The Role of Urban Wastewater in the Environmental Transmission of Antimicrobial Resistance: The Current Situation in Italy (2010-2019)

Scientific studies show that urban wastewater treatment plants (UWWTP) are among the main sources of release of antibiotics, antibiotic resistance genes (ARG) and antibiotic-resistant bacteria (ARB) into the environment, representing a risk to human health. This review summarizes selected publications from 1 January 2010 to 31 December 2019, with particular attention to the presence and treatment of ARG and ARB in UWWTPs in Italy. Following a brief introduction, the review is divided into three sections: (i) phenotypic assessment (ARB) and (ii) genotypic assessment (ARG) of resistant microorganisms, and (iii) wastewater treatment processes. Each article was read entirely to extract the year of publication, the geographical area of the UWWTP, the ARB and ARG found, and the type of disinfection treatment used. Among the ARB, we focused on the antibiotic resistance of Escherichia coli, Klebsiella pneumoniae, and Enterococci in UWWTP. The results show that the information presented in the literature to date is not exhaustive; therefore, future scientific studies at the national level are needed to better understand the spread of ARB and ARG, and also to develop new treatment methods to reduce this spread

Legionella and legionellosis in touristic-recreational facilities. Influence of climate factors and geostatistical analysis in Southern Italy (2001-2017)

Legionella is the causative agent of Legionnaires' disease, a flu-like illness normally acquired following inhalation or aspiration of contaminated water aerosols. Our recent studies revealed that climatic parameters can increase the number of reported cases of community-acquired Legionnaires' disease. Here, we evaluated the presence of Legionella in water networks and the distribution of Legionnaires' disease cases associated with touristic-recreational facilities in the Apulia region (southern Italy) during the period 2001-2017 using geostatistical and climatic analyses. Geostatistical analysis data revealed that the area with the highest concentration of Legionella in water systems also had the greatest number of cases of Legionnaires' disease associated with touristic-recreational facilities. Climatic analysis showed that higher daily temperature excursion (difference between maximum and minimum temperature) on the day of sampling was more often associated with Legionella-positive samples than Legionella-negative samples. In addition, our data highlighted an increased risk of Legionnaires' disease with increases in precipitation and average temperature and with decreases in daily temperature excursion (difference between maximum and minimum temperature over the course of 24 h in the days of incubation period of disease) and minimum temperature. Healthcare professionals should be aware of this phenomenon and be particularly vigilant for cases of community-acquired pneumonia during such climatic conditions and among the tourist population. The innovative geo-statistical approach used in this study could be applied in other contexts when evaluating the effects of climatic conditions on the incidence of Legionella infections

Integrated approach for legionellosis risk analysis in touristic-recreational facilities

Legionellosis is a severe pneumonia caused by the inhalation of aerosols containing Legionella, Gram-negative bacteria present in the water systems of touristic-recreational facilities. The purpose of this study was to develop a scoring tool to predict the risk of both environmental contamination and Legionnaires' disease cases in such facilities in the Apulia region of southern Italy. We analyzed 47 structural and management parameters/risk factors related to the buildings, water systems, and air conditioning at the facilities. A Poisson regression model was used to compute an overall risk score for each facility with respect to three outcomes: water samples positive for Legionella (risk score range: 7-54), water samples positive for Legionella with an average load exceeding 1000 colony-forming units per liter (CFU/L) (risk score range: 22-179,871), and clinical cases of Legionnaire's disease (risk score range: 6-31). The cut-off values for three outcomes were determined by receiver operating characteristic curves (first outcome, samples positive for Legionella in a touristic-recreational facility: 19; second outcome, samples positive for Legionella in a touristic-recreational facility with an average load exceeding 1000 CFU/L: 2062; third outcome, clinical cases of Legionnaire's disease in a touristic-recreational facility: 22). Above these values, there was a significant probability of observing the outcome. We constructed this predictive model using 70% of a large dataset (18 years of clinical and environmental surveillance) and tested the model on the remaining 30% of the dataset to demonstrate its reliability. Our model enables the assessment of risk for a touristic facility and the creation of a conceptual framework to link the risk analysis with prevention measures

Management of Microbiological Contamination of the Water Network of a Newly Built Hospital Pavilion

