Survival of viral haemorrhagic septicaemia virus and infectious haematopoietic necrosis virus in the environment and dried on stainless steel

Identification of environmental and methodological factors driving variability of Pepper Mild Mottle Virus (PMMoV) across three wastewater treatment plants in the City of Toronto

PMMoV has been widely used to normalize the concentration of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA, influenza, and respiratory syncytial virus (RSV) to account for variations in the fecal content of wastewater. PMMoV is also used as an internal RNA recovery control for wastewater-based epidemiology (WBE) tests. While potentially useful for the interpretation of WBE data, previous studies have suggested that PMMoV concentration can be affected by various physico-chemical characteristics of wastewater. There is also the possibility that laboratory methods, particularly the variability in centrifugation steps to remove supernatant from pellets can cause PMMoV variability. The goal of this study is to improve our understanding of the main drivers of PMMoV variability by assessing the relationship between PMMoV concentration, the physico-chemical characteristics of wastewater, and the methodological approach for concentrating wastewater samples. We analyzed 24-hour composite wastewater samples collected from the influent stream of three wastewater treatment plants (WWTPs) located in the City of Toronto, Ontario, Canada. Samples were collected 3 to 5 times per week starting from the beginning of March 2021 to mid-July 2023. The influent flow rate was used to partition the data into wet and dry weather conditions. Physico-chemical characteristics (e.g., total suspended solids (TSS), biological oxygen demand (BOD), alkalinity, electrical conductivity (EC), and ammonia (NH3)) of the raw wastewater were measured, and PMMoV was quantified. Spatial and temporal variability of PMMoV was observed throughout the study period. PMMoV concentration was significantly higher during dry weather conditions. Multiple linear regression analysis demonstrates that the number and type of physico-chemical parameters that drive PMMoV variability are site-specific, but overall BOD and alkalinity were the most important predictors. Differences in PMMoV concentration for a single WWTP between two different laboratory methods, along with a weak correlation between pellet mass and TSS using one method may indicate that differences in sample concentration and subjective subsampling bias could alter viral recovery and introduce variability to the data.

Decay of HCoV-OC43 infectivity is lower in cell debris-containing media than in fresh culture media

In the quantitative description of viral dynamics within cell cultures and, more broadly, in modeling within-host viral infections, a question that commonly arises is whether the degradation of a fraction of the virus could be disregarded in comparison with the massive synthesis of new viral particles. Surprisingly, quantitative data on the synthesis and degradation rates of RNA viruses in cell cultures are scarce. In this study, we investigated the decay of the human betacoronavirus OC43 (HCoV-OC43) infectivity in cell culture lysates and in fresh media. Our findings revealed a significantly slower viral decay rate in the medium containing lysate cells compared to the fresh medium. This observation suggests that the presence of cellular debris from lysed cells may offer protection or stabilize virions, slowing down their degradation. Moreover, the growth rate of HCoV-OC43 infectivity is significantly higher than degradation as long as there are productive cells in the medium, suggesting that, as a first approximation, degradation can be neglected during early infection.

The aquaculture disease network model (AquaNet-Mod): A simulation model to evaluate disease spread and controls for the salmonid industry in England and Wales

Infectious disease causes significant mortality in wild and farmed systems, threatening biodiversity, conservation and animal welfare, as well as food security. To mitigate impacts and inform policy, tools such as mathematical models and computer simulations are valuable for predicting the potential spread and impact of disease. This paper describes the development of the Aquaculture Disease Network Model, AquaNet-Mod, and demonstrates its application to evaluating disease epidemics and the efficacy of control, using a Viral Haemorrhagic Septicaemia (VHS) case study. AquaNet-Mod is a data-driven, stochastic, state-transition model. Disease spread can occur via four different mechanisms, i) live fish movement, ii) river based, iii) short distance mechanical and iv) distance independent mechanical. Sites transit between three disease states: susceptible, clinically infected and subclinically infected. Disease spread can be interrupted by the application of disease mitigation measures and controls such as contact tracing, culling, fallowing and surveillance. Results from a VHS case study highlight the potential for VHS to spread to 96% of sites over a 10 year time horizon if no disease controls are applied. Epidemiological impact is significantly reduced when live fish movement restrictions are placed on the most connected sites and further still, when disease controls, representative of current disease control policy in England and Wales, are applied. The importance of specific disease control measures, particularly contact tracing and disease detection rate, are also highlighted. The merit of this model for evaluation of disease spread and the efficacy of controls, in the context of policy, along with potential for further application and development of the model, for example to include economic parameters, is discussed.

