Viral Mutation Rates Research Articles

Genetic and phenotypic changes to Venezuelan equine encephalitis virus following treatment with β-D-N4-hydroxycytidine, an RNA mutagen

The high mutation rate of RNA viruses provides viral populations with the ability to adapt to new environments but also makes them vulnerable to extinction due to the deleterious effects of mutations, which is the conceptual basis for the antiviral activity of RNA mutagens. However, there are still gaps in the quantitative understanding of the dynamics between the mutations induced by an RNA mutagen and its effects on viral fitness. To address this, we used Venezuelan Equine Encephalitis Virus (VEEV) and the potent RNA mutagen β-d-N4-hydroxycytidine (NHC) as a model to analyze virus replication competency and mutation frequency following treatment in the total and replication-competent viral populations separately. We found that NHC induced transition mutations in a concentration dependent manner in the total population, while the replication-competent population maintained itself within an increased, yet narrow, mutation spectrum. The incorporation of NHC mainly happened during the positive sense RNA synthesis of VEEV. A growth kinetic analysis of VEEV population treated with NHC pointed to a lower but more diverse distribution in mutational fitness, demonstrating that NHC-induced mutations negatively and broadly affect the fitness of the virus. Together, our study provides mechanistic insight into how RNA mutagens affect viral population landscape and the potential of RNA mutagens as an antiviral strategy for alphaviruses.

A Comprehensive Review of Statistical Methods in Microbiology and epidemiology: A Data-Driven Approach

The rapid growth of computational power and big data analytics has transformed the landscape of statistical methods in microbiology and epidemiology. Advanced techniques such as machine learning, Bayesian inference, and network modeling are now being used alongside traditional statistical approaches. These methods offer unprecedented precision in identifying microbial patterns, tracking infectious diseases, and predicting outbreaks. This review highlights recent advances in statistical tools used in microbiology and epidemiology, particularly in analyzing antibiotic resistance, viral mutation rates, and epidemiological forecasting models for global pandemics such as COVID-19. The integration of novel statistical methodologies has improved our understanding of complex microbial interactions, resistance evolution, and the dynamics of infectious disease spread, enabling more informed public health interventions.

Understanding Viral Haemorrhagic Fevers: Virus Diversity, Vector Ecology, and Public Health Strategies.

Viral haemorrhagic fevers encompass a diverse group of severe, often life-threatening illnesses caused by viruses from multiple families, including Arenaviridae, Filoviridae, Flaviviridae, Hantaviridae, Nairoviridae, Peribunyaviridae, and Phenuiviridae. Characterised by fever and haemorrhagic symptoms, these diseases challenge public health systems by overwhelming healthcare facilities, complicating diagnostic processes, and requiring extensive resources for containment and treatment, especially in resource-limited settings. This discussion explores the intricate relationships between VHFs and their transmission vectors-both animal and arthropod-and examines the impact of ecological and geographic factors on disease spread. The primary transmission of VHFs typically occurs through direct contact with infected animals or via bites from haematophagous arthropods, facilitating zoonotic and, at times, human-to-human transmission. With an emphasis on the role of diverse wildlife, domesticated animals, and vectors such as mosquitoes and ticks in the epidemiology of VHFs, there is a recognised need for robust surveillance and strategic public health responses to manage outbreaks. This review discusses the necessity of interdisciplinary approaches that integrate virology, ecology, and public health to enhance diagnostic capabilities, develop vaccines and antivirals, and improve outbreak interventions. Exploring the ecological and biological dynamics of VHFs will help bolster a deeper understanding of these emerging viruses and underpin preparation for future outbreaks. The importance of enhanced global cooperation, continuous research, and collaboration to mitigate the public health threats posed by these complex infections is a central theme, serving as a foundational strategy to reinforce worldwide preparedness and response efforts. Future directions include addressing gaps in vaccine development and tailoring public health strategies to the unique challenges of managing VHFs, such as the rapid mutation rates of viruses, the need for cold chain logistics for vaccine distribution, and socio-economic barriers to healthcare access, in order to ensure readiness for and effective response to emerging threats worldwide.

