Process & Systems Modelling

Estimating transmission rates in spatio-temporal epidemics in crop mixtures

We have developed Bayesian methodology for the estimation of transmission parameters for a stochastic model of epidemics in heterogeneous host populations, in collaboration with partners at Heriot-Watt and Cambridge Universities. Application to successive spatial maps of epidemics from replicated microcosms of mixed populations of radish (favourable hosts, F) and mustard (unfavourable hosts, U) seedlings exposed to the fungal plant pathogen Rhizoctonia solani showed the best fitting model has primary and secondary infection rates that depend fully on the recipient and recipientdonor host combination respectively.

Estimated posterior
means (solid curves)Estimated posterior means (solid curves) and 95% credible intervals (dashed curves) for timespecific primary infection rates of favourable α[F](t) and unfavourable α[U](t) hosts, and each of the four secondary transmission rates, e.g. β[FU](t) for transmission from the favourable to the unfavourable host.

Further details from: Glenn Marion

Article date 2009


Statistical Genomics and Bioinformatics

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