Molecular and biological characterization of influenza A viruses isolated from human fecal samples

Global wastewater surveillance for pathogens with pandemic potential: opportunities and challenges

Wastewater surveillance holds great promise as a sensitive method to detect spillover of zoonotic infections and early pandemic emergence, thereby informing risk mitigation and public health response. Known viruses with pandemic potential are shed in human stool or urine, or both, and the experiences with SARS-CoV-2, monkeypox virus, and Zika virus highlight the feasibility of community-based wastewater surveillance for pandemic viruses that have different transmission routes. We reviewed human shedding and wastewater surveillance data for prototype viruses representing viral families of concern to estimate the likely sensitivity of wastewater surveillance compared with that of clinical surveillance. We examined how data on wastewater surveillance detection, together with viral genetic sequences and animal faecal biomarkers, could be used to identify spillover infections or early human transmission and adaptation. The opportunities and challenges associated with global wastewater surveillance for the prevention of pandemics are described in this Personal View, focusing on low-income and middle-income countries, where the risk of pandemic emergence is the highest. We propose a research and public health agenda to ensure an equitable and sustainable solution to these challenges.

Influenza virus infection and aerosol shedding kinetics in a controlled human infection model

Establishing effective mitigation strategies to reduce the spread of influenza virus requires an improved understanding of the mechanisms of transmission. We evaluated the use of a controlled human infection model using an H3N2 seasonal influenza virus to study critical aspects of transmission, including symptom progression and the dynamics of virus shedding. Eight volunteers were challenged with influenza A/Perth/16/2009 (H3N2) virus between July and September 2022 at Emory University Hospital. Viral shedding in the nasopharynx, saliva, stool, urine, and respiratory aerosols was monitored over the quarantine period, and symptoms were tracked until day 15. In addition, environmental swabs were collected from participant rooms to examine fomite contamination, and participant sera were collected to assess seroconversion by hemagglutination inhibition or microneutralization assays. Among the eight participants, influenza virus infection was confirmed in six (75%). Infectious virus or viral RNA was found in multiple physiological compartments, fecal samples, aerosol particles, and on surfaces in the immediate environment. Illness was moderate, with upper respiratory symptoms dominating. In participants with the highest viral loads, antibody titers rose by day 15 post-inoculation, while in participants with low or undetectable viral loads, there was little or no increase in functional antibody titers. These data demonstrate the safety and utility of the human infection model to study features critical to influenza virus transmission dynamics in a controlled manner and will inform the design of future challenge studies focused on modeling and limiting transmission.CLINICAL TRIALSThis study is registered with ClinicalTrials.gov as NCT05332899.

IMPORTANCE

We use a controlled human infection model to assess respiratory and aerosol shedding kinetics to expand our knowledge of influenza infection dynamics and help inform future studies aimed at understanding human-to-human transmission.

Combating Emerging Respiratory Viruses: Lessons and Future Antiviral Strategies

Emerging viral diseases, including seasonal illnesses and pandemics, pose significant global public health risks. Respiratory viruses, particularly coronaviruses and influenza viruses, are associated with high morbidity and mortality, imposing substantial socioeconomic burdens. This review focuses on the current landscape of respiratory viruses, particularly influenza and SARS-CoV-2, and their antiviral treatments. It also discusses the potential for pandemics and the development of new antiviral vaccines and therapies, drawing lessons from past outbreaks to inform future strategies for managing viral threats.

Wastewater Surveillance to Confirm Differences in Influenza A Infection between Michigan, USA, and Ontario, Canada, September 2022-March 2023

Wastewater surveillance is an effective way to track the prevalence of infectious agents within a community and, potentially, the spread of pathogens between jurisdictions. We conducted a retrospective wastewater surveillance study of the 2022-23 influenza season in 2 communities, Detroit, Michigan, USA, and Windsor-Essex, Ontario, Canada, that form North America's largest cross-border conurbation. We observed a positive relationship between influenza-related hospitalizations and the influenza A virus (IAV) wastewater signal in Windsor-Essex (ρ = 0.785; p<0.001) and an association between influenza-related hospitalizations in Michigan and the IAV wastewater signal for Detroit (ρ = 0.769; p<0.001). Time-lagged cross correlation and qualitative examination of wastewater signal in the monitored sewersheds showed the peak of the IAV season in Detroit was delayed behind Windsor-Essex by 3 weeks. Wastewater surveillance for IAV reflects regional differences in infection dynamics which may be influenced by many factors, including the timing of vaccine administration between jurisdictions.