A Comparative Analysis of COVID-19 Response Measures and Their Impact on Mortality Rate

(1) Background: The coronavirus disease 2019 (COVID-19) pandemic significantly affected the population worldwide, with varying responses implemented to control its spread. This study aimed to compare the epidemic data compiled by the World Health Organization (WHO) to understand the impact of the measures adopted by each country on the mortality rate. (2) Methods: The increase or decrease in the number of confirmed cases was understood in logarithmic terms, for which logarithmic growth rates “K” were used. The mortality rate was calculated as the percentage of deaths from the confirmed cases, which was also used for logarithmic comparison. (3) Results: Countries that effectively detected and isolated patients had a mortality rate 10 times lower than those who did not. Although strict lockdowns were once effective, they could not be implemented on an ongoing basis. After their cancellation, large outbreaks occurred because of medical breakdowns. The virus variants mutated with increased infectivity, which impeded the measures that were once effective, including vaccinations. Although the designs of mRNA vaccines were renewed, they could not keep up with the virus mutation rate. The only effective defence lies in steadily identifying and isolating patients. (4) Conclusions: these findings have crucial implications for the complete containment of the pandemic and future pandemic preparedness.

Exploration of Informatization Teaching Mode of College Students’ Psychological Education Courses under Cognitive Behavioral Theory

Abstract This paper discusses the informatization teaching mode of college students’ psychoeducation courses under the cognitive-behavioral theory, highlighting the importance of informatization in education and the changes in psychoeducation courses in the past 30 years. Effective identification of college students’ psychological characteristics, especially in the early identification and intervention of psychological crisis, was realized through graph neural networks and attention mechanisms. The study involved extensive data analysis, including the psychological identification of 189,134 images of students’ study screens and the analysis of the psychological characteristics of study screens from multiple dimensions. In addition, the study designed a psychoeducational management system based on graph convolutional neural networks, which can recognize students’ psychological states and provide real-time feedback. The analysis of college students’ psychological emotions in the COVID-19 epidemic revealed the association between students’ stress reactions and the development of the epidemic and the virus mutation rate, which emphasized the necessity of the innovative “Internet+” psychoeducational model. Overall, this study provides theoretical and practical support for improving the effectiveness of psychoeducation, and demonstrates the potential application of information technology in psychoeducation.

Evolutionary stability of antigenically escaping viruses.

Antigenic variation is the main immune escape mechanism for RNA viruses like influenza or SARS-CoV-2. While high mutation rates promote antigenic escape, they also induce large mutational loads and reduced fitness. It remains unclear how this cost-benefit trade-off selects the mutation rate of viruses. Using a traveling wave model for the coevolution of viruses and host immune systems in a finite population, we investigate how immunity affects the evolution of the mutation rate and other nonantigenic traits, such as virulence. We first show that the nature of the wave depends on how cross-reactive immune systems are, reconciling previous approaches. The immune-virus system behaves like a Fisher wave at low cross-reactivities, and like a fitness wave at high cross-reactivities. These regimes predict different outcomes for the evolution of nonantigenic traits. At low cross-reactivities, the evolutionarily stable strategy is to maximize the speed of the wave, implying a higher mutation rate and increased virulence. At large cross-reactivities, where our estimates place H3N2 influenza, the stable strategy is to increase the basic reproductive number, keeping the mutation rate to a minimum and virulence low.

Integrase inhibitors: current protagonists in antiretroviral therapy.

Since HIV was identified as the etiological agent of AIDS, there have been significant advances in antiretroviral therapy (ART)that hasreduced morbidity/mortality. Still, the viral genome's high mutation rate, suboptimal ARTregimens, incomplete adherence to therapyand poor control of the viral loadgenerate variants resistant to multiple drugs. Licensing over 30anti-HIV drugs worldwide, including integrase inhibitors, has marked a milestone since they are potent and well-tolerated drugs. In addition, they favor a faster recovery of CD4+ T cells. They also increase the diversity profile of the gut microbiota and reduce inflammatory markers. All of these highlight the importance of including them in different ART regimens.

Emergence of a second SARS-CoV-2 variant with a tremendous genetic leap from its ancestors.

The on-going emergence of the Omicron BA.2.86 variant is one of the major events in SARS-CoV-2 genetic evolution that remain enigmatic regarding the overall virus mutation rate, together with the emergence of the initial Omicron variant, BA.1. Indeed, the genomes of the Omicron BA.2.86 lineage, an offspring of the second major Omicron subvariant, BA.2, harbor 39 additional mutations in the spike compared to this ancestor. Here we comment on the phylogeny of BA.2.86, on the positions, and frequencies in other SARS-CoV-2, of mutations in its spike, and on the structural model of this protein that concentrates most of BA.2.86 additional mutations.

