scholarly journals Risk of COVID-19 Infection in Public Transportation: The Development of a Model

2021 ◽  
Vol 18 (23) ◽  
pp. 12790
Author(s):  
Junsik Park ◽  
Gurjoong Kim
Keyword(s):  
Public Transportation ◽  
Ventilation System ◽  
Ventilation Rate ◽  
Accurate Information ◽  
Risk Of Infection ◽  
Social Distancing ◽  
Indoor Space ◽  
The Government ◽  
Major Factors ◽  
Indoor Spaces

South Korea’s social distancing policies on public transportation only involve mandatory wearing of masks and prohibition of food intake, similar to policies on other indoor spaces. This is not because public transportation is safe from coronavirus disease 2019 (COVID-19), but because no suitable policies based on accurate data have been implemented. To relieve fears regarding contracting COVID-19 infection through public transportation, the government should provide accurate information and take appropriate measures to lower the risk of COVID-19. This study aimed to develop a model for determining the risk of COVID-19 infection on public transportation considering exposure time, mask efficiency, ventilation rate, and distance. The risk of COVID-19 infection on public transportation was estimated, and the effectiveness of measures to reduce the risk was assessed. The correlation between the risk of infection and various factors was identified through sensitivity analysis of major factors. The analysis shows that, in addition to the general indoor space social distancing policy, ventilation system installation, passenger number reduction in a vehicle, and seat distribution strategies were effective. Based on these results, the government should provide accurate guidelines and implement appropriate policies.

scholarly journals Semantic-Linked Data Ontologies for Indoor Navigation System in Response to COVID-19

2021 ◽  
Vol 10 (9) ◽  
pp. 607
Author(s):  
Abdullah Alamri
Keyword(s):  
Linked Data ◽  
Global Scale ◽  
Indoor Navigation ◽  
Accurate Information ◽  
Humanitarian Crisis ◽  
Social Distancing ◽  
Indoor Space ◽  
Crowd Density ◽  
Indoor Navigation System ◽  
Human Density

Indoor navigation has become more important these days due to the current situation worldwide in the aftermath of the outbreak of the COVID-19 pandemic, posing an unparalleled threat amounting to a humanitarian crisis on a global scale. Indoor navigation employs a variety of technologies, including Wi-Fi, Bluetooth, and RFID. Support for these technologies requires accurate information and appropriate processing and modeling to help and direct users of the optimal route to desired destinations and to monitor crowd density in order to maintain social distancing. This research will present a semantic indoor ontology model for indoor navigation and the reduction of human density in indoor space to ensure social distancing and prevent transmission. The proposed system is based on semantic representations of the components of navigation paths which, in turn, enable reasoning functionality. Despite the system’s complexity, the evaluation revealed that it functions well.

scholarly journals Numerical Investigations of Virus Transport Aboard a Commuter Bus

2021 ◽  
Author(s):  
Hamid Rahai ◽  
Jeremy Bonifacio
Keyword(s):  
Ventilation System ◽  
Ventilation Rate ◽  
Solid Particles ◽  
Long Beach ◽  
Risk Of Infection ◽  
Virus Transport ◽  
High Exposure ◽  
Bus Transit ◽  
Bus Stop ◽  
In Transit

The authors performed unsteady numerical simulations of virus/particle transport released from a hypothetical passenger aboard a commuter bus. The bus model was sized according to a typical city bus used to transport passengers within the city of Long Beach in California. The simulations were performed for the bus in transit and when the bus was at a bus stop opening the middle doors for 30 seconds for passenger boarding and drop off. The infected passenger was sitting in an aisle seat in the middle of the bus, releasing 1267 particles (viruses)/min. The bus ventilation system released air from two linear slots in the ceiling at 2097 cubic feet per minute (CFM) and the air was exhausted at the back of the bus. Results indicated high exposure for passengers sitting behind the infectious during the bus transit. With air exchange outside during the bus stop, particles were spread to seats in front of the infectious passenger, thus increasing the risk of infection for the passengers sitting in front of the infectious person. With higher exposure time, the risk of infection is increased. One of the most important factors in assessing infection risk of respiratory diseases is the spatial distribution of the airborne pathogens. The deposition of the particles/viruses within the human respiratory system depends on the size, shape, and weight of the virus, the morphology of the respiratory tract, as well as the subject’s breathing pattern. For the current investigation, the viruses are modeled as solid particles of fixed size. While the results provide details of particles transport within a bus along with the probable risk of infection for a short duration, however, these results should be taken as preliminary as there are other significant factors such as the virus’s survival rate, the size distribution of the virus, and the space ventilation rate and mixing that contribute to the risk of infection and have not been taken into account in this investigation.

