Shedding of SARS-CoV-2 in feces and urine and its potential role in person-to-person transmission and the environment-based spread of COVID-19

Optimized methods for wastewater SARS-CoV-2 surveillance at military installations: direct extraction showed higher recoveries relative to polyethylene glycol precipitation

Wastewater surveillance is an economical approach to track community level pathogen prevalence and outbreak monitoring. Monitoring pathogens of public health concern in military installation wastewater can help mitigation efforts to protect service members. We used laboratory-prepared samples seeded with heat-inactivated SARS-CoV-2 and optimized two methods for wastewater SARS-CoV-2 surveillance. The first one is based on polyethylene glycol/sodium chloride precipitation to which fetal bovine serum (FBS) was added during precipitation (FBS-PEG/NaCl) followed by nucleic acid extraction and SARS-CoV-2 N1 and N2 specific RT-qPCR. This FBS-PEG/NaCl method (method-1) produced a visible pellet and improved recoveries (∼ 84.13 ± 9.12 % for N1 and 71.59 ± 9.77 % for N2, with 300 μL of added FBS) relative to standard PEG/NaCl method (no FBS; ∼7.98 ± 8.24 % for N1 and ∼ 7.42 ± 5.21 % for N2). The second one is a magnetic bead-based improved direct extraction method (method-2) wherein we showed that addition of carrier RNA (polyadenylic acid or poly-A) during extraction improved viral RNA recovery relative to direct extraction without poly-A. We evaluated the analytical sensitivity (process limit of detection; PLOD) and process efficiency of method-1 and method-2. The PLOD was 2,500 genome copies (GC)/L for method-1 and 12,500 GC/L for method-2. Controlled samples with serial dilutions of virus showed that method-1 is as effective in recovering the virus as method-2 at all concentrations of the virus tested. SARS-CoV-2 temporal trends were analyzed in 52 wastewater samples by method-2 of which the first 22 were also analyzed by method-1. SARS-CoV-2 trends correlate well in both approaches while the magnitude (copies/L) was much higher with method-2 (N1: 0.25-2.3 log; N2: 0.058-1.89 log) than with method-1. Possible reason for lower recoveries by method-1 with wastewater samples and the advantages of using controlled samples for method optimization are discussed. Better recoveries and higher throughput suggest improved direct extraction (method-2) is advantageous for wastewater SARS-CoV-2 surveillance.

Aircraft lavatory wastewater surveillance for movement of antimicrobial resistance genes: a proof-of-concept study

Long-haul flight aircraft wastewater may serve as a representative microbial footprint, often of mixed country origin, offering valuable insight into the movement of pathogens and antimicrobial resistance (AMR) on a global scale. Herein, we present a proof-of-concept for aircraft-based surveillance of AMR by investigating lavatory wastewater samples from 44 repatriation flights to Australia departing from nine countries. Profiles of pathogens including ESKAPE pathogens (Salmonella spp., Mycobacterium spp., Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) and antibiotic resistance genes (ARGs) (aph(3')-IIIa, blaNDM-1, blaCTX_M-1, blaKPC, ermB, qnrS, sul1, tetM, and vanA) were investigated along with traditional fecal indicator bacteria (Escherichia coli and Enterococcus spp.) and fecal/urine marker genes (Bacteroides HF183, Carjivirus, human polyomavirus, and a cryptic plasmid pBI143) using quantitative PCR (qPCR). Two fecal indicator bacteria (FIB) and four human fecal/urine marker genes were detected in all aircraft wastewater samples. Detection rates for ESKAPE pathogens ranged from 6.8% (S. aureus) to 84.1% (K. pneumoniae). Of all ARG targets, aph(3')-IIIa, ermB, qnrS, sul1, and tetM were detected in all wastewater samples, whereas blaKPC and vanA were not detected in any of the samples. Results reflected geographic differences in ARG abundance originating from departure countries/continents and suggested a potential risk of importing ARGs that might be rare in local wastewater systems. The loss of nucleic acid targets was less than 10% over a 24 h incubation in the presence of disinfectants, suggesting that nucleic acids are resilient enough to persist in aircraft wastewater over the maximum duration of a flight.IMPORTANCEIn the context of international connectedness, aircraft-based wastewater surveillance should be viewed as a beyond-national tool to enhance global AMR management and foster international cooperation.

Advances in Wastewater-Based Epidemiology for Pandemic Surveillance: Methodological Frameworks and Future Perspectives

Wastewater-based epidemiology (WBE) has emerged as a transformative approach for community-level health monitoring, particularly during the COVID-19 pandemic. This review critically examines the methodological framework of WBE systems through the following three core components: (1) sampling strategies that address spatial-temporal variability in wastewater systems, (2) comparative performance of different platforms in pathogen detection, and (3) predictive modeling integrating machine learning approaches. We systematically analyze how these components collectively overcome the limitations of conventional surveillance methods through early outbreak detection, asymptomatic case identification, and population-level trend monitoring. While highlighting technical breakthroughs in viral concentration methods and variant tracking through sequencing, the review also identifies persistent challenges, including data standardization, cost-effectiveness concerns in resource-limited settings, and ethical considerations in public health surveillance. Drawing insights from global implementation cases, we propose recommendations for optimizing each operational phase and discuss emerging applications beyond pandemic response. This review highlights WBE as an indispensable tool for modern public health, whose methodological refinements and cross-disciplinary integration are critical for transforming pandemic surveillance from reactive containment to proactive population health management.

Uncovering SARS-CoV-2 Molecular Epidemiology Across the Pandemic Transition: Insights into Transmission in Clinical and Environmental Samples

BACKGROUND

Respiratory droplets are the main way in which the COVID-19 pandemic's causal agent, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), spreads. Angiotensin-converting enzyme 2 (ACE2) receptors, especially in lung cells, allow the virus to enter host cells. However, ACE2 expression in intestinal cells has sparked worries about possible fecal transfer, particularly in poor-sanitation areas like India.

METHODS

Between July 2021 and July 2024, clinical (nasopharyngeal, saliva, and stool samples) and sewage samples were collected from outpatient departments and sewage treatment plants (STPs), respectively, from the high-population-density area under study in order to investigate SARS-CoV-2 transmission.

RESULTS

This proof-of-concept study analyzed clinical samples from n = 60 COVID-19-positive patients at a central Indian tertiary care hospital and n = 156 samples from hospital STPs. Variants of SARS-CoV-2 were found using qRT-PCR and Next-Generation Sequencing (NGS). Of the n = 37 qRT-PCR-positive patients who gave their assent, 30% had stool samples that tested positive for viral RNA. In 70% of positive NP and 65% of positive saliva samples, along with two stool samples from immunocompromised patients, the live virus was identified using Vero E6 cell lines. Although 18% of the tests reported qRT-PCR-positive results, no live virus was detected in sewage samples despite NGS validation. The detection of SARS-CoV-2 in the absence of confirmed clinical cases may indicate the silent circulation of the virus within the community, suggesting that sewage surveillance can serve as an early warning system before an outbreak occurs.

CONCLUSIONS

These findings provide critical insights into the importance of continuous environmental surveillance, silent virus circulation, changes in viral epidemiology throughout the years, and strategies to mitigate coronavirus outbreaks.

Wastewater Speaks: Evaluating SARS-CoV-2 Surveillance, Sampling Methods, and Seasonal Infection Trends on a University Campus

Wastewater surveillance has emerged as a cost-effective and equitable approach for tracking the spread of SARS-CoV-2. In this study, we monitored the prevalence of SARS-CoV-2 on a university campus over three years (2021-2023) using wastewater-based epidemiology (WBE). Wastewater samples were collected from 11 manholes on campus, each draining wastewater from a corresponding dormitory building, and viral RNA concentrations were measured using reverse transcription-quantitative PCR (RT-qPCR). Weekly clinical case data were also obtained from the university health center. A strong positive and significant correlation was observed between Grab and Composite sampling methods, supporting their robustness as equally effective approaches for sample collection. Specifically, a strong correlation was observed between Aggie Village 4 Grab and Aggie Village 4 Composite samples (R2 = 0.84, p = 0.00) and between Barbee Grab and Barbee Composite samples (R2 = 0.80, p = 0.00). Additionally, higher viral RNA copies of SARS-CoV-2 (N1 gene) were detected during the Spring semester compared to the Fall and Summer semesters. Notably, elevations in raw N1 concentrations were observed shortly after the return of college students to campus, suggesting that these increases were predominantly associated with students returning at the beginning of the Fall and Spring semesters (January and August). To account for variations in fecal loading, SARS-CoV-2 RNA concentrations were normalized using Pepper Mild Mottle Virus (PMMoV), a widely used viral fecal biomarker. However, normalization using PMMoV did not improve correlations between SARS-CoV-2 RNA levels and clinical case data. Despite these findings, our study did not establish WBE as a consistently reliable complement to clinical testing in a university campus setting, contrary to many retrospective studies. One key limitation was that numerous off-campus students did not contribute to the campus wastewater system corresponding to the monitored dormitories. However, some off-campus students were still subjected to clinical testing at the university health center under mandated protocols. Moreover, the university health center discontinued reporting cases per dormitory after 2021, making direct comparisons more challenging. Nevertheless, this study highlights the continued value of WBE as a surveillance tool for monitoring infectious diseases and provides critical insights into its application in campus environments.