Vaccination strategies and virulent mutation spread: A game theory study

The frequent mutations of viruses often result in enhanced infectivity and pathogenicity, presenting substantial challenges to human populations worldwide. This study employs the SVIPIMR model, grounded in the principles of evolutionary game theory, to thoroughly investigate the dynamics of infectious diseases under a single-dose vaccination strategy. The model’s dynamics are divided into two main stages. Initially, during the epidemic phase, the model propagates within a season and ultimately stabilizes at a steady state. The basic reproduction number R0 produced at this stage is influenced by the basic reproduction numbers of two strains, R01 and R02. Our findings affirm that the persistence of the disease is guaranteed if both these numbers surpass one. Furthermore, it is observed that the strain with a higher basic reproduction number will invariably overshadow the other. In the following phase, the model assesses the impact of voluntary vaccination strategies and viral mutation rates on the spread of the disease, using two distinct strategy-updating rules derived from evolutionary game theory. Interestingly, our study reveals that a large-scale vaccination campaign at the epidemic’s onset can significantly increase the prevalence of the original strain. Additionally, despite the original strain’s higher transmission rate, the mutated strain comes to dominate the transmission process as the mutation rate progressively escalates. In summary, our research elucidates the dynamics of infectious diseases and highlights the potential effectiveness of augmenting vaccination rates and enhancing vaccine efficacy against mutated strains. These strategies could prove instrumental in curbing the spread of mutated strains, reducing the overall epidemic size, and improving the societal health impact.

Sangivamycin is preferentially incorporated into viral RNA by the SARS-CoV-2 polymerase

Sangivamycin (S) is an adenosine (A) nucleoside analog with low nanomolar antiviral activity against SARS-CoV-2 in vitro. Previously, low nanomolar antiviral efficacy was revealed when tested against multiple viral variants in several cell types. SARS-CoV-2 RNA isolated from live virus infected cells and the virions released from these cells was analyzed by mass spectrometry (MS) for S incorporation. Dose-dependent incorporation occurred up to 1.8 S per 1,000 nucleotides (49 S per genome) throughout the viral genomes isolated from both infected cells and viral particles, but this incorporation did not change the viral mutation rate. In contrast, host mRNA, affinity purified from the same infected and treated cells, contained little or no S. Sangivamycin triphosphate (STP) was synthesized to evaluate its incorporation into RNA by recombinant SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) under defined in vitro conditions. SARS-CoV-2 RdRp showed that S was not a chain terminator and S containing oligonucleotides templated as A. Though the antiviral mechanism remains to be determined, the data suggests that SARS-CoV-2 RdRp incorporates STP into SARS-CoV-2 RNA, which does not significantly impair viral RNA synthesis or the mutation rate.

Importance of genomic surveillance of SARS-CoV-2 in cats during reverse zoonosis events: potential viral evolution may occur.

The apparition of new variants of severe acute respiratory syndrome coronavirus 2 and lineages is constantly happening because of the high viral mutation rate. Since numerous reverse zoonosis events have been reported so far, genomic surveillance should be conducted in susceptible species to evaluate potential adaptations that may trigger the apparition of new variants. Here, we evaluate the evolution of the infection in a cat naturally infected in parallel with its owner, performing a comparative phylogenetic analysis. Sequencing analysis showed that both were infected with the Omicron BA.5/BF.1 lineage and revealed the presence of nucleotide substitution in the viral genome recovered from the cat with respect to the viral genome from the human sample. This nucleotide substitution (C11897A) produced the amino acid change Orf1a: Q3878K. Therefore, genomic surveillance in the case of reverse zoonosis events is still necessary in order to control possible adaptations of the virus to other susceptible species. IMPORTANCE Genomic surveillance of pets for severe acute respiratory syndrome coronavirus 2 is important to monitor the emergence of new variants of the virus associated with these animals. Pets can serve as a potential reservoir for the virus, and their close contact with humans increases the risk of transmission. By conducting genomic surveillance in pets, it is possible to detect and track new variants early on, allowing for more effective control measures to be put in place. This can help prevent the spread of these variants to human populations and potentially mitigate the impact of the pandemic. Furthermore, it may also provide insight into the evolution and spread of the virus within the animal population.

