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

Department of Integrative Biology, University of South Florida, Tampa, Florida, United States
Department of Biology, Stanford University, Stanford, California, United States
Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom
Department of Statistics, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, Virginia, United States
DOI
10.7287/peerj.preprints.2059v1
Subject Areas
Agricultural Science, Ecology, Mathematical Biology, Plant Science
Keywords
intervention strategies, sensitivity analysis, vector-borne disease, mathematical modeling, insecticide, citrus greening, temperature variation, cost-benefit analysis
Copyright
© 2016 Taylor et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Taylor RA, Mordecai E, Gilligan CA, Rohr JR, Johnson LR. 2016. Mathematical models are a powerful method to understand and control the spread of Huanglongbing. PeerJ Preprints 4:e2059v1

Abstract

Huanglongbing, or citrus greening, is a global citrus disease occurring in almost all citrus growing regions and causing 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 Huanglongbing. We adapt a malaria model to Huanglongbing, by including temperature-dependent psyllid traits and economic costs, to show how models can be used to highlight which parameters require more data collection or which should be targeted for intervention. We analyze the most common intervention strategy, insecticide spraying, to determine the most cost-effective spraying strategy. We found that fecundity and feeding rate of the vector require more experimental data collection, for wider temperatures ranges. The best strategy for insecticide intervention was 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 Huanglongbing spread.

Author Comment

This is a submission to PeerJ for review.

Supplemental Information

Supplementary Article 1: Huanglongbing Model Details

DOI: 10.7287/peerj.preprints.2059v1/supp-1

Supplementary Article 2: Additional Results for the Huanglongbing Model

DOI: 10.7287/peerj.preprints.2059v1/supp-2