Validation of the prevalence to incidence conversion method for healthcare associated infections in long-term care facilities.

INTRODUCTION: Residents of long-term care facilities (LTCFs) are a population at high risk of developing severe healthcare associated infections (HAIs). In the assessment of HAIs in acute-care hospitals, selection bias can occur due to cases being over-represented: patients developing HAIs usually have longer lengths of stays compared to controls, and therefore have an increased probability of being sampled in PPS, leading to an overestimation of HAI prevalence. Our hypothesis was that in LTCFs, the opposite may occur: residents developing HAIs either may have a greater chance of being transferred to acute-care facilities or of dying, and therefore could be under-represented in PPS, leading to an underestimation of HAI prevalence. Our aim was to test this hypothesis by comparing HAI rates obtained through longitudinal and cross-sectional studies. METHODS: Results from two studies conducted simultaneously in four LTCFs in Italy were compared: a longitudinal study promoted by the European Centre for Disease Prevention and Control (ECDC, HALT4 longitudinal study, H4LS), and a PPS. Prevalence was estimated from the PPS and converted into incidence per year using an adapted version of the Rhame and Sudderth formula proposed by the ECDC. Differences between incidence rates calculated from the PPS results and obtained from H4LS were investigated using the Byar method for rate ratio (RR). RESULTS: On the day of the PPS, HAI prevalence was 1.47% (95% confidence interval, CI 0.38-3.97), whereas the H4LS incidence rate was 3.53 per 1000 patient-days (PDs, 95% CI 2.99-4.08). Conversion of prevalence rates obtained through the PPS into incidence using the ECDC formula resulted in a rate of 0.86 per 1000 PDs (95% CI 0-2.68). Comparing the two rates, a RR of 0.24 (95% CI 0.03-2.03, p 0.1649) was found. CONCLUSIONS: This study did not find significant differences between HAI incidence estimates obtained from a longitudinal study and through conversion from PPS data. Results of this study support the validity of the ECDC method.

Implementation of a centralized, web-based surveillance for healthcare associated infections among residents of long-term care facilities in Italy.

Objective: The Italian National Action Plan to contrast AMR identified among its objectives the development and implementation of a national Healthcare-Associated Infection (HAI) surveillance system based on European Centre for Disease Prevention and Control (ECDC) indications, through point prevalence surveys (PPS) of HAIs and antibiotic use in acute-care hospitals and long-term care facilities (LTCFs). We aimed to assess feasibility and appropriateness of proposed tools for a national surveillance system of HAIs and antibiotic use in LTCFs. Study design: Point prevalence survey. Methods: A pilot PPS was conducted between May-June 2022, among 15 LTCFs of 7 Italian regions. Data were collected in a single day in each LTCF, at the LTCF, ward, and resident levels, using a web-based data collection tool developed ad hoc. Data collector teams of each facility were invited to complete a questionnaire investigating opinions on the proposed tools. Results: Among 1025 included residents, the prevalence of residents with at least one HAI was 2.5% (95% CI 1.7%-3.7%) considering all HAIs and 2.2% (95% CI 1.3%-3%) without considering SARS-CoV-2 infections. The prevalence of antimicrobial use was 3% (95% CI 0.2%-4.3%). Overall, most respondents were satisfied with the web-based software, training and protocol, even though some difficulties were reported. Conclusions: A national surveillance network was established, which will facilitate future surveillance efforts. Further studies are necessary to evaluate the impact of the pandemic on HAI transmission and antibiotic use in LTCFs.

Analysis of the Fatality Rate in Relation to Testing Capacity during the First 50 days of the COVID-19 Epidemic in Italy.

Italy has been one of the most severely affected countries by the COVID-19 pandemic, and the case fatality rate (CFR) estimated based on Italian data is one of the highest worldwide. We analyzed public data from the first 50 days of the epidemic in Italy (from February 24 to April 13, 2020) to evaluate whether evolving testing strategies and capacity could account for trends in the CFR. The CFR increased during the study period, and a significant positive correlation was found between the CFR and the percentage of positive tests among performed real-time PCR tests (positive tests % [POS%]) until March 25, suggesting the surveillance system did not detect a growing number of cases in the initial phase of the epidemic. To avoid distortion due to the delay between the identification of cases and deaths, the expected CFR (expCFR) was calculated, which represents the ratio between the predicted number of cases and deaths at the end of the epidemic based on the best fitting logistic curves of the cumulative numbers of cases and deaths. The expCFR began a downward trend from the 40th day. In the final phase, a decrease in both expCFR and POS% was identified, suggesting an improvement in surveillance. The results of this study suggest data from the first 50 days of the COVID-19 epidemic in Italy were severely affected by ascertainment bias. Insufficient testing and isolation of cases could have facilitated the widespread transmission of COVID-19 in the early stages of the outbreak.