Evolutionary safety of lethal mutagenesis driven by antiviral treatment.

Nucleoside analogs are a major class of antiviral drugs. Some act by increasing the viral mutation rate causing lethal mutagenesis of the virus. Their mutagenic capacity, however, may lead to an evolutionary safety concern. We define evolutionary safety as a probabilistic assurance that the treatment will not generate an increased number of mutants. We develop a mathematical framework to estimate the total mutant load produced with and without mutagenic treatment. We predict rates of appearance of such virus mutants as a function of the timing of treatment and the immune competence of patients, employing realistic assumptions about the vulnerability of the viral genome and its potential to generate viable mutants. We focus on the case study of Molnupiravir, which is an FDA-approved treatment against Coronavirus Disease-2019 (COVID-19). We estimate that Molnupiravir is narrowly evolutionarily safe, subject to the current estimate of parameters. Evolutionary safety can be improved by restricting treatment with this drug to individuals with a low immunological clearance rate and, in future, by designing treatments that lead to a greater increase in mutation rate. We report a simple mathematical rule to determine the fold increase in mutation rate required to obtain evolutionary safety that is also applicable to other pathogen-treatment combinations.

Mathematical Modeling of SARS-CoV-2 Transmission between Minks and Humans Considering New Variants and Mink Culling.

We formulated and studied mathematical models to investigate control strategies for the outbreak of the disease caused by SARS-CoV-2, considering the transmission between humans and minks. Two novel models, namely SEIR and SVEIR, are proposed to incorporate human-to-human, human-to-mink, and mink-to-human transmission. We derive formulas for the reproduction number R0 for both models using the next-generation matrix technique. We fitted our model to the daily number of COVID-19-infected cases among humans in Denmark as an example, and using the best-fit parameters, we calculated the values of R0 to be 1.58432 and 1.71852 for the two-strain and single-strain models, respectively. Numerical simulations are conducted to investigate the impact of control measures, such as mink culling or vaccination strategies, on the number of infected cases in both humans and minks. Additionally, we investigated the possibility of the mutated virus in minks being transmitted to humans. Our results indicate that to control the disease and spread of SARS-CoV-2 mutant strains among humans and minks, we must minimize the transmission and contact rates between mink farmers and other humans by quarantining such individuals. In order to reduce the virus mutation rate in minks, culling or vaccination strategies for infected mink farms must also be implemented. These measures are essential in managing the spread of SARS-CoV-2 and its variants, protecting public health, and mitigating the potential risks associated with human-to-mink transmission.

Mutation rate, selection, andepistasis inferred from RNA virus haplotypes via neural posterior estimation.

RNA viruses are particularly notorious for their high levels of genetic diversity, which is generated through the forces of mutation and natural selection. However, disentangling these two forces is a considerable challenge, and this may lead to widely divergent estimates of viral mutation rates, as well as difficulties in inferring the fitness effects of mutations. Here, we develop, test, and apply an approach aimed at inferring the mutation rate and key parameters that govern natural selection, from haplotype sequences covering full-length genomes of an evolving virus population. Our approach employs neural posterior estimation, a computational technique that applies simulation-based inference with neural networks to jointly infer multiple model parameters. We first tested our approach on synthetic data simulated using different mutation rates and selection parameters while accounting for sequencing errors. Reassuringly, the inferred parameter estimates were accurate and unbiased. We then applied our approach to haplotype sequencing data from a serial passaging experiment with the MS2 bacteriophage, a virus that parasites Escherichia coli. We estimated that the mutation rate of this phage is around 0.2 mutations per genome per replication cycle (95% highest density interval: 0.051-0.56). We validated this finding with two different approaches based on single-locus models that gave similar estimates but with much broader posterior distributions. Furthermore, we found evidence for reciprocal sign epistasis between four strongly beneficial mutations that all reside in an RNA stem loop that controls the expression of the viral lysis protein, responsible for lysing host cells and viral egress. We surmise that there is a fine balance between over- and underexpression of lysis that leads to this pattern of epistasis. To recap, we have developed an approach for joint inference of the mutation rate and selection parameters from full haplotype data with sequencing errors and used it to reveal features governing MS2 evolution.

Mammalian ANP32A and ANP32B Proteins Drive Differential Polymerase Adaptations in Avian Influenza Virus.