Temporal dynamics of SARS-CoV-2 shedding in feces and saliva: a longitudinal study in Norfolk, United Kingdom during the 2021-2022 COVID-19 waves

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was originally described as a respiratory illness; however, it is now known that the infection can spread to the gastrointestinal tract, leading to shedding in feces potentially being a source of infection through wastewater. We aimed to assess the prevalence and persistence of SARS-CoV-2 in fecal and saliva samples for up to 7 weeks post-detection in a cohort of 98 participants from Norfolk, United Kingdom using RT-qPCR. Secondary goals included sequencing the viral isolates present in fecal samples and comparing the genetic sequence with isolates in the saliva of the same participant. Furthermore, we sought to identify factors associated with the presence of detectable virus in feces or saliva after a positive SARS-CoV-2 test. Saliva remained SARS-CoV-2-positive for longer periods compared to fecal samples, with all positive fecal samples occurring within 4 weeks of the initial positive test. Detectable virus in fecal samples was positively associated with the number of symptoms experienced by the individuals. Based on the genome sequencing and taxonomic classification of the virus, one donor had a distinct strain in feces compared to saliva on the same collection date, which suggests that different isolates could dominate different tissues. Our results underscore the importance of considering multiple biological samples, such as feces, in the detection and characterization of SARS-CoV-2, particularly in clinical procedures involving patient fecal material transplant. Such insights could contribute to enhancing the safety protocols surrounding the handling of patient samples and aid in devising effective strategies for mitigating the spread of coronavirus disease.

IMPORTANCE

This study provides critical insights into the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shedding in fecal and saliva samples, demonstrating that while viral RNA is detectable shortly after diagnosis, its prevalence declines rapidly over the course of infection. Detection was more common among individuals with more concurrent symptoms, emphasizing the potential influence of symptom burden on viral persistence. By analyzing a United Kingdom-based cohort, this study fills a significant gap in the literature, which has largely focused on Asian and North American populations, offering a geographically unique perspective on viral shedding dynamics. Our findings contribute to a globally relevant understanding of SARS-CoV-2 shedding by revealing differences in shedding durations compared to studies from other regions. These differences highlight the need for geographically diverse research to account for variations in genetic background, immune response, and healthcare practices.

Measuring SARS-CoV-2 RNA in Bangkok wastewater treatment plants and estimating infected population after fully opening the country in 2023, Thailand

Wastewater-based epidemiology (WBE) has been employed for monitoring the presence of SARS-CoV-2 infected population. Herein, the study aims to apply the WBE for surveillance and monitoring SARS-CoV-2 in Bangkok, where the highest official covid-19 cases reported in Thailand, during the fully opening for international tourists in early 2023. A total of 200 wastewater samples (100 influent and 100 effluent samples) were collected from 10 wastewater treatment plants (WWTPs) during January-May 2023. SARS-CoV-2 RNA was detected by real time qRT-PCR with accounting for 51% (102/200). Of these, 88% (88/100) and 14% (14/100) were detected in influent and effluent samples, respectively. The SARS-CoV-2 RNA concentration was detected in ranged of 4.76 × 102-1.48 × 105 copies/L. The amount of SARS-CoV-2 RNA has increased approximately 4 times from the lag phase (January-March) to the log phase (April-May). Spearman's correlation coefficient revealed that correlation between estimated infected population and weekly reported cases was statistically significant (p-value = 0.017). SARS-CoV-2 RNA in influent had a statistically significant relationship with weekly reported cases (r = 0.481, p-value < 0.001). Lag time analysis revealed early warning 1-3 weeks before rising covid-19 cases observed. GIS was applied for spatial-temporal analysis at the province level, suggesting real time dashboard should be further developed.

Diagnostic performance of allele-specific RT-qPCR and genomic sequencing in wastewater-based surveillance of SARS-CoV-2

Clinical genomic surveillance is regarded as the gold standard for monitoring SARS-CoV-2 variants globally. However, as the pandemic wanes, reduced testing poses a risk to effectively tracking the trajectory of these variants within populations. Wastewater-based genomic surveillance that estimates variant frequency based on its defining set of alleles derived from clinical genomic surveillance has been successfully implemented. This method has its challenges, and allele-specific (AS) RT-qPCR or RT-dPCR may instead be used as a complementary method for estimating variant prevalence. Demonstrating equivalent performance of these methods is a prerequisite for their continued application in current and future pandemics. Here, we compared single-allele frequency using AS-RT-qPCR, to single-allele or haplotype frequency estimations derived from amplicon-based sequencing to estimate variant prevalence in wastewater during emergent and prevalent periods of Delta, Omicron, and two sub-lineages of Omicron. We found that all three methods of frequency estimation were concordant and contained sufficient information to describe the trajectory of variant prevalence. We further confirmed the accuracy of these methods by quantifying the diagnostic performance through Youden's index. The Youden's index of AS-RT-qPCR was reduced during the low prevalence period of a particular variant while the same allele in sequencing was negatively influenced due to insufficient read depth. Youden's index of haplotype-based calls was negatively influenced when alleles were common between variants. Coupling AS-RT-qPCR with sequencing can overcome the shortcomings of either platform and provide a comprehensive picture to the stakeholders for public health responses.

Visualizing Neighborhood COVID-19 Levels, Trends, and Inequities in Wastewater: An Equity-Centered Approach and Comparison to CDC Methods

CONTEXT

Monitoring neighborhood-level SARS-CoV-2 wastewater concentrations can help guide public health interventions and provide early warning ahead of lagging COVID-19 clinical indicators. To date, however, U.S. Centers for Disease Control and Prevention's (CDC) National Wastewater Surveillance System (NWSS) has provided methodology solely for communicating national and state-level "wastewater viral activity levels."

PROGRAM

In October 2022, the Boston Public Health Commission (BPHC) began routinely sampling wastewater at 11 neighborhood sites to better understand COVID-19 epidemiology and inequities across neighborhoods, which vary widely in sociodemographic and socioeconomic characteristics. We developed equity-centered methods to routinely report interpretable and actionable descriptions of COVID-19 wastewater levels, trends, and neighborhood-level inequities.

APPROACH AND IMPLEMENTATION

To produce these data visualizations, spanning October 2022 to December 2023, we followed four general steps: (1) smoothing raw values; (2) classifying current COVID-19 wastewater levels; (3) classifying current trends; and (4) reporting and visualizing results.

EVALUATION

COVID-19 wastewater levels corresponded well with lagged COVID-19 hospitalizations and deaths over time, with "Very High" wastewater levels coinciding with winter surges. When citywide COVID-19 levels were at the highest and lowest points, levels and trends tended to be consistent across sites. In contrast, when citywide levels were moderate, neighborhood levels and trends were more variable, revealing inequities across neighborhoods, emphasizing the importance of neighborhood-level results. Applying CDC/NWSS state-level methodology to neighborhood sites resulted in vastly different neighborhood-specific wastewater cut points for "High" or "Low," obscured inequities between neighborhoods, and systematically underestimated COVID-19 levels during surge periods in neighborhoods with the highest COVID-19 morbidity and mortality.

DISCUSSION

Our methods offer an approach that other local jurisdictions can use for routinely monitoring, comparing, and communicating neighborhood-level wastewater levels, trends, and inequities. Applying CDC/NWSS methodology at the neighborhood-level can obscure and perpetuate COVID-19 inequities. We recommend jurisdictions adopt equity-focused approaches in neighborhood-level wastewater surveillance for valid community comparisons.

Air sampling accurately captures circulating zoonotic viral diversity emerging from poultry live-animal markets

Environmental surveillance has emerged as a pivotal strategy for early detection of pathogens that pose threats to humans (1) but has not been utilized for zoonotic agents. In Asia, live-bird markets (LBMs) are key human-animal interfaces for zoonotic virus transmission (2). Traditional sampling strategies are time-consuming, expensive, threaten animal welfare and have significant occupational biosafety risks. In this study, we assessed the performance of metagenomics on environmental samples (ES) compared to traditional poultry swabs for detecting avian viral pathogens in LBMs in Cambodia. ES, including air, cage swabs, and carcass wash water, were collected alongside throat and cloacal swabs from domestic chickens and ducks across twelve sampling visits in two LBMs over a 15-month period. Viral nucleic acids were extracted and sequenced using a capture probe-based metagenomics approach. Our results show that metagenomics on ES outperformed traditional poultry samples in detecting the highly pathogenic Influenza A/H5N1, including circulating clades 2.3.4.4b and 2.3.2.1c, which were found in the environment but missed by poultry swabs on multiple occasions. Environmental metagenomics was also highly sensitive in the detection of over 40 other viruses from key pathogen families such as Astroviridae, Coronaviridae, Picornaviridae, and Retroviridae. Viral contigs from ES showed high similarity to those from poultry swabs further highlighting the accuracy of this approach. Our findings highlight metagenomics on ES can precisely and effectively replicate metagenomic results from traditional surveillance samples, offering broader coverage and enhanced detection of avian pathogens. This robust approach could be pivotal for mitigating zoonotic spillover, controlling pathogen transmission at LBMs, and enhancing pandemic preparedness strategies.

