SARS-CoV-2 and other respiratory pathogens are detected in continuous air samples from congregate settings

Hospital air sampling enables surveillance of respiratory virus infections and genomes

There is an urgent need for early detection and comprehensive surveillance of respiratory pathogens. Environmental surveillance may be key to timely responses for newly emerging pathogens and infections that are unreported or underreported. Here, we employed air sampling in a large urban hospital. Air samples (n = 358) were collected weekly at five locations, including two in the emergency department, two in hospital common areas and one in a storage room, for two respiratory virus seasons (November 2022 to June 2024). Air samples were tested for eight respiratory pathogens by qPCR, including RNA and DNA viruses and a bacterium. Air samples had an average of four detected pathogens per sample and 97 % samples contained SARS-CoV-2. Air sample pathogen positivity and quantity were strongly correlated with clinical surveillance for four seasonal respiratory pathogens: influenza A and B, respiratory syncytial virus, and human metapneumovirus. Targeted amplicon sequencing of SARS-CoV-2 showed that lineages detected in air samples reflected those in contemporaneous regional clinical specimens. Metagenomic sequencing with viral capture enrichment detected myriad human pathogens, including respiratory-associated viruses with recovery of full viral genomes. Detection of viral pathogens correlated well between virus capture sequencing and qPCR. Overall, this suggests air sampling can be an agile and effective tool for pathogen early warning, surveillance and genome characterization.

Development of COPMAN-Air method for high-sensitivity detection of SARS-CoV-2 in air

Several studies have successfully detected SARS-CoV-2 in air samples. However, most of these studies focused on validating the air collection method, and there was no report on the development of a virus detection method. In this study, to detect viruses in air samples with greater sensitively than conventional detection methods, we utilized COPMAN, a highly sensitive virus detection method originally used for wastewater samples. We applied COPMAN to air samples, thereby developing COPMAN-Air. Briefly, this method efficiently detects the extremely low levels of viral RNA in air samples via three reaction steps: RT, preamplification, and qPCR, as it is performed with COPMAN. We evaluated COPMAN-Air using samples from a fever clinic for COVID-19 patients. COPMAN-Air demonstrated a higher detection rate of viral RNA compared with conventional methods, detecting the virus in 22 out of 23 samples (95.7%) vs. 14 out of 23 samples (60.9%). Additionally, a positive correlation (r = 0.70) was detected between the amount of viral RNA detected by COPMAN-Air and the number of confirmed COVID-19 cases, suggesting that COPMAN-Air could estimate the number of SARS-CoV-2-positive individuals in a given space based on the quantitative values of SARS-CoV-2 RNA in air samples. Surveillance systems for airborne pathogens using COPMAN-Air are expected to be valuable for estimating the number of infected individuals and for guiding the implementation of public health measures.

Detection of equine influenza virus gene in the air around infected horses

Equine influenza virus (EIV) can be transmitted by inhalation of aerosolized droplets, direct contact, and contaminated fomites. However, to our knowledge, there are no reports of the recovery of EIV from the air surrounding infected horses. Here, we evaluated whether EIV can be recovered from the air in the stalls of experimentally infected horses by using an air sampler. Furthermore, we examined whether rapid molecular test kits with reaction times of less than 30 min can detect EIV from air samples for potential field application. Two horses kept in individual stalls were experimentally infected with EIV. Air samples were collected daily by using an air sampler until 13 days post-inoculation (dpi). Viral genes were detected in 26 out of 28 air samples from both horses at 1-13 dpi by real-time RT-PCR. A rapid molecular test kit based on real-time RT-PCR detected viral genes in 23 air samples from one horse at 1-9 and 12 dpi, and from the other at 1-13 dpi. These findings confirm that horses infected with EIV shed the virus into the air. Air sampling is safe for humans and horses and avoids the potential for injury when nasopharyngeal swabs need to be collected from untrained or aggressive horses. EIV RNA was detected in the air samples by using real-time RT-PCR or the rapid molecular test kit before the horses showed clinical signs. Thus, air samplers can detect EIV RNA as early as possible through routine testing in locations such as quarantine facilities.

