Page Banner

United States Department of Agriculture

Agricultural Research Service

Related Topics

Research Project: DEVELOPMENT OF STOCHASTIC MODELS TO DESCRIBE AND PREDICT THE INCREASE AND SPREAD OF HUANGLONGBING

Location: Subtropical Plant Pathology Research

2012 Annual Report


1a.Objectives (from AD-416):
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.


1b.Approach (from AD-416):
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.


3.Progress Report:

This research is related to inhouse project objective 3. Develop or improve comprehensive integrated disease management strategies.

A Susceptible Exposed Infected Diseased Removed (SEIDR) model was developed that uses Markov-chain Monte Carlo methods, and extensive data from South Florida. This model portrays successive snapshots of the occurrence of symptomatic detected trees in known populations of susceptible trees. To date we have been able to estimate the transmission rates and dispersal kernel for huanglongbing (HLB) by interrogating this prior data center. Currently we are working on differential effects of host age on epidemiological parameters and variability across the plantation. This allows us to explore the uncertainty how the predictions which is then incorporated in models to predict spread and to allow for uncertainty in the efficiency and comparison of control methods. A web based version of the model is in the final stages of development. This web-based model is for non-researcher users you can utilize it as a tool to understand how the disease will increase and spread both residential and commercial situations. It can also be used to test a wide variety of epidemiological and climate/weather variables and their effects on an HLB epidemic as well as various disease control/mitigation parameters to see the effect of these various control strategies. The team has been using the data from southern gardens citrus that includes both young and mature trees, since host age is likely to be an important consideration for HLB. The model continues to be improved upon to capture more and more of the true features of the data and the disease. The model is being extended to estimate spread in diverse situations, should HLB be introduced into new areas such as Texas, California or Arizona. Field plots were established at the USDA, ARS Picos Farm to examine the effects of insecticide control and roguing in various combinations, both to evaluate treatment effects and to collect epidemiological data for model development. These field studies are underway as well however, at the time of this writing there are no detectable statistical differences among various control strategies.


Last Modified: 9/20/2014
Footer Content Back to Top of Page