"Smart markets": harnessing the potential of new technologies for endemic and emerging infectious disease surveillance in traditional food markets

Emerging and endemic zoonotic diseases continue to threaten human and animal health, our social fabric, and the global economy. Zoonoses frequently emerge from congregate interfaces where multiple animal species and humans coexist, including farms and markets. Traditional food markets are widespread across the globe and create an interface where domestic and wild animals interact among themselves and with humans, increasing the risk of pathogen spillover. Despite decades of evidence linking markets to disease outbreaks across the world, there remains a striking lack of pathogen surveillance programs that can relay timely, cost-effective, and actionable information to decision-makers to protect human and animal health. However, the strategic incorporation of environmental surveillance systems in markets coupled with novel pathogen detection strategies can create an early warning system capable of alerting us to the risk of outbreaks before they happen. Here, we explore the concept of "smart" markets that utilize continuous surveillance systems to monitor the emergence of zoonotic pathogens with spillover potential.IMPORTANCEFast detection and rapid intervention are crucial to mitigate risks of pathogen emergence, spillover and spread-every second counts. However, comprehensive, active, longitudinal surveillance systems at high-risk interfaces that provide real-time data for action remain lacking. This paper proposes "smart market" systems harnessing cutting-edge tools and a range of sampling techniques, including wastewater and air collection, multiplex assays, and metagenomic sequencing. Coupled with robust response pathways, these systems could better enable Early Warning and bolster prevention efforts.

Longitudinal wastewater surveillance of four key pathogens during an unprecedented large-scale COVID-19 outbreak in China facilitated a novel strategy for addressing public health priorities-A proof of concept study

Wastewater-based epidemiology (WBE) is a promising tool for monitoring the spread of SARS-CoV-2 and other pathogens, providing a novel public health strategy to combat disease. In this study, we first analysed nationwide reports of infectious diseases and selected Salmonella, norovirus, and influenza A virus (IAV) as prioritized targets apart from SARS-CoV-2 for wastewater surveillance. Next, the decay rates of Salmonella, norovirus, and IAV in wastewater at various temperatures were established to obtain corrected pathogen concentrations in sewage. We then monitored the concentrations of these pathogens in wastewater treatment plant (WWTP) influents in three cities, establishing a prediction model to estimate the number of infected individuals based on the mass balance between total viral load in sewage and individual viral shedding. From October 2022 to March 2023, we conducted multipathogen wastewater surveillance (MPWS) in a WWTP serving one million people in Xi'an City, monitoring the concentration dynamics of SARS-CoV-2, Salmonella, norovirus, and IAV in sewage. The infection peaks of each pathogen were different, with Salmonella cases and sewage concentration declining from October to December 2022 and only occasionally detected thereafter. The SARS-CoV-2 concentration rapidly increased from December 5th, peaked on December 26th, and then quickly decreased until the end of the study. Norovirus and IAV were detected in wastewater from January to March 2023, peaking in February and March, respectively. We used the prediction models to estimate the rate of SARS-CoV-2 infection in Xi'an city, with nearly 90 % of the population infected in urban regions. There was no significant difference between the predicted and actual number of hospital admissions for IAV. We also accurately predicted the number of norovirus cases relative to the reported cases. Our findings highlight the importance of wastewater surveillance in addressing public health priorities, underscoring the need for a novel workflow that links the prediction results of populations with public health interventions and allocation of medical resources at the community level. This approach would prevent medical resource panic squeezes, reduce the severity and mortality of patients, and enhance overall public health outcomes.