The prevalence and outcomes of viremia in patients with acute respiratory viral infection: a systematic review and meta-analysis

BACKGROUND

Viremia has been detected in a significant proportion of patients with acute respiratory viral infection, yet its clinical value remains underappreciated.

OBJECTIVES

This study synthesized available evidence to comprehensively assess the prevalence of viremia and its impact on clinical outcomes.

METHODS

Data sources: Data were retrieved from Medline (via Ovid), Embase, and the WHO COVID-19 database.

STUDY ELIGIBILITY CRITERIA

This review included original clinical studies analysing the prevalence of viremia in patients with acute respiratory viral infection or its association with clinical outcomes, while excluding non-original research, insufficiently detailed studies, inconsistent pathogen observations, or those with inadequate sample sizes.

PARTICIPANTS

Patients with acute respiratory viral infection.

ASSESSMENT OF RISK OF BIAS

Newcastle-Ottawa scale and an adapted version were used.

EXPOSURE

Respiratory viral infection-related viremia.

METHODS OF DATA SYNTHESIS

Data synthesis utilized random-effects models to pool prevalence and hazard ratio (HR), OR, and adjusted HR/OR for clinical outcomes.

RESULTS

In the comprehensive analysis of viremia prevalence, data were pooled from 101 studies, which included a total of 16,388 non-overlapping patients. Viremia was present in 34% (95% CI, 28-41%) of patients with acute respiratory viral infection. A total of 45 studies provided information on the clinical outcomes of 2002 patients with viremia and 3907 patients without viremia. Viremia was associated with increased risks of mortality (OR, 6.83; 95% CI, 4.92-9.48; adjusted HR, 2.91; 95% CI, 1.87-4.53; adjusted OR, 3.68; 95% CI, 2.37-5.71), intensive care unit admission (OR, 4.74; 95% CI, 2.66-8.46; adjusted OR, 4.89; 95% CI, 1.61-14.91), mechanical ventilation (OR, 4.12; 95% CI, 2.25-7.52), and hepatic complications (OR, 3.10; 95% CI, 1.30-7.40).

CONCLUSIONS

Viremia is prevalent in patients with respiratory viral infection and is associated with elevated risks of adverse clinical outcomes.

Assessment of upper respiratory and gut bacterial microbiomes during COVID-19 infection in adults: potential aerodigestive transmission

SARS-CoV-2 is the viral pathogen responsible for COVID-19. Although morbidity and mortality frequently occur as a result of lung disease, the gastrointestinal (GI) tract is recognized as a primary location for SARS-CoV-2. Connections and interactions between the microbiome of the gut and respiratory system have been linked with viral infections via what has been referred to as the 'gut-lung axis' with potential aerodigestive communication in health and disease. This research explored the relationship between the microbiomes of the upper respiratory and GI tracts in patients with COVID-19 and examined Extraesophageal reflux (EOR), a mechanism which could contribute to dysregulated communication between the GI and respiratory tract (as identified in COVID-19). 97 patients with a laboratory diagnosis of COVID-19 infection, and 50 age-matched controls were recruited and stool, saliva and sputum were obtained from each participant. ELISA Pepsin tests and Reflux Symptom Index scores (RSI) were conducted for EOR assessment. DNA sequencing of the V4 region of the 16 S rRNA gene was performed for microbiome analysis. No differences were observed between the fecal microbiome's alpha and Shannon diversity indices; however, a distinct microbial composition was observed in COVID-19 patients (when compared to the controls). The respiratory microbiota from individuals with COVID-19 demonstrated a statistically significant reduction in Shannon diversity and bacterial richness alongside an overall reduction in the prevalence of organisms from a typical healthy respiratory microbiome. Furthermore, the bacterial richness of the stool and sputum samples was significantly lower among COVID-19 patients admitted to ICU. A significantly higher RSI score and salivary pepsin level were detected among those with COVID-19. The data indicates that COVID-19 is associated with a dysregulation of both the gut and lung microbiome with a more marked perturbation in the lung, particularly among COVID-19 patients who had been admitted to the ICU. The presence of increased RSI scores, combined with elevated levels of Pepsin, suggests that increased micro-aspiration may occur, which is consistent with of under-recognized interactions between the GI and lung microbiomes in COVID-19 patients and requires additional study. Such studies would benefit from the insights provided by biological samples which reflect the continuum of the aerodigestive tract.

Investigating the Role of Gut Microbiota in Pediatric Patients with Severe COVID-19 or MIS-C

Severe COVID-19 and MIS-C are rare but serious outcomes associated with SARS-CoV-2 infection. The onset of MIS-C often involves the gastrointestinal system, suggesting a potential connection with gut microbiota. This study aims to compare the gut microbiota of children with severe COVID-19 and those with MIS-C using various biomolecular approaches. Gut microbiota composition and specific microbial modulations were analyzed using fecal samples collected at hospital admission. The study included hospitalized patients (mean age 6 ± 5 years) diagnosed with severe COVID-19 (37 patients) or MIS-C (37 patients). Microbial differences were assessed using both NGS and qRT-PCR methodologies. In 75% of cases, pharmacological treatments included antibiotics and corticosteroids, which influenced the microbiota composition. Early age was found to have the most significant impact on microbiota diversity. Significant differences in alpha and beta diversity were observed between COVID-19 and MIS-C patients, particularly concerning low-abundance species. Levels of Bacteroides spp., Bifidobacterium spp., and Akkermansia muciniphila were comparable between groups, while an increased activity of Bifidobacterium spp. was noted in children with positive fecal samples (p = 0.019). An in-depth evaluation of lesser-known gut species may be key to reducing the risk of severe outcomes and developing microbiota-based biomarkers for the early diagnosis of MIS-C.

State-space modelling using wastewater virus and epidemiological data to estimate reported COVID-19 cases and the potential infection numbers

The current situation of COVID-19 measures makes it difficult to accurately assess the prevalence of SARS-CoV-2 due to a decrease in reporting rates, leading to missed initial transmission events and subsequent outbreaks. There is growing recognition that wastewater virus data assist in estimating potential infections, including asymptomatic and unreported infections. Understanding the COVID-19 situation hidden behind the reported cases is critical for decision-making when choosing appropriate social intervention measures. However, current models implicitly assume homogeneity in human behaviour, such as virus shedding patterns within the population, making it challenging to predict the emergence of new variants due to variant-specific transmission or shedding parameters. This can result in predictions with considerable uncertainty. In this study, we established a state-space model based on wastewater viral load to predict both reported cases and potential infection numbers. Our model using wastewater virus data showed high goodness-of-fit to COVID-19 case numbers despite the dataset including waves of two distinct variants. Furthermore, the model successfully provided estimates of potential infection, reflecting the superspreading nature of SARS-CoV-2 transmission. This study supports the notion that wastewater surveillance and state-space modelling have the potential to effectively predict both reported cases and potential infections.

Wastewater-based epidemiology for COVID-19 surveillance and beyond: A survey

The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding wastewater-based epidemiology for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.

Emerging zooanthroponotic risks: Detection of the human norovirus GII.4 Sydney[P31] strain in a domestic dog in Brazil

Recent increases in zoonotic diseases underscore the integration of companion animals into urban environments, posing complex transmission risks and highlighting the necessity of One Health approaches. Respiratory and enteric viruses have been consistently linked to interspecies transmission between humans and animals. This study aimed to assess the circulation of human noroviruses (NoV), human adenoviruses (HAdV), enteroviruses (EV), parechoviruses (PeV-A), human bocaviruses (HBoV), hepatitis A (HAV) and E viruses (HEV), Influenza A and B viruses (Flu A/B), respiratory syncytial virus (RSV), and SARS-CoV-2 in domestic dogs and cats in Brazil to understand potential zooanthroponosis risks. Between 2012 and 2021, 600 fecal samples from dogs and cats (516 and 84, respectively) were collected at small animal clinics in São Paulo state, Brazil. The specimens underwent in-house qPCR screening for HBoV and HAdV, while EV, PeV-A, NoV, and HEV were tested using in-house RT-qPCR. SARS-CoV-2, Flu A/B, and RSV were investigated with a commercial RT-qPCR kit assay. HAV detection utilized conventional nested (RT)-PCR. Positive samples were sequenced for molecular characterization and phylogenetic analysis. NoV was detected in 0.2 % (1/600) of the animals, while all other investigated viruses tested negative. The NoV-positive sample, collected in 2012 from a pet dog, was identified as genotype GII.4_Sydney[P31]. The Dog/BRA/2012/GII.4_Sydney[P31]/IAL-M21 strain exhibited a close genetic relationship to Brazilian human and environmental NoV GII.4_Sydney[P31] strains, with 98.1-99.2 % nucleotide similarity in ORF1 and 99.2-99.6 % in ORF2 sequences, suggesting interspecies transmission. Pet dogs are frequently exposed to human fecal-borne viruses, highlighting the potential for zooanthroponotic transmission due to their close interaction with humans in shared environments. There is an urgent need to enhance surveillance studies in companion animals to better understand the implications of detecting human NoV strains in pets, as NoV could potentially act as a reverse zoonotic disease in households, animal hospitals, or shelters worldwide.