ANP32 proteins, which act as influenza polymerase cofactors, vary between birds and mammals. In mammals, ANP32A and ANP32B have been reported to serve essential but redundant roles to support influenza polymerase activity. The well-known mammalian adaptation PB2-E627K enables influenza polymerase to use mammalian ANP32 proteins. However, some mammalian-adapted influenza viruses do not harbor this substitution. Here, we show that alternative PB2 adaptations, Q591R and D701N, also allow influenza polymerase to use mammalian ANP32 proteins, whereas other PB2 mutations, G158E, T271A, and D740N, increase polymerase activity in the presence of avian ANP32 proteins as well. Furthermore, PB2-E627K strongly favors use of mammalian ANP32B proteins, whereas D701N shows no such bias. Accordingly, PB2-E627K adaptation emerges in species with strong pro-viral ANP32B proteins, such as humans and mice, while D701N is more commonly seen in isolates from swine, dogs, and horses, where ANP32A proteins are the preferred cofactor. Using an experimental evolution approach, we show that the passage of viruses containing avian polymerases in human cells drove acquisition of PB2-E627K, but not in the absence of ANP32B. Finally, we show that the strong pro-viral support of ANP32B for PB2-E627K maps to the low-complexity acidic region (LCAR) tail of ANP32B. IMPORTANCE Influenza viruses naturally reside in wild aquatic birds. However, the high mutation rate of influenza viruses allows them to rapidly and frequently adapt to new hosts, including mammals. Viruses that succeed in these zoonotic jumps pose a pandemic threat whereby the virus adapts sufficiently to efficiently transmit human-to-human. The influenza virus polymerase is central to viral replication and restriction of polymerase activity is a major barrier to species jumps. ANP32 proteins are essential for influenza polymerase activity. In this study, we describe how avian influenza viruses can adapt in several different ways to use mammalian ANP32 proteins. We further show that differences between mammalian ANP32 proteins can select different adaptive changes and are responsible for some of the typical mutations that arise in mammalian-adapted influenza polymerases. These different adaptive mutations may determine the relative zoonotic potential of influenza viruses and thus help assess their pandemic risk.

A Multiplexed, Tiled PCR Method for Rapid Whole-Genome Sequencing of Infectious Spleen and Kidney Necrosis Virus (ISKNV) in Tilapia.

Tilapia farming is one of the most important sectors in aquaculture worldwide and of major importance to global food security. Infectious spleen and kidney necrosis virus (ISKNV) has been identified as an agent of high morbidity and mortality, threatening tilapia aquaculture. ISKNV was detected in Lake Volta, Ghana, in September 2018 and spread rapidly, with mortality rates between 60 and 90% and losses of more than 10 tonnes of fish per day. Understanding the spread and evolution of viral pathogens is important for control strategies. Here, we developed a tiled-PCR sequencing approach for the whole-genome sequencing of ISKNV, using long read sequencing to enable field-based, real-time genomic surveillance. This work represents the first use of tiled-PCR for whole genome recovery of viruses in aquaculture, with the longest genome target (>110 kb dsDNA) to date. Our protocol was applied to field samples collected from the ISKNV outbreaks from four intensive tilapia cage culture systems across Lake Volta, between October 2018 and May 2022. Despite the low mutation rate of dsDNA viruses, 20 single nucleotide polymorphisms accumulated during the sampling period. Droplet digital PCR identified a minimum requirement of template in a sample to recover 50% of an ISKNV genome at 275 femtograms (2410 viral templates per 5 µL sequencing reaction). Overall, tiled-PCR sequencing of ISKNV provides an informative tool to assist in disease control in aquaculture.

Infection Defects of RNA and DNA Viruses Induced by Antiviral RNA Interference.

