Prediction of the spread of highly pathogenic avian influenza using a multifactor network: Part 1 – Development and application of computational fluid dynamics simulations of airborne dispersion

Seo, Il Won; Lee, In-Bok; Moon, Oun-Kyung; Jung, Nam-Su; Lee, Hyung‐Jin; Hong, Suk-Jin; Kwon, Kilsung; Bitog, J. P.

doi:10.1016/j.biosystemseng.2014.02.013

Cited by 17 publications

(9 citation statements)

References 30 publications

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“…These effects were largest at distances up to 2 km. Seo and Lee (2013) and Seo et al (2014) applied CFD modelling (Fluent) to the South Korean outbreak of 2008. The possibility of spread from each of the 39 farms to another was calculated as a function of wind direction and three different wind speeds.…”

Section: Avian Influenza Virusmentioning

confidence: 99%

“…TCID 50 is the median dose to infect a tissue culture; however, the actual meaning of this measure can be disputed, since it represents a probability of infection and not a concentration or dose. Furthermore, threshold values were also used in several other studies (Blatny et al, 2011;Cannon and Garner, 1999;Casal et al, 1997;Champion et al, 2002;Daggupaty and Sellers, 1990;Donaldson et al, 1987;Gloster et al, 1981;Lee et al, 2014;Seo et al, 2014;Traulsen et al, 2010).…”

Section: Probability Of Infectionmentioning

confidence: 99%

See 1 more Smart Citation

Atmospheric dispersion modelling of bioaerosols that are pathogenic to humans and livestock – A review to inform risk assessment studies

Leuken

Swart

Havelaar

et al. 2016

Microbial Risk Analysis

121

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Section: Avian Influenza Virusmentioning

confidence: 99%

Section: Probability Of Infectionmentioning

confidence: 99%

Atmospheric dispersion modelling of bioaerosols that are pathogenic to humans and livestock – A review to inform risk assessment studies

Leuken

Swart

Havelaar

et al. 2016

Microbial Risk Analysis

121

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“…These findings are helpful to the understanding of the dispersion of airborne pollutants around high-rise buildings and the related hazard management in urban design. et al / Applied Mathematical Modelling 81 (2020) 582-602 583 Rising reports of such outbreaks have attracted scientific attention on understanding the spreading of airborne hazards in urban areas, which is helpful for the prediction and control of the outbreak of airborne diseases for public health [7][8][9][10][11] .The pollutant outbreaks are riskier near high-rise residential (HRR) buildings due to the high population density [12] . Additionally, the spreading of pollutants around and inside such buildings is more complex as a result of strong windstructure interactions and diverse spreading scenarios.…”

mentioning

confidence: 99%

Effect of pollutant source location on air pollutant dispersion around a high-rise building