Environmental DNA/RNA for pathogen and parasite detection, surveillance, and ecology

Detection of pathogens, parasites, and other symbionts in environmental samples via eDNA/eRNA (collectively eNA) is an increasingly important source of information about their occurrence and activity. There is great potential for using such detections as a proxy for infection of host organisms in connected habitats, for pathogen monitoring and surveillance, and for early warning systems for disease. However, many factors require consideration, and appropriate methods developed and verified, in order that eNA detections can be reliably interpreted and adopted for surveillance and assessment of disease risk, and potentially inclusion in international standards, such as the World Organisation for Animal Health guidelines. Disease manifestation results from host-symbiont-environment interactions between hosts, demanding a multifactorial approach to interpretation of eNA signals.

Evaluation of intra- and inter-lab variability in quantifying SARS-CoV-2 in a state-wide wastewater monitoring network

In December 2019, SARS-CoV-2, the virus that causes coronavirus disease 2019, was first reported and subsequently triggered a global pandemic. Wastewater monitoring, a strategy for quantifying viral gene concentrations from wastewater influents within a community, has served as an early warning and management tool for the spread of SARS-CoV-2 in a community. Ohio built a collaborative statewide wastewater monitoring network that is supported by eight labs (university, government, and commercial laboratories) with unique sample processing workflows. Consequently, we sought to characterize the variability in wastewater monitoring results for network labs. Across seven trials between October 2020 and November 2021, eight participating labs successfully quantified two SARS-CoV-2 RNA targets and human fecal indicator virus targets in wastewater sample aliquots with reproducible results, although recovery efficiencies of spiked surrogates ranged from 3 to 75%. When SARS-CoV-2 gene fragment concentrations were adjusted for recovery efficiency and flow, the proportion of variance between laboratories was minimized, serving as the best model to account for between-lab variance. Another adjustment factor (alone and in different combinations with the above factors) considered to account for sample and measurement variability includes fecal marker normalization. Genetic quantification variability can be attributed to many factors, including the methods, individual samples, and water quality parameters. In addition, statistically significant correlations were observed between SARS-CoV-2 RNA and COVID-19 case numbers, supporting the notion that wastewater surveillance continues to serve as an effective monitoring tool. This study serves as a real-time example of multi-laboratory collaboration for public health preparedness for infectious diseases.

Persistence of Tilapia tilapinevirus in fish rearing and environmental water and its ability to infect cell line

Tilapia tilapinevirus, or Tilapia Lake Virus (TiLV), is a RNA virus associated with mass morbidity and mortality in tilapia, leading to severe economic losses for global tilapia aquaculture. In this study, we investigated the persistence of TiLV in water by spiking sterile distilled water (SDW), freshwater collected from rearing fish tanks (FW) and natural pond water (PW) at 27°C as a representative of environmental water conditions with 0.6 ml of stock virus (3.18 × 10⁷ viral copies/ml of water). The water samples were filtered through an electronegative charge membrane and quantified using reverse transcriptase quantitative PCR at 0, 3, 5, 7, 10 and 14 days post-inoculation. The results revealed that TiLV RNA in SDW was reduced by 1.34 log₁₀ in 14 days. A similar approximately 4 log₁₀ removal of the virus in FW and PW was observed at 3 and 7 days, respectively. Moreover, the infectivity of TiLV was further studied; the virus lost its infectivity in E-11 cells after 1 day in SDW, FW and PW water samples, even though the virus was spiked 10 more times than in the viral persistence study. Taken together, the results could be applied to improving biosecurity practices in tilapia farms by disinfecting or resting reservoir water for at least three to five days prior to stocking tilapia, to limit the spread of TiLV.

