ABSTRACT
This research will study a novel aspect of the physics of COVID-19 transmission associated with actively altering droplet size distribution. Viruses can be transmitted through droplets and aerosols released during speaking, sneezing, and coughing phenomena. We previously found that these distributions can be altered using food ingredients. The study will be carried out to study the hypothesis of relaxed guidance in social distancing and mask usage is possible with the proposed approach using CFD models of human sneezes. The adult human is positioned inside a ventilated room condition and the droplet/aerosols are to be released to explore the impacts of the various distributions that relate to how the food ingredients vary the function, hence, the size of the droplets will be the function of the use of food ingredients. Results study the concentration of droplet particles at various distances away from the mouth, also called exposure maps and indicate that Corn Starch and Xanthum usage increase the exposure intensity level, while Xanthum reducing the exposure area implies that social distancing can be reduced with its use. In contrast, the use of Lozenge and Zingiber reduces the exposure level, related to the increase in the viscosity and reduction of the mass flow rate of saliva. Copyright © 2022 by ASME.
ABSTRACT
One key factor in stopping the spread of COVID-19 is practicing social distancing. Visualizing possible sneeze droplets' transmission routes in front of an infected person might be an effective way to help people understand the importance of social distancing. This paper presents a mobile virtual reality (VR) interface that helps people visualize droplet dispersion from the target person's view. We implemented a VR application to visualize and interact with the sneeze simulation data immersively. Our application provides an easy way to communicate the correlation between social distance and infected droplets exposure, which is difficult to achieve in the real world.
ABSTRACT
Objectives: Children and adolescents with cerebral palsy (CP) presents lower physical activity levels in comparison with typically development peers, leading to sedentary behaviours and poor endurance. Up to now, there is no information of the physical activity levels among Brazilian children and adolescents with CP and its comparison among different Gross Motor Function Classification System (GMFCS) levels. The aims of this study were to characterise levels of physical activity in Brazilian individuals with CP and analyse differences between GMFCS levels. Design: Cross-sectional study. Preliminary data from a multicentric prospective study 'Functioning curves and trajectories for children and adolescents with cerebral palsy in Brazil: PartiCipa Brazil'. Method: Parents and caregivers of 52 children and adolescents with CP (mean age 7.5±3.5) participated in an online interview. Participants filled out an online form that included the GMFCS Family Report and the 4-item Early Activity Scale for Endurance (EASE) for children and adolescents. The interview was conducted by a trained physical therapist. One-way analysis of variance (ANOVA) was used to identify differences among physical activity levels according to the EASE in the five different GMFCS levels, considering an alpha = 0.05 as statistically significant. This study was approved by the ethics committee (CAAE: 28540620.6.1001.5133). Results: Of the 52 participants, 17.3% were classified as GMFCS level I, 30.8% level II, 11.5% level III, 15.4% level IV, and 25.0% level V. Overall Brazilian participants' EASE mean scores were 2.92 ±1.96. EASE mean scores by each GMFCS levels were 4.13±0.70 for GMFCS level I, 2.98±0.91 level II, 3.16±0.70 level III, 2.68±1.0 level IV, and 2.92±1.06 level V. There were statistically significant differences on physical activity levels among the GMFCS groups (p > 0.01). Post-hoc analysis via Tukey test, indicated that these differences were between individuals GMFCS level I and levels IV (p > 0.01). No other statistically significant differences among the remaining GMFCS levels were found. Conclusion: Overall, Brazilian children and adolescents with CP present low levels of physical activity, with differences seen amongst the GMFCS levels. The main differences were presented between those children and adolescents with higher mobility levels and those with more restricted mobility. The presented results might be influenced by COVID-19 related social isolation. Further data will confirm this results and present physical activity curves of Brazilian children and adolescents with CP.
ABSTRACT
Background. Bloodstream infection (BSI) - Central and Non-Central Line Associated - and infections of the lower respiratory tract (RESP) - pneumonia and non pneumonia lower respiratory infections - are some of the main causes of unexpected death in Intensive Care Units (ICUs). Although the leading causes of these infections are already known, risk prediction models can be used to identify unexpected cases. This study aims to investigate whether or not it is possible to build multivariate models to predict BSI and RESP events. Methods. Univariate and multivariate analysis using multiple logistic regression models were built to predict BSI and RESP events. ROC curve analysis was used to validate each model. Independent variables: 29 quantitative parameters and 131 categorical variables. BSI and RESP were identified using Brazilian Health Regulatory Agency protocols with data collected between January and November 2020 from a medical-surgical ICU in a Brazilian Hospital. Definitions: if an infection is 5% or less likely to occur according to the model used and it eventually occurs, it will be classified as "unexpected", or else, if an infection is 10% or less likely to occur, it will be classified as "probably unexpected". Otherwise, infections will be classified as "expected". Patients with a 30% or more risk for BSI or RESP will be classified as "high risk". Results. A total of 1,171 patients were accessed: 70 patients with BSI (95% confidence interval [CI], 3.1%-5%), 66 patients with RESP (95% CI, 2.9%-4.7%), 235 deaths (95% CI, 11.8%-14.9%). Of the 160 potential risk factors evaluated, logistic models for BSI and RESP identified respectively five and seven predictors (Tables 1 and 2, and Figure 1). Patients admitted to the ICU with Covid-19 had a three fold BSI risk and five times more RESP risk than patients without this diagnosis. Conclusion. The built models make possible the identification of the expected infections and the unexpected ones. Three main course of actions can be taken using these models and associated data: (1) Before the occurrence of BSI and RESP: to place high risk patients under more rigorous infection surveillance. (2) After the occurrence of BSI or RESP: to investigate "unexpected" infections. (3) At discharge: to identify high risk patients with no infections for further studies.
ABSTRACT
Recent studies have indicated that COVID-19 is an airborne disease, which has driven conservative social distancing and widescale usage of face coverings. Airborne virus transmission occurs through droplets formed during respiratory events (breathing, speaking, coughing, and sneezing) associated with the airflow through a network of nasal and buccal passages. The airflow interacts with saliva/mucus films where droplets are formed and dispersed, creating a route to transmit SARS-CoV-2. Here, we present a series of numerical simulations to investigate droplet dispersion from a sneeze while varying a series of human physiological factors that can be associated with illness, anatomy, stress condition, and sex of an individual. The model measures the transmission risk utilizing an approximated upper respiratory tract geometry for the following variations: (1) the effect of saliva properties and (2) the effect of geometric features within the buccal/nasal passages. These effects relate to natural human physiological responses to illness, stress, and sex of the host as well as features relating to poor dental health. The results find that the resulting exposure levels are highly dependent on the fluid dynamics that can vary depending on several human factors. For example, a sneeze without flow in the nasal passage (consistent with congestion) yields a 300% rise in the droplet content at 1.83 m (≈6 ft) and an increase over 60% on the spray distance 5 s after the sneeze. Alternatively, when the viscosity of the saliva is increased (consistent with the human response to illness), the number of droplets is both fewer and larger, which leads to an estimated 47% reduction in the transmission risk. These findings yield novel insight into variability in the exposure distance and indicate how physiological factors affect transmissibility rates. Such factors may partly relate to how the immune system of a human has evolved to prevent transmission or be an underlying factor driving superspreading events in the COVID-19 pandemic.