Machine Learning-Assisted Surface-Enhanced Raman Spectroscopy Detection for Environmental Applications: A Review

Surface-enhanced Raman spectroscopy (SERS) has gained significant attention for its ability to detect environmental contaminants with high sensitivity and specificity. The cost-effectiveness and potential portability of the technique further enhance its appeal for widespread application. However, challenges such as the management of voluminous quantities of high-dimensional data, its capacity to detect low-concentration targets in the presence of environmental interferents, and the navigation of the complex relationships arising from overlapping spectral peaks have emerged. In response, there is a growing trend toward the use of machine learning (ML) approaches that encompass multivariate tools for effective SERS data analysis. This comprehensive review delves into the detailed steps needed to be considered when applying ML techniques for SERS analysis. Additionally, we explored a range of environmental applications where different ML tools were integrated with SERS for the detection of pathogens and (in)organic pollutants in environmental samples. We sought to comprehend the intricate considerations and benefits associated with ML in these contexts. Additionally, the review explores the future potential of synergizing SERS with ML for real-world applications.

Multisite community-scale monitoring of respiratory and enteric viruses in the effluent of a nursing home and in the inlet of the local wastewater treatment plant

The aim of this study was to evaluate whether community-level monitoring of respiratory and enteric viruses in wastewater can provide a comprehensive picture of local virus circulation. Wastewater samples were collected weekly at the wastewater treatment plant (WWTP) inlet and at the outlet of a nearby nursing home (NH) in Burgundy, France, during the winter period of 2022/2023. We searched for the pepper mild mottle virus as an indicator of fecal content as well as for the main respiratory viruses [severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza, and respiratory syncytial virus] and enteric viruses (rotavirus, sapovirus, norovirus, astrovirus, and adenovirus). Samples were analyzed using real-time reverse transcription PCR-based methods. SARS-CoV-2 was the most frequently detected respiratory virus, with 66.7% of positive samples from the WWTP and 28.6% from the NH. Peaks of SARS-CoV-2 were consistent with the chronological incidence of infections recorded in the sentinel surveillance and the nearby hospital databases. The number of positive samples was lower in the NH than in WWTP for the three respiratory viruses. Enteric viruses were frequently detected, most often sapovirus and norovirus genogroup II, accounting both for 77.8% of positive samples in the WWTP and 57.1% and 37%, respectively, in the NH. The large circulation of sapovirus was unexpected in particular in the NH. Combined wastewater surveillance using simple optimized methods can be a valuable tool for monitoring viral circulation and may serve as a suitable early warning system for identifying both local outbreaks and the onset of epidemics. These results encourage the application of wastewater-based surveillance (WBS) to SARS-CoV2, norovirus, and sapovirus.IMPORTANCEWBS provides valuable information on the spread of epidemic viruses in the environment using appropriate and sensitive detection methods. By monitoring the circulation of viruses using reverse transcription PCR methods in wastewater from the inlet of a wastewater treatment plant and the outlet of a nearby retirement home (connected to the same collective sewer network), we aimed to demonstrate that implementing combined WBS at key community sites allows effective detection of the occurrence of respiratory (influenza, respiratory syncytial virus, and SARS-CoV-2) and enteric (norovirus, rotavirus, and sapovirus) virus infections within a given population. This analysis on a localized scale provided new information on the viral circulation in the two different sites. Implementing WBS to monitor the circulation or the emergence of infectious diseases is an important means of alerting the authorities and improving public health management. WBS could participate actively to the health of humans, animals, and the environment.

Monitoring Influenza A (H1N1, H3N2), RSV, and SARS-CoV-2 Using Wastewater-Based Epidemiology: A 2-Year Longitudinal Study in an Indian Megacity Covering Omicron and Post-Omicron Phases

The bourgeoning field of wastewater-based epidemiology (WBE) for the surveillance of several respiratory viruses which includes Influenza A, H1N1pdm09, H3N2, respiratory syncytial viruses (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of interest for public health concerns. However, there are few long-term monitoring studies globally. In this study, respiratory viruses were detected and quantified from 11 sewer sheds by utilizing reverse transcription-quantitative polymerase chain reaction analysis in Pune city, India, from Jan 2022 to Dec 2023. The RNA fragments of respiratory viruses were detected in sewage samples before clinical cases were reported, underscoring the potential of WBE for early detection and monitoring within the population. The Spearman correlation of wastewater viral copies was positively and significantly correlated with the clinically positive case of H1N1pdm09 (ρ = 0.55, p = 1.4 × 10-9), H3N2 (ρ = 0.25, p = 9.9 × 10-3), and SARS-CoV-2 (ρ = 0.43, p = 4.1 × 10-6). The impact of public health interventions on the circulation of infectious respiratory diseases showed a significant difference in the viral load during the period when many preventing measures were carried out against the COVID-19 pandemic (restriction phase), compared to the period when no such preventive measures are followed (no-restriction phase) for Influenza A, H1N1pdm09, H3N2, and RSV with p-value < 0.05, which indicates the influence of health policy implementation in controlling disease spread. The present study provides an effective approach to detecting multiple respiratory viruses from wastewater and provides insights into the epidemiology of respiratory illnesses. The WBE aids in providing information on the spread of pathogens (viruses) in the community, offering a proactive strategy for public health management, allowing for timely interventions and implementing targeted measures to mitigate the spread of these viruses under one health approach.

Evaluation of wastewater surveillance for SARS-CoV-2 in a prison population: a mixed-methods approach

Background

Prisons are high-risk settings for the transmission of communicable disease. Robust surveillance systems are required to identify and control outbreaks. Wastewater surveillance for SARS-CoV-2 was introduced in four prisons in Wales in March 2022. We investigated its contribution to the COVID-19 surveillance programme.

Methods

We evaluated prison wastewater surveillance against eight system attributes using a mixed-methods approach. Semi-structured interviews were completed with key stakeholders to assess usefulness, flexibility and acceptability. Quantitative analyses were completed to assess data quality, sensitivity, positive-predictive value, representativeness and timeliness. To assess sensitivity of the system to detect changes in incidence we carried out a time-series analysis comparing levels of virus in wastewater with trends in confirmed COVID-19 cases from clinical surveillance.

Results

Interviews with stakeholders indicated that wastewater surveillance is a useful adjunct to existing case-based surveillance. However, it had limited influence on action taken within the prison, often lagging behind existing surveillance and not specific enough to target interventions. The novelty of wastewater surveillance meant stakeholders lacked confidence in interpreting the data. Despite these limitations, wastewater surveillance detected changes in SARS-CoV-2 activity in Welsh prison populations which corroborated trends in case surveillance.

Conclusion

Prison wastewater surveillance, implemented in Wales for a period during the COVID-19 pandemic, was useful and should be considered as part of a wider surveillance programme in response to future SARS-CoV-2 waves, or in response to future pandemics. It is particularly beneficial in the absence of comprehensive clinical testing. We identified several limitations to address should this surveillance be re-started.

Detection of SARS-CoV-2 in wastewater as an earlier predictor of COVID-19 epidemic peaks in Venezuela

Wastewater-based epidemiological surveillance has proven to be a useful and cost-effective tool for detecting COVID-19 outbreaks. Here, our objective was to evaluate its potential as an early warning system in Venezuela by detecting SARS-CoV-2 RNA in wastewater and its correlation with reported cases of COVID-19. Viral RNA was concentrated from wastewater collected at various sites in Caracas (northern Venezuela), from September 2021 to July 2023, using the polyethylene glycol (PEG) precipitation method. Viral quantification was performed by RT-qPCR targeting the N1 and ORF1ab genes. A significant association (p < 0.05) was found between viral load in wastewater and reported cases of COVID-19 up to six days after sampling. During the whole study, two populated areas of the city were persistent hotspots of viral infection. The L452R mutation, suggestive of the presence of the Delta variant, was identified in the only sample where a complete genomic sequence could be obtained. Significant differences (p < 0.05) between the physicochemical conditions of the wastewater samples positive and negative for the virus were found. Our results support proof of concept that wastewater surveillance can serve as an early warning system for SARS-CoV-2 outbreaks, complementing public health surveillance in those regions where COVID-19 is currently underreported.

Wastewater Surveillance of SARS-CoV-2 in Slovenia: Key Public Health Tool in Endemic Time of COVID-19

With the reclassification of COVID-19 as an endemic disease and the relaxation of measures, Slovenia needed a complementary system for monitoring SARS-CoV-2 infections. This article provides an overview of the epidemiological situation of SARS-CoV-2 in Slovenia using a wastewater surveillance system, demonstrating its usefulness as a complementary tool in epidemiological surveillance. This study found that estimated SARS-CoV-2 infections in Slovenia peaked in September 2022 and showed a declining trend with subsequent lower peaks in March-April and December 2023, mirroring the trends observed from clinical data. Based on both surveillance systems, the most prevalent variant in 2022 was BA.5. By 2023, BQ.1 and other Omicron variants increased in prevalence. By the end of 2023, XBB sublineages and the BA.2.86 variant had become predominant, demonstrating consistent dynamic shifts in variant distribution across both monitoring methods. This study found that wastewater surveillance at wastewater treatment plants in Slovenia effectively tracked SARS-CoV-2 infection trends, showing a moderate to strong correlation with clinical data and providing early indications of changes in infection trends and variant emergence. Despite limitations during periods of low virus concentration, the system proved significant in providing early warnings of infection trends and variant emergence, thus enhancing public health response capabilities.