The good installation, as well as commissioning plan, of a water network is a crucial step in reducing the risk of waterborne diseases. The aim of this study was to monitor the microbiological quality of water from a newly built pavilion before it commenced operation. Overall, 91 water samples were tested for coliforms, Escherichia coli, enterococci, Pseudomonas aeruginosa and Legionella at three different times: T0 (without any water treatment), T1 (after treatment with hydrogen peroxide and silver ions at initial concentration of 20 mg/L and after flushing of water for 20 min/day for seven successive days) and T2 (15 days later). Coliforms were detected in 47.3% of samples at T0, 36.3% at T1 and 4.4% at T2. E. coli was isolated in 4.4% of the samples only at T1, while enterococci appeared in 12.1% of the samples at T1 and in 2.2% at T2. P. aeruginosa was isolated in 50.5% of the samples at T0, 29.7% at T1 and 1.1% at T2. Legionella pneumophila serogroup 8 was isolated in 80.2% of the samples at T0, 36.3% at T1 and 2.2% at T2. Our results confirmed the need for a water safety plan in new hospital pavilions to prevent the risk of waterborne diseases

Impact of lockdown on the microbiological status of the hospital water network during COVID-19 pandemic

The COVID-19 pandemic started in China in early December 2019, and quickly spread around the world. The epidemic gradually started in Italy at the end of February 2020, and by May 31, 2020, 232,664 cases and 33,340 deaths were confirmed. As a result of this pandemic, the Italian Ministerial Decree issued on March 11, 2020, enforced lockdown; therefore, many social, recreational, and cultural centers remained closed for months. In Apulia (southern Italy), all non-urgent hospital activities were suspended, and some wards were closed, with a consequent reduction in the use of the water network and the formation of stagnant water. This situation could enhance the risk of exposure of people to waterborne diseases, including legionellosis. The purpose of this study was to monitor the microbiological quality of the water network (coliforms, E. coli, Enterococci, P. aeruginosa, and Legionella) in three wards (A, B and C) of a large COVID-19 regional hospital, closed for three months due to the COVID-19 emergency. Our study revealed that all three wards' water network showed higher contamination by Legionella pneumophila sg 1 and sg 6 at T1 (after lockdown) compared to the period before the lockdown (T0). In particular, ward A at T1 showed a median value = 5600 CFU/L (range 0-91,000 CFU/L) vs T0, median value = 75 CFU/L (range 0-5000 CFU/L) (p-value = 0.014); ward B at T1 showed a median value = 200 CFU/L (range 0-4200 CFU/L) vs T0, median value = 0 CFU/L (range 0-300 CFU/L) (p-value = 0.016) and ward C at T1 showed a median value = 175 CFU/L (range 0-22,000 CFU/L) vs T0, median value = 0 CFU/L (range 0-340 CFU/L) (p-value < 0.001). In addition, a statistically significant difference was detected in ward B between the number of positive water samples at T0 vs T1 for L. pneumophila sg 1 and sg 6 (24% vs 80% p-value < 0.001) and for coliforms (0% vs 64% p-value < 0.001). Moreover, a median value of coliform load resulted 3 CFU/100 ml (range 0-14 CFU/100 ml) at T1, showing a statistically significant increase versus T0 (0 CFU/100 ml) (p-value < 0.001). Our results highlight the need to implement a water safety plan that includes staff training and a more rigorous environmental microbiological surveillance in all hospitals before occupying a closed ward for a longer than one week, according to national and international guidelines

The rapid spread of SARS-COV-2 Omicron variant in Italy reflected early through wastewater surveillance

The SARS-CoV-2 Omicron variant emerged in South Africa in November 2021, and has later been identified worldwide, raising serious concerns. A real-time RT-PCR assay was designed for the rapid screening of the Omicron variant, targeting characteristic mutations of the spike gene. The assay was used to test 737 sewage samples collected throughout Italy (19/21 Regions) between 11 November and 25 December 2021, with the aim of assessing the spread of the Omicron variant in the country. Positive samples were also tested with a real-time RT-PCR developed by the European Commission, Joint Research Centre (JRC), and through nested RT-PCR followed by Sanger sequencing. Overall, 115 samples tested positive for Omicron SARS-CoV-2 variant. The first occurrence was detected on 7 December, in Veneto, North Italy. Later on, the variant spread extremely fast in three weeks, with prevalence of positive wastewater samples rising from 1.0% (1/104 samples) in the week 5–11 December, to 17.5% (25/143 samples) in the week 12–18, to 65.9% (89/135 samples) in the week 19–25, in line with the increase in cases of infection with the Omicron variant observed during December in Italy. Similarly, the number of Regions/Autonomous Provinces in which the variant was detected increased fromone in the first week, to 11 in the second, and to 17 in the last one. The presence of the Omicron variant was confirmed by the JRC real-time RT-PCR in 79.1% (91/115) of the positive samples, and by Sanger sequencing in 66% (64/97) of PCR amplicons

The rapid spread of SARS-COV-2 Omicron variant in Italy reflected early through wastewater surveillance

