Optimising risk-based surveillance for early detection of invasive plant pathogens

Mastin, A ORCID: https://orcid.org/0000-0002-9536-3378, Gottwald, TR ORCID: https://orcid.org/0000-0003-0885-8004, van den Bosch, F, Cunniffe, NJ ORCID: https://orcid.org/0000-0002-3533-8672 and Parnell, SR ORCID: https://orcid.org/0000-0002-2625-4557 2020, 'Optimising risk-based surveillance for early detection of invasive plant pathogens' , PLOS Biology, 18 (10) , e3000863.

PDF - Published Version
Available under License Creative Commons Public Domain Dedication.

Download (3MB) | Preview


Emerging infectious diseases (EIDs) of plants continue to devastate ecosystems and livelihoods worldwide. Effective management requires surveillance to detect epidemics at an early stage. However, despite the increasing use of risk-based surveillance programs in plant health, it remains unclear how best to target surveillance resources to achieve this. We combine a spatially explicit model of pathogen entry and spread with a statistical model of detection and use a stochastic optimisation routine to identify which arrangement of surveillance sites maximises the probability of detecting an invading epidemic. Our approach reveals that it is not always optimal to target the highest-risk sites and that the optimal strategy differs depending on not only patterns of pathogen entry and spread but also the choice of detection method. That is, we find that spatial correlation in risk can make it suboptimal to focus solely on the highest-risk sites, meaning that it is best to avoid ‘putting all your eggs in one basket’. However, this depends on an interplay with other factors, such as the sensitivity of available detection methods. Using the economically important arboreal disease huanglongbing (HLB), we demonstrate how our approach leads to a significant performance gain and cost saving in comparison with conventional methods to targeted surveillance.

Item Type: Article
Contributors: Perrings, C (Editor)
Schools: Schools > School of Environment and Life Sciences > Ecosystems and Environment Research Centre
Journal or Publication Title: PLOS Biology
Publisher: PLOS
ISSN: 1545-7885
Related URLs:
Funders: USDA APHIS farm bill grant, Defra, Biotechnology and Biosciences Sciences Research Council (BBSRC)
Depositing User: USIR Admin
Date Deposited: 15 Oct 2020 14:48
Last Modified: 16 Feb 2022 05:51
URI: https://usir.salford.ac.uk/id/eprint/58570

Actions (login required)

Edit record (repository staff only) Edit record (repository staff only)


Downloads per month over past year