Evaluating infection risks and importance of hand hygiene during the household laundry process using a quantitative microbial risk assessment approach.

BACKGROUND: Contaminated laundry contributes to infectious disease spread in residential and home health care settings. The objectives were to (1) evaluate pathogen transmission risks for individuals doing laundry, and (2) compare hand hygiene timing to reduce risks. METHODS: A quantitative microbial risk assessment using experimental data from a laundry washing effectiveness study was applied to estimate infection risks from SARS-CoV-2, rotavirus, norovirus, nontyphoidal Salmonella, and Escherichia coli in 4 laundry scenarios: 1 baseline scenario (no hand hygiene event) and 3 hand hygiene scenarios (scenario 1: after moving dirty clothes to the washing machine, scenario 2: after moving washed clothes to the dryer, and scenario 3: hand hygiene events following scenario 1 and 2). RESULTS: The average infection risks for the baseline scenario were all greater than 2 common risk thresholds (1.0×10-6and 1.0×10-4). For all organisms, scenario 1 yielded greater risk reductions (39.95%-99.86%) than scenario 2 (1.35%-55.25%). Scenario 3 further reduced risk, achieving 1.0×10-6(SARS-CoV-2) and 1.0×10-4risk thresholds (norovirus and E. coli). CONCLUSIONS: The modeled results suggest individuals should reduce hand-to-facial orifice (eyes, nose, and mouth) contacts and conduct proper hand hygiene when handling contaminated garments. More empirical data are needed to confirm the estimated risks. DATA AVAILABILITY STATEMENT: The data and code that support the findings of this study can be retrieved via a Creative Commons Zero v1.0 Universal license in GitHub at https://github.com/yhjung1231/Laundry-QMRAproject-2022.git DOI: http://doi.org/10.5281/zenodo.7122065.

Measurement of Phthalates in Settled Dust in University Dormitories and Its Implications for Exposure Assessment

Six phthalates: dimethyl phthalate (DMP), diethyl phthalate (DEP), di(n-butyl) phthalate (DnBP), butyl benzyl phthalate (BBzP), di(2-ethylhexyl) phthalate (DEHP), and di(n-octyl) phthalate (DOP) in settled dust on different indoor surfaces were measured in 30 university dormitories. A Monte Carlo simulation was used to estimate college students' exposure via inhalation, non-dietary ingestion, and dermal absorption based on measured concentrations. The detection frequencies for targeted phthalates were more than 80% except for DEP (roughly 70%). DEHP was the most prevalent compound in the dust samples, followed by DnBP, DOP, and BBzP. Statistical analysis suggested that phthalate levels were higher in bedside dust than that collected from table surfaces, indicating a nonuniform distribution of dust-phase phthalates in the sleep environment. The simulation showed that the median DMP daily intake was 0.81 μg/kg/day, which was the greatest of the targeted phthalates. For the total exposures to all phthalates, the mean contribution of exposures during the daytime and sleeping time was 54% and 46%, respectively.

Ratings of Hand Activity and Force Levels among Women and Men Who Perform Identical Hand-Intensive Work Tasks.

We compared hand activity and force ratings in women and men doing identical hand-intensive work tasks. Musculoskeletal disorders are more common in women and hand-intensive work leads to an increased risk of these disorders. Knowledge of the gender influence in the rating of work exposure is lacking. The aim of this study was to investigate whether women and men performing identical hand-intensive work tasks were equally rated using hand activity and normalized peak force levels with the Hand Activity Threshold Limit Value®. Fifty-six workers participated, comprising 28 women-men pairs. Four observers-two woman-man pairs-were also involved. Self-ratings and observers' ratings of hand activity and force level were collected. The results of these ratings showed no significant gender differences in self-rated hand activity and force, as well as observer-rated hand activity. However, there was a significant gender difference in the observer-rated force, where the women were rated higher (mean (SD): women 3.9 (2.7), men 3.1 (1.8) (p = 0.01)). This difference remained significant in the adjusted model (p = 0.04) with grip strength and forearm-finger anthropometrics. The results provide new insights that observers' estimates of force can be higher in women compared with men in the same work tasks. Force should be further investigated and preferably compared to objective measurements.