scholarly journals Predictors of the COVID-19 Social Distancing Practice among Undergraduate Health Students in Samarinda City, Indonesia: A Cross-Sectional Study

2021 ◽  
Vol 16 (4) ◽  
Author(s):  
Siti Hadijah Aspan ◽  
Pramon Viwattanakulvanid
Keyword(s):  
Social Media ◽  
Undergraduate Students ◽  
Online Survey ◽  
Target Population ◽  
World Health ◽  
Survey Study ◽  
Accurate Information ◽  
Cross Sectional ◽  
Social Distancing ◽  
The Government

Social distancing is a health protocol recommended by the World Health Organization (WHO) for reducing the spread of COVID-19. Undergraduate health students play an important role in the dissemination of accurate information. This study identified predictors that influenced the COVID-19 social distancing practice and examined the sources of social distancing information among undergraduate health students in Samarinda City, Indonesia. This cross-sectional online survey study (March-April 2021) to involved 422 undergraduate students from medicine, public health, and pharmacy faculties at Mulawarman University. Binary logistic regression was conducted to identify factors associated with the COVID-19 social distancing practice. The results showed that age (AOR 1.47; 95% CI 1.97–2.22, p = 0.045), sex (AOR 2.26; 95% CI 1.38–3.69, p=0.001), and attitude (AOR 2.61, 95% CI: 1.75, 3.90, p<0.001) were significantly associated with social distancing practices. The top three sources of COVID-19 social distancing information used were social media (80.6%), websites (14.0%), and television (3.8%). The study findings encourage the government to disseminate more health information on social media and education programs to this target population.

scholarly journals Identifying the Indoor Space Characteristics of an Urban Railway Station Based on Pedestrian Trajectory Data

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Eunbi Jeong ◽  
Soyoung Iris You ◽  
Jun Lee ◽  
Daeseop Moon
Keyword(s):  
Public Transportation ◽  
Spatial Clustering ◽  
Trajectory Data ◽  
Railway Station ◽  
Indoor Space ◽  
Characteristics Analysis ◽  
Functional Extension ◽  
Pedestrian Space ◽  
Indoor Spaces

Stations are being converted into various living spaces that can be used for public transportation, work, commerce, and leisure. To satisfy the various requirements and expectations for functional extension, it is necessary to investigate and understand the phenomena caused by users. A methodology to cluster the characteristics of pedestrian space of a railway station through the pedestrian trajectory data collected from an actual operating station is proposed in this paper. Then the spatial usability of the movement and stay of pedestrians were defined through the results of the clustering. The procedure to cluster the indoor space characteristics of an urban railway station in this study consists of four steps: data collection, feature vector extraction, K-means clustering, and cluster characteristics analysis. A case study was conducted for the Samseong station. The results of the proposed spatial clustering analysis showed that there are several types of spaces depending on the space occupancy characteristics of pedestrians. The proposed methodology could be applied to indoor space diagnosis from the perspective of station monitoring and management. In addition, the station operator could respond flexibly to unexpected events by monitoring the indoor spaces according to whether the flow is normal or suggestive of an emergency.

scholarly journals Social Distancing in Indoor Spaces: An Intelligent Guide Based on the Internet of Things: COVID-19 as a Case Study

Computers ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 91
Author(s):  
Malek Alrashidi
Keyword(s):  
Internet Of Things ◽  
Particle Swarm ◽  
Ant Colony ◽  
Swarm Optimization ◽  
Social Distancing ◽  
Indoor Space ◽  
Iot Devices ◽  
Indoor Spaces ◽  
The Internet Of Things

