### Abstract

Original language | English |
---|---|

Article number | e1002174. |

Number of pages | 9 |

Journal | PLoS Computational Biology |

Volume | 7 |

Issue number | 9 |

DOIs | |

State | Published - Sep 2011 |

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*PLoS Computational Biology*,

*7*(9), [e1002174.]. DOI: 10.1371/journal.pcbi.1002174

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*PLoS Computational Biology*, vol 7, no. 9, e1002174.. DOI: 10.1371/journal.pcbi.1002174

**The effect of heterogeneity on invasion in spatial epidemics: from theory to experimental evidence in a model system.** / Neri, Franco M.; Bates, Anne; Füchtbauer, Winnie S.; Pérez-Reche, Francisco J.; Taraskin, Sergei N.; Otten, Wilfred; Bailey, Douglas J.; Gilligan, Christopher A.

Research output: Contribution to journal › Article

TY - JOUR

T1 - The effect of heterogeneity on invasion in spatial epidemics: from theory to experimental evidence in a model system

AU - Neri,Franco M.

AU - Bates,Anne

AU - Füchtbauer,Winnie S.

AU - Pérez-Reche,Francisco J.

AU - Taraskin,Sergei N.

AU - Otten,Wilfred

AU - Bailey,Douglas J.

AU - Gilligan,Christopher A.

PY - 2011/9

Y1 - 2011/9

N2 - Heterogeneity in host populations is an important factor affecting the ability of a pathogen to invade, yet the quantitative investigation of its effects on epidemic spread is still an open problem. In this paper, we test recent theoretical results, which extend the established “percolation paradigm” to the spread of a pathogen in discrete heterogeneous host populations. In particular, we test the hypothesis that the probability of epidemic invasion decreases when host heterogeneity is increased. We use replicated experimental microcosms, in which the ubiquitous pathogenic fungus Rhizoctonia solani grows through a population of discrete nutrient sites on a lattice, with nutrient sites representing hosts. The degree of host heterogeneity within different populations is adjusted by changing the proportion and the nutrient concentration of nutrient sites. The experimental data are analysed via Bayesian inference methods, estimating pathogen transmission parameters for each individual population. We find a significant, negative correlation between heterogeneity and the probability of pathogen invasion, thereby validating the theory. The value of the correlation is also in remarkably good agreement with the theoretical predictions. We briefly discuss how our results can be exploited in the design and implementation of disease control strategies.

AB - Heterogeneity in host populations is an important factor affecting the ability of a pathogen to invade, yet the quantitative investigation of its effects on epidemic spread is still an open problem. In this paper, we test recent theoretical results, which extend the established “percolation paradigm” to the spread of a pathogen in discrete heterogeneous host populations. In particular, we test the hypothesis that the probability of epidemic invasion decreases when host heterogeneity is increased. We use replicated experimental microcosms, in which the ubiquitous pathogenic fungus Rhizoctonia solani grows through a population of discrete nutrient sites on a lattice, with nutrient sites representing hosts. The degree of host heterogeneity within different populations is adjusted by changing the proportion and the nutrient concentration of nutrient sites. The experimental data are analysed via Bayesian inference methods, estimating pathogen transmission parameters for each individual population. We find a significant, negative correlation between heterogeneity and the probability of pathogen invasion, thereby validating the theory. The value of the correlation is also in remarkably good agreement with the theoretical predictions. We briefly discuss how our results can be exploited in the design and implementation of disease control strategies.

U2 - 10.1371/journal.pcbi.1002174

DO - 10.1371/journal.pcbi.1002174

M3 - Article

VL - 7

JO - PLoS Computational Biology

T2 - PLoS Computational Biology

JF - PLoS Computational Biology

SN - 1553-734X

IS - 9

M1 - e1002174.

ER -