ABSTRACT
Ventilation in confined spaces is essential to reduce the airborne transmission of viruses responsible for respiratory diseases such as COVID-19. Mechanical ventilation using purifiers is an interesting solution for elevator cabins to reduce the risk of infection and improve the air quality. In this work, the optimal position and blowing direction of these devices to maximize ventilation and minimize the residence time of the air inside two cabins (large and small) is studied. Special attention is devoted to idle periods when the cabin is not used by the passengers, in order to keep the cabin ambient safe and clean, avoiding that the trapped air in the cabin (after its use) could suppose a reservoir for contaminants. CFD numerical models of two typical cabin geometries, including the discretization of small slots and grilles for infiltration, have been developed. A full 3D URANS approach with a k-epsilon RNG turbulence model and a non-reactive scalar to compute the mean age of air (MAA) was employed. The CFD results have been also validated with experimental measurements from a home-made 1:4 small-scale mock-up. The optimal position of the purifier is on the larger sidewall of the cabins for a downward blowing direction (case 1 of the database). Flow rates in the range of 0.4–0.6 m3/min, depending on the size of the cabin, are sufficient to assure a correct ventilation. Upward blowing may be preferable only if interaction of the jet core with the ceiling or other flow deflecting elements are found. In general, the contribution of infiltrations (reaching values of up to 10%), and how these secondary flows interact with the main flow pattern driven by the purifier, is relevant and not considered previously in the literature. Though an optimal position can improve ventilation considerably, it has been proven that a good choice of the purification flow rate is more critical to ensure an adequate air renewal. © 2022 The Authors
ABSTRACT
School lecture halls are often designed as confined spaces. During the period of COVID-19, indoor ventilation has played an even more important role. Considering the economic reasons and the immediacy of the effect, the natural ventilation mechanism becomes the primary issue to be evaluated. However, the commonly used CO2 tracer gas concentration decay method consumes a lot of time and cost. To evaluate the ventilation rate fast and effectively, we use the common methods of big data analysis - Principal Component Analysis (PCA), K-means and linear regression to analyze the basic information of the lecture hall to explore the relation between variables and air change rate. The analysis results show that the target 37 lecture halls are divided into two clusters, and the measured 11 lecture halls contributed 64.65%. When analyzing the two clusters separately, there is a linear relation between the opening area and air change rate (ACH), and the model error is between 6% and 12%, which proves the feasibility of the basic information of the lecture hall by calculating the air change rate. © 2023 Elsevier Ltd
ABSTRACT
On January 30, 2020, WHO officially declared the outbreak of COVID-19 a Public Health Emergency of International Concern. Japan announced the state of emergency and implemented safety protocols the "Three Cs", a warning guideline addressing to voluntarily avoid potentially COVID-19 hazardous situations such as confined and closed spaces, crowded places and close-contact settings that lead to occurrence of serious clusters. The primary goal of this research is to identify the factors which help to estimate whether the user is in the Three Cs. We propose COVIDGuardian, a system that detects the Three Cs based on data such as CO2, temperature, humidity, and wireless packet log. The results show that estimation of closed space had the highest accuracy followed by close-contact settings and crowded places. The ensemble Random Forest (RF) classifier demonstrates the highest accuracy and F score in detecting closed spaces and crowded spaces. The findings indicated that integrated loudness value, average CO2, average humidity, probe request log, and average RSSI are of critical importance. In addition, when the probe request logs were filtered at three RSSI cutoff points (1m, 3m, and 5m), 1m cut-off points had the highest accuracy and F Score among the Three C models. © 2022 Copyright held by the owner/author(s).