Interpretation of indoor air surveillance for respiratory infections: a prospective longitudinal observational study in a childcare setting

BACKGROUND

Sampling the air in indoor congregate settings, where respiratory pathogens are ubiquitous, may constitute a valuable yet underutilised data source for community-wide surveillance of respiratory infections. However, there is a lack of research comparing air sampling and individual sampling of attendees. Therefore, it remains unclear how air sampling results should be interpreted for the purpose of surveillance.

METHODS

In this prospective observational study, we compared the presence and concentration of several respiratory pathogens in the air with the number of attendees with infections and the pathogen load in their nasal mucus. Weekly for 22 consecutive weeks, we sampled the air in a single childcare setting in Belgium. Concurrently, we collected the paper tissues used to wipe the noses of 23 regular attendees: children aged zero to three and childcare workers. All samples were tested for 29 respiratory pathogens using PCR.

FINDINGS

Air sampling sensitively detected most respiratory pathogens found in nasal mucus. Some pathogens (SARS-CoV-2, Pneumocystis jirovecii) were found repeatedly in the air, but rarely in nasal mucus, whilst the opposite was true for others (Human coronavirus NL63). All three pathogens with a clear outbreak pattern (Human coronavirus HKU-1, human parainfluenza virus 3 and 4) were found in the air one week before or concurrent with the first detection in paper tissue samples. The presence and concentration of pathogens in the air was best predicted by the pathogen load of the most infectious case. However, air pathogen concentrations also correlated with the number of attendees with infections. Detection and concentration in the air were associated with CO2 concentration, a marker of ventilation and occupancy.

INTERPRETATION

Our results suggest that air sampling could provide sensitive, responsive epidemiological indicators for the surveillance of respiratory pathogens. Using air CO2 concentrations to normalise such signals emerges as a promising approach.

FUNDING

KU Leuven; DURABLE project, under the EU4Health Programme of the European Commission; Thermo Fisher Scientific.

Multi-scenario surveillance of respiratory viruses in aerosols with sub-single-copy spatial resolution

Highly sensitive airborne virus monitoring is critical for preventing and containing epidemics. However, the detection of airborne viruses at ultra-low concentrations remains challenging due to the lack of ultra-sensitive methods and easy-to-deployment equipment. Here, we present an integrated microfluidic cartridge that can accurately detect SARS-COV-2, Influenza A, B, and respiratory syncytial virus with a sensitivity of 10 copies/mL. When integrated with a high-flow aerosol sampler, our microdevice can achieve a sub-single-copy spatial resolution of 0.83 copies/m3 for airborne virus surveillance with an air flow rate of 400 L/min and a sampling time of 30 minutes. We then designed a series of virus-in-aerosols monitoring systems (RIAMs), including versions of a multi-site sampling RIAMs (M-RIAMs), a stationary real-time RIAMs (S-RIAMs), and a roaming real-time RIAMs (R-RIAMs) for different application scenarios. Using M-RIAMs, we performed a comprehensive evaluation of 210 environmental samples from COVID-19 patient wards, including 30 aerosol samples. The highest positive detection rate of aerosol samples (60%) proved the aerosol-based SARS-CoV-2 monitoring represents an effective method for spatial risk assessment. The detection of 78 aerosol samples in real-world settings via S-RIAMs confirmed its reliability for ultra-sensitive and continuous airborne virus monitoring. Therefore, RIAMs shows the potential as an effective solution for mitigating the risk of airborne virus transmission.

Rapid intra-host diversification and evolution of SARS-CoV-2 in advanced HIV infection

Previous studies have linked the evolution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic variants to persistent infections in people with immunocompromising conditions, but the processes responsible for these observations are incompletely understood. Here we use high-throughput, single-genome amplification and sequencing (HT-SGS) to sequence SARS-CoV-2 spike genes from people with HIV (PWH, n = 22) and people without HIV (PWOH, n = 25). In PWOH and PWH with CD4 T cell counts (i.e., CD4 counts) ≥ 200 cells/μL, we find that most SARS-CoV-2 genomes sampled in each person share one spike sequence. By contrast, in people with advanced HIV infection (i.e., CD4 counts < 200 cells/μL), HT-SGS reveals a median of 46 distinct linked groupings of spike mutations per person. Elevated intra-host spike diversity in people with advanced HIV infection is detected immediately after COVID-19 symptom onset, and early intra-host spike diversity predicts SARS-CoV-2 shedding duration among PWH. Analysis of longitudinal timepoints reveals rapid fluctuations in spike sequence populations, replacement of founder sequences by groups of new haplotypes, and positive selection at functionally important residues. These findings demonstrate remarkable intra-host genetic diversity of SARS-CoV-2 in advanced HIV infection and suggest that adaptive intra-host SARS-CoV-2 evolution in this setting may contribute to the emergence of new variants of concern.

