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1.
Atmos Pollut Res ; 13(11): 101594, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2104373

ABSTRACT

Nowadays, there has been a substantial proliferation in the use of low-cost particulate matter (PM) sensors and facilitating as an indicator of overall air quality. However, during COVID-19 epidemics, air pollution sources have been deteriorated significantly, and given offer to evaluate the impact of COVID-19 on air quality in the world's most polluted city: Delhi, India. To address low-cost PM sensors, this study aimed to a) conduct a long-term field inter-comparison of twenty-two (22) low-cost PM sensors with reference instruments over 10-month period (evaluation period) spanning months from May 2019 to February 2020; b) trend of PM mass and number count; and c) probable local and regional sources in Delhi during Pre-CVOID (P-COVID) periods. The comparison of low-cost PM sensors with reference instruments results found with R2 ranging between 0.74 and 0.95 for all sites and confirm that PM sensors can be a useful tool for PM monitoring network in Delhi. Relative reductions in PM2.5 and particle number count (PNC) due to COVID-outbreaks showed in the range between (2-5%) and (4-13%), respectively, as compared to the P-COVID periods. The cluster analysis reveals air masses originated ∼52% from local, while ∼48% from regional sources in P-COVID and PM levels are encountered 47% and 66-70% from local and regional sources, respectively. Overall results suggest that low-cost PM sensors can be used as an unprecedented aid in air quality applications, and improving non-attainment cities in India, and that policy makers can attempt to revise guidelines for clean air.

2.
Infect Control Hosp Epidemiol ; : 1-6, 2022 Apr 20.
Article in English | MEDLINE | ID: covidwho-1805485

ABSTRACT

OBJECTIVE: To determine the impact of various aerosol mitigation interventions and to establish duration of aerosol persistence in a variety of dental clinic configurations. METHODS: We performed aerosol measurement studies in endodontic, orthodontic, periodontic, pediatric, and general dentistry clinics. We used an optical aerosol spectrometer and wearable particulate matter sensors to measure real-time aerosol concentration from the vantage point of the dentist during routine care in a variety of clinic configurations (eg, open bay, single room, partitioned operatories). We compared the impact of aerosol mitigation strategies (eg, ventilation and high-volume evacuation (HVE), and prevalence of particulate matter) in the dental clinic environment before, during, and after high-speed drilling, slow-speed drilling, and ultrasonic scaling procedures. RESULTS: Conical and ISOVAC HVE were superior to standard-tip evacuation for aerosol-generating procedures. When aerosols were detected in the environment, they were rapidly dispersed within minutes of completing the aerosol-generating procedure. Few aerosols were detected in dental clinics, regardless of configuration, when conical and ISOVAC HVE were used. CONCLUSIONS: Dentists should consider using conical or ISOVAC HVE rather than standard-tip evacuators to reduce aerosols generated during routine clinical practice. Furthermore, when such effective aerosol mitigation strategies are employed, dentists need not leave dental chairs fallow between patients because aerosols are rapidly dispersed.

3.
J Med Syst ; 45(12): 105, 2021 Nov 02.
Article in English | MEDLINE | ID: covidwho-1491288

ABSTRACT

Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is usually more complicated. Reliable deployment of ML4H to the real world is challenging as examples from diabetic retinopathy or Covid-19 screening show. We envision an integrated framework of algorithm auditing and quality control that provides a path towards the effective and reliable application of ML systems in healthcare. In this editorial, we give a summary of ongoing work towards that vision and announce a call for participation to the special issue  Machine Learning for Health: Algorithm Auditing & Quality Control in this journal to advance the practice of ML4H auditing.


Subject(s)
Algorithms , Machine Learning , Quality Control , Humans
4.
BMJ Open ; 11(9): e045557, 2021 09 02.
Article in English | MEDLINE | ID: covidwho-1394106

ABSTRACT

OBJECTIVE: The COVID-19 pandemic has precipitated widespread shortages of filtering facepiece respirators (FFRs) and the creation and sharing of proposed substitutes (novel designs, repurposed materials) with limited testing against regulatory standards. We aimed to categorically test the efficacy and fit of potential N95 respirator substitutes using protocols that can be replicated in university laboratories. SETTING: Academic medical centre with occupational health-supervised fit testing along with laboratory studies. PARTICIPANTS: Seven adult volunteers who passed quantitative fit testing for small-sized (n=2) and regular-sized (n=5) commercial N95 respirators. METHODS: Five open-source potential N95 respirator substitutes were evaluated and compared with commercial National Institute for Occupational Safety and Health (NIOSH)-approved N95 respirators as controls. Fit testing using the 7-minute standardised Occupational Safety and Health Administration fit test was performed. In addition, protocols that can be performed in university laboratories for materials testing (filtration efficiency, air resistance and fluid resistance) were developed to evaluate alternate filtration materials. RESULTS: Among five open-source, improvised substitutes evaluated in this study, only one (which included a commercial elastomeric mask and commercial HEPA filter) passed a standard quantitative fit test. The four alternative materials evaluated for filtration efficiency (67%-89%) failed to meet the 95% threshold at a face velocity (7.6 cm/s) equivalent to that of a NIOSH particle filtration test for the control N95 FFR. In addition, for all but one material, the small surface area of two 3D-printed substitutes resulted in air resistance that was above the maximum in the NIOSH standard. CONCLUSIONS: Testing protocols such as those described here are essential to evaluate proposed improvised respiratory protection substitutes, and our testing platform could be replicated by teams with similar cross-disciplinary research capacity. Healthcare professionals should be cautious of claims associated with improvised respirators when suggested as FFR substitutes.


Subject(s)
COVID-19 , Occupational Exposure , Respiratory Protective Devices , Adult , Equipment Design , Humans , N95 Respirators , Pandemics/prevention & control , SARS-CoV-2 , United States , Ventilators, Mechanical
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