The fate of severe acute respiratory syndrome coronavirus-2 and pepper mild mottle virus at various stages of wastewater treatment process

This study investigated the efficiency of the treatment processes of wastewater treatment plants (WWTPs) to remove severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and pepper mild mottle virus (PMMoV) from the wastewater and sewage sludge, as well as the influence of the mode of operation on the quality of the treated wastewater. SARS-CoV-2 and PMMoV were detected and quantified at different stages of the wastewater and sludge treatment process of three major WWTPs in Stockholm, Sweden. The results showed that primary, biological, and advanced membrane treatment processes are effective in removing SARS-CoV-2 from the wastewater with removal efficiencies of 99-100 % for all WWTPs, while the virus was accumulated in the primary and waste-activated sludges due to higher affinity to biosolids. Operation strategies such as bypass reintroduced the virus into the treated wastewater. The WWTPs achieved relatively low PMMoV removal efficiencies (63-87 %) most probably due to the robust capsid structure of the virus. Anaerobic digestion could not completely remove SARS-CoV-2 and PMMoV from the sludge leading to increased levels of SARS-CoV-2 and PMMoV in dewatered sludge. The study gives an overview of WWTPs' role in tackling pathogen spread in society in the event of a pandemic and disease breakout.

Longitudinal wastewater-based surveillance of SARS-CoV-2 during 2023 in Ethiopia

Introduction

Although wastewater-based epidemiology (WBE) successfully functioned as a tool for monitoring the coronavirus disease 2019 (COVID-19) pandemic globally, relatively little is known about its utility in low-income countries. This study aimed to quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater, estimate the number of infected individuals in the catchment areas, and correlate the results with the clinically reported COVID-19 cases in Addis Ababa, Ethiopia.

Methods

A total of 323 influent and 33 effluent wastewater samples were collected from three Wastewater Treatment Plants (WWTPs) using a 24-h composite Moore swab sampling method from February to November 2023. The virus was captured using Ceres Nanotrap® Enhancement Reagent 2 and Nanotrap® Microbiome A Particles, and then nucleic acids were extracted using the Qiagen QIAamp Viral RNA Mini Kit. The ThermoFisher TaqPath™ COVID-19 kit was applied to perform real-time reverse transcriptase polymerase chain reaction (qRT-PCR) to quantify the SARS-CoV-2 RNA. Wastewater viral concentrations were normalized using flow rate and number of people served. In the sampling period, spearman correlation was used to compare the SARS-CoV-2 target gene concentration to the reported COVID-19 cases. The numbers of infected individuals under each treatment plant were calculated considering the target genes' concentration, the flow rate of treatment plants, a gram of feces per person-day, and RNA copies per gram of feces.

Results

SARS-CoV-2 was detected in 94% of untreated wastewater samples. All effluent wastewater samples (n = 22) from the upflow anaerobic sludge blanket (UASB) reactor and membrane bioreactor (MBR) technology were SARS-COV-2 RNA negative. In contrast, two out of 11 effluents from Waste Stabilization Pond were found positive. Positive correlations were observed between the weekly average SARS-CoV-2 concentration and the cumulative weekly reported COVID-19 cases in Addis Ababa. The estimated number of infected people in the Kality Treatment catchment area was 330 times the number of COVID-19 cases reported during the study period in Addis Ababa.

Discussion

This study revealed that SARS-CoV-2 was circulating in the community and confirmed previous reports of more asymptomatic COVID-19 cases in Ethiopia. Additionally, this study provides further evidence of the importance of wastewater-based surveillance in general to monitor infectious diseases in low-income settings.

Conclusion

Wastewater-based surveillance of SARS-CoV-2 can be a useful method for tracking the increment of COVID-19 cases before it spreads widely throughout the community.

Piloting wastewater-based surveillance of norovirus in England

Wastewater-based epidemiology (WBE) gained widespread use as a tool for supporting clinical disease surveillance during the COVID-19 pandemic. There is now significant interest in the continued development of WBE for other pathogens of clinical significance. In this study, approximately 3,200 samples of wastewater from across England, previously collected for quantification of SARS-CoV-2, were re-analysed for the quantification of norovirus genogroup I (GI) and II (GII). Overall, GI and GII were detected in 93% and 98% of samples respectively, and at least one of the genogroups was detected in 99% of samples. GI was found at significantly lower concentrations than GII, but the proportion of each genogroup varied over time, with GI becoming more prevalent than GII in some areas towards the end of the study period (May 2021 - March 2022). Using relative strength indices (RSI), it was possible to study the trends of each genogroup, and total norovirus over time. Increases in norovirus levels appeared to coincide with the removal of COVID-19 related lockdown restrictions within England. Local Moran's I analyses indicated several localised outbreaks of both GI and GII across England, notably the possible GI outbreak in the north of England in early 2022. Comparisons of national average norovirus concentrations in wastewater against concomitant norovirus reported case numbers showed a significant linear relationship. This highlights the potential for wastewater-based monitoring of norovirus as a valuable approach to support surveillance of norovirus in communities.

Wastewater-based Epidemiology for COVID-19 Surveillance and Beyond: A Survey

The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding wastewater-based epidemiology for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.

The first detection of SARS-CoV-2 RNA in the wastewater of Bucharest, Romania

Wastewater-based epidemiology (WBE) has been previously used as a tool for pathogen identification within communities. After the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) outbreak, in 2020, Daughton proposed the implementation of a wastewater surveillance strategy that could determine the incidence of COVID-19 (coronavirus disease 2019) nationally. Individuals in various stages of SARS-CoV-2 infection, including presymptomatic, asymptomatic and symptomatic patients, can be identified as carriers of the virus in their urine, saliva, stool and other bodily secretions. Studies using this method were conducted to monitor the prevalence of the virus in high-density populations, such as cities but also in smaller communities, such as schools and college campuses. The aim of this pilot study was to assess the feasibility and effectiveness of wastewater surveillance in Bucharest, Romania, and wastewater samples were collected weekly from seven locations between July and September 2023. RNA (ribonucleic acid) extraction, followed by dPCR (digital polymerase chain reaction) analysis, was performed to detect viral genetic material. Additionally, NGS (next generation sequencing) technology was used to identify the circulating variants within the wastewater of Bucharest, Romania. Preliminary results indicate the successful detection of SARS-CoV-2 RNA in wastewater, providing valuable insights into the circulation of the virus within the community.

Longitudinal fecal shedding of SARS-CoV-2, pepper mild mottle virus, and human mitochondrial DNA in COVID-19 patients

Since the coronavirus disease 2019 (COVID-19) pandemic, wastewater-based epidemiology (WBE) has been widely applied in many countries and regions for monitoring COVID-19 transmission in the population through testing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater. However, the amount of virus shed by individuals over time based on the stage of infection and accurate number of infections in the community creates challenges in predicting COVID-19 prevalence in the population and interpreting WBE results. In this study, we measured SARS-CoV-2, pepper mild mottle virus (PMMoV), and human mitochondrial DNA (mtDNA) in longitudinal fecal samples collected from 42 COVID-19 patients for up to 42 days after diagnosis. SARS-CoV-2 RNA was detected in 73.1% (19/26) of inpatient study participants in at least one of the collected fecal specimens during the sampling period. Most participants shed the virus within 3 weeks after diagnosis, but five inpatient participants still shed the virus between 20 and 60 days after diagnosis. The median concentration of SARS-CoV-2 in positive fecal samples was 1.08 × 105 genome copies (GC)/gram dry fecal material. PMMoV and mtDNA were detected in 99.4% (154/155) and 100% (155/155) of all fecal samples, respectively. The median concentrations of PMMoV RNA and mtDNA in fecal samples were 1.73 × 107 and 2.49 × 108 GC/dry gram, respectively. These results provide important information about the dynamics of fecal shedding of SARS-CoV-2 and two human fecal indicators in COVID-19 patients. mtDNA showed higher positive rates, higher concentrations, and less variability between and within individuals than PMMoV, suggesting that mtDNA could be a better normalization factor for WBE results than PMMoV.

Fecal shedding of SARS-CoV-2 in infants born to SARS-CoV-2 positive mothers: a pilot study

Background

Fecal shedding of SARS-CoV-2 occurs during infection, particularly in pediatric populations. The gut microbiota are associated with resistance to enteric pathogens. COVID-19 is associated with alterations to the gut microbiome. We hypothesized that the gut microbiome of infants born to SARS-CoV-2+ mothers differs between infants with and without fecal shedding of the virus.

Methods

We enrolled 10 infants born to SARS-CoV-2+ mothers. We used qPCR on fecal RNA to test for SARS-CoV-2 and 16S rRNA gene sequencing of the V4 region to assess the gut microbiome. Infant SARS-CoV-2 status from nasal swabs was abstracted from medical records.

