Non Technical Summary
The majority of US citrus production now occurs in states with environments that are probably sub-optimal for HLB development. Disease management approaches for these chronic situations are needed. The research and outreach in this project will combine several existing sources of data with new analyses and modeling work to produce tools for growers in these states to manage HLB risk appropriately. A key issue facing citrus producers in these regions is that the majority of research on HLB has been conducted with sub-tropical or tropical clinates in mind. In such climates the Asian Citrus Psyllid (ACP) can reproduce year-round and the pathogen vectoring capacity of the vector population is so large that risk of infection is constantly very high. As a consequence, the epidemiology of HLB has been relatively under-researched (since it is irrelevant in situations where infection is more or less guaranteed), and there are significant gaps in understanding how risk varies seasonally in other types of climate where citrus is produced. Our project builds on previous field studies conducted in California, and relevant controlled environment experiments done elsewherel, to address the epidemiological gaps in HLB risk management for Mediterranean and other more arid climates than the typical sub-tropical environment found in Florida. The work also borrows from long-established work on vector-borne diseases in public health to take a new approach for establishing action thresholds for the control of ACP.

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
216	0999	1170	100%

Knowledge Area
216 - Integrated Pest Management Systems;

Subject Of Investigation
0999 - Citrus, general/other;

Field Of Science
1170 - Epidemiology;

Goals / Objectives
The broad strategic goal of this project is to improve the management of HLB in regions of the USA where the environment is sub-optimal for vector and/or pathogen development and for which, therefor, risk-based disease management is a possibilit. The project has two major practicalgoals:Understanding Vector-pathogen relationships and temporal dynamics of HLB riskEpidemiological understanding, modeling capability and disease forecastingVector-pathogen relationship and temporal dynamics of HLB riskWithin the first major goal the following specific objectives will be addressedCharacterizationof seasonal CLas titre dynamics in ACPCharacterizationof seasonal infectivity of ACP as a function of CLastitreOptimization of qPCR for CLas titre estimationOptimization/validation of ACP phenology models with temperature and location2. Epidemiological understanding, modeling capability and disease forecastingThe second major goal will focus on deeper understanding of fundamental issues in HLB epidemiology:Develop a new biologically-grounded compartment model of HLB dynamics accounting for vector-pathogen relationshipsTriangulation of results from the new modelwith existing an Agent-Based Model for HLBUse of Vector-biology approach from public health applicationsto derive ACP population thresholds for control

Project Methods
Objective 1CLas titre dynamics in ACPStatistical analysis of existing data sets from field-collected insects plus some new field collection, combined with statistical analysisInfectivity as a function of titreStatistical analysis (logistic regression) of data collected by McCollum at USDA-ARSOptimization of qPCR for titre estimationRe-analysis of field and experimental data to determine best practice for generating reliable titre estimatesAnalysis of long RNA and proteome databasesMine existing databases for the above from ACP to identify potential novel insights to infection riskOptimization/validation of ACP phenology with temperatureCompare field observations from PCAs with phenology model in multiple locationsObjective 2Biologically-grounded compartment model of HLB dynamicsMathematical modeling of biologically detailed vector-pathogen and host infection processesTriangulation with existing Agent-Based Model for HLBComparison of model output and dynamic properties of equation-based (compartment) model with Agent-Based (computational model) to cross validate approaches.Vector-biology approach to derive ACP population thresholdsSelection of most appropriate equation to adapt, parameterize equation, analysis of temporal stability, derive dynamic thresholds if neededInternational HLB Epidemiology/modeling workshopHold a workshop for national and international modeling experts at Ft Pierce, FL