Social media exposure assessment: influence on attitudes toward generic vaccination during the COVID-19 pandemic

Purpose: Even though social media (SM) has been explored in-depth, its role remains unclear regarding short- and long-term preventive attitudes in global health emergencies. To fill this gap, the Stimulus-Organism-Response framework aims to clarify the social media exposure mission in acknowledging risk perception and triggering preventive attitudes and behaviors toward COVID-19 and general vaccination. Design/methodology/approach: The authors conducted an explanatory-predictive study on 480 Romanian students, using partial least squares structural equation modeling, and performed model evaluation, multi-group, model selection, and importance-performance map analyses. Findings: The study provides insights in understanding significant relationships and drivers explaining and predicting attitudes towards vaccines. The main relationships are between fear and risk perception;risk and preventive attitudes and behaviors;and vaccination degree and attitudes to vaccines. The most important factor is the vaccination degree and media exposure is the most performant. Practical implications: Developing and applying regulations and communication strategies for quality mass information may positively increase attitudes toward vaccines by indirectly enforcing the main drivers. Social implications: Organizations, authorities, and opinion leaders must have a coherent supportive presence in media. Originality/value: This study filled the literature gap by building a generic theoretical and empirical proven framework that investigates the mediated effect towards vaccines of all media types by COVID-19 experience and vaccination degree. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2021-0621. © 2022, Emerald Publishing Limited.

Geo-referenced simulations of E. coli in a sub-catchment of the Vecht River using a probabilistic approach.

The proportion of wild swimmers at non-official bathing sites has increased during the Covid-19 pandemic. Bathing water quality at designated sites is monitored through analysis of the concentration of fecal indicator bacteria such as E. coli. However, non-official sites are generally not monitored. In a previous work, steady state modelling of E. coli was achieved at catchment scale, enabling a comparison of expected concentrations along an entire catchment for longtime average. However, E. coli concentrations can vary over several orders of magnitude at the same monitoring site throughout the year. To capture the temporal variability of E. coli concentrations on the catchment scale, we extended the existing deterministic E. coli sub-module of the GREAT-ER (Geo-referenced Exposure Assessment tool for European Rivers) model for probabilistic Monte-Carlo simulations. Here, selected model parameters are represented by probability distributions instead of fixed values. Wastewater treatment plant (WWTP) emissions and diffuse emissions were parameterized using selected data from a previous monitoring campaign (calibration data set) and in-stream processes were modeled using literature data. Comparison of simulation results with monitoring data (evaluation data set) indicates that predicted E. coli concentrations well-represent median measured concentrations, although the range of predicted concentrations is slightly larger than the observed concentration variability. The parameters with the largest influence on the range of predicted concentrations are flow rate and E. coli removal efficiency in WWTPs. A comparison of predicted 90th percentiles with the threshold for sufficient bathing water quality (according to the EU Bathing Water Directive) indicates that year-round swimming at sites influenced by WWTP effluents is advisable almost nowhere in the study area. A refinement of the model can be achieved if quantitative relationships between the WWTP removal efficiency and both, the treatment technologies as well as the operating parameters are further established.

Comparative Mask Protection against Inhaling Wildfire Smoke, Allergenic Bioaerosols, and Infectious Particles.

This work compares relative mask inhalation protection against a range of airborne particle sizes that the general public may encounter, including infectious particles, wildfire smoke and ash, and allergenic fungal and plant particles. Several mask types available to the public were modeled with respirable fraction deposition. Best-case collection efficiencies for cloth, surgical, and respirator masks were predicted to be lowest (0.3, 0.6, and 0.8, respectively) for particle types with dominant sub-micrometer modes (wildfire smoke and human-emitted bronchial particles). Conversely, all mask types were predicted to achieve good collection efficiency (up to ~1.0) for the largest-sized particle types, including pollen grains, some fungal spores, and wildfire ash. Polydisperse infectious particles were predicted to be captured by masks with efficiencies of 0.3-1.0 depending on the pathogen size distribution and the type of mask used. Viruses aerosolized orally are predicted to be captured efficiently by all mask types, while those aerosolized from bronchiolar or laryngeal-tracheal sites are captured with much lower efficiency by surgical and cloth masks. The predicted efficiencies changed very little when extrathoracic deposition was included (inhalable rather than respirable fraction) or when very large (100 µm) particles were neglected. Actual mask fit and usage will determine protection levels in practice, but the relative comparisons in this work can inform mask guidance for different inhalation hazards, including particles generated by yard work, wildfires, and infections.

