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 i s 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).

Public Health Relevance

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.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM100471-01
Application #
8244574
Study Section
Special Emphasis Panel (ZGM1-CBCB-5 (BM))
Program Officer
Eckstrand, Irene A
Project Start
2011-09-15
Project End
2015-06-30
Budget Start
2011-09-15
Budget End
2012-06-30
Support Year
1
Fiscal Year
2011
Total Cost
$381,544
Indirect Cost
Name
Arizona State University-Tempe Campus
Department
Miscellaneous
Type
Other Domestic Higher Education
DUNS #
943360412
City
Tempe
State
AZ
Country
United States
Zip Code
85287
Reeling, Carson; Horan, Richard D (2018) Economic Incentives for Managing Filterable Biological Pollution Risks from Trade. Environ Resour Econ (Dordr) 70:651-671
Morin, B R; Kinzig, A P; Levin, S A et al. (2018) Economic Incentives in the Socially Optimal Management of Infectious Disease: When [Formula: see text] is Not Enough. Ecohealth 15:274-289
Berry, Kevin; Anderson, Julia E; Bayham, Jude et al. (2018) Linking Time-Use Data to Explore Health Outcomes: Choosing to Vaccinate Against Influenza. Ecohealth 15:290-301
Berry, Kevin; Bayham, Jude; Meyer, Spencer R et al. (2018) The allocation of time and risk of Lyme: A case of ecosystem service income and substitution effects. Environ Resour Econ (Dordr) 70:631-650
Chitchumnong, Piyayut; Horan, Richard D (2018) Managing Disease Risks from Trade: Strategic Behavior with Many Choices and Price Effects. Ecohealth 15:259-273
Chowell, Gerardo (2017) Fitting dynamic models to epidemic outbreaks with quantified uncertainty: A Primer for parameter uncertainty, identifiability, and forecasts. Infect Dis Model 2:379-398
Moreno, Victor; Espinoza, Baltazar; Barley, Kamal et al. (2017) The role of mobility and health disparities on the transmission dynamics of Tuberculosis. Theor Biol Med Model 14:3
Wu, Tong; Perrings, Charles; Kinzig, Ann et al. (2017) Economic growth, urbanization, globalization, and the risks of emerging infectious diseases in China: A review. Ambio 46:18-29
Castillo-Chavez, Carlos; Bichara, Derdei; Morin, Benjamin R (2016) Perspectives on the role of mobility, behavior, and time scales in the spread of diseases. Proc Natl Acad Sci U S A 113:14582-14588
Kiskowski, Maria; Chowell, Gerardo (2016) Modeling household and community transmission of Ebola virus disease: Epidemic growth, spatial dynamics and insights for epidemic control. Virulence 7:163-73

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