Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 949-956 |
| Number of pages | 8 |
| Journal | Journal of the Royal Society Interface |
| Volume | 9 |
| Issue number | 70 |
| DOIs | |
| State | Published - May 2012 |
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Applications of percolation theory to fungal spread with synergy. / Ludlam, Jonathan J.; Gibson, Gavin J.; Otten, Wilfred; Gilligan, Christopher A.
In: Journal of the Royal Society Interface, Vol. 9, No. 70, 05.2012, p. 949-956.Research output: Contribution to journal › Article
TY - JOUR
T1 - Applications of percolation theory to fungal spread with synergy
AU - Ludlam,Jonathan J.
AU - Gibson,Gavin J.
AU - Otten,Wilfred
AU - Gilligan,Christopher A.
PY - 2012/5
Y1 - 2012/5
N2 - There is increasing interest in the use of the percolation paradigm to analyze and predict the progress of disease spreading in spatially-structured populations of animals and plants. The wider utility of the approach has been limited, however, by several restrictive assumptions, foremost of which is a strict requirement for simple nearest-neighbour transmission, in which the disease history of an individual is in uenced only by that of its neighbours. In a recent paper the percolation paradigm has been generalised to incorporate synergistic interactions in host infectivity and susceptibility and the impact of these interactions on the invasive dynamics of an epidemic has been demonstrated. In the current paper we elicit evidence that such synergistic interactions may underlie transmission dynamics in real-world systems by rst formulating a model for the spread of a ubiquitous parasitic and saprotrophic fungus through replicated populations of nutrient sites and subsequently tting and testing the model using data from experimental microcosms. Using Bayesian computational methods for model tting, we demonstrate that synergistic interactions are necessary to explain the dynamics observed in the replicate experiments. The broader implications of this work in identifying disease control strategies that de ect epidemics from invasive to non-invasive regimes are discussed.
AB - There is increasing interest in the use of the percolation paradigm to analyze and predict the progress of disease spreading in spatially-structured populations of animals and plants. The wider utility of the approach has been limited, however, by several restrictive assumptions, foremost of which is a strict requirement for simple nearest-neighbour transmission, in which the disease history of an individual is in uenced only by that of its neighbours. In a recent paper the percolation paradigm has been generalised to incorporate synergistic interactions in host infectivity and susceptibility and the impact of these interactions on the invasive dynamics of an epidemic has been demonstrated. In the current paper we elicit evidence that such synergistic interactions may underlie transmission dynamics in real-world systems by rst formulating a model for the spread of a ubiquitous parasitic and saprotrophic fungus through replicated populations of nutrient sites and subsequently tting and testing the model using data from experimental microcosms. Using Bayesian computational methods for model tting, we demonstrate that synergistic interactions are necessary to explain the dynamics observed in the replicate experiments. The broader implications of this work in identifying disease control strategies that de ect epidemics from invasive to non-invasive regimes are discussed.
U2 - 10.1098/rsif.2011.0506
DO - 10.1098/rsif.2011.0506
M3 - Article
VL - 9
SP - 949
EP - 956
JO - Journal of the Royal Society Interface
T2 - Journal of the Royal Society Interface
JF - Journal of the Royal Society Interface
SN - 1742-5689
IS - 70
ER -