Sensor Networks with Edge Intelligence for Reliable Air Quality Monitoring in the Covid-19 Era

Rapid advancements in affordable, miniaturised air pollution sensor technologies offer the potential to capture the high variability of personal exposure to air pollution during daily life with unprecedented spatial and temporal resolution. However, concerns remain regarding the suitability of these novel technologies for scientific and policy purposes due to their lack of reliability. The aim of this work is the development of three types of portable air quality devices that monitor particulate matter, differential pressure and outdoor emissions (CO, CO2, O3 and VOCs) with high reliability using low-cost sensors and communicating measurements to the cloud in real time. Reliability is strengthened in all three places: at the sensor level, the device/edge level and at the cloud, cashing data until network connectivity is restored. In order to evaluate their efficiency, two case studies were deployed: (a) in a modern industrial setting and (b) in an IT office space in Greece and the findings are reported.

Ambient concentrations and dosimetry of inhaled size-segregated particulate matter during periods of low urban mobility in Bragança, Portugal.

The restrictive measures in place during the COVID-19 pandemic provided a timely scenario to investigate the effects of human activities on air quality, and the extent to which mobility reduction strategies can impact atmospheric pollutant levels. Real-time concentrations of PM1, PM2.5 and PM10 were measured using a mobile platform in a small city of Portugal, during morning and afternoon rush hours, in two distinct phases of the pandemic: emergency phase (cold period, lockdown) and calamity phase (warm period, less restricted). The Multiple-Path Particle Dosimetry Model (MPPD) was used to calculate the PM deposition for adults. Large spatio-temporal variabilities and pronounced changes in mean PM concentrations were observed, with lower concentrations in the calamity phase: PM1 = 2.33 ± 1.61 µg m-3; PM2.5 = 5.15 ± 2.77 µg m-3; PM10 = 23.30 ± 21.53 µg m-3 than in the emergency phase: PM1 = 16.85 ± 31.80 µg m-3; PM2.5 = 30.92 ± 31.93 µg m-3; PM10 = 111.27 ± 104.53 µg m-3. These changes are explained by a combination of meteorological factors and local emissions, mainly residential firewood burning. Regarding regional deposition, PM1 was the main contributor to deposition in the tracheobronchial (5%) and pulmonary (12%) regions, and PM10 in the head region (92%). In general, total deposition doses were higher for males than for females. This work quantitatively demonstrated that even with a 38% reduction in urban mobility during the lockdown, the use of firewood for residential heating is the main contributor to the high concentrations of PM and the respective inhaled dose.

Use of Low-Cost Sensors to Characterize Occupational Exposure to PM2.5 Concentrations Inside an Industrial Facility in Santa Ana, CA: Results from a Worker- and Community-Led Pilot Study

PM2.5 is an air contaminant that has been widely associated with adverse respiratory and cardiovascular health, leading to increased hospital admissions and mortality. Following concerns reported by workers at an industrial facility located in Santa Ana, California, workers and community leaders collaborated with experts in the development of an air monitoring pilot study to measure PM2.5 concentrations to which employees and local residents are exposed during factory operating hours. To detect PM2.5, participants wore government-validated AtmoTube Pro personal air monitoring devices during three separate workdays (5 AM–1:30 PM) in August 2021. Results demonstrated a mean PM2.5 level inside the facility of 112.3 µg/m3, nearly seven-times greater than outdoors (17.3 µg/m3). Of the eight workers who wore personal indoor sampling devices, five showed measurements over 100 μg/m3. Welding-related activity inside the facility resulted in the greatest PM2.5 concentrations. This study demonstrates the utility of using low-cost air quality sensors combined with employee knowledge and participation for the investigation of workplace air pollution exposure as well as facilitation of greater health-related awareness, education, and empowerment among workers and community members. Results also underscore the need for basic measures of indoor air pollution control paired with ongoing air monitoring within the Santa Ana facility, and the importance of future air monitoring studies aimed at industrial facilities.

