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Rationale: The aerosolized solid, liquid, mix-phased particles are the Particulate Matter or PM having serious health impacts. In the recent years with the unprecedented situation of COVID-19 pandemic, it became a necessity that the scientific world comes forward with an objective of developing more equipment for air purification with novel technology to combat airborne pathogen, aeroallergen and viruses. We have applied AFLPCO Nanotechnology to build equipment and mask. Methods: We built a fiberglass chamber to evaluate the capacity of the AFL-Mask to prevent entry of particulate matters and pathogens. To evaluate the air in the chamber, we used a LightHouse Handheld Particle Counter to sample airborne particles. We have recorded the particle concentrations at time-intervals to determine the percentage of particles entering the other chamber with the mask placed in the junction dividing the chamber. Results: This mask involves a 4-stage filtration system designed to combat all forms of airborne pathogens including bacteria, viruses, mold spores and harmful VOCs. We found that the AFL-Mask was efficient in preventing any particulate matter including PM2.5, PM10, bacterial and fungal spores and VOCs. Conclusions: The AFL-Mask and AFLPCO air purifiers built for long-term use to improve the inhaled air quality. The ergonomic design with padded lining and straps and improved filtration technology made the AFL-Mask a superior mask that provides a continuous airflow to prevent suffocation, troubled breathing and fluctuating blood pressure, especially pertaining to patients with cardiovascular or pulmonary issues. AFLPCO airpurifers were efficient in improving IAQ.
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A proper ventilation strategy in an isolation ward could promote better indoor air quality for the occupants. This could also reduce the risk of immunocompromised patients contracting healthcare-associated infections (HAI) or airborne diseases such as COVID-19, tuberculosis, and measles among others. This study aims to propose and examine appropriate ventilation strategies in a single-patient isolation ward that can reduce particle settlement in patients. A simplified CFD model of the isolation ward was developed and well-validated against established data. An RNG k-ε model and discrete phase model (DPM) were used to simulate airflow and particle transportation. The study examined the airflow and particle dispersion under a baseline case and four proposed ventilation strategies. Results showed that the baseline case study, which used the ceiling-mounted air curtain was insufficient to prevent the particles from dispersing into the vicinity of the patient. Likewise, the dilution effect under the baseline case and case 4 (wall-mounted air supply diffuser) were relatively weak due to the low air change rate (ACH) of 4/hr and 9/hr respectively. The ventilation strategy in case 4 has a negligible effect on reducing the particles (14%) settling on the patient although the ACH in case 4 was 2-times the baseline case. The present finding ascertains that utilising the combination of ceiling-mounted air diffuser and air curtain jet (case 3) results in zero particle settlement on both patient's and the patient's bed. It also reduced 57% of particles in the vicinity of the medical staff's breathing zone compared to the baseline case. © 2023 Elsevier Ltd
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Introduction. Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Symptoms of COVID-19 are variable, but often include fever, cough, headache, fatigue, breathing difficulties, and loss of smell and taste. Symptoms may begin one to fourteen days after exposure to the virus. COVID-19 transmits when people breathe in air contaminated by droplets and small airborne particles containing the virus. The present analysis aims to define the cost-effectiveness profile of the anti-COVID vaccination campaign in the Italian healthcare setting. Methods. The analysis was based on the collection and analysis of data regarding the number of hospitalizations (ordinary regime and intensive care) and infections recorded by the Italian Ministry of Health in vaccinated and unvaccinated patient cohorts. The acquisition costs of the available vaccine alternatives were considered as well as the cost of the personnel involved in the vaccination campaign. The reduction in hospitalizations was considered as a measure of effectiveness. We have compared the current scenario of campaign vaccination versus a scenario in which the total of the eligible population would be vaccinated. Results are reported in terms of Incremental Cost Effectiveness Ratio (ICER). Deterministic and probabilistic sensitivity analyses were carried out in order to test the robustness of the results. Results. The vaccination campaign allowed for savings amounting to EUR 9,398,012.10 (EUR 60,499,053.25 vs EUR 69,897,065.35) and 6,647 hospitalizations avoided (715 and 5,932 in the intensive care and ordinary regimen, respectively), thus resulting a dominant strategy as compared with the alternative (no vaccination). As the costeffectiveness profile of the campaign improves, we should consider the period (May-July 2021), during which the daily threshold of 500,000 doses administered on a national basis was consistently exceeded. Conclusions. The analysis underlined how the vaccination campaign represents a cost-saving alternative in the Italian healthcare setting.