Keshavarzian

Jin

Dong

et al. 2020

Applied Mathematical Modelling

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a b s t r a c tThis article investigates the dispersion of airborne pollutants emitted from different locations near a high-rise building. A Computational Fluid Dynamics (CFD) model for simulating the wind flow field and the pollutant dispersion was developed and validated by wind tunnel data. Then the spreading of the pollutant emitted from different locations to a rectangular-shaped high-rise residential (HRR) building was numerically studied. The pollutant source location was set in a wide range of the position angle and distance between the source and the building. It was found that the pollutant concentration on the building decreases with an increase in the emission distance whereas the effect of the position angle is more complicated. Interestingly, there is a critical range of the position angle from which the emitted pollutants will not spread to the building in a significant way. The effect of the source location was linked to the wind flow field around the building, particularly with several major flows. The vertical distributions of the pollutant concentration on different faces were also investigated, and it was found that these are more affected by the vertical flow near each face. Finally, a mathematical model was developed to evaluate the pollutant concentration as a function of the emission distance and position angle. These findings are helpful to the understanding of the dispersion of airborne pollutants around high-rise buildings and the related hazard management in urban design. et al. / Applied Mathematical Modelling 81 (2020) 582-602 583 Rising reports of such outbreaks have attracted scientific attention on understanding the spreading of airborne hazards in urban areas, which is helpful for the prediction and control of the outbreak of airborne diseases for public health [7][8][9][10][11] .The pollutant outbreaks are riskier near high-rise residential (HRR) buildings due to the high population density [12] . Additionally, the spreading of pollutants around and inside such buildings is more complex as a result of strong windstructure interactions and diverse spreading scenarios. Pollutants may be emitted from an HRR building (e.g. from a kitchen exhaust) and spread to the same building at different positions [13 , 14] , like the possible SARS spreading in typical HRR buildings in Hong Kong [15][16][17] . Pollutants may also be released from sources located around a HRR building at lower levels [18][19][20][21][22] , such as the evaporative facilities (e.g. cooling tower or air scrubber) of public facilities, which have been responsible for reported disease outbreaks [23][24][25] . Accordingly, the position of the potential pollutant source is an important factor in evaluating the risk of the spreading of pollutants near an HRR building, but it has not been fully evaluated in terms of the distance and the position angle between the source and the building.The spreading of pollutants in urban areas has been studied using various methods. Wind tunnel is a valuable tool in studying such...

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“…To comprehend the route of airborne transmission, tracer had been applied into both lab and field experiment. Tracer gases such as N 2 O, SF 6 , R134a and He were widely used to investigate the spread of airborne microorganism in indoor and outdoor environment by means of computational fluid dynamics (CFD) for its quantitative evaluation of the cross-infection risks and low-budget [24][25][26][27][28][29][30]. However, airborne microorganism transporting process across built environments was unable to be interpreted thoroughly by tracer gases for their distinct absence of physical and biological characteristics of airborne microorganism.…”

Section: Introductionmentioning

confidence: 99%

A tracing method of airborne bacteria transmission across built environments

Wang

Zheng

et al. 2019

Building and Environment

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A B S T R A C TDisease transmission across built environments has been found to be a serious health risk. Airborne transmission is a vital route of disease infection caused by bacteria and virus. However, tracing methods of airborne bacteria in both lab and field research failed to veritably express the transporting process of microorganism in the air. A new tracing method of airborne bacteria used for airborne transmission was put forward and demonstrated its feasibility by conducting a field evaluation on the basis of genetic modification and bioaerosol technology. A specific gene fragment (pFPV-mCherry fluorescent protein plasmid) was introduced into nonpathogenic E. coli DH5α as tracer bacteria by high-voltage electroporation. Gel electrophoresis and DNA sequencing proved the success of the synthesis. Genetic stability, effect of aerosolization on the survival rate of tracer bacteria, and the application of the tracer bacteria to the airborne bacteria transmission were examined in both lab and field. Both the introduced plasmid stability rates of tracer E. coli in pre-aerosolization and post-aerosolization were above 95% in five test days. Survival rate of tracer E. coli at 97.5% ± 1.2% through aerosolization was obtained by an air-atomizer operated at an air pressure of 30 Psi. In the field experiment, the airborne transmission of E. coli between poultry houses was proved and emitted E. coli was more easily transmitted into self-house than adjacent house due to the ventilation design and weather condition. Our results suggested that the tracing method of airborne bacteria was available for the investigation of airborne microbial transmission across built environments.

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Prediction of the spread of highly pathogenic avian influenza using a multifactor network: Part 1 – Development and application of computational fluid dynamics simulations of airborne dispersion

Cited by 17 publications

References 30 publications

Atmospheric dispersion modelling of bioaerosols that are pathogenic to humans and livestock – A review to inform risk assessment studies

Atmospheric dispersion modelling of bioaerosols that are pathogenic to humans and livestock – A review to inform risk assessment studies

Effect of pollutant source location on air pollutant dispersion around a high-rise building

A tracing method of airborne bacteria transmission across built environments

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