Multiquenching-Based Aggregation-Induced Electrochemiluminescence Sensing for Highly Sensitive Detection of the SARS-CoV-2 N Protein

The rapid epidemic around the world of coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, proves the need and stimulates efforts to explore efficient diagnostic tests for the sensitive detection of the SARS-CoV-2 virus. An aggregation-induced electrochemiluminescence (AIECL) sensor was developed for the ultrasensitive detection of the SARS-CoV-2 nucleocapsid (N) protein in this work. Tetraphenylethylene doped in zeolite imidazole backbone-90 (TPE-ZIF-90) showed highly efficient aggregation-induced emission (AIE) to endow TPE-ZIF-90 with high ECL intensity. Upon the capture of the SARS-CoV-2 N protein by immune recognition, an alkaline phosphatase (ALP)-modified gold nanoparticle (AuNP)-decorated zinc oxide (ZnO) nanoflower (ALP/Au-ZnO) composite was introduced on the sensing platform, which catalyzed L-ascorbate-2-phosphate trisodium salt (AA2P) to produce PO43- and ascorbic acid (AA). Based on a multiquenching of the ECL signal strategy, including resonance energy transfer (RET) between TPE-ZIF-90 and Au-ZnO, disassembly of TPE-ZIF-90 triggered by the strong coordination between PO43- and Zn2+, and RET between TPE-ZIF-90 and AuNPs produced in situ by the AA reductive reaction, the constructed AIECL sensor achieved highly sensitive detection of the SARS-CoV-2 N protein with a low limit of detection of 0.52 fg/mL. With the merits of high specificity, good stability, and proven application ability, the present RET- and enzyme-triggered multiquenching AIECL sensor may become a powerful tool in the field of SARS-CoV-2 virus diagnosis.

Surveillance of respiratory viruses by aerosol screening in indoor air as an early warning system for epidemics

The development of effective methods for the surveillance of seasonal respiratory viruses is required for the timely management of outbreaks. We aimed to survey Influenza-A, Influenza-B, RSV-A, Rhinovirus and SARS-CoV-2 surveillance in a tertiary hospital and a campus over 5 months. The effectiveness of air screening as an early warning system for respiratory viruses was evaluated in correlation with respiratory tract panel test results. The overall viral positivity was higher on the campus than in the hospital (55.0% vs. 38.0%). Influenza A was the most prevalent pathogen in both locations. There were two influenza peaks (42nd and 49th weeks) in the hospital air, and a delayed peak was detected on campus in the 1st-week of January. Panel tests indicated a high rate of Influenza A in late December. RSV-A-positivity was higher on the campus than the hospital (21.6% vs. 7.4%). Moreover, we detected two RSV-A peaks in the campus air (48th and 51st weeks) but only one peak in the hospital and panel tests (week 49). Although rhinovirus was the most common pathogen in panel tests, rhinovirus positivity was low in air samples. The air screening for Influenza-B and SARS-Cov-2 revealed comparable positivity rates with panel tests. Air screening can be integrated into surveillance programs to support infection control programs for potential epidemics of respiratory virus infections except for rhinoviruses.

Advancements in Airborne Viral Nucleic Acid Detection with Wearable Devices

Wearable health sensors for an expanding range of physiological parameters have experienced rapid development in recent years and are poised to disrupt the way healthcare is tracked and administered. The monitoring of environmental contaminants with wearable technologies is an additional layer of personal and public healthcare and is also receiving increased focus. Wearable sensors that detect exposure to airborne viruses could alert wearers of viral exposure and prompt proactive testing and minimization of viral spread, benefitting their own health and decreasing community risk. With the high levels of asymptomatic spread of COVID-19 observed during the pandemic, such devices could dramatically enhance our pandemic response capabilities in the future. To facilitate advancements in this area, this review summarizes recent research on airborne viral detection using wearable sensing devices as well as technologies suitable for wearables. Since the low concentration of viral particles in the air poses significant challenges to detection, methods for airborne viral particle collection and viral sensing are discussed in detail. A special focus is placed on nucleic acid-based viral sensing mechanisms due to their enhanced ability to discriminate between viral subtypes. Important considerations for integrating airborne viral collection and sensing on a single wearable device are also discussed.