Results

Of the 10 included infants, nine were tested for SARS-CoV-2 by nasal swab with 1 testing positive. Four infants, including the nasal swab positive infant, had at least one sample with detectable levels of SARS-CoV-2 fecal shedding. Detection of both SARS-CoV-2 genes in feces was associated with increased gut alpha diversity compared to no detection by a linear mixed effects model (p < 0.001). Detection of both SARS-CoV-2 genes was associated with increased levels Erysipelotrichaceae, Lactobacillaceae, and Ruminococceae by MaAsLin2.

Conclusion

Fecal shedding of SARS-CoV-2 occurs in infants who test negative on nasal swabs and is associated with differences in the gut microbiome.

Wastewater monitoring of SARS-CoV-2 gene for COVID-19 epidemiological surveillance in Tucumán, Argentina

Wastewater-based epidemiology provides temporal and spatial information about the health status of a population. The objective of this study was to analyze and report the epidemiological dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the province of Tucumán, Argentina during the second and third waves of coronavirus disease 2019 (COVID-19) between April 2021 and March 2022. The study aimed to quantify SARS-CoV-2 RNA in wastewater, correlating it with clinically reported COVID-19 cases. Wastewater samples (n = 72) were collected from 16 sampling points located in three cities of Tucumán (San Miguel de Tucumán, Yerba Buena y Banda del Río Salí). Detection of viral nucleocapsid markers (N1 gene) was carried out using one-step reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Viral loads were determined for each positive sample using a standard curve. A positive correlation (p < 0.05) was observed between viral load (copies/mL) and the clinically confirmed COVID-19 cases reported at specific sampling points in San Miguel de Tucumán (SP4, SP7, and SP8) in both months, May and June. Indeed, the high viral load concurred with the peaks of COVID-19 cases. This method allowed us to follow the behavior of SARS-CoV-2 infection during epidemic outbreaks. Thus, wastewater monitoring is a valuable epidemiological indicator that enables the anticipation of increases in COVID-19 cases and tracking the progress of the pandemic. SARS-CoV-2 genome-based surveillance should be implemented as a routine practice to prepare for any future surge in infections.

Graphene Multiplexed Sensor for Point-of-Need Viral Wastewater-Based Epidemiology

Wastewater-based epidemiology (WBE) can help mitigate the spread of respiratory infections through the early detection of viruses, pathogens, and other biomarkers in human waste. The need for sample collection, shipping, and testing facilities drives up the cost of WBE and hinders its use for rapid detection and isolation in environments with small populations and in low-resource settings. Given the ubiquitousness and regular outbreaks of respiratory syncytial virus, SARS-CoV-2, and various influenza strains, there is a rising need for a low-cost and easy-to-use biosensing platform to detect these viruses locally before outbreaks can occur and monitor their progression. To this end, we have developed an easy-to-use, cost-effective, multiplexed platform able to detect viral loads in wastewater with several orders of magnitude lower limit of detection than that of mass spectrometry. This is enabled by wafer-scale production and aptamers preattached with linker molecules, producing 44 chips at once. Each chip can simultaneously detect four target analytes using 20 transistors segregated into four sets of five for each analyte to allow for immediate statistical analysis. We show our platform's ability to rapidly detect three virus proteins (SARS-CoV-2, RSV, and Influenza A) and a population normalization molecule (caffeine) in wastewater. Going forward, turning these devices into hand-held systems would enable wastewater epidemiology in low-resource settings and be instrumental for rapid, local outbreak prevention.

Use of wastewater from passenger ships to assess the movement of COVID-19 and other pathogenic viruses across maritime international boundaries

Objective

The worldwide spread of SARS-CoV-2 and the resulting COVID-19 pandemic has been driven by international travel. This has led to the desire to develop surveillance approaches which can estimate the rate of import of pathogenic organisms across international borders. The aim of this study was to investigate the use of wastewater-based approaches for the surveillance of viral pathogens on commercial short-haul (3.5 h transit time) roll-on/roll-off passenger/freight ferries operating between the UK and the Republic of Ireland.

Methods

Samples of toilet-derived wastewater (blackwater) were collected from two commercial ships over a 4-week period and analysed for SARS-CoV-2, influenza, enterovirus, norovirus, the faecal-marker virus crAssphage and a range of physical and chemical indicators of wastewater quality.

Results

A small proportion of the wastewater samples were positive for SARS-CoV-2 (8% of the total), consistent with theoretical predictions of detection frequency (4%-15% of the total) based on the national COVID-19 Infection Survey and defecation behaviour. In addition, norovirus was detected in wastewater at low frequency. No influenza A/B viruses, enterovirus or enterovirus D68 were detected throughout the study period.

Conclusion

We conclude that testing of wastewater from ships that cross international maritime boundaries may provide a cost-effective and relatively unbiased method to estimate the flow of infected individuals between countries. The approach is also readily applicable for the surveillance of other disease-causing agents.

Application of wastewater-based epidemiology for monitoring COVID-19 in hospital and housing wastewaters

An alternative and complementary diagnostic method of surveillance is provided by wastewater-based surveillance (WBS), particularly in low-income nations like Nepal with scant wastewater treatment facilities and clinical testing infrastructure. In this study, a total of 146 water samples collected from two hospitals (n = 63) and three housing wastewaters (n = 83) from the Kathmandu Valley over the period of March 2021-Febraury 2022 were investigated for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using quantitative reverse transcription TaqMan PCR assays targeting the N and E genes. Of the total, 67 % (98/146) samples were positive for SARS-CoV-2 RNA either by using N- or E-gene assay, with concentrations ranging from 3.6 to 9.1 log10 copies/L. There was a significant difference found between positive ratio (Chi-square test, p < 0.05) and concentration (t-test, p = 0.009) of SARS-CoV-2 RNA detected from hospital wastewater and housing waters. Wastewater data are correlated with COVID-19 active cases, indicating significance in specific areas like the Hospital (APFH) (p < 0.05). According to the application of a bivariate linear regression model (p < 0.05), the concentrations of N gene may be used to predict the COVID-19 cases in the APFH. Remarkably, SARS-CoV-2 RNA was detected prior to, during, and following clinical case surges, implying that wastewater surveillance could serve as an early warning system for public health decisions. The significance of WBS in tracking and managing pandemics is emphasized by this study, especially in resource-constrained settings.

COVID-19: Post infection implications in different age groups, mechanism, diagnosis, effective prevention, treatment, and recommendations

SARS-CoV-2 is a highly contagious pathogen that predominantly caused the COVID-19 pandemic. The persistent effects of COVID-19 are defined as an inflammatory or host response to the virus that begins four weeks after initial infection and persists for an undetermined length of time. Chronic effects are more harmful than acute ones thus, this review explored the long-term effects of the virus on various human organs, including the pulmonary, cardiovascular, and neurological, reproductive, gastrointestinal, musculoskeletal, endocrine, and lymphoid systems and found that SARS-CoV-2 adversely affects these organs of older adults. Regarding diagnosis, the RT-PCR is a gold standard method of diagnosing COVID-19; however, it requires specialized equipment and personnel for performing assays and a long time for results production. Therefore, to overcome these limitations, artificial intelligence employed in imaging and microfluidics technologies is the most promising in diagnosing COVID-19. Pharmacological and non-pharmacological strategies are the most effective treatment for reducing the persistent impacts of COVID-19 by providing immunity to post-COVID-19 patients by reducing cytokine release syndrome, improving the T cell response, and increasing the circulation of activated natural killer and CD8 T cells in blood and tissues, which ultimately reduces fever, nausea, fatigue, and muscle weakness and pain. Vaccines such as inactivated viral, live attenuated viral, protein subunit, viral vectored, mRNA, DNA, or nanoparticle vaccines significantly reduce the adverse long-term virus effects in post-COVID-19 patients; however, no vaccine was reported to provide lifetime protection against COVID-19; consequently, protective measures such as physical separation, mask use, and hand cleansing are promising strategies. This review provides a comprehensive knowledge of the persistent effects of COVID-19 on people of varying ages, as well as diagnosis, treatment, vaccination, and future preventative measures against the spread of SARS-CoV-2.

ern: An R package to estimate the effective reproduction number using clinical and wastewater surveillance data

The effective reproduction number,R t , is an important epidemiological metric used to assess the state of an epidemic, as well as the effectiveness of public health interventions undertaken in response. WhenR t is above one, it indicates that new infections are increasing, and thus the epidemic is growing, while anR t is below one indicates that new infections are decreasing, and so the epidemic is under control. There are several established software packages that are readily available to statistically estimateR t using clinical surveillance data. However, there are comparatively few accessible tools for estimatingR t from pathogen wastewater concentration, a surveillance data stream that cemented its utility during the COVID-19 pandemic. We present theR package ern that aims to perform the estimation of the effective reproduction number from real-world wastewater or aggregated clinical surveillance data in a user-friendly way.

SARS-CoV-2 in Captive Nonhuman Primates, Spain, 2020-2023

We conducted a serologic and molecular study to assess exposure of captive nonhuman primates (NHPs) to SARS-CoV-2 in Spain during the 2020-2023 COVID-19 pandemic. We found limited exposure of NHPs to SARS-CoV-2. Biosafety measures must be strictly maintained to avoid SARS-CoV-2 reverse-zoonotic transmission in the human-NHP interface.

