Trade-off between local transmission and long-range dispersal drives infectious disease outbreak size in spatially structured populations.

• Main Authors: Elisa Benincà, Thomas Hagenaars, Gert Jan Boender, Jan van de Kassteele, Michiel van Boven
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2020-07-01
• Series: PLoS Computational Biology
• Online Access: https://doi.org/10.1371/journal.pcbi.1008009

Transmission of infectious diseases between immobile hosts (e.g., plants, farms) is strongly dependent on the spatial distribution of hosts and the distance-dependent probability of transmission. As the interplay between these factors is poorly understood, we use spatial process and transmission modelling to investigate how epidemic size is shaped by host clustering and spatial range of transmission. We find that for a given degree of clustering and individual-level infectivity, the probability that an epidemic occurs after an introduction is generally higher if transmission is predominantly local. However, local transmission also impedes transfer of the infection to new clusters. A consequence is that the total number of infections is maximal if the range of transmission is intermediate. In highly clustered populations, the infection dynamics is strongly determined by the probability of transmission between clusters of hosts, whereby local clusters act as multiplier of infection. We show that in such populations, a metapopulation model sometimes provides a good approximation of the total epidemic size, using probabilities of local extinction, the final size of infections in local clusters, and probabilities of cluster-to-cluster transmission. As a real-world example we analyse the case of avian influenza transmission between poultry farms in the Netherlands.