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COVID-19 is an ongoing global pandemic and is continuing to be a fast-spreading virus all over the world. It transmits when people breathe in air contaminated by droplets and small airborne particles containing the virus. The risk becomes highest when people are nearby, but they can be over longer distances, while indoors. It is necessary to isolate such infected persons in public places with large gatherings. In addition to screening them, individual protection measures can also be taken.Two primary requirements that fulfil the entry to the public are by scanning of temperature to prevent person suspected and also to ensure one has masked face properly to permit entry. At the moment, all places use this system. But they are manual and depend on the person inspecting temperature and mask. There are few automated processes, but they do not have automatic entry control. Thus, there are risks of false entry of people inside the public place.In this paper, an integrated approach in mask detection and temperature scanning, indicated visually by LED and LCD Display, and further control entry with the operation of boom barrier has been presented. The information is also recorded to identify each entry. Open CV is used to detect masks and obtain better accuracy. An infrared temperature sensor and a proper guide to scan the temperature are used. Each step of the process is implemented on one Raspberry PI-based board. The system is suitably packaged and demonstrated. © 2022 IEEE.
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BACKGROUND AND OBJECTIVE: Bronchoscopy is an airborne particle-generating procedure. However, few methods for safe bronchoscopy have been developed. To reduce airborne particles during bronchoscopy, we created an 'e-mask', which is a simple, disposable mask for patients. Our objective was to evaluate the e-mask's protective ability against airborne particles and to assess respiratory adverse events and complications. METHODS: Patients with stage 2-4 chronic obstructive pulmonary disease were excluded. We performed visualization and quantifying experiments on airborne particles with and without the e-mask. We prospectively evaluated whether wearing the e-mask during bronchoscopy was associated with the incidence of patients requiring >5 L/min oxygen to maintain >90% oxygen saturation, and patients with >45 mm Hg end-tidal carbon dioxide (EtCO2 ) elevation, in addition to complications, compared to historical controls. RESULTS: In the visualization experiment, more than ten thousand times of airborne particles were generated without the e-mask than with the e-mask. The volume of airborne particles was significantly reduced with the e-mask, compared to that without the e-mask (p = 0.011). Multivariate logistic regression analysis revealed that wearing the e-mask had no significant effect on the incidence of patients requiring >5 L/min oxygen to maintain >90% oxygen saturation, (p = 0.959); however, wearing the e-mask was a significant factor in >45 mm Hg EtCO2 elevation (p = 0.026). No significant differences in complications were observed between the e-mask and control groups (5.8% vs. 2.5%, p = 0.395). CONCLUSION: Wearing the e-mask during bronchoscopy significantly reduced the generation of airborne particles during bronchoscopy without increasing complications.