Using Internet of Things (IoT) solutions is a promising way to ensure that social distancing is respected, especially in common indoor spaces. This paper proposes a system of placement and relocation of people within an indoor space, using an intelligent method based on two optimizers (ant colony and particle swarm) to find the optimal relocation of a set of people equipped with IoT devices to control their locations and movements. As a real-world test, an amphitheater with students was used, and the algorithms guided students toward correct, safe positions. Two evolutionary algorithms are proposed to resolve the studied problem, ant colony optimization and particle swarm optimization. Then, a comparative analysis was performed between these two algorithms and a genetic algorithm, using different evaluation metrics to assess the behavior of the proposed system. The results show the efficiency of the proposed intelligent IoT system.

scholarly journals The Meaning of Rebo Buntung for Pringgabaya Villager, East Lombok During the COVID-19 Pandemic

2021 ◽  
Author(s):  
Dharmika Ida Bagus ◽  
Gede Kharisma Pradana
Keyword(s):  
Qualitative Research ◽  
Environmental Conditions ◽  
Cultural Tradition ◽  
Risk Of Infection ◽  
Functional Theory ◽  
Social Distancing ◽  
Social Lives ◽  
The Government ◽  
Religious Theory ◽  
The Village

Rebo Buntung is a Sasak cultural tradition performed on the island of Lombok in Indonesia, primarily aimed at preventing disasters. Although the government warned people in Lombok to engage in social distancing and to reduce activities outside to reduce the risk of infection associated with the COVID-19 pandemic, Rebo Buntung was carried out by Sasak people amid the pandemic. This purpose of this paper is to describe results from qualitative research, framed within religious theory and structural-functional theory, that explore the meaning of Rebo Bunting in the village of Pringgabaya, East Lombok and its role during the COVID-19 Pandemic. For villagers, Rebo Bunting reflected a request to God for protection from the dangers of the pandemic and an expression of gratitude to God for the sustainability of social lives and environmental conditions that continue to provide support for the village. Rebo Buntung was also practiced by the Pringgabaya villagers during the pandemic because of its potential to contribute to the sustainability of their tourist-dependent economy, whose condition had worsened since the COVID-19 pandemic.

On the Major Differences between the Banking Systems of the EAEU States

2020 ◽  
Vol 26 (4) ◽  
pp. 397-406
Author(s):  
T. E. Chekanova
Keyword(s):  
Financial Stability ◽  
Systems Approach ◽  
Negative Impact ◽  
Banking Regulation ◽  
Member States ◽  
Banking Systems ◽  
Significant Negative Impact ◽  
The Difference ◽  
The Government ◽  
Major Factors

The presented study examines the problems of integration of the national banking systems of the member states of the Eurasian Economic Union (EAEU).Aim. The study aims to examine the major differences in various aspects of functioning of banking systems in the EAEU member states in terms of their impact on integration processes.Tasks. The author identifies the most prominent features of the banking systems of the EAEU states; reveals the depth of the existing differences through a comparative analysis of various indicators of national banking systems; outlines ways of overcoming integration problems associated with differences in the banking sectors of the Union states.Methods. This study is based on universal general scientific methods and elements of comparative, functional, and economic analysis within the framework of a systems approach. The author uses regulatory documents and banking reports of the EAEU states, statistical and analytical materials of the Eurasian Economic Commission (EEC), and data of Moody’s international rating agency.Results. The study identifies a number of aspects that contain the major differences in the functioning of banking systems in the EAEU member states; highlights the disproportions in the scale, level of development, financial stability, and risks of the banking spheres of the Union states; comparatively analyzes the proportion of banking and non-banking structures in the system and the share of the government and non-resident companies in the capital of banks; marks the difference in the pricing of banking services; determines differences in the existing approaches to banking regulation and the established standards; analyzes the major differences in the legislative acts of the central banks and governments of the EAEU member states and in the terms and definitions used. According to the results of the study, the major factors hindering the development of integration processes between the banking systems of the EAEU states are identified.Conclusions. The existing differences between the banking systems of the EAEU countries are diverse and multifaceted. The author states that the aspects addressed in this study have a significant negative impact on the further development of integration processes, describing the major directions and actions of the member states aimed at minimizing the exiting differences, which are required to facilitate the convergence of the states and the transition towards a common financial market.

scholarly journals Polarized nature of the COVID-19 pandemic in Japan: associations with population age structure and behaviours

