Repository logo
 

Modelling the spread and mitigation of an emerging vector-borne pathogen: Citrus greening in the U.S.

Published version
Peer-reviewed

Repository DOI


Change log

Authors

Abstract

Predictive models, based upon epidemiological principles and fitted to surveillance data, play an increasingly important role in shaping regulatory and operational policies for emerging outbreaks. Data for parameterising these strategically important models are often scarce when rapid actions are required to change the course of an epidemic invading a new region. We introduce and test a flexible epidemiological framework for landscape-scale disease management of an emerging vector-borne pathogen for use with endemic and invading vector populations. We use the framework to analyse and predict the spread of Huanglongbing disease or citrus greening in the U.S. We estimate epidemiological parameters using survey data from one region (Texas) and show how to transfer and test parameters to construct predictive spatio-temporal models for another region (California). The models are used to screen effective coordinated and reactive management strategies for different regions.

Description

Acknowledgements: We wish to thank Tim Gottwald, Nik Cunniffe, Sunil Kumar and members of the Epidemiological and Modelling group for useful comments and discussions and to Lawrence Bower for assistance with figures and Alison Scott-Brown for assistance with literature.

Keywords

Citrus, Plant Diseases, Disease Outbreaks, Epidemics

Journal Title

PLoS Comput Biol

Conference Name

Journal ISSN

1553-734X
1553-7358

Volume Title

Publisher

Public Library of Science (PLoS)
Sponsorship
Animal and Plant Health Inspection Service (16-8130-0730-CA)
Bill and Melinda Gates Foundation (INV-010472_2020)
Relationships
Is supplemented by: