Abstract
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.
Original language | English |
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Pages (from-to) | 949-956 |
Number of pages | 8 |
Journal | Journal of the Royal Society Interface |
Volume | 9 |
Issue number | 70 |
DOIs | |
Publication status | Published - May 2012 |
Keywords
- Synergistic interactions
- Saprotrophic invasion
- Microcosm experiments
- Percolation
- Bayesian
- Markov chain methods