Faecal shedding of SARS-CoV-2 from patients with asymptomatic and mild COVID-19 without gastrointestinal symptoms in Ghana

OBJECTIVE

In this study, we sought to determine whether faecal shedding occurs among SARS-COV-2 positive Ghanaians, as reported elsewhere. Hence we assayed for SARS-COV-2 in the stools of 48 SARS-COV-2 confirmed patients at the Ho Municipal Hospital in Ghana.

RESULTS

Of the 48 COVID-19 patients, 45 (93.8%) had positive tests for SARS-CoV-2 faecal shedding. About 60% reported no respiratory symptoms, while only 2% (1 patient) reported gastrointestinal (GI) symptoms in the form of nausea. Other symptoms reported included headache (57.9%), weakness (57.9%), cough (52.6%), blocked/runny nose (47.4%), fever (31.6%), sore throat (31.6%), and shortness of breath (21.1%). One person complained of nausea (5.3%) Semi-quantitative comparison of the SARS COV-2 viral loads in matched respiratory and faecal samples using the cycle threshold (CT) values revealed no statistical differences. Furthermore, the duration between collection of respiratory and faecal samples did not have any direct influence on the differences in the CT values. This suggests that treatment and use of sewage for environmental surveillance of SARS COV-2 could be a potential public health countermeasure.

SARS-CoV-2 wastewater surveillance at two university campuses: lessons learned and insights on intervention strategies for public health guidance

Wastewater surveillance has been a tool for public health officials throughout the COVID-19 pandemic. Universities established pandemic response committees to facilitate safe learning for students, faculty, and staff. These committees met to analyze both wastewater and clinical data to propose mitigation strategies to limit the spread of COVID-19. This paper reviews the initial efforts of utilizing campus data inclusive of wastewater surveillance for SARS-CoV-2 RNA concentrations, clinical case data from university response teams, and mitigation strategies from Grand Valley State University in West Michigan (population 21,648 students) and Oakland University in East Michigan (population 18,552 students) from November 2020 to April 2022. Wastewater positivity rates for both universities ranged from 32.8 to 46.8%. Peak viral signals for both universities directly corresponded to variant points of entry within the campus populations from 2021 to 2022. It was found that the organization of clinical case data and variability of wastewater testing data were large barriers for both universities to effectively understand disease dynamics within the university population. We review the initial efforts of onboarding wastewater surveillance and provide direction for structuring ongoing surveillance workflows and future epidemic response strategies based on those that led to reduced viral signals in campus wastewater.

An overview for monitoring and prediction of pathogenic microorganisms in the atmosphere

Corona virus disease 2019 (COVID-19) has exerted a profound adverse impact on human health. Studies have demonstrated that aerosol transmission is one of the major transmission routes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Pathogenic microorganisms such as SARS-CoV-2 can survive in the air and cause widespread infection among people. Early monitoring of pathogenic microorganism transmission in the atmosphere and accurate epidemic prediction are the frontier guarantee for preventing large-scale epidemic outbreaks. Monitoring of pathogenic microorganisms in the air, especially in densely populated areas, may raise the possibility to detect viruses before people are widely infected and contain the epidemic at an earlier stage. The multi-scale coupled accurate epidemic prediction system can provide support for governments to analyze the epidemic situation, allocate health resources, and formulate epidemic response policies. This review first elaborates on the effects of the atmospheric environment on pathogenic microorganism transmission, which lays a theoretical foundation for the monitoring and prediction of epidemic development. Secondly, the monitoring technique development and the necessity of monitoring pathogenic microorganisms in the atmosphere are summarized and emphasized. Subsequently, this review introduces the major epidemic prediction methods and highlights the significance to realize a multi-scale coupled epidemic prediction system by strengthening the multidisciplinary cooperation of epidemiology, atmospheric sciences, environmental sciences, sociology, demography, etc. By summarizing the achievements and challenges in monitoring and prediction of pathogenic microorganism transmission in the atmosphere, this review proposes suggestions for epidemic response, namely, the establishment of an integrated monitoring and prediction platform for pathogenic microorganism transmission in the atmosphere.

Wastewater based epidemiology as a surveillance tool during the current COVID-19 pandemic on a college campus (East Carolina University) and its accuracy in predicting SARS-CoV-2 outbreaks in dormitories

The COVID-19 outbreak led governmental officials to close many businesses and schools, including colleges and universities. Thus, the ability to resume normal campus operation required adoption of safety measures to monitor and respond to COVID-19. The objective of this study was to determine the efficacy of wastewater-based epidemiology as a surveillance method in monitoring COVID-19 on a college campus. The use of wastewater monitoring as part of a surveillance program to control COVID-19 outbreaks at East Carolina University was evaluated. During the Spring and Fall 2021 semesters, wastewater samples (N = 830) were collected every Monday, Wednesday, and Friday from the sewer pipes exiting the dormitories on campus. Samples were analyzed for SARS-CoV-2 and viral quantification was determined using qRT-PCR. During the Spring 2021 semester, there was a significant difference in SARS-CoV-2 virus copies in wastewater when comparing dorms with the highest number student cases of COVID-19 and those with the lowest number of student cases, (p = 0.002). Additionally, during the Fall 2021 semester it was observed that when weekly virus concentrations exceeded 20 copies per ml, there were new confirmed COVID-19 cases 85% of the time during the following week. Increases in wastewater viral concentration spurred COVID-19 swab testing for students residing in dormitories, aiding university officials in effectively applying COVID testing policies. This study showed wastewater-based epidemiology can be a cost-effective surveillance tool to guide other surveilling methods (e.g., contact tracing, nasal/salvia testing, etc.) to identify and isolate afflicted individuals to reduce the spread of pathogens and potential outbreaks within a community.

Cross-continental comparative experiences of wastewater surveillance and a vision for the 21st century

The COVID-19 pandemic has brought the epidemiological value of monitoring wastewater into sharp focus. The challenges of implementing and optimising wastewater monitoring vary significantly from one region to another, often due to the array of different wastewater systems around the globe, as well as the availability of resources to undertake the required analyses (e.g. laboratory infrastructure and expertise). Here we reflect on the local and shared challenges of implementing a SARS-CoV-2 monitoring programme in two geographically and socio-economically distinct regions, São Paulo state (Brazil) and Wales (UK), focusing on design, laboratory methods and data analysis, and identifying potential guiding principles for wastewater surveillance fit for the 21st century. Our results highlight the historical nature of region-specific challenges to the implementation of wastewater surveillance, including previous experience of using wastewater surveillance, stakeholders involved, and nature of wastewater infrastructure. Building on those challenges, we then highlight what an ideal programme would look like if restrictions such as resource were not a constraint. Finally, we demonstrate the value of bringing multidisciplinary skills and international networks together for effective wastewater surveillance.

Polyethylenimine mediated recovery of SARS-CoV-2 and total viral RNA: Impact of aqueous conditions on behaviour and recovery

Wastewater-based epidemiology (WBE) is an emerging, practical surveillance tool for monitoring community levels of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, SC2). However, a paucity of data exists regarding SARS-CoV-2 and viral biomarker behaviour in aqueous and wastewater environments. Therefore, there is a pressing need to develop efficient and robust methods that both improve method sensitivity and reduce time and cost. We present a novel method for SARS-CoV-2, Human Coronavirus 229E (229E), and Pepper Mild Mottle Virus (PMMoV) recovery utilizing surface charge-based attraction via the branched cationic polymer, polyethylenimine (PEI). Initially, dose-optimization experiments demonstrated that low concentrations of PEI (0.001% w/v) proved most effective at flocculating suspended viruses and viral material, including additional unbound SC2 viral fragments and/or RNA from raw wastewater. A design-of-experiments (DOE) approach was used to optimize virus and/or viral material aggregation behaviour and recovery across varying aqueous conditions, revealing pH as a major influence on recoverability in this system, combinatorially due to both a reduction in viral material surface charge and increased protonation of PEI-bound amine groups. Overall, this method has shown great promise in significantly improving quantitative viral recovery, providing a straightforward and effective augmentation to standard centrifugation techniques.

Wastewater based surveillance can be used to reduce clinical testing intensity on a university campus

Clinical testing has been a vital part of the response to and suppression of the COVID-19 pandemic; however, testing imposes significant burdens on a population. College students had to contend with clinical testing while simultaneously dealing with health risks and the academic pressures brought on by quarantines, changes to virtual platforms, and other disruptions to daily life. The objective of this study was to analyze whether wastewater surveillance can be used to decrease the intensity of clinical testing while maintaining reliable measurements of diseases incidence on campus. Twelve months of human health and wastewater surveillance data for eight residential buildings on a university campus were analyzed to establish how SARS-CoV-2 levels in the wastewater can be used to minimize clinical testing burden on students. Wastewater SARS-CoV-2 levels were used to create multiple scenarios, each with differing levels of testing intensity, which were compared to the actual testing volumes implemented by the university. We found that scenarios in which testing intensity fluctuations matched rise and falls in SARS-CoV-2 wastewater levels had stronger correlations between SARS-CoV-2 levels and recorded clinical positives. In addition to stronger correlations, most scenarios resulted in overall fewer weekly clinical tests performed. We suggest the use of wastewater surveillance to guide COVID-19 testing as it can significantly increase the efficacy of COVID-19 surveillance while reducing the burden placed on college students during a pandemic. Future efforts should be made to integrate wastewater surveillance into clinical testing strategies implemented on college campuses.