Subject(s)
Bronchoscopy , Carbon Dioxide , Bronchoscopy/adverse effects , Bronchoscopy/methods , Endoscopy , Humans , Masks/adverse effects , Oxygen , Respiratory RateABSTRACT
Bioaerosols, in addition to common gaseous or particulate pollutants, are also important air pollutants that deteriorate indoor air quality. Bioaerosols are the airborne particles present as or originating from living organisms such as fungi, bacteria, and viruses and include toxins, fragments, or waste product from various organisms. In this chapter, the characteristics of indoor bioaerosols are provided. The common type and sources of bioaerosols are summarized. These biological pollutants are commonly generated both by the activities and behaviors of the occupants, and by housing materials and substances that penetrate from the outdoor environment. Fungi and bacteria are the most common bioaerosols present in the indoor environment. After exposure, occupants may experience adverse health outcomes such as infection or allergy. If the indoor environment is severely contaminated, as observed in many places during the COVID-19 pandemic, especially in public areas, a large number of people may be affected by contamination. This chapter also summarizes monitoring and assessment technologies. The monitoring procedure can be chosen and performed according to the objective of the assessment. Advance technologies such as real-time sensor monitoring, Internet of Things, and artificial intelligence have been integrated, but their use for bioaerosols monitoring is still limited as compared to their use for other types of indoor air pollutants. Effective control strategies to reduce the contamination of indoor bioaerosols are also provided in this chapter that could benefit occupants to reduce the contamination and minimize exposure. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Introduction: It is suitable for a patient to wear a respirator or face mask during any radiological investigation during Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) pandemic. Some face masks may have nanoparticles, or antimicrobial coating, which may comprise metal to help shape the mask according to user face shape. This kind of ferromagnetic substances can cause artefacts in the image. Aim: To detect and compare the artefacts while using different types of respirators and surgical masks in the Magnetic Resonance Imaging (MRI) phantom images. Materials and Methods: This was a prospective cross-sectional study which was conducted from July 2021-September 2021. Two Not resistant to oil-based aerosols with 95% efficiency to airborne particles (N95) respirators and two types of three-ply surgical disposable masks with a metal and plastic nose holder were used. The N95 respirators were of Halo N95 Filtering Facepiece 2 Particulate Matter (FFP2) PM 2.5 and Suchi N95 S-7400, while the surgical masks were from Venus 3 ply V-1010 with a metal nose holder and the Thea Tex Filtra 3 ply with plastic nose holder. A polymethyl methacrylate plastic phantom was used with 1.5 Tesla (Siemens Magnetom Avanto) MRI scanner for imaging. Results: When exposed to the metal detector both N95 respirators and one of the surgical masks with a metal nose clip showed strong ferromagnetic attraction. Both respirators and a surgical mask with a metal nasal holder showed magnetic susceptibility artefacts. The signal loss is caused by dephasing of spins from metal strip on the image. Conclusion: All the patients must have a recognised MR safe masks prior to an MRI investigation. When this is not possible to follow, metallic components from the face mask should be removed before the patient's arrival at the MR room. After removing the metal strip from the mask, the paper tape may be applied across the nasal bridge region for adequate transmission control and to maintain the intended function of the mask. The mask with a plastic nasal holder was ideal to use in an MR environment since it doesn't have any distortion in the image.
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Purpose of Study This project was developed to find a quick and effective way for frontline workers to obtain a well-fitting N95 in resource limited settings when a fit test may not be plausible. The goal was to determine if facial shape could be used as a predictor of N95 fit. Methods Used Forty volunteers were given a facial shape selfassessment questionnaire which asked them to subjectively determine their own facial shape and then measure several dimensions with a disposable tape measure: half facial height (nasion to menton), full facial height (trichion to menton), and facial width (bizygomatic breadth). Two free facial assessment phone applications, 'Face Shape' and 'Zennioptical', were used as an additional assessment for facial shape. Participants were then fit tested with an AccuFIT 9000 Respirator Fit Test Machine using an OSHA standardized technique to assess the quantitative fit of four different N95's - a small and regular sized duckbill type mask, and a small and regular sized cup style mask. Pass/fail criteria was determined per OSHA standards and was set at a fit factor greater than or equal to 100. Summary of Results There was no association between face shape and best fitting mask based on either self-assessment (p= 0.51), the zenni app (p=0.59), or the Face Shape app (p=0.095). Correlation was not seen even when grouping face shapes into curved and angular. Face shape based on the 3 self-measured objective facial dimensions can be predicted with about 65% accuracy. Self-assigned face shape correlated with Zenni app face shape 40% of the time and with the Face Shape app 37.5% of the time (p>0.1). All three correlated 25% of the time, however the mutual face shape was 'oval' which was the most common facial shape identified in this study by both the applications and self-assessment. Forty-four percent of the participants did not pass fit testing per OSHA standards with their routinely worn N95's. The participants in this group also generally had poorer fit testing overall, with 50% of this group failing fit testing for all four masks. In addition, 33% of the entire study group only passed fit testing with one of the available N95's in this study. Conclusions Data from this pilot study shows that there is no correlation between N95 fit and face shape, largely due to the variability and subjectivity in the determination of facial shape by either app, self-assessment, or objective self-measurement. However, the researchers learned that nearly half of the participants did not pass fit testing for their regularly used N95's during the COVID pandemic. This illustrates a significant concern for the safety of healthcare workers and the inability for them to access appropriate, well-fitting respirators in resource limited settings. Furthermore, it highlights the importance of personalized fit testing prior to exposure to airborne particles and the need for access to multiple styles and sizes of respirators.
