DESCRIPTION (provided by applicant): Globalization has increased the likelihood that susceptible and infected individuals of many species will be brought into contact, so increasing the disease risks for humans and animals alike. For human diseases, contact depends on choices that people make that bring susceptible and infected individuals together. For domesticated and wild animals, contact depends on the transactions people make that bring susceptible animals into contact with infectious agents. The spread of emerging infectious zoonotic diseases, depends on both things. While epidemiologists recognize the importance of human behavior in the spread of diseases they do not model the decision processes involved. Embedding these decision processes in the contact function in compartmental epidemiological models is expected to enhance their capacity to predict the introduction and spread of infectious diseases, and to provide an opportunity to evaluate incentive based disease management policies (Fenichel et al, 2011). The research will incorporate the economic drivers of 'contact' into dynamic models of emerging human and animal infectious disease systems, and analyze the system dynamics with and without adaptive responses. The models will be calibrated for a set of diseases where people's trade and travel decisions are potentially important (initially H1N1, H5N1,FMD). The aim is to strengthen the power of compartmental epidemiological models (a) to predict the likelihood that diseases of particular types will be introduced and the course of diseases once introduced, and (b) to evaluate the potential for incentive-based policy responses to disease threats and disease outbreaks. The research team has been built over a number of years through collaboration in three networks: an RCN - BESTNet; the international biodiversity science program DIVERSITAS; and a NIMBIOS working group - SPIDER. It comprises mathematical epidemiologists (Castillo-Chavez and Chowell at ASU), ecologists (Daszak, EcoHEALTH; Kilpatrick, UCSC; Smith, Brown; Kinzig, ASU; Levin, Princeton) and resource economists (Perrings, Kuminoff and Fenichel at ASU; Horan, MSU; Springborn, UCD and Finnoff, UW).

We expect the research to benefit regulatory bodies responsible for disease risk assessment and management (e.g. NIH; NCID, CDC and the Communicable Diseases Working Group on Emergencies (CD-WGE) at WHO and the OIE). The models will provide 'test-beds' for the evaluation of alternative incentive-based disease management tools of potential value in managing outbreaks and controlling introduction risks.