Wastewater Levels of Respiratory Syncytial Virus Associated with Influenza-like Illness Rates in Children-A Case Study in Larissa, Greece (October 2022-January 2023).

The emergence of the COVID-19 pandemic has led to significant progress in the field of wastewater-based surveillance (WBS) of respiratory pathogens and highlighted its potential for a wider application in public health surveillance. This study aimed to evaluate whether monitoring of respiratory syncytial virus (RSV) in wastewater can provide a comprehensive picture of disease transmission at the community level. The study was conducted in Larissa (Central Greece) between October 2022 and January 2023. Forty-six wastewater samples were collected from the inlet of the wastewater treatment plant of Larissa and analyzed with a real-time reverse transcription polymerase chain reaction (RT-PCR) based method. RSV and SARS-CoV-2 wastewater viral loads (genome copies/100,000 inhabitants) were analyzed against sentinel surveillance data on influenza-like illness (ILI) to identify potential associations. Univariate linear regression analysis revealed that RSV wastewater viral load (lagged by one week) and ILI notification rates in children up to 14 years old were strongly associated (std. Beta: 0.73 (95% CI: 0.31-1.14), p = 0.002, R2 = 0.308). A weaker association was found between SARS-CoV-2 viral load and ILI rates in the 15+ age group (std. Beta: 0.56 (95% CI: 0.06-1.05), p = 0.032, R2 = 0.527). The results support the incorporation of RSV monitoring into existing wastewater-based surveillance systems.

Wastewater monitoring as a supplementary surveillance tool for capturing SARS-COV-2 community spread. A case study in two Greek municipalities.

A pilot study was conducted from late October 2020 until mid-April 2021, aiming to examine the association between SARS-CoV-2 RNA concentrations in untreated wastewater and recorded COVID-19 cases in two Greek municipalities. A population of Random Forest and Linear Regression Machine Learning models was trained and evaluated incorporating the concentrations of SARS-CoV-2 RNA in 111 wastewater samples collected from the inlets of two Wastewater Treatment Plants, along with physicochemical parameters of the wastewater influent. The model's predictions were adequately associated with the 7-day cumulative cases with the correlation coefficients (after 5-fold cross validation) ranging from 0.754 to 0.960 while the mean relative errors ranged from 30.42% to 59.46%. Our results provide indications that wastewater-based predictions can be applied in diverse settings and in prolonged time periods, although the accuracy of these predictions may be mitigated. Wastewater-based epidemiology can support and strengthen epidemiological surveillance.

Preparing dental schools to refunction safely during the COVID-19 pandemic: an infection prevention and control perspective.

In late 2019 a novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in China and spread throughout the world over a short period of time causing a pandemic of a respiratory disease named coronavirus disease 2019 (COVID-19). SARS-CoV-2 is easily transmitted from person to person through respiratory droplets and direct contact. The scarce available data indicate that dental healthcare personnel are at increased risk for acquisition of infection. Following the lockdown lifting, dental schools should be prepared to refunction safely and provide essential educational and healthcare services while protecting their students, patients, and personnel. The generation of aerosols in dental practice, in association with the high-transmissibility of SARS-CoV-2 through aerosol-generation procedures, the simultaneous provision of dental services to patients in the same areas, and the fact that asymptomatic and pre-symptomatic infected persons may transmit the virus, render the implementation of specific infection prevention and control measures imperative for dental schools. Herein we review the few evidence-based data available to guide infection prevention and control measures for COVID-19 in dental schools.