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This paper presents a mobile UVC disinfection robot designed to mitigate the threat of airborne and surface pathogens. Our system comprises a mobile robot base, a custom UVC lamp assembly, and algorithms for autonomous navigation and path planning. We present a model of UVC disinfection and dosage of UVC light delivered by the mobile robot. We also discuss challenges and prototyping decisions for rapid deployment of the robot during the COVID-19 pandemic. Experimental results summarize a long-term deployment at The Greater Boston Food Bank, where the robot delivers (nightly) UVC dosages of at least 10 mJ/cm to a 4000 ft area in under 30 minutes. These dosages are capable of neutralizing 99% of coronaviruses, including SARS-CoV-2, on surfaces and in airborne particles. Further simulations present how this mobile UVC disinfection robot may be extended to classic problems in robotic path planning and adaptive multi-robot coverage control. © 2021 IEEE.
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The Coronavirus pandemic, also known as the Covid pandemic, is a global disease (Coronavirus) pandemic caused by SARS Covid 2019 that causes severe respiratory illness (SARS-CoV-2). Side effects differ incredibly in seriousness, going from subtle to perilous. Individuals who are old or have basic clinical issues are more inclined to foster serious infection. Coronavirus is spread by means of the air when beads and small airborne particles dirty it. In this project we would be analyzing the data set images of Chest CT Scans and Chest X Rays for the Detection of Corona Virus using the different kind of deep learning algorithms and checking the efficiency of both of them as to which is more accurate and beneficial for detection of the corona virus pandemics so that this study can be used for future detection of COVID in the patients. © 2022, Springer Nature Switzerland AG.
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Assessing and improving the safety of social settings is pivotal for the reopening of facilities and institutions during the pandemic. Recent discoveries now suggest that the predominant medium of SARS-CoV-2 transmission is exposure to infectious respiratory aerosols. Airborne viral spread is particularly effective in indoor environments-which have been strongly implicated in high transmission rates and super-spreading events. This study focuses on computational fluid dynamics models developed to study the specific ventilation features of an indoor space and their effects on indoor particle spread. A case study is conducted on a typical classroom at the Cooper Union. Masked occupants are modeled in the room as aerosol sources to compare the performance of different ventilation settings on the exhaust rates of airborne particles. Simulation results reveal that increasing ventilation rates accelerate particle evacuation. Visualization and segregated data comparisons indicate regions of particle accumulation induced by the design and geometry of the classroom in relation to its occupants. Visualization is also used to observe a uniform distribution of airborne particles after only 10 minutes of simulated time-confirming the need for safety measures beyond the six feet distancing guideline. © 2021 by ASME.
