DEVELOPMENT OF STOCHASTIC MODELS TO DESCRIBE AND PREDICT THE INCREASE AND SPREAD OF HUANGLONGBING
Subtropical Plant Pathology Research
Project Number: 6618-22000-039-25
Specific Cooperative Agreement
Start Date: Nov 30, 2010
End Date: Aug 31, 2013
Develop stochastic models to estimate the temporal increase and spatial spread of Huanglongbing (HLB). The models and statistical methods will be used to test alternative disease control strategies and select those strategies which appear to have the best chance of success prior to deployment of control methods in the field. The ultimate goal is to improve disease control and thus improve citrus productivity with the minimal horticultural disruption. Such new methodologies are in direct support of future USDA, APHIS and Florida Department of Agriculture and Consumer Services regulatory actions as well as the citrus industries of Florida, California, Texas and Arizona.
Existing epidemiology data sets will be used from sites in Florida and other countries infected with HLB. Parameter estimation will focus on the use of Markov-Chain Monte-Carlo (MCMC) simulation methods of SIR Susceptibles/ Infectious/Recovered) models for spatio-temporal data, together with maximum likelihood estimation of mean-field temporal models in order to derive estimates for epidemiological parameters including rates of primary and secondary infection and, where appropriate, parameters for dispersal kernels. Simple methods will be used to quantify anisotropy to analyse and predict directionality of spread.