Omicron and Delta variant prevalence detection and identification during the fourth COVID-19 wave in Mexico using wastewater-based epidemiology

Objectives

To identify the SARS-CoV-2 variants Delta and Omicron during the fourth wave of the COVID-19 pandemic in Mexico using samples taken from 19 locations in 18 out of the 32 states.

Methods

The genetic material concentration was done with PEG/NaCl precipitation, SARS-CoV-2 presence was confirmed by reverse transcriptase-quantitative polymerase chain reaction assay, the variant detection was carried out using a commercial mutation detection panel kit, and variant/mutation confirmation was done by amplicon sequencing of receptor-binding domain target region. The study used 41 samples.

Results

The Delta variant was confirmed in two samples during August 2021 (Querétaro and CDMX) and in three samples during November 2021 (Aguascalientes, Ciudad Juárez campuses, and Nuevo Leon). In December 2021, another sample with the Delta variant was confirmed in Nuevo Leon. Between January to March 2022 only the presence of Omicron was confirmed, (variant BA.1). Additionally, in this period six samples were identified with the status "Variant Not Determined".

Conclusion

To our knowledge, this study is one of the first to identify Omicron and Delta variants with polymerase chain reaction in Mexico and Latin America and its distribution across the country with 56% Mexican states making it a viable alternative for variant detection without conducting a large quantity of sequencing of clinical tests.

Environmental surface monitoring as a noninvasive method for SARS-CoV-2 surveillance in community settings: Lessons from a university campus study

Environmental testing of high-touch objects is a potential noninvasive approach for monitoring population-level trends of SARS-CoV-2 and other respiratory viruses within a defined setting. We aimed to determine the association between SARS-CoV-2 contamination on high-touch environmental surfaces, community level case incidence, and university student health data. Environmental swabs were collected from January 2022 to November 2022 from high-touch objects and surfaces from five locations on a large university campus in Florida, USA. RT-qPCR was used to detect and quantify viral RNA, and a subset of positive samples was analyzed by viral genome sequencing to identify circulating lineages. During the study period, we detected SARS-CoV-2 viral RNA on 90.7 % of 162 tested samples. Levels of environmental viral RNA correlated with trends in community-level activity and case reports from the student health center. A significant positive correlation was observed between the estimated viral gene copy number in environmental samples and the weekly confirmed cases at the university. Viral sequencing data from environmental samples identified lineages concurrently circulating in the local community and state based on genomic surveillance data. Further, we detected emerging variants in environmental samples prior to their identification by clinical genomic surveillance. Our results demonstrate the utility of viral monitoring on high-touch environmental surfaces for SARS-CoV-2 surveillance at a community level. In communities with delayed or limited testing facilities, immediate environmental surface testing may considerably inform epidemic dynamics.

Air Change Rate and SARS-CoV-2 Exposure in Hospitals and Residences: A Meta-Analysis

As SARS-CoV-2 swept across the globe, increased ventilation and implementation of air cleaning were emphasized by the US CDC and WHO as important strategies to reduce the risk of inhalation exposure to the virus. To assess whether higher ventilation and air cleaning rates lead to lower exposure risk to SARS-CoV-2, 1274 manuscripts published between April 2020 and September 2022 were screened using key words "airborne SARS-CoV-2 or "SARS-CoV-2 aerosol". Ninety-three studies involved air sampling at locations with known sources (hospitals and residences) were selected and associated data were compiled. Two metrics were used to assess exposure risk: SARS-CoV-2 concentration and SARS-CoV-2 detection rate in air samples. Locations were categorized by type (hospital or residence) and proximity to the sampling location housing the isolated/quarantined patient (primary or secondary). The results showed that hospital wards had lower airborne virus concentrations than residential isolation rooms. A negative correlation was found between airborne virus concentrations in primary-occupancy areas and air changes per hour (ACH). In hospital settings, sample positivity rates were significantly reduced in secondary-occupancy areas compared to primary-occupancy areas, but they were similar across sampling locations in residential settings. ACH and sample positivity rates were negatively correlated, though the effect was diminished when ACH values exceeded 8. While limitations associated with diverse sampling protocols exist, data considered by this meta-analysis support the notion that higher ACH may reduce exposure risks to the virus in ambient air.