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Background and Objectives: The COVID-19 pandemic has highlighted the risk of airborne transmission of infections in health-care facilities such as dental clinics. In this experimental study, methods to control airborne particles in a simulated dental clinic setting were measured and compared using a low cost and convenient technique. Materials and Methods: Particles representing inhalable airborne particles were generated using smoke from incense sticks and their concentration measured by handheld particle sensors whereas using different engineering controls for the particle removal in dental clinic equivalent settings. Measurements were made at short (<3 ft) and intermediate (between 3 and 6 ft) distance from the source. The particle filtration through surgical masks and N95 masks was also studied. Results: Natural ventilation, by keeping windows open, can reduce intermediate range particles (removal of 4.7% of ambient particles/min). However, in closed facilities without natural ventilation, particle removal by air purifier combined with overhead fan or with high volume evacuators was found most suitable for intermediate range particles (25.9%/min) and for short range particles (27.6%/min), respectively. N95 masks were found to filter out 99.5% of the generated PM 2.5 particles. Conclusions: Potentially inhalable airborne particles can persist in the air of a dental clinic. The use of N95 masks and environmental controls is essential for the dental team's safety. The choice of an engineering control is governed by multiple factors explained in the study. Smoke particles generated by incense sticks and measurement by handheld particle sensors are low-cost methods to estimate the effectiveness of airborne particle controls.
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The aim of this study was to establish a method for predicting heavy metal concentrations in PM1 (aerosol particles with an aerodynamic diameter ≤ 1.0 µm) based on back propagation artificial neural network (BP-ANN) and support vector machine (SVM) methods. The annual average PM1 concentration was 26.31 µg/m3 (range: 7.00-73.40 µg/m3). The concentrations of most metals were higher in winter and lower in autumn and summer. Mn and Ni had the highest noncarcinogenic risk, and Cr the highest carcinogenic risk. The hazard index was below safe limit, and the integrated carcinogenic risk was less than precautionary value. There were no obvious differences in the simulation performances of BP-ANN and SVM models. However, in both models many elements had better simulation effects when input variables were atmospheric pollutants (SO2, NO2, CO, O3 and PM2.5) rather than PM1 and meteorological factors (temperature, relative humidity, atmospheric pressure and wind speed). Models performed better for Pb, Tl and Zn, as evidenced by training R and test R values consistently >0.85, whereas their performances for Ti and V were relatively poor. Predicted results by the fully trained models showed atmospheric heavy metal pollution was heavier in December and January and lighter in August and July of 2019. For the period covering the COVID-19 outbreak in China, from January to March 2020, most of the predicted element concentrations were lower than in 2018 and 2019, and the concentrations of nearly all metals were lowest during the nationwide implementation of countermeasures taken against the pandemic.
Subject(s)
Air Pollutants/analysis , Air Pollution/statistics & numerical data , Coronavirus Infections/epidemiology , Metals, Heavy/analysis , Neural Networks, Computer , Particulate Matter/analysis , Pneumonia, Viral/epidemiology , Aerosols , Betacoronavirus , COVID-19 , China/epidemiology , Cities , Computer Simulation , Environmental Exposure/statistics & numerical data , Environmental Monitoring/methods , Humans , Meteorological Concepts , Pandemics , SARS-CoV-2 , Seasons , Support Vector Machine , WindABSTRACT
The influenza virus and SARS-CoV-2 cause trivial upper and severe lower respiratory infections (Influenza virus 290,000 to 650,000 deaths/year). These viruses come into contact with the airways either by direct projection, by secondary inhalation of airborne droplets, or by handling (fomites). The objective of this article is to clarify the mechanisms of production and penetration of droplets of secretions emitted during all expiratory phenomena likely to transport these viruses and come into contact with the respiratory mucosa. The droplets>5µm follow the laws of ballistics, those<5µm follow Brownian motion and remain suspended in the air. The aerosols of droplets are very heterogeneous whether the subject is healthy or sick. During an infectious period, not all droplets contain viral RNA. If these RNAs are detectable around patients, on surfaces, and in the ambient air at variable distances according to the studies (from 0.5m to beyond the patient's room), this is without prejudice to the infectious nature (viability) of the virus and the minimum infectious dose. There is a time lag between the patient's infectious period and that of RNA detection for both viruses. Subsequently, the inhaled particles must meet the laws of fluid dynamics (filtration) to settle in the respiratory tree. All of this partly explains the contagiousness and the clinical expression of these two viruses from the olfactory cleft to the alveoli.