Mathematical models are a powerful method to understand and control the spread of Huanglongbing

PeerJ

article

Rachel A. Taylor¹  Erin A. Mordecai²  Christopher A. Gilligan³  Jason R. Rohr¹  Leah R. Johnson¹ 

[1] Department of Integrative Biology, University of South Florida;Department of Biology, Stanford University;Department of Plant Sciences, University of Cambridge;Department of Statistics, Virginia Polytechnic Institute and State University

关键词: Intervention strategies;    Sensitivity analysis;    Vector-borne disease;    Mathematical modeling;    Insecticide;    Citrus greening;    Temperature variation;    Cost-benefit analysis;    Flush;   

DOI  :  10.7717/peerj.2642

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Huanglongbing (HLB), or citrus greening, is a global citrus disease occurring in almost all citrus growing regions. It causes substantial economic burdens to individual growers, citrus industries and governments. Successful management strategies to reduce disease burden are desperately needed but with so many possible interventions and combinations thereof it is difficult to know which are worthwhile or cost-effective. We review how mathematical models have yielded useful insights into controlling disease spread for other vector-borne plant diseases, and the small number of mathematical models of HLB. We adapt a malaria model to HLB, by including temperature-dependent psyllid traits, “flushing” of trees, and economic costs, to show how models can be used to highlight the parameters that require more data collection or that should be targeted for intervention. We analyze the most common intervention strategy, insecticide spraying, to determine the most cost-effective spraying strategy. We find that fecundity and feeding rate of the vector require more experimental data collection, for wider temperatures ranges. Also, the best strategy for insecticide intervention is to spray for more days rather than pay extra for a more efficient spray. We conclude that mathematical models are able to provide useful recommendations for managing HLB spread.

【 授权许可】

CC BY