Prevalence and duration of SARS-CoV-2 fecal shedding in breastfeeding dyads following maternal COVID-19 diagnosis

Background

There is a paucity of data on the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in feces of lactating women with coronavirus disease 2019 (COVID-19) and their breastfed infants as well as associations between fecal shedding and symptomatology.

Objective

We examined whether and to what extent SARS-CoV-2 is detectable in the feces of lactating women and their breastfed infants following maternal COVID-19 diagnosis.

Methods

This was a longitudinal study carried out from April 2020 to December 2021 involving 57 breastfeeding maternal-infant dyads: 33 dyads were enrolled within 7 d of maternal COVID-19 diagnosis, and 24 healthy dyads served as controls. Maternal/infant fecal samples were collected by participants, and surveys were administered via telephone over an 8-wk period. Feces were analyzed for SARS-CoV-2 RNA.

Results

Signs/symptoms related to ears, eyes, nose, and throat (EENT); general fatigue/malaise; and cardiopulmonary signs/symptoms were commonly reported among mothers with COVID-19. In infants of mothers with COVID-19, EENT, immunologic, and cardiopulmonary signs/symptoms were most common, but prevalence did not differ from that of infants of control mothers. SARS-CoV-2 RNA was detected in feces of 7 (25%) women with COVID-19 and 10 (30%) of their infants. Duration of fecal shedding ranged from 1-4 wk for both mothers and infants. SARS-CoV-2 RNA was sparsely detected in feces of healthy dyads, with only one mother's and two infants' fecal samples testing positive. There was no relationship between frequencies of maternal and infant SARS-CoV-2 fecal shedding (P=0.36), although presence of maternal or infant fever was related to increased likelihood (7-9 times greater, P≤0.04) of fecal shedding in infants of mothers with COVID-19.

Wastewater-based epidemiology for COVID-19 using dynamic artificial neural networks

Global efforts in vaccination have led to a decrease in COVID-19 mortality but a high circulation of SARS-CoV-2 is still observed in several countries, resulting in some cases of severe lockdowns. In this sense, wastewater-based epidemiology remains a powerful tool for supporting regional health administrations in assessing risk levels and acting accordingly. In this work, a dynamic artificial neural network (DANN) has been developed for predicting the number of COVID-19 hospitalized patients in hospitals in Valladolid (Spain). This model takes as inputs a wastewater epidemiology indicator for COVID-19 (concentration of RNA from SARS-CoV-2 N1 gene reported from Valladolid Wastewater Treatment Plant), vaccination coverage, and past data of hospitalizations. The model considered both the instantaneous values of these variables and their historical evolution. Two study periods were selected (from May 2021 until September 2022 and from September 2022 to July 2023). During the first period, accurate predictions of hospitalizations (with an overall range between 6 and 171) were favored by the correlation of this indicator with N1 concentrations in wastewater (r = 0.43, p < 0.05), showing accurate forecasting for 1 day ahead and 5 days ahead. The second period's retraining strategy maintained the overall accuracy of the model despite lower hospitalizations. Furthermore, risk levels were assigned to each 1 day ahead prediction during the first and second periods, showing agreement with the level measured and reported by regional health authorities in 95 % and 93 % of cases, respectively. These results evidenced the potential of this novel DANN model for predicting COVID-19 hospitalizations based on SARS-CoV-2 wastewater concentrations at a regional scale. The model architecture herein developed can support regional health authorities in COVID-19 risk management based on wastewater-based epidemiology.

Feasibility of wastewater-based detection of emergent pandemics through a global network of airports

Wastewater-based surveillance has been put into practice during the pandemic. Persistence of SARS-CoV-2 in faeces of infected individuals, and high volume of passengers travelling by air, make it possible to detect virus from aircraft wastewater, lending itself to the potential identification of a novel pathogen prior to clinical diagnosis. In this study, we estimated the likelihood of detecting the virus through aircraft wastewater from the probabilities of air travel, viral shedding, defecation, testing sensitivity, and sampling. We considered various hypothetical scenarios, with diverse sampling proportions of inbound flights, surveillance airports, and sources of outbreaks. Our calculations showed that the probability of detecting SARS-CoV-2 would increase exponentially against time in the early phase of the pandemic, and would be much higher if the 20 major airports in Asia, Europe, and North America cooperated to perform aircraft wastewater surveillance. We also found other contributors to early detection, including high sampling proportion of inbound flight at destination airports, small population size of the epicentre relative to the travel volume, and large volume of outbound travelers to major airports around the globe. We concluded that routine aircraft wastewater monitoring could be a feasible approach for early identification and tracking of an emerging pathogen with high faecal shedding rates, particularly when implemented through a global surveillance network of major airports.

Exploring the Interplay between COVID-19 and Gut Health: The Potential Role of Prebiotics and Probiotics in Immune Support

The COVID-19 pandemic has profoundly impacted global health, leading to extensive research focused on developing strategies to enhance outbreak response and mitigate the disease's severity. In the aftermath of the pandemic, attention has shifted towards understanding and addressing long-term health implications, particularly in individuals experiencing persistent symptoms, known as long COVID. Research into potential interventions to alleviate long COVID symptoms has intensified, with a focus on strategies to support immune function and mitigate inflammation. One area of interest is the gut microbiota, which plays a crucial role in regulating immune responses and maintaining overall health. Prebiotics and probiotics, known for their ability to modulate the gut microbiota, have emerged as potential therapeutic agents in bolstering immune function and reducing inflammation. This review delves into the intricate relationship between long COVID, the gut microbiota, and immune function, with a specific focus on the role of prebiotics and probiotics. We examine the immune response to long COVID, emphasizing the importance of inflammation and immune regulation in the persistence of symptoms. The potential of probiotics in modulating immune responses, including their mechanisms in combating viral infections such as COVID-19, is discussed in detail. Clinical evidence supporting the use of probiotics in managing long COVID symptoms is summarized, highlighting their role as adjunctive therapy in addressing various aspects of SARS-CoV-2 infection and its aftermath.

Real-Time On-Site Monitoring of Viruses in Wastewater Using Nanotrap® Particles and RICCA Technologies

Wastewater-based epidemiology (WBE) is an effective and efficient tool for the early detection of infectious disease outbreaks in a community. However, currently available methods are laborious, costly, and time-consuming due to the low concentration of viruses and the presence of matrix chemicals in wastewater that may interfere with molecular analyses. In the present study, we designed a highly sensitive "Quick Poop (wastewater with fecal waste) Sensor" (termed, QPsor) using a joint approach of Nanotrap microbiome particles and RICCA (RNA Isothermal Co-Assisted and Coupled Amplification). Using QPsor, the WBE study showed a strong correlation with standard PEG concentrations and the qPCR technique. Using a closed format for a paper-based lateral flow assay, we were able to demonstrate the potential of our assay as a real-time, point-of-care test by detecting the heat-inactivated SARS-CoV-2 virus in wastewater at concentrations of 100 copies/mL and within one hour. As a proof-of-concept demonstration, we analyzed the presence of viral RNA of the SARS-CoV-2 virus and PMMoV in raw wastewater samples from wastewater treatment plants on-site and within 60 min. The results show that the QPsor method can be an effective tool for disease outbreak detection by combining an AI-enabled case detection model with real-time on-site viral RNA extraction and amplification, especially in the absence of intensive clinical laboratory facilities. The lab-free, lab-quality test capabilities of QPsor for viral prevalence and transmission in the community can contribute to the efficient management of pandemic situations.

Reduction of acute respiratory infections in day-care by non-pharmaceutical interventions: a narrative review

Objective

Children who start in day-care have 2-4 times as many respiratory infections compared to children who are cared for at home, and day-care staff are among the employees with the highest absenteeism. The extensive new knowledge that has been generated in the COVID-19 era should be used in the prevention measures we prioritize. The purpose of this narrative review is to answer the questions: Which respiratory viruses are the most significant in day-care centers and similar indoor environments? What do we know about the transmission route of these viruses? What evidence is there for the effectiveness of different non-pharmaceutical prevention measures?

Design

Literature searches with different terms related to respiratory infections in humans, mitigation strategies, viral transmission mechanisms, and with special focus on day-care, kindergarten or child nurseries, were conducted in PubMed database and Web of Science. Searches with each of the main viruses in combination with transmission, infectivity, and infectious spread were conducted separately supplemented through the references of articles that were retrieved.

Results

Five viruses were found to be responsible for ≈95% of respiratory infections: rhinovirus, (RV), influenza virus (IV), respiratory syncytial virus (RSV), coronavirus (CoV), and adenovirus (AdV). Novel research, emerged during the COVID-19 pandemic, suggests that most respiratory viruses are primarily transmitted in an airborne manner carried by aerosols (microdroplets).

Conclusion

Since airborne transmission is dominant for the most common respiratory viruses, the most important preventive measures consist of better indoor air quality that reduces viral concentrations and viability by appropriate ventilation strategies. Furthermore, control of the relative humidity and temperature, which ensures optimal respiratory functionality and, together with low resident density (or mask use) and increased time outdoors, can reduce the occurrence of respiratory infections.