Close physical proximity on the job-An exposure matrix.

BACKGROUND: The workplace is a setting for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission via respiratory droplets and aerosols for those working in close proximity to others. Currently, limited methods exist for assessing SARS-CoV-2 exposure. Since occupation serves as a surrogate measure, job exposure matrices (JEMs) can be useful for population-based exposure assessment for a portion of exposure. METHODS: We developed a JEM to assess physical proximity at work. Scores for questions related to frequency of face-to-face discussions, working closely with others, and working with a team were extracted from a US-based, comprehensive source of descriptive occupational information (Occupational Information Network [O*NET]). We described score distributions using univariate analyses, devised thresholds, and assigned exposure levels for 968 O*NET occupations. Three exposure measures were constructed using combinations of O*NET data, with expert judgment, and accounting for telework. National and California employment estimates were used to assess the workforce proportions by proximity level and demographic characteristics. RESULTS: We categorized 535 US Census occupations (2010) into four-level ordinal exposure levels (not close to very close). Overall, an estimated 56% of the California workforce worked in very close proximity, which decreased to 46% when accounting for telework. The occupational groups working very close across all three measures were: healthcare support, healthcare practitioner, food preparation and serving, building and grounds cleaning and maintenance, and protective service occupations. Latinos and women were overrepresented within occupations working in very close physical proximity. CONCLUSION: JEMs can inform SARS-CoV-2 exposure assessment for epidemiologic studies, assist in resource allocation, and inform prevention strategies.

Spatiotemporal neural network for estimating surface NO2 concentrations over north China and their human health impact.

Atmospheric nitrogen dioxide (NO2) is an important reactive gas pollutant harmful to human health. The spatiotemporal coverage provided by traditional NO2 monitoring methods is insufficient, especially in the suburban and rural areas of north China, which have a high population density and experience severe air pollution. In this study, we implemented a spatiotemporal neural network (STNN) model to estimate surface NO2 from multiple sources of information, which included satellite and in situ measurements as well as meteorological and geographical data. The STNN predicted NO2 with high accuracy, with a coefficient of determination (R2) of 0.89 and a root mean squared error of 5.8 µg/m3 for sample-based 10-fold cross-validation. Based on the surface NO2 concentration determined by the STNN, we analyzed the spatial distribution and temporal trends of NO2 pollution in north China. We found substantial drops in surface NO2 concentrations ranging between 9.1% and 33.2% for large cities during the 2020 COVID-19 lockdown when compared to those in 2019. Moreover, we estimated the all-cause deaths attributed to NO2 exposure at a high spatial resolution of about 1 km, with totals of 6082, 4200, and 18,210 for Beijing, Tianjin, and Hebei Provinces in 2020, respectively. We observed remarkable regional differences in the health impacts due to NO2 among urban, suburban, and rural areas. Generally, the STNN model could incorporate spatiotemporal neighboring information and infer surface NO2 concentration with full coverage and high accuracy. Compared with machine learning regression techniques, STNN can effectively avoid model overfitting and simultaneously consider both spatial and temporal correlations of input variables using deep convolutional networks with residual blocks. The use of the proposed STNN model, as well as the surface NO2 dataset, can benefit air quality monitoring, forecasting, and health burden assessments.

A Strategy for Field Evaluations of Exposures and Respiratory Health of Workers at Small- to Medium-Sized Coffee Facilities.

Coffee production is a global industry with roasteries throughout the world. Workers in this industry are exposed to complex mixtures of gases, dusts, and vapors including carbon monoxide, carbon dioxide, coffee dust, allergens, alpha-diketones, and other volatile organic compounds (VOCs). Adverse respiratory health outcomes such as respiratory symptoms, reduced pulmonary function, asthma, and obliterative bronchiolitis can occur among exposed workers. In response to health hazard evaluations requests received from 17 small- to medium-sized coffee facilities across the United States, the National Institute for Occupational Safety and Health conducted investigations during 2016-2017 to understand the burden of respiratory abnormalities, exposure characteristics, relationships between exposures and respiratory effects, and opportunities for exposure mitigation. Full-shift, task-based, and instantaneous personal and area air samples for diacetyl, 2,3-pentanedione and other VOCs were collected, and engineering controls were evaluated. Medical evaluations included questionnaire, spirometry, impulse oscillometry, and fractional exhaled nitric oxide. Exposure and health assessments were conducted using standardized tools and approaches, which enabled pooling data for aggregate analysis. The pooled data provided a larger population to better address the requestors' concern of the effect of exposure to alpha-diketones on the respiratory heath of coffee workers. This paper describes the rationale for the exposure and health assessment strategy, the approach used to achieve the study objectives, and its advantages and limitations.