ABSTRACT
On January 30, 2020, WHO officially declared the outbreak of COVID-19 a Public Health Emergency of International Concern. Japan announced the state of emergency and implemented safety protocols the "Three Cs", a warning guideline addressing to voluntarily avoid potentially COVID-19 hazardous situations such as confined and closed spaces, crowded places and close-contact settings that lead to occurrence of serious clusters. The primary goal of this research is to identify the factors which help to estimate whether the user is in the Three Cs. We propose COVIDGuardian, a system that detects the Three Cs based on data such as CO2, temperature, humidity, and wireless packet log. The results show that estimation of closed space had the highest accuracy followed by close-contact settings and crowded places. The ensemble Random Forest (RF) classifier demonstrates the highest accuracy and F score in detecting closed spaces and crowded spaces. The findings indicated that integrated loudness value, average CO2, average humidity, probe request log, and average RSSI are of critical importance. In addition, when the probe request logs were filtered at three RSSI cutoff points (1m, 3m, and 5m), 1m cut-off points had the highest accuracy and F Score among the Three C models. © 2022 Copyright held by the owner/author(s).
ABSTRACT
The COVID-19 pandemic has seen the importance of confined space ventilation to reduce the risks of cross infection. To evaluate and compare the relative impacts of different mitigation strategies is important in order to reduce the risk of infection in a given situation. Using CFD methods, this study aimed to modulate the spread of exhaled contaminants in a floor-heated and ventilated space. Three different inlet velocities and four floor temperatures were used to assess the effect of the radiant floor combined with the displacement ventilation (RFDV) on room airflow and pollutant spread. Results show that RFDV reduced exposure to infection from 87% to 50% compared to the reference case. The inlet velocity is required to increase when the floor temperature is higher to decrease the contaminant exposure risk to in the room. This research provides a timely and necessary study of the ventilation and heating systems. These findings are expected to be useful for designing future of RFDV. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The aircraft boarding process is characterized by great movement and close contact between passengers in a confined space, which is a situation of particular concern considering the risk of exposure to airborne infectious diseases such as the COVID-19. In order to evaluate the airborne exposure risk during a commercial aircraft boarding process, an agent-based simulation model approach is adopted in the present work. Since the elderly population is one of the most at risk groups, special features are included in the simulation model in order to evaluate how this group is affected in the process. Three aspects are considered: priority boarding (elders boarding order);boarding strategy;and social distancing measures. The main findings are that care must be taken when interpreting average exposure risks, since although the overall risk of exposure is low, there may be cases in which significant risk is presented. © 2022, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
ABSTRACT
A Face Mask Wear Detection Device for Entrance Authorization is designed to ensure that everyone wears a face mask at all times in a confined space. It is one of the easiest methods to lower the rate of coronavirus infection and hence save lives. Asthma, high blood pressure, heart failure, and many other chronic conditions can be fatal to those who are infected by the novel Coronavirus (nCoV-21). Consequently, the goal of this research is for face mask wear detection devices that help to reduce the rate of Novel Coronavirus infection on-premises or in public places by ensuring that customers comply with Standard Handling Procedures (SOP) set by the Ministry of Malaysian Health (MOH). Customers' faces are recognized by this device whether or not they are covered by a face mask upon entry into a facility. Additionally, the use of this device can contribute to ensuring compliance with the maximum number of customers allowed on the premises. A facial recognition system is the goal of this study that uses technology designed as an individual disciplinary aid and follows the safety procedure at this critical time. This research was developed using the engineering design process development model which has four phases namely;identifying the problem, making possible solutions, prototype development and testing and evaluating the solution. Results indicate that the developed product can function effectively. Experts have discovered that using this product helps people stick to their face mask routines. The design of this product has improved, which means that the overall quality of the product is elevated to be capable of performing as intended in terms of intelligent technologies © 2022. International Journal of Advanced Computer Science and Applications.All Rights Reserved.
