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

Keeling, Matthew James; Woolhouse, Mark; Shaw, Darren; Matthews, Louise; Chase-Topping, Margo; Haydon, Daniel T.; Cornell, Stephen J.; Kappey, Jens; Wilesmith, J. W.; Grenfell, Bryan T.

doi:10.1126/science.1065973

Cited by 771 publications

(932 citation statements)

References 24 publications

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“…Factors other than distance can influence the dynamics, and this is particularly apparent for epidemiological invasions [30,39]. Here, we have used an admittedly simplified colonization model to represent both ecological invasions and spread of disease.…”

Section: Results and Discussion (A) Simulations Of Invasionmentioning

confidence: 99%

“…In this paper, we take yet another step and focus on invasion of organisms in environments where the habitats or epidemiological units are best represented as discrete entities with a fixed spatial location. Examples of this are studies of livestock epidemics [6,30] and ecological invasions, where habitats and epidemiological units are regarded as isolated patches surrounded by a hostile matrix (as is done in metapopulation studies). Throughout this article, we refer to such habitats and epidemiological units as patches, hence using terminology that is perhaps more familiar to ecologists.…”

Section: Introductionmentioning

confidence: 99%

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The shape of the spatial kernel and its implications for biological invasions in patchy environments

2010

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Ecological and epidemiological invasions occur in a spatial context. We investigated how these processes correlate to the distance dependence of spread or dispersal between spatial entities such as habitat patches or epidemiological units. Distance dependence is described by a spatial kernel, characterized by its shape (kurtosis) and width (variance). We also developed a novel method to analyse and generate point-pattern landscapes based on spectral representation. This involves two measures: continuity, which is related to autocorrelation and contrast, which refers to variation in patch density. We also analysed some empirical data where our results are expected to have implications, namely distributions of trees (Quercus and Ulmus) and farms in Sweden. Through a simulation study, we found that kernel shape was not important for predicting the invasion speed in randomly distributed patches. However, the shape may be essential when the distribution of patches deviates from randomness, particularly when the contrast is high. We conclude that the speed of invasions depends on the spatial context and the effect of the spatial kernel is intertwined with the spatial structure. This implies substantial demands on the empirical data, because it requires knowledge of shape and width of the spatial kernel, and spatial structure.

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Section: Results and Discussion (A) Simulations Of Invasionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The shape of the spatial kernel and its implications for biological invasions in patchy environments

2010

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“…Spatially explicit herd based transmission simulation models are often used to simulate the evolution of FMD under alternative control measures in disease free developed countries (Bates et al, 2003;Durand and Mahul, 2000;Keeling et al, 2001;Martínez-López et al, 2010). Such sophisticated simulation models are not available for endemic FMD countries because of a lack of spatial and structural data on livestock farms, and animal movement data.…”

Section: Estimation Of the Incidence Of Fmdmentioning

confidence: 99%

Cost-benefit analysis of foot and mouth disease control in Ethiopia

Jemberu

Mourits

Rushton

et al. 2016

Preventive Veterinary Medicine

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“…can be used to determine the number of expected outbreaks in the high risk period of an epidemic or to evaluate which measures can reduce transmission to such a level that the virus will be eradicated. Mathematical models have for example already been used extensively during the 2001 FMD epidemic in the UK [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Quantification of within- and between-pen transmission of Foot-and-Mouth disease virus in pigs

Eblé¹,

Koeijer

Bouma

et al. 2006

Vet. Res.

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-Quantified transmission parameters of Foot-and-Mouth Disease Virus (FMDV) are needed for epidemic models used for control and surveillance. In this study, we quantified the within-and between-pen transmission of FMDV in groups of pigs by estimating the daily transmission rate β, i.e. the number of secondary infections caused by one infectious pig during one day, using an SIR (susceptible-infectious-removed) model. Within-pen transmission was studied in four groups of ten pigs in which 5 infected and 5 susceptible pigs had direct contact; betweenpen transmission was studied in one group of ten pigs in which 5 infected and 5 susceptible pigs had indirect contact. Daily results of virus isolation of oropharyngeal fluid were used to quantify the transmission rate β, using Generalised Linear Modelling (GLM) and a maximum likelihood method. In addition, we estimated the expected time to infection of the first pig within a pen T w and in the indirect-contact pen T b . The between-pen transmission rate β b was estimated to be 0.59 (0.083-4.18) per day, which was significantly lower than the within-pen transmission rate β w of 6.14 (3.75-10.06). T w was 1.6 h, and T b was 16 h. Our results show that the transmission rate is influenced by contact structure between pigs.foot-and-mouth disease / pigs / transmission / transmission rate / modelling

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

Cited by 771 publications

References 24 publications

The shape of the spatial kernel and its implications for biological invasions in patchy environments

The shape of the spatial kernel and its implications for biological invasions in patchy environments

Cost-benefit analysis of foot and mouth disease control in Ethiopia

Quantification of within- and between-pen transmission of Foot-and-Mouth disease virus in pigs

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