Towards enabling accurate measurements of CO2 exposure indoors

Indoor climate standards recommend maximum CO2 concentration levels in rooms. At present the CO2 exposure of occupants is assessed by measurements in a room's exhaust air or near the walls. However, most often room air is not perfectly mixed and CO2 emitted in air exhaled by occupants is non-uniformly distributed. It is more reliable to assess CO2 concentration in the air inhaled by occupants by measurements in the breathing zone as close as possible to the face. In this work the importance of the location of air sampling in front of the face, the time and frequency of sampling, and the breathing mode, for the accuracy of CO2 measurements were studied. For this a breathing thermal manikin was used. The CO2 concentration in the air exhaled by the manikin was adjusted to be the same as that for an average person. The results show that synchronization of the air sampling with the inhalation period of breathing is the most accurate method. The air sampling locations positioned between the centre of the chin and the mouth, or at the left (or right) corner of the mouth, or next to and above the nostrils, are the most representative for assessing CO2 concentration in the inhaled air. The obtained results can be used for the development of wearable devices for accurate assessment of exposure to CO2 and other indoor pollution, as well as advanced air distribution methods, such as personalised ventilation that supplies clean air to the breathing zone.

COVID-19 in Malaysia: exposure assessment and prevention practices among healthcare workers at a teaching hospital.

INTRODUCTION: During the second wave of the coronavirus disease 19 (COVID-19) pandemic, Malaysia reported several COVID-19 clusters related to healthcare workers. Thus, addressing and understanding the risk of exposure in healthcare workers is important to prevent future infection and reduce secondary COVID-19 transmission within the healthcare settings. In this study, we aim to assess exposure and prevention practices against COVID-19 among healthcare workers at the Hospital Canselor Tuanku Muhriz, a university teaching hospital based in Kuala Lumpur, Malaysia. METHODOLOGY: A total of 571 healthcare workers at COVID-19 and non-COVID-19 wards as well as the emergency department and laboratory staff at COVID-19 testing labs were recruited. The presence of novel human coronavirus (SARS-CoV-2) and IgM/IgG antibodies were confirmed in all healthcare workers. The healthcare workers responded to an online Google Forms questionnaire that evaluates demographic information and comorbidities, exposure and adherence to infection prevention and control measures against COVID-19. Descriptive analysis was performed using Statistical Package for the Social Sciences 24.0. RESULTS: Three healthcare workers (0.5%) tested positive for SARS-CoV-2, while the remaining 568 (99.5%) were negative. All were negative for IgM and IgG antibodies during recruitment (day 1) and follow-up (day 15). More than 90% of the healthcare workers followed infection prevention and control practices recommendations regardless of whether they have been exposed to occupational risk for COVID-19. CONCLUSIONS: The healthcare workers' high level of adherence to infection prevention practices at this hospital helped reduce and minimize their occupational exposure to COVID-19.

Can high-school students contribute to seismic risk mitigation? Lessons learned from the development of a crowd-sourced exposure database

