Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples.

Wastewater-based epidemiology has emerged as a promising and efficacious surveillance system for SARS-CoV-2 and other infectious diseases in many nations. The process typically involves wastewater concentration, nucleic acid extraction, amplification of selected genomic segments, and detection and quantification of the amplified genomic segment. This methodology can similarly be leveraged to detect and quantify infectious agents, such as SARS-CoV-2, in air samples. Initially, SARS-CoV-2 was presumed to spread primarily through close personal contact with droplets generated by an infected individual while speaking, sneezing, coughing, singing, or breathing. However, a growing number of studies have reported the presence of SARS-CoV-2 RNA in the air of healthcare facilities, establishing airborne transmission as a viable route for the virus. This study presents a composite of established protocols to facilitate environmental detection, quantification, and sequencing of viruses from both wastewater and air samples.

Interspecies transmission of porcine-originated G4P[6] rotavirus A between pigs and humans: a synchronized spatiotemporal approach.

As a leading viral cause of acute gastroenteritis in both humans and pigs, rotavirus A (RVA) poses a potential public health concern. Although zoonotic spillover of porcine RVA strains to humans is sporadic, it has been detected worldwide. The origin of chimeric human-animal strains of RVA is closely linked to the crucial role of mixed genotypes in driving reassortment and homologous recombination, which play a major role in shaping the genetic diversity of RVA. To better understand how genetically intertwined porcine and zoonotic human-derived G4P[6] RVA strains are, the present study employed a spatiotemporal approach to whole-genome characterization of RVA strains collected during three consecutive RVA seasons in Croatia (2018-2021). Notably, sampled children under 2 years of age and weanling piglets with diarrhea were included in the study. In addition to samples tested by real-time RT-PCR, genotyping of VP7 and VP4 gene segments was conducted. The unusual genotype combinations detected in the initial screening, including three human and three porcine G4P[6] strains, were subjected to next-generation sequencing, followed by phylogenetic analysis of all gene segments, and intragenic recombination analysis. Results showed a porcine or porcine-like origin for each of the eleven gene segments in all six RVA strains. The G4P[6] RVA strains detected in children most likely resulted from porcine-to-human interspecies transmission. Furthermore, the genetic diversity of Croatian porcine and porcine-like human G4P[6] strains was propelled by reassortment events between porcine and porcine-like human G4P[6] RVA strains, along with homologous intragenotype and intergenotype recombinations in VP4, NSP1, and NSP3 segments. Described concurrent spatiotemporal approach in investigating autochthonous human and animal RVA strains is essential in drawing relevant conclusions about their phylogeographical relationship. Therefore, continuous surveillance of RVA, following the One Health principles, may provide relevant data for assessing the impact on the protectiveness of currently available vaccines.

SARS-CoV-2 molecular epidemiology in Slovenia, January to September 2021.

BackgroundSequencing of SARS-CoV-2 PCR-positive samples was introduced in Slovenia in January 2021. Our surveillance programme comprised three complementary schemes: (A) non-targeted sequencing of at least 10% of samples, (B) sequencing of samples positive after PCR screening for variants of concern (VOC) and (C) sequencing as per epidemiological indication.AimWe present the analysis of cumulative data of the non-targeted surveillance of SARS-CoV-2 and variant-dependent growth kinetics for the five most common variants in Slovenia for the first 9 months of 2021.MethodsSARS-CoV-2 PCR-positive samples, from January to September 2021, were selected for sequencing according to the national surveillance plan. Growth kinetics studies were done on Vero E6 cells.ResultsAltogether 15,175 genomes were sequenced and 64 variants were detected, of which three successively prevailed. Variant B.1.258.17 was detected in ca 80% of samples in January and was replaced, within 9 weeks, by the Alpha variant. The number of cases decreased substantially during the summer of 2021. However, the introduction of the Delta variant caused a fourth wave and completely outcompeted other variants. Other VOC were only detected in small numbers. Infection of Vero E6 cells showed higher replication rates for the variants Alpha and Delta, compared with B.1.258.17, B.1.258, and B.1.1.70, which dominated in Slovenia before the introduction of the Alpha and Delta variants.ConclusionInformation on SARS-CoV-2 variant diversity provided context to the epidemiological data of PCR-positive cases, contributed to control of the initial spread of known VOC and influenced epidemiological measures.

Alternaria spore exposure in Bavaria, Germany, measured using artificial intelligence algorithms in a network of BAA500 automatic pollen monitors.

