Epidemiological risk assessment using linked network and grid based modelling: Phytophthora ramorum and Phytophthora kernoviae in the UK

We developed a stochastic simulation model incorporating most processes likely to be important in the spread of Phytophthora ramorum and similar diseases across the British landscape (covering Rhododendron ponticum in woodland and nurseries, and Vaccinium myrtillus in heathland). The simulation allows for movements of diseased plants within a realistically modelled trade network and long-distance natural dispersal. A series of simulation experiments were run with the model, representing an experiment varying the epidemic pressure and linkage between natural vegetation and horticultural trade, with or without disease spread in commercial trade, and with or without inspections-with-eradication, to give a 2 x 2 x 2 x 2 factorial started at 10 arbitrary locations spread across England. Fifty replicate simulations were made at each set of parameter values. Individual epidemics varied dramatically in size due to stochastic effects throughout the model. Across a range of epidemic pressures, the size of the epidemic was 5-13 times larger when commercial movement of plants was included. A key unknown factor in the system is the area of susceptible habitat outside the nursery system. Inspections, with a probability of detection and efficiency of infected-plant removal of 80% and made at 90-day intervals, reduced the size of epidemics by about 60% across the three sectors with a density of 1% susceptible plants in broadleaf woodland and heathland. Reducing this density to 0.1% largely isolated the trade network, so that inspections reduced the final epidemic size by over 90%, and most epidemics ended without escape into nature. Even in this case, however, major wild epidemics developed in a few percent of cases. Provided the number of new introductions remains low, the current inspection policy will control most epidemics. However, as the rate of introduction increases, it can overwhelm any reasonable inspection regime, largely due to spread prior to detection. (C) 2009 Elsevier B.V. All rights reserved.

Optimality analysis of Th1/Th2 immune responses during microparasite-macroparasite co-infection, with epidemiological feedbacks

Individuals are typically co-infected by a diverse community of microparasites (e.g. viruses or protozoa) and macroparasites (e.g. helminths). Vertebrates respond to these parasites differently, typically mounting T helper type 1 (Th1) responses against microparasites and Th2 responses against macroparasites. These two responses may be antagonistic such that hosts face a 'decision' of how to allocate potentially limiting resources. Such decisions at the individual host level will influence parasite abundance at the population level which, in turn, will feed back upon the individual level. We take a first step towards a complete theoretical framework by placing an analysis of optimal immune responses under microparasite-macroparasite co-infection within an epidemiological framework. We show that the optimal immune allocation is quantitatively sensitive to the shape of the trade-off curve and qualitatively sensitive to life-history traits of the host, microparasite and macroparasite. This model represents an important first step in placing optimality models of the immune response to co-infection into an epidemiological framework. Ultimately, however, a more complete framework is needed to bring together the optimal strategy at the individual level and the population-level consequences of those responses, before we can truly understand the evolution of host immune responses under parasite co-infection.