On a global scale, one out of three people is exposed to earthquakes, and most injuries and deaths in case of seismic events are caused by the damage or collapse of residential buildings. Knowing the type and distribution of exposed assets, in particular buildings, is thus paramount for effective mitigation of disasters. Citizens' involvement in disaster risk reduction activities is constantly increasing by means of crowdsourced data collection, education/training and citizen science activities. In particular, schools have a central role in engaging young students and increasing risk awareness and preparedness. In this work, we explored whether students’ participation in this kind of activities can lead to the improvement of current exposure datasets, while increasing citizens' risk-related understanding. In 2021, due to the restrictions imposed by the COVID-19 pandemic, the National Institute of Oceanography and Applied Geophysics - OGS started a new project to be deployed in fully remote mode, named “CEDAS: building CEnsus for seismic Damage ASsessment”. The project consists in the collection and elaboration of crowdsourced data on main residential buildings typologies of northeastern Italy, a seismically active area which suffered consequences from strong past earthquakes. During the project, 170 high school students collected reports on more than 3200 buildings, performing a statistical analysis of theing results. The CEDAS project makes a first step beyond crowdsourcing activities and applies citizen science to exposure development. Results allow identifying the most common building typologies in the region and the challenges and opportunities associated with data collection and analysis. The experience collected during the CEDAS project shows that crowdsourcing and citizen science activities can contribute to both enhancing the exposure data available for the scientific community and increasing risk awareness among young students in the region.

Widespread occurrence of phthalate and non-phthalate plasticizers in single-use facemasks collected in the United States.

Single-use or disposable facemasks have been widely used by the public for personal protection against the spread of COVID-19. The majority of disposable facemasks are made of synthetic polymers such as polypropylene, polyethylene terephthalate (as polyester), and polystyrene, and could therefore be a source of human exposure to plasticizers that are incorporated into these polymers during production. Little is known, however, about the occurrence of plasticizers in facemasks. In this study, we determined the concentrations of nine phthalate diesters and six non-phthalate plasticizers in 66 facemasks purchased in the United States. Among phthalate diesters, dibutyl phthalate, di(2-ethylhexyl)phthalate, di-iso-butyl phthalate, and butyl benzyl phthalate were found in all facemask samples, at median concentrations of 486, 397, 254, and 92 ng/g, respectively. Among non-phthalate plasticizers, dibutyl sebacate (median: 3390 ng/g) and di(2-ethylhexyl)adipate (352 ng/g) were found at notable concentrations. Inhalation exposure to select phthalate and non-phthalate plasticizers from the use of facemasks was estimated to range from 0.1 to 3.1 and 3.5 to 151 ng/kg-bw/d, respectively. To our knowledge, this is the first study to report the occurrence of phthalate and non-phthalate plasticizers in facemasks collected from the United States.

Modeling the impacts of physical distancing and other exposure determinants on aerosol transmission.

Minimization of airborne virus transmission has become increasingly important due to pandemic and endemic infectious respiratory diseases. Physical distancing is a frequently advocated control measure, but the proximity-based transmission it is intended to control is challenging to incorporate into generalized, ventilation-based models. We utilize a size-dependent aerosol release model with turbulent dispersion to assess the impact of direct, near-field transport in conjunction with changes in ventilation, exposure duration, exhalation/inhalation rates, and masks. We demonstrate this model on indoor and outdoor scenarios to estimate the relative impacts on infection risk. The model can be expressed as a product of six multiplicative factors that may be used to identify opportunities for risk reduction. The additive nature of the short-range (proximity) and long-range (background) transmission components of the aerosol transport factor implies that they must be minimized simultaneously. Indoor simulations showed that close physical distances attenuated the impact of most other risk reduction factors. Increasing ventilation resulted in a 17-fold risk decrease at further physical distances but only a 6-fold decrease at shorter distances. Distance, emission rate, and duration also had large impacts on risk (11-65-fold), while air direction and inhalation rate had lower risk impacts (3-4-fold range). Surgical mask and respirator models predicted higher maximum risk impacts (33- and 280-fold, respectively) than cloth masks (4-fold). Most simulations showed decreasing risk at distances > 1-2 m (3-6 ft). The risk benefit of maintaining 2-m distance vs. 1 m depended substantially on the environmental turbulence and ventilation rate. Outdoors, long-range transmission was negligible and short-range transmission was the primary determinant of risk. Temporary passing events increased risk by up to 50 times at very slow walking speeds and close passing distances, but the relative risks outdoors were still much lower than indoors. The current model assumes turbulent dispersion typical of a given room size and ventilation rate. However, calm environments or confined airflows may increase transmission risks beyond levels predicted with this turbulent model.

Methodology for Addressing Infectious Aerosol Persistence in Real-Time Using Sensor Network.

