.4% in the South) and measles (−6.2% in Abruzzo), while MenB increased in regions with lower initial uptake (r = −0.918, p < 0.001). Post-pandemic, coverage rebounded, with varicella improving by +20.1% in central regions and measles by +13.9% in Abruzzo. A strong inverse correlation between baseline coverage and improvement was observed for varicella across all periods (r from −0.877 to −0.915). Conclusions: Mandatory vaccination policies led to substantial coverage improvements, and despite the disruption caused by the pandemic, recovery trends were observed for most vaccines. The consistent association between low baseline coverage and stronger gains highlights the resilience of the system, but also the ongoing need for regionally tailored strategies to reduce geographic disparities and ensure equitable immunization across Italy.

Background: The success of vaccination programs depends on a complex interplay of logistical, social, and structural factors. The objective of this study was to analyze the different approaches to vaccine administration implemented by several Italian regions since the onset of the SARS-CoV-2 pandemic. Methods: After careful qualitative review of information gathered from scientific articles, official reports (grey literature), contact with regional health authorities, and local health departments, five vaccination strategies across several Italian regions focusing on alternative vaccine providers and/or settings were identified. The innovative practices implemented by different actors covered specific topics and were then examined and described in detail. Results: In Veneto, where prevention departments were the main actor, herpes zoster vaccination coverage for the 65-year-old cohort increased from 44.4% to 54.9%; in Tuscany, family pediatricians administered 64% of all childhood vaccines; in Liguria, pharmacies delivered 70.1% of COVID-19 vaccines, while vaccinating in schools in Taranto led to higher human papilloma virus vaccination rates compared to regional and national averages. Finally, in all the regions, hospitals focused on vaccinating healthcare workers and vulnerable populations. Conclusions: The positive outcomes of these five experiences may, in a context of limited resources, encourage other national and international entities to adopt innovative practices, which offer new perspectives beyond the traditional delivery methods (i.e., local health authority vaccination centers for childhood and adolescent immunizations, and family doctors for adults and the elderly). These strategies suggest the efficacy of specific local approaches favored by regional autonomy in optimizing vaccine distribution and coverage.

The emergence of antimicrobic-resistant infectious pathogens and the consequent rising in the incidence and prevalence of demises caused by or associated t

Dengue (DENV) and Zika (ZIKV) viruses are mosquito-borne human pathogens. In Italy, the presence of the competent vector Aedes albopictus increases the risk of autochthonous transmission, and a national plan for arboviruses prevention, surveillance, and response (PNA 2020–2025) is in place. The results of laboratory diagnosis of both viruses by the National Reference Laboratory for arboviruses (NRLA) from November 2015 to November 2022 are presented. Samples from 655 suspected cases were tested by both molecular and serological assays. Virus and antibody kinetics, cross-reactivity, and diagnostic performance of IgM ELISA systems were analysed. Of 524 cases tested for DENV, 146 were classified as confirmed, 7 as probable, while 371 were excluded. Of 619 cases tested for ZIKV, 44 were classified as confirmed, while 492 were excluded. All cases were imported. Overall, 75.3% (110/146) of DENV and 50% (22/44) of ZIKV cases were confirmed through direct virus detection methods. High percentages of cross reactivity were observed between the two viruses. The median lag time from symptoms onset to sample collection was 7 days for both DENV molecular (range 0–20) and NS1 ELISA (range 0–48) tests, with high percentages of positivity also after 7 days (39% and 67%, respectively). For ZIKV, the median lag time was 5 days (range 0–22), with 16% positivity after 7 days. Diagnostic performance was assessed with negative predictive values ranging from 92% to 95% for the anti-DENV systems, and of 97% for the ZIKV one. Lower positive predictive values were seen in the tested population (DENV: 55% to 91%, ZIKV: 50%). DENV and ZIKV diagnosis by molecular test is the gold standard, but sample collection time is a limitation. Serological tests, including Plaque Reduction Neutralization Test, are thus necessary. Co-circulation and cross-reactivity between the two viruses increase diagnostic difficulty. Continuous evaluation of diagnostic strategies is essential to improve laboratory testing.