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

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 mod...

Full description

Saved in:
Bibliographic Details
Published in:PLoS computational biology 2020-07, Vol.16 (7), p.e1008009-e1008009
Main Authors: Benincà, Elisa, Hagenaars, Thomas, Boender, Gert Jan, van de Kassteele, Jan, van Boven, Michiel
Format: Article
Language:English
Subjects:
Avian flu
Bacteriology
Biology and Life Sciences
Clustering
Computational biology
Disease control
Disease transmission
Dispersal
Epidemics
Epidemiology
Evaluation
Farms
Host plants
Infections
Infectious diseases
Infectivity
Influenza
Medical statistics
Medicine and Health Sciences
Metapopulations
Methods
Netherlands
Pathogens
Populations
Poultry
Poultry farming
Public health
Software
Spatial distribution
Species extinction
Supervision
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1008009