The SARS-CoV-2 Omicron variant emerged in South Africa in November 2021, and has later been identified worldwide, raising serious concerns. A real-time RT-PCR assay was designed for the rapid screening of the Omicron variant, targeting characteristic mutations of the spike gene. The assay was used to test 737 sewage samples collected throughout Italy (19/21 Regions) between 11 November and 25 December 2021, with the aim of assessing the spread of the Omicron variant in the country. Positive samples were also tested with a real-time RT-PCR developed by the European Commission, Joint Research Centre (JRC), and through nested RT-PCR followed by Sanger sequencing. Overall, 115 samples tested positive for Omicron SARS-CoV-2 variant. The first occurrence was detected on 7 December, in Veneto, North Italy. Later on, the variant spread extremely fast in three weeks, with prevalence of positive wastewater samples rising from 1.0% (1/104 samples) in the week 5-11 December, to 17.5% (25/143 samples) in the week 12-18, to 65.9% (89/135 samples) in the week 19-25, in line with the increase in cases of infection with the Omicron variant observed during December in Italy. Similarly, the number of Regions/Autonomous Provinces in which the variant was detected increased from one in the first week, to 11 in the second, and to 17 in the last one. The presence of the Omicron variant was confirmed by the JRC real-time RT-PCR in 79.1% (91/115) of the positive samples, and by Sanger sequencing in 66% (64/97) of PCR amplicons. In conclusion, we designed an RT-qPCR assay capable to detect the Omicron variant, which can be successfully used for the purpose of wastewater-based epidemiology. We also described the history of the introduction and diffusion of the Omicron variant in the Italian population and territory, confirming the effectiveness of sewage monitoring as a powerful surveillance tool

Gaussian processes and expected signature for time series classification

The theory of rough paths has gained much attention in the mathematical community since it allows to define a robust theory for controlled differential equation driven by poorly regular signals, such as fractional Brownian motion sample paths. The concept of signature is strictly related to the theory of rough paths and it has been shown that it is very well suited for machine learning usage. Indeed, it has been proved that a universal approximation theorem holds and that the expected signature allows to distinguish stochastic processes' law. In this thesis a new time series classification model that combines gaussian processes and expected signature will be introduced and analyzed. In particular, the model's forward pass exploits gaussian processes for obtaining a certain number of new time series from a single one, then the expected signature is computed by averaging over each time series's signature and it is used in order to get the output

The Role of Urban Wastewater in the Environmental Transmission of Antimicrobial Resistance: The Current Situation in Italy (2010–2019)

Scientific studies show that urban wastewater treatment plants (UWWTP) are among the main sources of release of antibiotics, antibiotic resistance genes (ARG) and antibiotic-resistant bacteria (ARB) into the environment, representing a risk to human health. This review summarizes selected publications from 1 January 2010 to 31 December 2019, with particular attention to the presence and treatment of ARG and ARB in UWWTPs in Italy. Following a brief introduction, the review is divided into three sections: (i) phenotypic assessment (ARB) and (ii) genotypic assessment (ARG) of resistant microorganisms, and (iii) wastewater treatment processes. Each article was read entirely to extract the year of publication, the geographical area of the UWWTP, the ARB and ARG found, and the type of disinfection treatment used. Among the ARB, we focused on the antibiotic resistance of Escherichia coli, Klebsiella pneumoniae, and Enterococci in UWWTP. The results show that the information presented in the literature to date is not exhaustive; therefore, future scientific studies at the national level are needed to better understand the spread of ARB and ARG, and also to develop new treatment methods to reduce this spread

No-Touch Automated Disinfection System Based on Hydrogen Peroxide and Ethyl Alcohol Aerosols for Use in Healthcare Environments

Healthcare-related infections are sustained by various bacteria and fungi. In recent years, various technologies have emerged for the sanitation of healthcare-related environments. This study evaluated the effectiveness of a no-touch disinfection system that aerosolizes 5% hydrogen peroxide and 10% ethyl alcohol. After selecting an environment, the Total Bacterial Count and the Total Fungal Count in the air and on a surface of the room were determined to evaluate the effectiveness of the aerosolization system. In addition, sterile stainless-steel plates inoculated with S. aureus, P. aeruginosa, and Aspergillus spp. isolated from hospitalized patients and reference strains were used to evaluate the effectiveness of the system. For each organism, three plates were used: A (cleaned), B (not cleaned), and C (control). The A plates were treated with non-ionic surfactant and the aerosolization system, the B plates were subjected to the aerosolization system, and the plates C were positioned outside the room that was sanitized. Following sanitization, air and surface sampling was conducted, after which, swabs were processed for bacterial and fungal enumeration. The results showed that the air sanitization system had good efficacy for both bacteria and fungi in the air and on stainless-steel plates, particularly for the A plates