ABSTRACT
With the spread of COVID-19,elevators as a confined space and a frequently used tool in human life, have a very urgent need for disinfection. Currently, most elevator disinfection products on the market focus on local disinfection. However, when elevators carry a large number of people and the distance between people is too close, the probability of virus transmission is greatly increased. Then simple local disinfection will not meet the high disinfection requirements. At this point, the expectations generated by the overall disinfection product increase. In this paper, a hard systems approach-Hall 3D structure is used to create a 3D model for the design of elevator disinfection equipment based on the propagation environment of COVID-19. The design process can be carried out in a smooth manner with continuous progress and optimization. This paper presents the whole process of investigation and experimentation for the design of elevator disinfection equipment in a temporal dimension, complemented by a logical dimension and a knowledge dimension to help designers get timely feedback, identify problems in the design process, and conduct actual user experience. The design of the elevator disinfection device was finalized through experimental research. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
INTRODUCTION: SARS-CoV-2 (COVID-19) was declared a global pandemic on 11 March 2020 and has become a serious threat to public health. As it can easily be transmitted through droplets and aerosols, there is an increased risk of transmission in enclosed environments such as hyperbaric oxygen treatment (HBOT) units if preventive measures are not taken. CASE REPORT: A 16-year-old female tested positive for SARS-CoV-2 during HBOT for idiopathic sudden sensorineural hearing loss. The other patients and the inside attendant who attended the sessions with her were regarded as contacts, tested for SARS-CoV-2, and quarantined until the test results were available. Ultimately, none of them tested positive. DISCUSSION: As HBOT in multiplace chambers entails a high risk of SARS-CoV-2 transmission, we strictly adapted our practice to consider that every patient could be a potential asymptomatic carrier. Therefore, the negative results of all contacts in this case and the fact that no confirmed cases of COVID-19 were reported suggests that these measures successfully prevented SARS-CoV-2 transmission in our HBOT clinic. SARS-CoV-2 transmission can be prevented if sufficient protective measures are taken.
Subject(s)
COVID-19 , Hearing Loss, Sudden , Hyperbaric Oxygenation , Adolescent , COVID-19/diagnosis , COVID-19/prevention & control , Female , Hearing Loss, Sudden/therapy , Humans , Hyperbaric Oxygenation/methods , Oxygen , SARS-CoV-2ABSTRACT
In the ongoing COVID19 situation, one of the most basic yet necessary supplies for any human being is the face mask. Medical stores are facing shortage of face masks and it is also leading to crowding in confined spaces like medical stores hence aggravating the situation. The only solution to this is increasing the sources from where the citizens can get face masks and at the same time avoiding crowding and contact with any other human. The proposed Mask Vending Machine will make this happen. The physical machine that will store and vend the masks will have the Raspberry Pi as the central processing unit and the additional components like the steppers motors and monitor for display will be controlled by the Raspberry Pi. For payment and choice of quantity, an app has been designed. A QR code will be displayed on the monitor of the vending machine which has to be scanned with the app. Once scanned, it will ask the user for the number of masks needed and also facilitate the transaction process. Once successful, the masks will be vended. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
A fundamental aspect of the fight against the Coronavirus and against any other virus, is represented by the sanitization of the sites and objects contained therein. This operation is normally carried out using mixtures of ozone and steam and it is certainly effective but also limited due the damages that the vapor can cause to rooms and objects. The following paper introduce machines able to overcome this issue thanks to innovative systems based on the principles of Engineering 4.0. Those systems reproduce the Chapman cycle in the to-be sanitized environments which allows producing ozone in a gaseous state, in the proper quantity and for the time necessary for sanitization. At the end of the operation, the ozone will be converted back into oxygen, leaving the environment re-habitable by humans and pets in a short time. The operation has low costs and times and guarantees positive results. This is therefore a real revolution to be considered today against the COVID-19. © 2021 Newswood Limited. All rights reserved.
ABSTRACT
Airborne transmission of COVID-19 plays an important role for the pandemic. However, nucleic acid based evidence of direct association of COVID-19 with environmental contamination is lacking. Here, we investigated a COVID-19 outbreak with two fast food employees infected, in which a traveler despite of a 14-day quarantine turned positive after check in with a hotel, using environmental SARS-CoV-2 sampling, epidemiological tracing, viral RNA sequence as well as surveillance method. Out of 25 positive environmental air and surface swab samples (N = 237) collected, SARS-CoV-2 was found to have remained airborne (5640–7840 RNA copies m–3 ) for more than 4 days in a female washroom. After aging for 5 days in the air, no viable virus was detected. The traveler did not have any contacts with the two employees;however, genome sequencing showed that SARS-CoV-2 variants from three patients and two environmental surface samples belonged to 20B viral clade, sharing a nucleic acid identity of more than 99.9%. We concluded that the outbreak was triggered by SARS-CoV-2 contaminated environments, where the employees inhaled the virus from the air or touching facility surfaces where the traveler did not have any physical contacts with. © The Author(s).
