ArticleEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin2025
Application of an updated methodology to estimate the burden of healthcare-associated infections in Italy, 2022.
Article in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Effectiveness of an artificial intelligence-assisted training program on cleaning competency among hospital environmental service staff.BMC health services research · 2026Trial
- High Antimicrobial Consumption, Low Reported Infection Rates: An Ecological Analysis of HAI Surveillance Discordance Across EU/EEA Countries.Antibiotics (Basel, Switzerland) · 2026Article
- Italy's progress towards the objectives of the national action plan to combat antimicrobial resistance.PloS one · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BackgroundAccurate burden estimates are necessary to inform priority setting and rational resource allocation. Weighting prevalence inversely proportional to time-at-risk has been proposed as a solution for length-biased sampling, an important limitation affecting prevalence to incidence conversion for healthcare-associated infections (HAIs).AimThis study aimed to update Italian burden estimates by calculating HAI incidence, attributable mortality and disability-adjusted life years (DALYs). Further, we describe an adapted methodology for burden estimations.MethodsWe used data from the latest European Centre for Disease Prevention and Control (ECDC) point prevalence survey (PPS) of HAIs, conducted in Italy in November 2022, to calculate the burden of five major HAIs at national level. We adapted the Burden of Communicable Diseases in Europe (BCoDE) methodology to include inverse probability weighting and compared results of naïve and weighted calculations.ResultsThe national sample included 18,397 patients. Overall, 564.8 DALYs per 100,000 general population resulted from weighted calculations (95% uncertainty interval (UI): 450.04-694.38), with an annual incidence of 685.42 cases per 100,000 general population (95% UI: 611.09-760.86) and 33.23 deaths per 100,000 general population per year (95% UI: 28.62-38.33). Concerning naïve estimates, overall 1,017.81 DALYs per 100,000 general population were calculated (95% UI: 855.16-1,190.59). In both calculations, healthcare-acquired bloodstream infections had the highest burden in terms of DALYs per 100,000 hospitalised and general population.ConclusionOur study confirmed the substantial burden of HAIs in Italy and renews the need to prioritise resources for infection prevention and control interventions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.