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
Junko Okumura
Keyword(s):  
Age Structure ◽  
Public Transportation ◽  
Perceived Risk ◽  
Online Survey ◽  
Preventive Measures ◽  
Age Groups ◽  
Cumulative Number ◽  
Population Age Structure ◽  
Major Factors ◽  
Drinking Places

Abstract Background Although the scale of the coronavirus disease (COVID-19) pandemic was relatively small in Japan compared with the rest of the world, the polarisation of areas into high- and low-COVID-19-incidence areas was observed among the 47 prefectures. The aims of this study were not only identifying the factors associated with the polarised COVID-19 pandemic in Japan but also discussing effective preventive measures. Methods This was an ecological study using online survey data which was cross-sectionally conducted by the author. A total of 6000 respondents who resided in 10 low- and 10 high-COVID-19 incidence prefectures, with a wide gap in terms of COVID-19 incidence, in Japan were recruited. Data on COVID-19 cases and geodemographic information were obtained from official government sites. Statistical analyses were conducted to compare variables between the two areas and age groups. Results This study revealed that that age influenced people’s behaviours and perceptions, except one behaviour of ‘wearing facemasks’. The major factors significantly associated with the cumulative number of COVID-19 cases per 100,000 people were ‘commuting by private automobile’ (adjusted odds ratio [AOR], 0.444; 95% confidence interval [CI], 0.394–0.501), ‘commuting by public transportation’ (AOR, 6.813; 95% CI, 5.567–8.336), ‘washing hands’ (AOR, 1.233; 95% CI, 1.005–1.511), ‘opening windows regularly’ (AOR, 1.248; 95% CI, 1.104–1.412), ‘avoiding crowded places (AOR, 0.757; 95% CI, 0.641–0.893), ‘non-scheduled visits to drinking places’ (AOR, 1.212; 95% CI, 1.054–1.392) and ‘perceived risk of contracting COVID-19’ (AOR, 1.380; 95% CI, 1.180–1.612). These factors were strongly associated with age groups. Conclusions Effective preventive measures for COVID-19 transmission can be developed by understanding the characteristics of populated areas, such as public transportation infrastructure and younger people’s movements and behaviours in relation to the population age structure to contain the current epidemic and protect the most vulnerable elderly people.

scholarly journals An adaptive social distancing SIR model for COVID-19 disease spreading and forecasting

2021 ◽  
Vol 10 (s1) ◽  
Author(s):  
Said Gounane ◽  
Yassir Barkouch ◽  
Abdelghafour Atlas ◽  
Mostafa Bendahmane ◽  
Fahd Karami ◽  
...  
Keyword(s):  
Mathematical Theory ◽  
Real Data ◽  
Sir Model ◽  
Epidemic Threshold ◽  
Social Distancing ◽  
Sir Epidemic ◽  
Proposed Model ◽  
Disease Spreading ◽  
The Government ◽  
The Impact

Abstract Recently, various mathematical models have been proposed to model COVID-19 outbreak. These models are an effective tool to study the mechanisms of coronavirus spreading and to predict the future course of COVID-19 disease. They are also used to evaluate strategies to control this pandemic. Generally, SIR compartmental models are appropriate for understanding and predicting the dynamics of infectious diseases like COVID-19. The classical SIR model is initially introduced by Kermack and McKendrick (cf. (Anderson, R. M. 1991. “Discussion: the Kermack–McKendrick Epidemic Threshold Theorem.” Bulletin of Mathematical Biology 53 (1): 3–32; Kermack, W. O., and A. G. McKendrick. 1927. “A Contribution to the Mathematical Theory of Epidemics.” Proceedings of the Royal Society 115 (772): 700–21)) to describe the evolution of the susceptible, infected and recovered compartment. Focused on the impact of public policies designed to contain this pandemic, we develop a new nonlinear SIR epidemic problem modeling the spreading of coronavirus under the effect of a social distancing induced by the government measures to stop coronavirus spreading. To find the parameters adopted for each country (for e.g. Germany, Spain, Italy, France, Algeria and Morocco) we fit the proposed model with respect to the actual real data. We also evaluate the government measures in each country with respect to the evolution of the pandemic. Our numerical simulations can be used to provide an effective tool for predicting the spread of the disease.

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