Rapid Emergence and Evolution of SARS-CoV-2 Variants in Advanced HIV Infection

Previous studies have linked the evolution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic variants to persistent infections in people with immunocompromising conditions1-4, but the evolutionary processes underlying these observations are incompletely understood. Here we used high-throughput, single-genome amplification and sequencing (HT-SGS) to obtain up to ~103 SARS-CoV-2 spike gene sequences in each of 184 respiratory samples from 22 people with HIV (PWH) and 25 people without HIV (PWOH). Twelve of 22 PWH had advanced HIV infection, defined by peripheral blood CD4 T cell counts (i.e., CD4 counts) <200 cells/μL. In PWOH and PWH with CD4 counts ≥200 cells/μL, most single-genome spike sequences in each person matched one haplotype that predominated throughout the infection. By contrast, people with advanced HIV showed elevated intra-host spike diversity with a median of 46 haplotypes per person (IQR 14-114). Higher intra-host spike diversity immediately after COVID-19 symptom onset predicted longer SARS-CoV-2 RNA shedding among PWH, and intra-host spike diversity at this timepoint was significantly higher in people with advanced HIV than in PWOH. Composition of spike sequence populations in people with advanced HIV fluctuated rapidly over time, with founder sequences often replaced by groups of new haplotypes. These population-level changes were associated with a high total burden of intra-host mutations and positive selection at functionally important residues. In several cases, delayed emergence of detectable serum binding to spike was associated with positive selection for presumptive antibody-escape mutations. Taken together, our findings show remarkable intra-host genetic diversity of SARS-CoV-2 in advanced HIV infection and suggest that adaptive intra-host SARS-CoV-2 evolution in this setting may contribute to the emergence of new variants of concern (VOCs).

Hot-Pressing Metal Covalent Organic Frameworks as Personal Protection Films

Effective personal protection is crucial for controlling infectious disease spread. However, commonly used personal protective materials such as disposable masks lack antibacterial/antiviral function and may lead to cross infection. Herein, a polyethylene glycol-assisted solvent-free strategy is proposed to rapidly synthesize a series of the donor-acceptor metal-covalent organic frameworks (MCOFs) (i.e., GZHMU-2, JNM-1, and JNM-2) under air atmosphere and henceforth extend it via in situ hot-pressing process to prepare MCOFs based films with photocatalytic disinfect ability. Best of them, the newly designed GZHMU-2 has a wide absorption spectrum (200 to 1500 nm) and can efficiently produce reactive oxygen species under sunlight irradiation, achieving excellent photocatalytic disinfection performance. After in situ hot-pressing as a film material, the obtained GZHMU-2/NMF can effectively kill E. coli (99.99%), S. aureus (99%), and H1N1 (92.5%), meanwhile possessing good reusability. Noteworthy, the long-term use of a GZHMU-2/NWF-based mask has verified no damage to the living body by measuring the expression of mouse blood routine, lung tissue, and inflammatory factors at the in-vivo level.

Advancing pathogen genomics in resource-limited settings

Genomic sequencing has emerged as a powerful tool to enhance early pathogen detection and characterization with implications for public health and clinical decision making. Although widely available in developed countries, the application of pathogen genomics among low-resource, high-disease burden settings remains at an early stage. In these contexts, tailored approaches for integrating pathogen genomics within infectious disease control programs will be essential to optimize cost efficiency and public health impact. We propose a framework for embedding pathogen genomics within national surveillance plans across a spectrum of surveillance and laboratory capacities. We adopt a public health approach to genomics and examine its application to high-priority diseases relevant in resource-limited settings. For each grouping, we assess the value proposition for genomics to inform public health and clinical decision-making, alongside its contribution toward research and development of novel diagnostics, therapeutics, and vaccines.