Immune recognition of viral genome-derived double-stranded RNA (dsRNA) molecules and their subsequent processing into small interfering RNAs (siRNAs) in plants, invertebrates, and mammals trigger specific antiviral immunity known as antiviral RNA interference (RNAi). Immune sensing of viral dsRNA is sequence-independent, and most regions of viral RNAs are targeted by virus-derived siRNAs which extensively overlap in sequence. Thus, the high mutation rates of viruses do not drive immune escape from antiviral RNAi, in contrast to other mechanisms involving specific virus recognition by host immune proteins such as antibodies and resistance (R) proteins in mammals and plants, respectively. Instead, viruses actively suppress antiviral RNAi at various key steps with a group of proteins known as viral suppressors of RNAi (VSRs). Some VSRs are so effective in virus counter-defense that potent inhibition of virus infection by antiviral RNAi is undetectable unless the cognate VSR is rendered nonexpressing or nonfunctional. Since viral proteins are often multifunctional, resistance phenotypes of antiviral RNAi are accurately defined by those infection defects of VSR-deletion mutant viruses that are efficiently rescued by host deficiency in antiviral RNAi. Here, we review and discuss in vivo infection defects of VSR-deficient RNA and DNA viruses resulting from the actions of host antiviral RNAi in model systems.

Modeling the effects of drugs of abuse on within-host dynamics of two HIV species

Injection drug use is one of the most significant risk factors associated with contracting human immunodeficiency virus (HIV), and drug users infected with HIV suffer from a higher viral load and rapid disease progression. While replication of HIV may result in many mutant viruses that can escape recognition of the host’s immune response, the presence of morphine (a drug of abuse) can decrease the viral mutation rate and cellular immune responses. This study develops a mathematical model to explore the effects of morphine-altered mutation and cellular immune response on the within-host dynamics of two HIV species, a wild-type and a mutant. Our model predicts that the morphine-altered mutation rate and cellular immune response allow the wild-type virus to outcompete the mutant virus, resulting in a higher set point viral load and lower CD4 count. We also compute the basic reproduction numbers and show that the dominant species is determined by morphine concentration, with the mutant dominating below and the wild-type dominating above a threshold. Furthermore, we identified three biologically relevant equilibria, infection-free, mutant-only, and coexistence, which are completely characterized by the fitness cost of mutation, mutant escape rate, and morphine concentration.

Quasispecies Nature of RNA Viruses: Lessons from the Past.

Viral quasispecies are distinct but closely related mutants formed by the disparity in viral genomes due to recombination, mutations, competition, and selection pressure. Theoretical derivation for the origin of a quasispecies is owed to the error-prone replication by polymerase and mutants of RNA replicators. Here, we briefly addressed the theoretical and mathematical origin of quasispecies and their dynamics. The impact of quasispecies for major salient human pathogens is reviewed. In the current global scenario, rapid changes in geographical landscapes favor the origin and selection of mutants. It comes as no surprise that a cauldron of mutants poses a significant risk to public health, capable of causing pandemics. Mutation rates in RNA viruses are magnitudes higher than in DNA organisms, explaining their enhanced virulence and evolvability. RNA viruses cause the most devastating pandemics; for example, members of the Orthomyxoviridae family caused the great influenza pandemic (1918 flu or Spanish flu), the SARS (severe acute respiratory syndrome) and MERS (Middle East respiratory syndrome) outbreak, and the human immunodeficiency viruses (HIV), lentiviruses of the Retroviridae family, caused worldwide devastation. Rapidly evolving RNA virus populations are a daunting challenge for the designing of effective control measures like vaccines. Developing awareness of the evolutionary dispositions of RNA viral mutant spectra and what influences their adaptation and virulence will help curtail outbreaks of past and future pathogens.

Hands off the Mink! Using Environmental Sampling for SARS-CoV-2 Surveillance in American Mink.

Throughout the COVID-19 pandemic, numerous non-human species were shown to be susceptible to natural infection by SARS-CoV-2, including farmed American mink. Once infected, American mink can transfer the virus from mink to human and mink to mink, resulting in a high rate of viral mutation. Therefore, outbreak surveillance on American mink farms is imperative for both mink and human health. Historically, disease surveillance on mink farms has consisted of a combination of mortality and live animal sampling; however, these methodologies have significant limitations. This study compared PCR testing of both deceased and live animal samples to environmental samples on an active outbreak premise, to determine the utility of environmental sampling. Environmental sampling mirrored trends in both deceased and live animal sampling in terms of percent positivity and appeared more sensitive in some low-prevalence instances. PCR CT values of environmental samples were significantly different from live animal samples' CT values and were consistently high (mean CT = 36.2), likely indicating a low amount of viral RNA in the samples. There is compelling evidence in favour of environmental sampling for the purpose of disease surveillance, specifically as an early warning tool for SARS-CoV-2; however, further work is needed to ultimately determine whether environmental samples are viable sources for molecular epidemiology investigations.