Although Alternaria spores are well-known allergenic fungal spores, automatic bioaerosol recognition systems have not been trained to recognize these particles until now. Here we report the development of a new algorithm able to classify Alternaria spores with BAA500 automatic bioaerosol monitors. The best validation score was obtained when the model was trained on both data from the original dataset and artificially generated images, with a validation unweighted mean Intersection over Union (IoU), also called Jaccard Index, of 0.95. Data augmentation techniques were applied to the training set. While some particles were not recognized (false negatives), false positives were few. The results correlated well with manual counts (mean of four Hirst-type traps), with R2 = 0.78. Counts from BAA500 were 1.92 times lower than with Hirst-type traps. The algorithm was then used to re-analyze the historical automatic pollen monitoring network (ePIN) dataset (2018-2022), which lacked Alternaria spore counts. Re-analysis of past data showed that Alternaria spore exposure in Bavaria was very variable, with the highest counts in the North (Marktheidenfeld, 154 m a.s.l.), and the lowest values close to the mountains in the South (Garmisch-Partenkirchen, 735 m a.s.l.). This approach shows that in our network future algorithms can be run on past datasets. Over time, the use of different algorithms could lead to misinterpretations as stemming from climate change or other phenological causes. Our approach enables consistent, homogeneous treatment of long-term series, thus preventing variability in particle counts owing to changes in the algorithms.

Centralized and decentralized wastewater-based epidemiology to infer COVID-19 transmission - A brief review.

Wastewater-based epidemiology has shown to be a promising and innovative approach to measure a wide variety of illicit drugs that are consumed in the communities. In the same way as for illicit drugs, wastewater-based epidemiology is a promising approach to understand the prevalence of viruses in a community-level. The ongoing coronavirus disease 2019 (COVID-19) pandemic created an unprecedented burden on public health and diagnostic laboratories all over the world because of the need for massive laboratory testing. Many studies have shown the applicability of a centralized wastewater-based epidemiology (WBE) approach, where samples are collected at WWTPs. A more recent concept is a decentralized approach for WBE where samples are collected at different points of the sewer system and at polluted water bodies. The second being particularly important in countries where there are insufficient connections from houses to municipal sewage pipelines and thus untreated wastewater is discharged directly in environmental waters. A decentralized approach can be used to focus the value of diagnostic tests in what we call targeted-WBE, by monitoring wastewater in parts of the population where an outbreak is likely to happen, such as student dorms, retirement homes and hospitals. A combination of centralized and decentralized WBE should be considered for an affordable, sustainable, and successful WBE implementation in high-, middle- and low-income countries.

Assessment of weather and atmospheric pollution as a co-factor in the spread of SARS-CoV-2.

BACKGROUND AND AIM: COVID-19 is a persistent and ongoing global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Non-anthropogenic factors, such as weather conditions and air quality are possible predictors of respiratory diseases, such as COVID-19. Weather conditions may also be a direct cause of biological interactions between SARS-CoV-2 and humans and vary widely between regions. The course of an epidemic is determined by several factors, including demographic and environmental parameters, many of which have an unknown correlation with COVID-19. The goal of this study is to access the influence of ground surface particulate matter and weather parameters on the dissemination of COVID-19 in Ljubljana, Slovenia. METHODS: Spearman rank correlation was used to investigate the association between new daily COVID-19 cases and weather data. RESULTS: The current study has found correlations between weather variables and PM particles with new cases of COVID-19. CONCLUSIONS: The correlations observed are highly dependent on the local policies that were in force during the period under study. The interaction between weather conditions and human behaviour may also be an important factor in understanding the relationship between weather and the spread of COVID -19.

Surface contamination with SARS-CoV-2: A systematic review.

Little is known about contaminated surfaces as a route of transmission for SARS-CoV- 2 and a systematic review is missing and urgently needed to provide guidelines for future research studies. As such, the aim of the present study was to review the current scientific knowledge and to summarize the existing studies in which SARS-CoV-2 has been detected in inanimate surfaces. This systematic review includes studies since the emergence of SARS-CoV-2, available in PubMed/MEDLINE and Scopus. Duplicate publications were removed, and exclusion criteria was applied to eliminate unrelated studies, resulting in 37 eligible publications. The present study provides the first overview of SARS-CoV-2 detection in surfaces. The highest detection rates occurred in hospitals and healthcare facilities with COVID-19 patients. Contamination with SARS-CoV-2 on surfaces was detected in a wide range of facilities and surfaces. There is a lack of studies performing viability testing for SARS-CoV-2 recovered from surfaces, and consequently it is not yet possible to assess the potential for transmission via surfaces.

Detection of SARS-CoV-2 RNA in hospital wastewater from a low COVID-19 disease prevalence area.

Previous studies on SARS-CoV and MERS-CoV reported the detection of viral RNA in the stool of both symptomatic and asymptomatic individuals. These clinical observations suggest that municipal and hospital wastewater from affected communities may contain SARS-CoV-2 RNA. Recent studies have also reported the presence of SARS-CoV-2 RNA in human feces. Wastewater-based epidemiology (WBE) is a promising approach to understand the prevalence of viruses in a given catchment population, as wastewater contains viruses from symptomatic and asymptomatic individuals. The current study reports the first detection of SARS-CoV-2 RNA in untreated wastewater in Slovenia. Two sizes of centrifugal filters were tested: 30 kDa and 10 kDA AMICON® Ultra-15 Centrifugal Filters, where 10 kDA resulted in a higher concentration factor and higher recovery efficiency. The results in hospital wastewater show that WBE can be used for monitoring COVID -19 and could be applied in municipal wastewater treatment plants as a potential complementary tool for public health monitoring at population level.