Disease dynamics over very different time-scales: foot-and-mouth disease and scrapie on the network of livestock movements in the UK

Abstract

We analyse the relationship between the network of livestock movements in the UK and the dynamics of two diseases: foot-and-mouth disease (FMD), which has an incubation period of days, and scrapie, which incubates over years. For FMD, the time-scale of expected epidemics is similar to the time-scale of the evolution of the network. We argue that, under appropriate conditions, a static network analysis can be an appropriate tool for gaining insights into disease dynamics even when the relevant time-scales are similar, as with FMD. We show that a subclass of 'linkage moves' maintains the network structure, and so removing these links has a dramatic effect on the number of potentially infected farms, an effect corroborated by simulations. In contrast, because scrapie has a low probability of transmission per contact and a long incubation period, a static network representation is probably appropriate; however, the signature of the network in the pattern of transmission is likely to be faint. Scrapie-notifying farms were more likely to be associated with each other via trading at markets than were control farms; however, network community structure proves to be less representative of prevalence patterns than geographical region. These contradictory indicators emphasize that appropriate observation time frames and good discrimination among types of potentially infectious contacts are vital in order for network analysis to be a valuable epidemiological tool.

A fully coupled, mechanistic model for infectious disease dynamics in a metapopulation: Movement and epidemic duration

“…If data are available on animal movements (e.g. in domestic cattle; Ezanno et al (2006) and Kao et al (2007)) it is possible to define a specific metapopulation structure. An adjacency matrix can be used to describe such a structure, for instance when not all patches are (equally) connected to each other (Keeling and Eames, 2005).…”

Evolving graphs: dynamical models, inverse problems and propagation

“…Until recently, one characteristic of such networks that is fundamental within almost all applications has received only marginal attention: that the networks may evolve (Saramäki & Kaski 2005;Kao et al 2007;Borgnat et al 2008;Gautreau et al 2009;Vernon & Keeling 2009). This issue is distinct from network growth, or aggregative phenomena: it embodies the property that all edges within the network are transient to some extent.…”

Preventable H5N1 avian influenza epidemics in the British poultry industry network exhibit characteristic scales

“…This property of 'connecting up the network' has previously been identified by Kao et al (2007), but in our interpretation, hotspots function as a single collective rather than as numerous individual bridges. To test this assumption, we ran EU and BC simulations in which only local and intra-company transmissions between hotspots were prevented, whereas their feed and abattoir associations were redistributed to minimize intra-hotspot contacts.…”