Effect of selected wastewater characteristics on estimation of SARS-CoV-2 viral load in wastewater

Wastewater-based epidemiology has been used as a tool for surveillance of COVID-19 infections. This approach is dependent on the detection and quantification of SARS-CoV-2 RNA in untreated/raw wastewater. However, the quantification of the viral RNA could be influenced by the physico-chemical properties of the wastewater. This study presents the first use of Adaptive Neuro-Fuzzy Inference System (ANFIS) to determine the potential impact of physico-chemical characteristics of wastewater on the detection and concentration of SARS-CoV-2 RNA in wastewater. Raw wastewater samples from four wastewater treatment plants were investigated over four months. The physico-chemical characteristics of the raw wastewater was recorded, and the SARS-CoV-2 RNA concentration determined via amplification with droplet digital polymerase chain reaction. The wastewater characteristics considered were chemical oxygen demand, flow rate, ammonia, pH, permanganate value, and total solids. The mean SARS-CoV-2 RNA concentrations ranged from 648.1(±514.6) copies/mL to 1441.0(±1977.8) copies/mL. Among the parameters assessed using the ANFIS model, ammonia and pH showed significant association with the concentration of SARS-CoV-2 RNA measured. Increasing ammonia concentration was associated with increasing viral RNA concentration and pH between 7.1 and 7.4 were associated with the highest SARS-CoV-2 concentration. Other parameters, such as total solids, were also observed to influence the viral RNA concentration, however, this observation was not consistent across all the wastewater treatment plants. The results from this study indicate the importance of incorporating wastewater characteristic assessment into wastewater-based epidemiology for a robust and accurate COVID-19 surveillance.

Survival of viral haemorrhagic septicaemia virus and infectious haematopoietic necrosis virus in the environment and dried on stainless steel

Viral haemorrhagic septicaemia virus (VHSV) and infectious haematopoietic necrosis virus (IHNV) are important viral pathogens posing a serious threat to salmonid fish. Survival of two isolates of IHNV and one of VHSV was assessed at temperatures ranging from 4 to 25°C: (a) after drying on stainless steel, (b) in cell culture medium, (c) in filtered river water, (d) in unfiltered river water, and (e) survival, adsorption and desorption in river sediment and five typical soil types. The viruses survived 1 hr to > 84 days depending on the conditions. Survival was inversely related to temperature and organic and inorganic content. Both viruses remained infectious after being dried on stainless steel for several weeks highlighting the risk of mechanical transmission and persistence in a dry environment. Both adsorbed to the soils from the river water inoculum, with titres between 5.56x10⁴ and 2.58x10⁸ TCID₅₀/ml after 1 hr. Clay soils adsorbed the least virus but had the greatest decrease in the river water inoculum (undetectable in ≤ 1 hr), and there was no desorption. Virus desorbed from the other soils into the surrounding water at different rates dependant on soil type (longest desorption was from chalk loam and sandy soil—detected at 28 days). When desorption was no longer detectable, virus persisted, adsorbed to the soil and remained infectious (the longest adsorption was detected in clay loam for ≥ 49 days, but all the viruses adsorbed to soils were likely to have survived longer than that detected, based on their rate of decay). The long survival of the viruses, particularly at cooler temperatures, highlights the risk of survival in the environment and waterborne spread. The data presented here are highly relevant for assessing risk of pathogen introduction via fomites (stainless steel) and for deciding on best control measures in the context of disease outbreaks.