Metagenomic sequencing detects human respiratory and enteric viruses in air samples collected from congregate settings

Innovative methods for evaluating virus risk and spread, independent of test-seeking behavior, are needed to improve routine public health surveillance, outbreak response, and pandemic preparedness. Throughout the COVID-19 pandemic, environmental surveillance strategies, including wastewater andair sampling, have been used alongside widespread individual-based SARS-CoV-2 testing programs to provide population-level data. These environmental surveillance strategies have predominantly relied on pathogen-specific detection methods to monitor viruses through space and time. However, this provides a limited picture of the virome present in an environmental sample, leaving us blind to most circulating viruses. In this study, we explore whether pathogen-agnostic deep sequencing can expand the utility of air sampling to detect many human viruses. We show that sequence-independent single-primer amplification sequencing of nucleic acids from air samples can detect common and unexpected human respiratory and enteric viruses, including influenza virus type A and C, respiratory syncytial virus, human coronaviruses, rhinovirus, SARS-CoV-2, rotavirus, mamastrovirus, and astrovirus.

Four Methods for Monitoring SARS-CoV-2 and Influenza A Virus Activity in Schools

This cross-sectional study describes 4 parallel approaches used simultaneously to monitor influenza A virus and SARS-CoV-2 activity within a Wisconsin school district during the Fall 2022 semester and briefly following winter break.

Metagenomic sequencing detects human respiratory and enteric viruses in air samples collected from congregate settings

Innovative methods for evaluating virus risk and spread, independent of test-seeking behavior, are needed to improve routine public health surveillance, outbreak response, and pandemic preparedness. Throughout the COVID-19 pandemic, environmental surveillance strategies, including wastewater and air sampling, have been used alongside widespread individual-based SARS-CoV-2 testing programs to provide population-level data. These environmental surveillance strategies have predominantly relied on pathogen-specific detection methods to monitor viruses through space and time. However, this provides a limited picture of the virome present in an environmental sample, leaving us blind to most circulating viruses. In this study, we explore whether pathogen-agnostic deep sequencing can expand the utility of air sampling to detect many human viruses. We show that sequence-independent single-primer amplification sequencing of nucleic acids from air samples can detect common and unexpected human respiratory and enteric viruses, including influenza virus type A and C, respiratory syncytial virus, human coronaviruses, rhinovirus, SARS-CoV-2, rotavirus, mamastrovirus, and astrovirus.

Detection and isolation of infectious SARS-CoV-2 omicron subvariants collected from residential settings

Airborne transmission of infectious (viable) SARS-CoV-2 is increasingly accepted as the primary manner by which the virus is spread from person to person. Risk of exposure to airborne virus is higher in enclosed and poorly ventilated spaces. We present a study focused on air sampling within residences occupied by individuals with COVID-19. Air samplers (BioSpot-VIVAS, VIVAS, and BC-251) were positioned in primary- and secondary-occupancy regions in seven homes. Swab samples were collected from high-touch surfaces. Isolation of SARS-CoV-2 was attempted for samples with virus detectable by RT-qPCR. Viable virus was quantified by plaque assay, and complete virus genome sequences were obtained for selected samples from each sampling day. SARS-CoV-2 was detected in 24 of 125 samples (19.2%) by RT-qPCR and isolated from 14 (11.2%) in cell cultures. It was detected in 80.9% (17/21) and cultured from 61.9% (13/21) of air samples collected using water condensation samplers, compared to swab samples which had a RT-qPCR detection rate of 10.5% (4/38) and virus isolation rate of 2.63% (1/38). No statistically significant differences existed in the likelihood of virus detection by RT-qPCR or amount of infectious virus in the air between areas of primary and secondary occupancy within residences. Our work provides information about the presence of SARS-CoV-2 in the air within homes of individuals with COVID-19. Information herein can help individuals make informed decisions about personal exposure risks when sharing indoor spaces with infected individuals isolating at home and further inform health departments and the public about SARS-CoV-2 exposure risks within residences.

Detection of mpox virus in ambient air in a sexual health clinic

Although transmitted mainly through direct (sexual) contact, mpox virus (MPXV) can be detected in ambient air. We explored the use of air sampling for diagnosis or (genomic) surveillance of mpox in a sexual health clinic. For six out of six patients who were infected with MPXV, all four of our ambient air PCR tests were positive. For 14 uninfected patients, PCR was positive in three ambient air samples, albeit with higher cycle threshold (Ct) values. Genomic sequencing of samples from two positive patients showed matching sequences between air and clinical samples.

