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Focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients

Empirical and mechanistic modeling indicate that pathogens transmitted via aerially dispersed inoculum follow a power law, resulting in dispersive epidemic waves. The spread parameter (b) of the power law model, which is an indicator of the distance of the epidemic wave front from an initial focus p...

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Autores principales: Ojiambo, Peter S., Gent, David H., Mehra, Lucky K., Christie, David, Magarey, Roger
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5480396/
https://www.ncbi.nlm.nih.gov/pubmed/28649473
http://dx.doi.org/10.7717/peerj.3465
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author Ojiambo, Peter S.
Gent, David H.
Mehra, Lucky K.
Christie, David
Magarey, Roger
author_facet Ojiambo, Peter S.
Gent, David H.
Mehra, Lucky K.
Christie, David
Magarey, Roger
author_sort Ojiambo, Peter S.
collection PubMed
description Empirical and mechanistic modeling indicate that pathogens transmitted via aerially dispersed inoculum follow a power law, resulting in dispersive epidemic waves. The spread parameter (b) of the power law model, which is an indicator of the distance of the epidemic wave front from an initial focus per unit time, has been found to be approximately 2 for several animal and plant diseases over a wide range of spatial scales under conditions favorable for disease spread. Although disease spread and epidemic expansion can be influenced by several factors, the stability of the parameter b over multiple epidemic years has not been determined. Additionally, the size of the initial epidemic area is expected to be strongly related to the final epidemic extent for epidemics, but the stability of this relationship is also not well established. Here, empirical data of cucurbit downy mildew epidemics collected from 2008 to 2014 were analyzed using a spatio-temporal model of disease spread that incorporates logistic growth in time with a power law function for dispersal. Final epidemic extent ranged from 4.16 ×10(8) km(2) in 2012 to 6.44 ×10(8) km(2) in 2009. Current epidemic extent became significantly associated (P < 0.0332; 0.56 < R(2) < 0.99) with final epidemic area beginning near the end of April, with the association increasing monotonically to 1.0 by the end of the epidemic season in July. The position of the epidemic wave-front became exponentially more distant with time, and epidemic velocity increased linearly with distance. Slopes from the temporal and spatial regression models varied with about a 2.5-fold range across epidemic years. Estimates of b varied substantially ranging from 1.51 to 4.16 across epidemic years. We observed a significant b ×time (or distance) interaction (P < 0.05) for epidemic years where data were well described by the power law model. These results suggest that the spread parameter b may not be stable over multiple epidemic years. However, b ≈ 2 may be considered the lower limit of the distance traveled by epidemic wave-fronts for aerially transmitted pathogens that follow a power law dispersal function.
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spelling pubmed-54803962017-06-23 Focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients Ojiambo, Peter S. Gent, David H. Mehra, Lucky K. Christie, David Magarey, Roger PeerJ Ecology Empirical and mechanistic modeling indicate that pathogens transmitted via aerially dispersed inoculum follow a power law, resulting in dispersive epidemic waves. The spread parameter (b) of the power law model, which is an indicator of the distance of the epidemic wave front from an initial focus per unit time, has been found to be approximately 2 for several animal and plant diseases over a wide range of spatial scales under conditions favorable for disease spread. Although disease spread and epidemic expansion can be influenced by several factors, the stability of the parameter b over multiple epidemic years has not been determined. Additionally, the size of the initial epidemic area is expected to be strongly related to the final epidemic extent for epidemics, but the stability of this relationship is also not well established. Here, empirical data of cucurbit downy mildew epidemics collected from 2008 to 2014 were analyzed using a spatio-temporal model of disease spread that incorporates logistic growth in time with a power law function for dispersal. Final epidemic extent ranged from 4.16 ×10(8) km(2) in 2012 to 6.44 ×10(8) km(2) in 2009. Current epidemic extent became significantly associated (P < 0.0332; 0.56 < R(2) < 0.99) with final epidemic area beginning near the end of April, with the association increasing monotonically to 1.0 by the end of the epidemic season in July. The position of the epidemic wave-front became exponentially more distant with time, and epidemic velocity increased linearly with distance. Slopes from the temporal and spatial regression models varied with about a 2.5-fold range across epidemic years. Estimates of b varied substantially ranging from 1.51 to 4.16 across epidemic years. We observed a significant b ×time (or distance) interaction (P < 0.05) for epidemic years where data were well described by the power law model. These results suggest that the spread parameter b may not be stable over multiple epidemic years. However, b ≈ 2 may be considered the lower limit of the distance traveled by epidemic wave-fronts for aerially transmitted pathogens that follow a power law dispersal function. PeerJ Inc. 2017-06-20 /pmc/articles/PMC5480396/ /pubmed/28649473 http://dx.doi.org/10.7717/peerj.3465 Text en ©2017 Ojiambo et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Ecology
Ojiambo, Peter S.
Gent, David H.
Mehra, Lucky K.
Christie, David
Magarey, Roger
Focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients
title Focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients
title_full Focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients
title_fullStr Focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients
title_full_unstemmed Focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients
title_short Focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients
title_sort focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients
topic Ecology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5480396/
https://www.ncbi.nlm.nih.gov/pubmed/28649473
http://dx.doi.org/10.7717/peerj.3465
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