Angeliki Chatziantoniou

Indoor particulate matter is a Group 1 carcinogen with no identified exposure threshold, and the portable air cleaners now widely deployed in European schools, hospitals and offices are almost always evaluated by a change in mean concentration measured before and after installation in the same room. We applied a probabilistic incremental lifetime cancer risk (ILCR) framework to size-resolved particulate matter in thirteen occupied micro-environments in five countries, monitored continuously at five-minute resolution within the TwinAIR pilot network, and then tested that evaluation design against the measurements it rests on. Risk was uniformly low: every site-by-fraction estimate fell below the 10⁻⁶ de minimis threshold by between one and three orders of magnitude, and the conclusion survived recomputation from the measured concentration distributions (11.2 to 353 times below the threshold across forty-two estimates) and the substitution of paediatric exposure parameters. The evaluation design did not survive. In the two rooms that received air cleaners, measured PM_2.5 rose by 7.8% and 21.0%, while a thermo-hygrometric regression explaining 1–6% of the variance—the concentration model underlying the probabilistic estimates—predicted reductions of 6.7% and 2.3%. Applying the same phase boundary to four sensors in three micro-environments that received no device produced changes from −74.3% to +37.2%, exceeding in magnitude and spanning in direction the contrast attributed to the intervention. The novelty of this work is therefore twofold: a harmonised probabilistic risk assessment of thirteen real occupied interiors on a single scale, and a demonstration, from the same network’s data, that within-room pre–post designs without concurrent controls cannot identify an air-cleaning effect.

Indoor environments are the dominant setting for human exposure to respiratory viruses, yet routine molecular surveillance of indoor air remains rare outside single-site studies. Within the Horizon Europe TwinAIR project, a single harmonised workflow was applied to 102 indoor air samples (2000 L each) collected between October 2024 and February 2026 at ten pilot settings in Germany, the United Kingdom, Ireland, Spain, Greece and Sweden, covering university teaching rooms, school classrooms and staff rooms, healthcare-associated offices, workplace offices, an elderly care facility and public transport vehicles. Air was collected onto gelatine membrane filters with a Sartorius MD8 Airport sampler, total nucleic acid was extracted with the QIAamp Viral RNA Mini kit, and five targets—SARS-CoV-2, human adenovirus, respiratory syncytial virus A/B, influenza A and rhinovirus—were quantified against target-specific standard curves as genome copies per cubic metre (GC/m³). At least one target was detected in 84 of 102 samples (82.4%; 95% CI 73.8–88.5). SARS-CoV-2 was the most frequent and most abundant target (64.7%; up to 8.36 × 10⁶ GC/m³) and adenovirus was the second most frequent though consistently low in concentration (33.3%); both were recovered from all six countries. Rhinovirus (14.7%, five countries), RSV A/B (8.8%, four) and influenza A (6.9%, four) were detected less often yet reached high concentrations when present, showing that detection frequency alone substantially understates airborne viral burden. Detection of viral genome does not establish infectivity.

Background/Objectives: Schools are recognised sites of exposure to respiratory viruses for students and staff, representing a recognised public health concern. Environmental air sampling has been developed as a non-invasive surveillance approach that can detect circulating respiratory viruses, including those shed by asymptomatic persons, without the need for individual testing. However, the methodological and operational evidence base for this approach within educational settings remains nascent. This scoping review systematically maps the extant literature, characterising targeted respiratory viruses, sampling and analytical methodologies, assessed environmental covariates, and critical knowledge gaps. Methods: Adhering to the PRISMA-ScR guidelines, a systematic search of PubMed, Web of Science, and ScienceDirect was executed without temporal restrictions. Results: Eleven studies met the inclusion criteria. Viral RNA detection frequencies exhibited substantial heterogeneity (0–98.5%), primarily attributable to the study design parameters, single-target assays yielding lower positivity versus broad-spectrum multiplex panels, compounded by the stringency of concurrent infection-control interventions. In the singular investigation reporting comprehensive viral ranking, rhinovirus predominated, followed by respiratory syncytial virus (RSV-A/B), and influenza A/B. SARS-CoV-2 detection was profoundly influenced by the pandemic phase dynamics. Critically, all positive detections signified nucleic acid presence, with zero studies confirming viable virions via infectivity assays, representing a fundamental interpretive limitation. Conclusions: Airborne respiratory viral RNA from infected school occupants is unequivocally detectable, positioning environmental sampling as a promising adjunct to clinical surveillance for syndromic characterisation. Nevertheless, translating this approach into a robust, real-time operational infection-control instrument necessitates rigorous methodological harmonisation, alongside comprehensive assessments of viral infectivity, economic viability, and pragmatic feasibility to bridge prevailing translational gaps. Beyond mapping the primary studies, this review additionally benchmarks school-based sampling against practice in hospitals, universities, and other congregate settings, evaluates surface sampling as a complementary environmental modality, and analyses the dilution-limited regime that governs airborne viral detection in ventilated classrooms, which defines the performance envelope that next-generation high-flow, low-loss samplers must meet.

The COVID-19 pandemic has underscored the importance of alternative epidemiological tools capable of providing real-time, population-level insights into infectious disease dynamics. Wastewater-based epidemiology (WBE) has emerged as a powerful, non-invasive method for tracking viral transmission within communities. While initially focused on SARS-CoV-2, WBE now offers the potential for multiplex surveillance of a broader range of respiratory pathogens. This study applied WBE to monitor the circulation of six major respiratory viruses such as Human adenovirus (HAdV), SARS-CoV-2, Influenza A and B, Respiratory Syncytial Virus (RSV) A/B, and Rhinoviruses, over a six-month period (ISO weeks 2022-40 to 2023-13) in the city of Patras, Greece. Weekly composite samples from a central wastewater treatment plant were analyzed via quantitative PCR, and viral genome concentrations were normalized per 100,000 inhabitants. The results revealed distinct circulation patterns: HAdV and SARS-CoV-2 were detected consistently throughout the period, while Influenza A peaked during the winter months, followed by Influenza B. RSV, however, appeared earlier in the season (first detectable from ISO week 2022-46) and overlapped with Influenza. Rhinoviruses displayed intermittent peaks, indicating multiple waves or persistent low-level transmission. Correlation analyses showed strong positive associations between influenza viruses, RSV, and SARS-CoV-2, suggesting synchronized seasonal trends. Hierarchical cluster analysis classified the viruses into three distinct groups: (1) an epidemic cluster including Influenza A/B, RSV, and Rhinoviruses; (2) a persistently present cluster represented by HAdV; and (3) a separate episodic cluster characterized by SARS-CoV-2. These groupings reflect differences in viral epidemiology and shedding behaviour. This study confirms the effectiveness of WBE in tracking the temporal dynamics of multiple respiratory viruses and provides evidence of its utility in supplementing traditional clinical surveillance systems. The consistent detection of underreported pathogens such as HAdV underscores the added value of environmental monitoring for public health preparedness and early warning applications. These findings advocate for the integration of WBE into routine respiratory virus surveillance frameworks.