Viral infections at the animal-human interface-Learning lessons from the SARS-CoV-2 pandemic

This Lilliput explores the current epidemiological and virological arguments for a zoonotic origin of the COVID-19 pandemic. While the role of bats, pangolins and racoon dogs as viral reservoirs has not yet been proven, a spill-over of a coronavirus infection from animals into humans at the Huanan food market in Wuhan has a much greater plausibility than alternative hypotheses such as a laboratory virus escape, deliberate genetic engineering or introduction by cold chain food products. This Lilliput highlights the dynamic nature of the animal-human interface for viral cross-infections from humans into feral white tail deer or farmed minks (reverse zoonosis). Surveillance of viral infections at the animal-human interface is an urgent task since live animal markets are not the only risks for future viral spill-overs. Climate change will induce animal migration which leads to viral exchanges between animal species that have not met in the past. Environmental change and deforestation will also increase contact between animals and humans. Developing an early warning system for emerging viral infections becomes thus a societal necessity not only for human but also for animal and environmental health (One Health concept). Microbiologists have developed tools ranging from virome analysis in key suspects such as viral reservoirs (bats, wild game animals, bushmeat) and in humans exposed to wild animals, to wastewater analysis to detect known and unknown viruses circulating in the human population and sentinel studies in animal-exposed patients with fever. Criteria need to be developed to assess the virulence and transmissibility of zoonotic viruses. An early virus warning system is costly and will need political lobbying. The accelerating number of viral infections with pandemic potential over the last decades should provide the public pressure to extend pandemic preparedness for the inclusion of early viral alert systems.

Indoor air surveillance and factors associated with respiratory pathogen detection in community settings in Belgium

Currently, the real-life impact of indoor climate, human behaviour, ventilation and air filtration on respiratory pathogen detection and concentration are poorly understood. This hinders the interpretability of bioaerosol quantification in indoor air to surveil respiratory pathogens and transmission risk. We tested 341 indoor air samples from 21 community settings in Belgium for 29 respiratory pathogens using qPCR. On average, 3.9 pathogens were positive per sample and 85.3% of samples tested positive for at least one. Pathogen detection and concentration varied significantly by pathogen, month, and age group in generalised linear (mixed) models and generalised estimating equations. High CO2 and low natural ventilation were independent risk factors for detection. The odds ratio for detection was 1.09 (95% CI 1.03-1.15) per 100 parts per million (ppm) increase in CO2, and 0.88 (95% CI 0.80-0.97) per stepwise increase in natural ventilation (on a Likert scale). CO2 concentration and portable air filtration were independently associated with pathogen concentration. Each 100ppm increase in CO2 was associated with a qPCR Ct value decrease of 0.08 (95% CI -0.12 to -0.04), and portable air filtration with a 0.58 (95% CI 0.25-0.91) increase. The effects of occupancy, sampling duration, mask wearing, vocalisation, temperature, humidity and mechanical ventilation were not significant. Our results support the importance of ventilation and air filtration to reduce transmission.

Detection of hospital environmental contamination during SARS-CoV-2 Omicron predominance using a highly sensitive air sampling device

Background and objectives

The high transmissibility of SARS-CoV-2 has exposed weaknesses in our infection control and detection measures, particularly in healthcare settings. Aerial sampling has evolved from passive impact filters to active sampling using negative pressure to expose culture substrate for virus detection. We evaluated the effectiveness of an active air sampling device as a potential surveillance system in detecting hospital pathogens, for augmenting containment measures to prevent nosocomial transmission, using SARS-CoV-2 as a surrogate.

Methods

We conducted air sampling in a hospital environment using the AerosolSense^TM air sampling device and compared it with surface swabs for their capacity to detect SARS-CoV-2.

Results

When combined with RT-qPCR detection, we found the device provided consistent SARS-CoV-2 detection, compared to surface sampling, in as little as 2 h of sampling time. The device also showed that it can identify minute quantities of SARS-CoV-2 in designated "clean areas" and through a N95 mask, indicating good surveillance capacity and sensitivity of the device in hospital settings.

Conclusion

Active air sampling was shown to be a sensitive surveillance system in healthcare settings. Findings from this study can also be applied in an organism agnostic manner for surveillance in the hospital, improving our ability to contain and prevent nosocomial outbreaks.