Airborne spread of foot-and-mouth disease – Model intercomparison

Gloster, J.; Jones, A. R.; Redington, Alison L.; Burgin, Laura; Sørensen, Jens Havskov; Turner, Richard M.; Dillon, Michael; Hullinger, Pam; Simpson, Matthew; Astrup, Poul; Garner, Graeme; Stewart, Paul; D’Amours, R.; Sellers, R. F.; Paton, David

doi:10.1016/j.tvjl.2008.11.011

Cited by 55 publications

(42 citation statements)

References 25 publications

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“…Technology to predict direction, speed, concentration, and deposition distance of pollution spread over user-specified boundaries has variously been developed, depending on the mathematics used to develop the model. The necessary data, collected over a suitable period of time from either direct measurements or inferences from empirical formula may include [8,9,15,16,19,22,[24][25][26]:  Meteorological conditions (wind direction, wind speed, atmospheric stability class, ambient temperature, mixing height, etc.) obtained from a meteorological monitoring station, and ideally collected at the receptor locations, or typically obtained from monitoring sites as close as possible, and with a similar profile [19,26].…”

Section: Atmospheric Dispersion Modelmentioning

confidence: 99%

“…at the source location(s), pathways, and at the receptor locations, including the consideration of natural effects such as building wake [19,26]. Several advanced dispersion modeling programs include a pre-processor module for the input of these data, and some also include a post-processor module for diagramming the graphical output [15,27]. Nevertheless, although modeling methodology on air pollution has been developing since at least the 1930s, two key atmospheric dispersion models for assessing airborne transmission of FMDV remain the Gaussian and Lagrangian particle dispersion models [8,9,22,[28][29][30].…”

Section: Atmospheric Dispersion Modelmentioning

confidence: 99%

“…Many accepted principles direct the predictive models. Appropriateness in selecting available dispersion models is important, and must be well considered, as can be seen from the results of a comparative study of various models [15]. The current paper reviews all previously used procedures for predicting dispersion of FMDV from farms to faraway distances via the airborne route.…”

Section: Introductionmentioning

confidence: 99%

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Review of Air Dispersion Modelling Approaches to Assess the Risk of Wind-Borne Spread of Foot-and-Mouth Disease Virus

Prueksakorn¹,

Kim²,

Kim³

et al. 2012

JEP

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Foot-and-mouth disease virus (FMDV) is one of the most economically serious veterinary pathogens due to its negative effects on livestock and its highly infectious nature via a variety of transmission paths through oral and inhalation routes. Measures to enhance outbreak management can be designed according to analytical results predicted by mathematical models for wind-borne dispersion, an important path of virus transmission. Accurate atmospheric dispersion models are useful tools for properly determining risk management plans, while inaccurate models may conversely lead to accidental loss in two possible ways. Overly strict measures, e.g., slaughter for too wide an area, can cause severe economic difficulties, including irreversible loss of business operations for a number of farms. On the contrary, inestimable loss potentially caused by lax controls is a persistent threat. In this paper, available modelling procedures for forecasting the spread of FMDV, which have been used since the 1970s, each having its advantages and limitations, are reviewed for the purpose of ensuring suitable application in various conditions of any future emergency cases.

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Section: Atmospheric Dispersion Modelmentioning

confidence: 99%

Section: Atmospheric Dispersion Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Review of Air Dispersion Modelling Approaches to Assess the Risk of Wind-Borne Spread of Foot-and-Mouth Disease Virus

Prueksakorn¹,

Kim²,

Kim³

et al. 2012

JEP

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“…For example, atmospheric dispersion models for FMDV are based on data of disease onset, virus strain, number and type of animals involved, and stage of the disease. 15,17,20,23,27 Because infectivity is linked to particle size, 3,28 characterization of pathogen-associated particle size in aerosols is important to understand and to predict the likelihood of transmission of infective viruses among farms. Furthermore, the efficiency of air sanitation methods such as air filtration and electrostatic ionization technology are particle size dependent.…”

Section: Introductionmentioning

confidence: 99%

Assessment of air sampling methods and size distribution of virus-laden aerosols in outbreaks in swine and poultry farms

et al. 2017

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Abstract. Swine and poultry viruses, such as porcine reproductive and respiratory syndrome virus (PRRSV), porcine epidemic diarrhea virus (PEDV), and highly pathogenic avian influenza virus (HPAIV), are economically important pathogens that can spread via aerosols. The reliability of methods for quantifying particle-associated viruses as well as the size distribution of aerosolized particles bearing these viruses under field conditions are not well documented. We compared the performance of 2 size-differentiating air samplers in disease outbreaks that occurred in swine and poultry facilities. Both air samplers allowed quantification of particles by size, and measured concentrations of PRRSV, PEDV, and HPAIV stratified by particle size both within and outside swine and poultry facilities. All 3 viruses were detectable in association with aerosolized particles. Proportions of positive sampling events were 69% for PEDV, 61% for HPAIV, and 8% for PRRSV. The highest virus concentrations were found with PEDV, followed by HPAIV and PRRSV. Both air collectors performed equally for the detection of total virus concentration. For all 3 viruses, higher numbers of RNA copies were associated with larger particles; however, a bimodal distribution of particles was observed in the case of PEDV and HPAIV.

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“…It is well known that bioaerosol multiplication and survival as well as downwind levels concentrations strongly depend on meteorological conditions like wind intensity, wind direction, temperature, humidity, and atmospheric stability, which are uncertain and specific of the place under study. Airborne virus concentrations in FMD epidemic cases (Hampshire & Worcestershire -1997) as well as micro-organism dispersion in rubbish dump, transference sites and municipal wastewater treatment plants, have been estimated using Gaussian models (Garner & Beckett, 2005a;Gloster et al, 2010;Karra & Katsivela, 2007;Mikkelsen et al, 2003;Pascual et al, 2003;Sorensen et al, 2000). In many works algorithms developed for consequences analysis (gas diffusion) have been modified and used for bioaerosols diffusion simulations (Casal et al, 1995;Garner et al, 2005b;Holmes & Morawska, 2006;Sorensen et al, 2000).…”

Section: Introductionmentioning

confidence: 99%