Dataset Information

Air cleaners and respiratory infections in schools: A modeling study using epidemiological, environmental, and molecular data.

ABSTRACT:

Background

Using a multiple-measurement approach, we examined the real-world effectiveness of portable HEPA-air filtration devices (air cleaners) in a school setting.

Methods

We collected environmental (CO₂, particle concentrations), epidemiological (absences related to respiratory infections), audio (coughing), and molecular data (bioaerosol and saliva samples) over seven weeks during winter 2022/2023 in two Swiss secondary school classes. Using a cross-over study design, we compared particle concentrations, coughing, and the risk of infection with vs without air cleaners.

Results

All 38 students (age 13-15 years) participated. With air cleaners, mean particle concentration decreased by 77% (95% credible interval 63%-86%). There were no differences in CO₂ levels. Absences related to respiratory infections were 22 without vs 13 with air cleaners. Bayesian modeling suggested a reduced risk of infection, with a posterior probability of 91% and a relative risk of 0.73 (95% credible interval 0.44-1.18). Coughing also tended to be less frequent (posterior probability 93%). Molecular analysis detected mainly non-SARS-CoV-2 viruses in saliva (50/448 positive), but not in bioaerosols (2/105 positive) or HEPA-filters (4/160). The detection rate was similar with vs without air cleaners. Spatiotemporal analysis of positive saliva samples identified several likely transmissions.

Conclusions

Air cleaners improved air quality, showed a potential benefit in reducing respiratory infections, and were associated with less coughing. Airborne detection of non-SARS-CoV-2 viruses was rare, suggesting that these viruses may be more difficult to detect in the air. Future studies should examine the importance of close contact and long-range transmission, and the cost-effectiveness of using air cleaners.

SUBMITTER: Banholzer N

PROVIDER: S-EPMC10793541 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

Air cleaners and respiratory infections in schools: A modeling study using epidemiological, environmental, and molecular data.

Banholzer Nicolas N Jent Philipp P Bittel Pascal P Zürcher Kathrin K Furrer Lavinia L Bertschinger Simon S Weingartner Ernest E Ramette Alban A Egger Matthias M Hascher Tina T Fenner Lukas L

medRxiv : the preprint server for health sciences 20231230

<h4>Background</h4>Using a multiple-measurement approach, we examined the real-world effectiveness of portable HEPA-air filtration devices (air cleaners) in a school setting.<h4>Methods</h4>We collected environmental (CO<sub>2</sub>, particle concentrations), epidemiological (absences related to respiratory infections), audio (coughing), and molecular data (bioaerosol and saliva samples) over seven weeks during winter 2022/2023 in two Swiss secondary school classes. Using a cross-over study desi ...[more]

PMID: 38234723

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Project description:BackgroundGrowing evidence suggests an important contribution of airborne transmission to the overall spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), in particular via smaller particles called aerosols. However, the contribution of school children to SARS-CoV-2 transmission remains uncertain. The aim of this study was to assess transmission of airborne respiratory infections and the association with infection control measures in schools using a multiple-measurement approach.Methods and findingsWe collected epidemiological (cases of Coronavirus Disease 2019 (COVID-19)), environmental (CO2, aerosol and particle concentrations), and molecular data (bioaerosol and saliva samples) over 7 weeks from January to March 2022 (Omicron wave) in 2 secondary schools (n = 90, average 18 students/classroom) in Switzerland. We analyzed changes in environmental and molecular characteristics between different study conditions (no intervention, mask wearing, air cleaners). Analyses of environmental changes were adjusted for different ventilation, the number of students in class, school and weekday effects. We modeled disease transmission using a semi-mechanistic Bayesian hierarchical model, adjusting for absent students and community transmission. Molecular analysis of saliva (21/262 positive) and airborne samples (10/130) detected SARS-CoV-2 throughout the study (weekly average viral concentration 0.6 copies/L) and occasionally other respiratory viruses. Overall daily average CO2 levels were 1,064 ± 232 ppm (± standard deviation). Daily average aerosol number concentrations without interventions were 177 ± 109 1/cm3 and decreased by 69% (95% CrI 42% to 86%) with mask mandates and 39% (95% CrI 4% to 69%) with air cleaners. Compared to no intervention, the transmission risk was lower with mask mandates (adjusted odds ratio 0.19, 95% CrI 0.09 to 0.38) and comparable with air cleaners (1.00, 95% CrI 0.15 to 6.51). Study limitations include possible confounding by period as the number of susceptible students declined over time. Furthermore, airborne detection of pathogens document exposure but not necessarily transmission.ConclusionsMolecular detection of airborne and human SARS-CoV-2 indicated sustained transmission in schools. Mask mandates were associated with greater reductions in aerosol concentrations than air cleaners and with lower transmission. Our multiple-measurement approach could be used to continuously monitor transmission risk of respiratory infections and the effectiveness of infection control measures in schools and other congregate settings.

Project description:BackgroundLower respiratory tract infections (LRTIs) are one of the leading causes of hospital admissions among children. In this study, we aimed to describe the epidemiological characteristics of viral pathogens associated with LRTIs in hospitalized children in Yan'an; this has yet to be reported in the literature and may guide public health interventions and resource allocation in this region.MethodsBetween June 2021 and May 2023, we conducted a retrospective analysis of the results of viral detection using oral pharyngeal swabs from 4565 children with LRTIs in the Inpatient Department of Yan'an University Affiliated Hospital. Eleven respiratory viruses, including influenza A virus (Flu A), influenza A H1N1 virus (H1N1), seasonal influenza A H3N2 virus (H3N2), influenza B virus (Flu B), parainfluenza virus (HPIV), adenovirus (HADV), bocavirus (HBoV), rhinovirus (HRV), metapneumovirus (HNPV), coronavirus (HCoV), and respiratory syncytial virus (HRSV), were confirmed by applying a multiplex real-time polymerase chain reaction (PCR) kit for respiratory viruses. We evaluated the epidemiological features of infections caused by respiratory pathogens, including aging, gender and the seasonal variations of different pathogens, and explored the high-risk factors associated with virus-caused pneumonia.ResultsAt least one virus was detected in all 4565 cases; the positivity rate was 27.95%. We also detected a total of 1,276 cases with mixed infections (with two or more viruses). Of the positive cases, 59.3% were male and 40.7% were female (x2 = 0.41, P = 0.68). The highest positivity rates for respiratory pathogens were observed for HRSV, HRV, and HADV, at 5.98%, 5.67%, and 4.38%, respectively. We also observed variations in the number and positivity rates of respiratory pathogen infections by season, age and gender. HPIV (x2 = 12.05, P < 0.05) and HADV (x2 = 11.73, P < 0.05) were more common in children under three years-of-age. Notably, with the exception of the 1 to < 3 years age group, males consistently demonstrated elevated infection rates across other age groups.ConclusionsOur analysis revealed that respiratory pathogen infections varied by gender, season, and age in the enrolled population of children.

Dataset Information

Air cleaners and respiratory infections in schools: A modeling study using epidemiological, environmental, and molecular data.

Background

Methods

Results

Conclusions

Publications

Air cleaners and respiratory infections in schools: A modeling study using epidemiological, environmental, and molecular data.

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