Metapopulation and network models for plant and human infections

Rights statement
Awarding institution
  • University of Strathclyde
Date of award
  • 2023
Thesis identifier
  • T16774
Person Identifier (Local)
  • 201977748
Qualification Level
Qualification Name
Department, School or Faculty
  • Plant pests and diseases infiltrate countries via international trade. Domestic trade moves the pest far beyond the point of entry, making eradication efforts challenging. Understanding the risks and control strategies surrounding trade is vital in mitigating the damage from invasions. While attention has been given to the structure of the international trade network, little is known about the within-UK network structure due to unregistered plant movement and limited data availability. We address this gap by constructing a directed and weighted network, using sales data from four plant nurseries. We find that nurseries specialise sales towards one of the four customer groups (commercial, consumer, nursery, retailer). This allows us to group nodes into classes differing by sales patterns, with trade volumes and customer numbers highly variable within and between classes. Using centrality measures, we identify nodes at higher risk of transmitting pests or diseases. We find that edge weights significantly affect node centrality, emphasising the importance of trade volumes in similar network models. Node centrality is robust to small changes in market structure, and customers’ contribution to network structure is minimal. We extend our network model to a compartmental metapopulation Susceptible-Infected framework and investigate the effect of different seedings, compare inspection strategies and conduct a cost-benefit analysis. Our results demonstrate that disease spread faster when originating in a nursery that primarily sells to other nurseries. We find the utility of inspecting consignments depends on the frequency of inspecting nursery stock. Finally, we identify inspection efficacy regions when nurseries benefit from more frequent inspections, considering cost. From our analysis of network structure, trade, and disease dynamics, this research provides guidance for targeted surveillance, intervention, and control to mitigate the spread of plant pests and diseases. We further use network and metapopulation methods to model the spread of COVID-19 in care homes.
Advisor / supervisor
  • Kleczkowski, Adam
Resource Type