Human exposure to infectious aerosols results in the transmission of diseases such as influenza, tuberculosis, and COVID-19. Most dental procedures generate a significant number of aerosolized particles, increasing transmission risk in dental settings. Since the generation of aerosols in dentistry is unavoidable, many clinics have started using intervention strategies such as area-filtration units and extraoral evacuation equipment, especially under the relatively recent constraints of the pandemic. However, the effectiveness of these devices in dental operatories has not been studied. Therefore, the ability of dental personnel to efficiently position and operate such instruments is also limited. To address these challenges, we utilized a real-time sensor network for assessment of aerosol dynamics during dental restoration and cleaning producers with and without intervention. The strategies tested during the procedures were (i) local area High-Efficiency Particle Air (HEPA) filters and (ii) Extra-Oral Suction Device (EOSD). The study was conducted at the University of Washington School of Dentistry using a network of 13 fixed sensors positioned within the operatory and one wearable sensor worn by the dental operator. The sensor network provides time and space-resolved particulate matter (PM) data. Three-dimensional (3D) visualization informed aerosol persistence in the operatory. It was found that area filters did not improve the overall aerosol concentration in dental offices in a significant way. A decrease in PM concentration by an average of 16% was observed when EOSD equipment was used during the procedures. The combination of real-time sensors and 3D visualization can provide dental personnel and facility managers with actionable feedback to effectively assess aerosol transmission in medical settings and develop evidence-based intervention strategies.

Fitness for work during the COVID-19 disease: principles and suggested assistive tool for protecting workers during the pandemic era.

OBJECTIVE: Amongst the many intricacies engendered by the COVID-19 pandemic was the posed risk of exposure to SARS-COV2 infections among workers and the need to evaluate fitness for work (FFW) of individuals in high exposure groups or those with background morbidity. A designated task force of the Israeli Association of Occupational Medicine has evaluated the relevant literature and published guidelines concerning medical work restrictions for employees in high-risk occupations during the epidemic of novel COVID-19. METHODS: The study depicts a case series of 17 FFW evaluations performed in Maccabi Health Services occupational clinics using the guidelines formulated by the Israeli Occupational Medicine Association. RESULTS: 17 patients, mainly healthcare workers, whose major health hazards were immunodeficiency, respiratory diseases and pregnancy, were assessed in this case series. We present the essential parameters of these FFW evaluations and discuss decision-making in selected cases. CONCLUSIONS: Applying guidelines in various work settings and health risk levels during the SARS-CoV-2 pandemic allows for both patients' health preservation and efficient workforce deployment.

Assessment of Coronavirus disease, the nose pollution filter, fermented spicy Kimchee, and peppery hot soup consumed in Korea.

Recent statistics of Coronavirus diseases in Korea are studied with respect to many other countries. It is found that as of 8 February 2021, Korea has recorded 15.8 patients per 10,000 people, and this is used to calculate ratio to compare with other countries. On average, the number of Coronavirus patients in the world is 136.2 that is 8.6 times more than in Korea. The number of Covid-19 patients recorded in Korea is relatively smaller than other countries. There was no clear evidence on the atmospheric transport of Coronaviruses over 1 km to cause infection to other people. The infection of Coronaviruses appeared to occur mainly by close contact with an infected person or by airborne droplets in confined indoor environments, as noted earlier (Lancet, Respir Med 8(12):1159, 2020). To reduce the transmission of Coronavirus and related infections, the wearing of a pollution filter (mask) covering the nose and mouth is mandatory for Coronavirus patients. For the general public, however, we have invented a filter which covers only the nose. When there is no need for conversation and deep breathing, the nose band would be sufficient to filter out Coronavirus and air pollutants. Meanwhile, air and sea port activities including ground transport continued and strict policy on people mingle was not tightly enforced, and control measures to reduce infection were not so effective. However, it is believed that consuming fermented Korean spicy Kimchee and hot peppery soup plus warm rice tea helps in washing Coronaviruses around the throat deep down to the stomach. We find that cleansing the mouth and throat deeply including pathway is better than doing shallow gargling. A possible mechanism for cleansing the mouth and throat of Coronaviruses is here explored. This could have contributed to the relatively small number of Coronavirus patients observed in Korea.