Wastewater surveillance of the most common circulating respiratory viruses in Athens: The impact of COVID-19 on their seasonality

Due to governments' actions to contain the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the activity of common circulating respiratory viruses was significantly disrupted after the COVID-19 pandemic and thorough surveillance of respiratory pathogens was considered essential worldwide. Wastewater-based epidemiology has proven to be a valuable tool, that provides complementary information on disease outbreaks and is increasingly used to study the infection dynamics of other viruses, apart from SARS-CoV-2. The aims of the present study were the detection of four commonly circulating respiratory viruses: SARS-CoV-2, influenza A, B and Human Respiratory Syncytial Virus (RSV), the evaluation of the COVID-19 pandemic impact on their seasonality and the determination of the possible common trends in the viral load of these viruses in the wastewater of the Attica region. A standardized and validated concentration and extraction protocol was used, generic for all four viruses, followed by Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) assays. The study proved that there was a prolonged period when all four viruses circulated in the population and an early outbreak of seasonal influenza and RSV in 2022-2023, compared to data from the pre-COVID-19 period. SARS-CoV-2, influenza A and RSV concentrations showed peak levels during December, followed by a slight decline in influenza A concentrations, followed by steady increase of influenza B concentrations in January 2023. SARS-CoV-2 was the dominant virus throughout the whole study period. This is the first study in Greece that investigated the most common circulating viruses simultaneously and in one of the largest timelines, providing crucial information about their infection dynamics during a period when an outbreak of respiratory diseases was declared by the National Public Health Organization. Presented results highlight the establishment of environmental surveillance as a non-invasive and complementary virus outbreak monitoring tool and the importance of influenza A, B and RSV integration into a wastewater-based surveillance system to help in disease management.

Wastewater surveillance of SARS-CoV-2 and influenza in preK-12 schools shows school, community, and citywide infections

Wastewater surveillance is a passive and efficient way to monitor the spread of infectious diseases in large populations and high transmission areas such as preK-12 schools. Infections caused by respiratory viruses in school-aged children are likely underreported, particularly because many children may be asymptomatic or mildly symptomatic. Wastewater monitoring of SARS-CoV-2 has been studied extensively and primarily by sampling at centralized wastewater treatment plants, and there are limited studies on SARS-CoV-2 in preK-12 school wastewater. Similarly, wastewater detections of influenza have only been reported in wastewater treatment plant and university manhole samples. Here, we present the results of a 17-month wastewater monitoring program for SARS-CoV-2 (n = 2176 samples) and influenza A and B (n = 1217 samples) in 51 preK-12 schools. We show that school wastewater concentrations of SARS-CoV-2 RNA were strongly associated with COVID-19 cases in schools and community positivity rates, and that influenza detections in school wastewater were significantly associated with citywide influenza diagnosis rates. Results were communicated back to schools and local communities to enable mitigation strategies to stop the spread, and direct resources such as testing and vaccination clinics. This study demonstrates that school wastewater surveillance is reflective of local infections at several population levels and plays a crucial role in the detection and mitigation of outbreaks.

Lingering SARS-CoV-2 in Gastric and Gallbladder Tissues of Patients with Previous COVID-19 Infection Undergoing Bariatric Surgery

BACKGROUND

Lingering severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in gut tissue might be a source of infection during bariatric surgery. This study aimed to confirm the presence of SARS-CoV-2 nucleocapsid in gastric and gallbladder tissues removed during bariatric surgery in individuals previously infected with coronavirus disease 2019 (COVID-19) who had negative polymerase chain reaction results prior to the surgery.

METHODS

Gastric and gallbladder specimens from 80 patients who underwent bariatric surgery between November 2021 and May 2022 and had a history of COVID-19 infection with gastrointestinal symptoms were examined for the presence of lingering SARS-CoV-2 nucleocapsid proteins using immunohistochemistry.

