Dynamics of the 2001 UK Foot and Mouth Epidemic: Stochastic Dispersal in a Heterogeneous Landscape

Foot-and-mouth is one of the world's most economically important livestock diseases. We developed an individual farm-based stochastic model of the current UK epidemic. The fine grain of the epidemiological data reveals the infection dynamics at an unusually high spatiotemporal resolution. We sh...

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Bibliographic Details
Published in:Science (American Association for the Advancement of Science) 2001-10, Vol.294 (5543), p.813-817
Main Authors: Keeling, Matt J., Mark E. J. Woolhouse, Shaw, Darren J., Matthews, Louise, Chase-Topping, Margo, Haydon, Dan T., Cornell, Stephen J., Kappey, Jens, Wilesmith, John, Grenfell, Bryan T.
Format: Article
Language:English
Subjects:
Animal diseases
Animal Husbandry
Animals
Biological and medical sciences
Cattle
Cattle Diseases - epidemiology
Cattle Diseases - transmission
Communicable Diseases
Development and progression
Disease control
Disease models
Disease Outbreaks - veterinary
Disease Susceptibility - veterinary
Disease transmission
Epidemics
Epidemiology
Foot & mouth disease
Foot and mouth disease
Foot-and-Mouth Disease - epidemiology
Foot-and-Mouth Disease - prevention & control
Foot-and-Mouth Disease - transmission
Foot-and-mouth disease virus
Foot-and-Mouth Disease Virus - immunology
Fundamental and applied biological sciences. Psychology
Health aspects
Herd culling
Infections
Least Squares Statistics
Livestock
Maximum Likelihood Statistics
Microbiology
Models, Biological
Models, Statistical
Monte Carlo Methods
Sheep
Sheep Diseases - epidemiology
Sheep Diseases - transmission
Space-Time Clustering
Stochastic Processes
United Kingdom
United Kingdom - epidemiology
Vaccination
Vaccination - veterinary
Viral Vaccines - administration & dosage
Virology
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Description
Summary:Foot-and-mouth is one of the world's most economically important livestock diseases. We developed an individual farm-based stochastic model of the current UK epidemic. The fine grain of the epidemiological data reveals the infection dynamics at an unusually high spatiotemporal resolution. We show that the spatial distribution, size, and species composition of farms all influence the observed pattern and regional variability of outbreaks. The other key dynamical component is long-tailed stochastic dispersal of infection, combining frequent local movements with occasional long jumps. We assess the history and possible duration of the epidemic, the performance of control strategies, and general implications for disease dynamics in space and time.
ISSN:0036-8075
1095-9203
DOI:10.1126/science.1065973