EPISYSTEM: Designing biological, social and economic environments to enhance resistance to zoonotic outbreaks

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Pathogens in their livestock, wildlife and environmental hosts exert a constant pressure on the human population. Coupled with their evolution and adaptation, the matter is not so much whether a new epidemic will emerge, but when and how it will happen. We must therefore ensure that the chances of emergence and invasion of pathogens are minimised. To understand and eventually control the ways pathogens emerge and spread we need to consider a complex system of interacting biological, environmental, economic and social factors. There is a pressing need to develop a holistic theory of such systems analogous to the social-ecological systems approach in ecology. By analogy to ecosystems we call them episystems. The key requirement of an episystem is its ability to mitigate emergence, invasion, spread and persistence of pathogens. Episystems are dynamic and subject to disturbances. As the environmental, social, economical, psychological and biological factors change, the structure of the episystem may be affected to the point when it is not longer able to function. For example, with an anticipated increase in human population, worldwide, there will be pressures to increase food supply, leading to an increased possibility of spillover from farm to human population. We therefore need to understand mechanisms underlining proper functioning of the episystem and to design its structure so that it continues to suppress pathogens even under changed conditions. For social-ecological systems, resilience characterises the capacity of an ecosystem to tolerate disturbance. We propose to extend the concept of resilience to study the response of socio-ecological systems to pathogen spillover and spread. We also need ways to coordinate people s actions in face of epidemic risk and potential economic losses, while the response of the society is partially driven by lay perceptions of health, immunity and risk. We propose to bring together biologists, economists and social scientists with mathematical and statistical modelling providing a common language in which models will be framed and recommendations produced.