RESULTS

Gastric specimens from 26 (32.5%) patients and 4 (100%) cholecystectomy specimens showed positive cytoplasmic staining for the anti-SARS-CoV-2 nucleocapsid protein in surface mucosal epithelial cells. The mean age was 37.8 ± 10.3 years. The average body mass index was 44.2 ± 7.0 kg/m²; most of the patients were females (71.3%). The positive staining group was significantly younger than the negative staining group (p = 0.007). The full-dose vaccination rate was 58.8%, with a median of 91 days after the last vaccine dose. A positive serological anti-spike IgG response was observed in 99% of the patients. The median time between initial COVID-19 infection and surgery was 274 and 380 days in the positive and negative staining groups, respectively (p = 0.371).

CONCLUSION

Gastric and gallbladder tissues can retain SARS-CoV-2 particles for a long time after COVID-19 infection, handling stomach specimens from patients during an operation must be done with care, as we usually do, but now with the knowledge that in 1/3 of patients they can be present. Performing LSG on post-COVID patients did not seem to increase perioperative morbidity.

Viral metagenomics analysis of stool specimens from children with unresolved gastroenteritis in Qatar

Acute gastroenteritis (AGE) is associated with significant global morbidity and mortality, especially among children under five years of age. Viruses are well established as etiologic agents of gastroenteritis since they are the most common pathogens that contribute to the disease burden in developing countries. Despite the advances in molecular diagnosis, a substantial proportion of AGE etiology remain unresolved. We implemented a viral metagenomics pipeline to determine the potential viral etiology associated with AGE among children under the age of five years in Qatar with undiagnosed etiology. Following enriching for the viral genome, ∼1.3 billion sequences were generated from 89 stool specimens using the Illumina HiSeq platform, of which 7% were mapped to viral genomes. Human viruses were detected in 34 specimens (38.2%); 14 were adenovirus, nine coxsackievirus A16, five rotavirus (G9P[8] and G4P[8]), four norovirus (GII), one influenza A virus (H3), and one respiratory syncytial virus A (RSVA). In conclusion, the viral metagenomics approach is useful for determining AGE's etiology when routine molecular diagnostic assays fail.

Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak

Recurrent influenza epidemics and pandemic potential are significant risks to global health. Public health authorities use clinical surveillance to locate and monitor influenza and influenza-like cases and outbreaks to mitigate hospitalizations and deaths. Currently, global integration of clinical surveillance is the only reliable method for reporting influenza types and subtypes to warn of emergent pandemic strains. The utility of wastewater surveillance (WWS) during the COVID-19 pandemic as a less resource intensive replacement or complement for clinical surveillance has been predicated on analyzing viral fragments in wastewater. We show here that influenza virus targets are stable in wastewater and partitions favorably to the solids fraction. By quantifying, typing, and subtyping the virus in municipal wastewater and primary sludge during a community outbreak, we forecasted a citywide flu outbreak with a 17-day lead time and provided population-level viral subtyping in near real-time to show the feasibility of influenza virus WWS at the municipal and neighbourhood levels in near real time using minimal resources and infrastructure.

Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak

Recurrent influenza epidemics and pandemic potential are significant risks to global health. Public health authorities use clinical surveillance to locate and monitor influenza and influenza-like cases and outbreaks to mitigate hospitalizations and deaths. Currently, global integration of clinical surveillance is the only reliable method for reporting influenza types and subtypes to warn of emergent pandemic strains. The utility of wastewater surveillance (WWS) during the COVID-19 pandemic as a less resource intensive replacement or complement for clinical surveillance has been predicated on analyzing viral fragments in wastewater. We show here that influenza virus targets are stable in wastewater and partitions favorably to the solids fraction. By quantifying, typing, and subtyping the virus in municipal wastewater and primary sludge during a community outbreak, we forecasted a citywide flu outbreak with a 17-day lead time and provided population-level viral subtyping in near real-time to show the feasibility of influenza virus WWS at the municipal and neighbourhood levels in near real time using minimal resources and infrastructure.