PubMed Health⌕ Search

Biomedical subjects

Edmund Peeler

Publications and source records attributed to Edmund Peeler.

4 recordsLinked to original sources

Stochastic simulation of live salmonid movement in England and Wales to predict potential spread of exotic pathogens.

The anthropogenic movement of live fish has been identified as the most important route for the transmission of disease between river catchments. To assist in contingency planning for exotic salmonid disease outbreaks, a stochastic model was developed to assess the potential geographic distribution of an introduced pathogen with time to first detection. The Live Fish Movement Database (a resource funded by the UK Department for Environment, Food and Rural Affairs [Defra] and managed by the Centre for Environment, Fisheries and Aquaculture Science [CEFAS] and the Environment Agency [EA]) was used to establish details of live fish movement in England and Wales. A contact network was created for farm to farm and farm to non-farm (fishery) movements of rainbow trout Oncorhynchus mykiss, brown trout Salmo trutta and Atlantic salmon Salmo salar, and probability functions were used to model the timing and destination of movements from farm sites, based on these trading activities. Monte Carlo simulations were run to track the progression of potential disease transmission from single index farm inputs through river catchments with time. Two hundred farms exported fish to 1653 destinations in 147 of the total 198 river catchments. The median number of catchments contacted after 3 and 12 mo were 3 and 6, respectively. In 5% of simulations 63 or more catchments were contacted, and in 1% of simulations 75 or more catchments were contacted after 12 mo. These results may be used to underpin the development of contingency plans for exotic disease outbreaks.

Animals↗

Pair-level approximations to the spatio-temporal dynamics of epidemics on asymmetric contact networks.

The process of infection during an epidemic can be envisaged as being transmitted via a network of routes represented by a contact network. Most differential equation models of epidemics are mean-field models. These contain none of the underlying spatial structure of the contact network. By extending the mean-field models to pair-level, some of the spatial structure can be contained in the model. Some networks of transmission such as river or transportation networks are clearly asymmetric, whereas others such as airborne infection can be regarded as symmetric. Pair-level models have been developed to describe symmetric contact networks. Here we report on work to develop a pair-level model that is also applicable to asymmetric contact networks. The procedure for closing the model at the level of pairs is discussed in detail. The model is compared against stochastic simulations of epidemics on asymmetric contact networks and against the predictions of the symmetric model on the same networks.

Communicable Diseases↗