ABSTRACT
BACKGROUND: If the different transmission risks of respiratory infectious diseases according to the type of confined space and associated factors could be discovered, this kind of information will be an important basis for devising future quarantine policies. However, no comprehensive systematic review or meta-analysis for this topic exists. OBJECTIVE: The objective of this study is to analyze different transmission risks of respiratory infectious diseases according to the type of confined space. This information will be an important basis for devising future quarantine policies. METHODS: A medical librarian searched MEDLINE, EMBASE, and the Cochrane Library (until December 01, 2020). RESULTS: A total of 147 articles were included. The risk of transmission in all types of confined spaces was approximately 3 times higher than in open space (combined RR, 2.95 (95% CI 2.62-3.33)). Among them, school or workplace showed the highest transmission risk (combined RR, 3.94 (95% CI 3.16-4.90)). Notably, in the sub-analysis for SARS-CoV-2, residential space and airplane were the riskiest space (combined RR, 8.30 (95% CI 3.30-20.90) and 7.30 (95% CI 1.15-46.20), respectively). DISCUSSION: Based on the equation of the total number of contacts, the order of transmission according to the type of confined space was calculated. The calculated order was similar to the observed order in this study. The transmission risks in confined spaces can be lowered by reducing each component of the aforementioned equation. However, as seen in the data for SARS-CoV-2, the closure of one type of confined space could increase the population density in another confined space. The authority of infection control should consider this paradox. Appropriate quarantine measures targeted for specific types of confined spaces with a higher risk of transmission, school or workplace for general pathogens, and residential space/airplane for SARS-CoV-2 can reduce the transmission of respiratory infectious diseases.
Subject(s)
COVID-19 , Communicable Diseases , Communicable Diseases/epidemiology , Confined Spaces , Humans , Pandemics , SARS-CoV-2ABSTRACT
In this paper, we construct a stochastic model of the 2019-nCoV transmission in a confined space, which gives a detailed account of the interaction between the spreading virus and mobile individuals. Different aspects of the interaction at mesoscopic level, such as the human motion, the shedding and spreading of the virus, its contamination and invasion of the human body and the response of the human immune system, are touched upon in the model, their relative importance during the course of infection being evaluated. The model provides a bridge linking the epidemic statistics to the physiological parameters of individuals and may serve a theoretical guidance for epidemic prevention and control.
ABSTRACT
Due to the outbreak and spread of COVID-19, SARS-CoV-2 has been proven to survive in aerosols for hours. Virus-containing aerosols may intrude into an uncontaminated area from a confined source space under certain ventilated conditions. The penetration factor, which is the most direct parameter for evaluating the invasion process, can effectively reflect the penetration fraction of aerosols and the shielding efficiency of buildings. Based on the observed concentrations of aerosols combined with a widely used concentration model, four numerical calculations of the penetration factor are proposed in this study. A theoretical time-correction Pest was applied to a size-dependent Pavg by proposing a correction coefficient r, and the error analysis of the real-time P(t) and the derived Pd were also performed. The results indicated that Pavg supplied the most stable values for laboratory penetration simulations. However, the time-correction is of little significance under current experimental conditions. P(t) and Pd are suitable for rough evaluation under certain conditions due to the inevitability of particles detaching and re-entering after capture. The proposed optimal penetration factor and the error analysis of each method in this study can provide insight into the penetration mechanism, and also provide a rapid and accurate assessment method for preventing and controlling the spread of the epidemic.