NIMBioS Working Group: SPIDER
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| (Back row, L to R): Chris Jerde, Eli Fenichel, Graziano Ceddia, Michael Springborn, Charles Perrings and Gerardo Chowell-Puente; (Front, L to R): Garth Holloway, Christina Villalobos, Leticia Velazquez and Paula Gonzalez Parra; (Not pictured): Peter Daszak, Graham Hickling, David Finnoff, Lynn Garrett, Carlos Castillo-Chaves, Kate Smith, Salvatore di Falco, David Cook, and William Brock. |
Scientists Examine Human Behavior and the Threat of Disease
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| Photo Credit: C. S. Goldsmith and A. Balish, CDC |
As swine flu spread from Mexico to Texas and then fanned out farther in the United States, Americans began to alter their behavior. Families kept children home from school, postponed trips to the mall, and stayed home instead of eating out. In so doing, the American population may have inadvertently altered the behavior of the pathogen itself.
How human behavior changes the spread of emerging infectious diseases, and how the spread of disease simultaneously changes human behavior, were among the topics discussed by scientists at a meeting at the National Institute for Biological and Mathematical Synthesis (NIMBioS) on the University of Tennessee campus, June 7-9.
Ecologists, epidemiologists, economists, and mathematicians comprise a NIMBioS Working Group to tackle the topic, Synthesizing and Predicting Infectious Disease While Accounting for Endogenous Risk or SPIDER.
Accounting for endogenous risk means jointly considering how human behavior influences disease and how disease influences human behavior, explained Eli Fenichel, working group co-organizer and assistant professor at Arizona State University. "When people perceive risks, they alter their behavior, which in turn, alters the risk. It's a feedback loop between people, the pathogen, and the risk."
Most current attempts to model the risks of emerging infectious diseases look at the disease itself and human behavior. The SPIDER Working Group aims to build on that classic view by also considering the economic impact of human decisions about risk.
"Epidemiological science has gotten good at modeling and projecting risk. The next major frontier is how do we manage risk in a cost effective way," Fenichel said. "It's a way of thinking about how resources get allocated to address emerging pathogens like the flu now. For example, if we believe that people will behave in a certain way given certain information sets, we might be able to find better ways to distribute medicine."
Another avenue for investigation is how the global food trade system would be affected if it becomes the source of a pathogen, Fenichel said. "One of the questions is how do we set up inspections in a cost effective way if we cannot reasonably inspect everything. We need to look at how to best balance the risks and the costs."
The group aims to develop predictive models to forecast the risks associated with emerging infectious diseases in humans, livestock, wildlife, and plants, and to collaborate in developing risk management strategies.
NIMBioS Working Groups are comprised of 10-15 invited participants and focus on specific questions related to mathematical biology. Each group typically meets two to three times over the course of two years at the Institute.
The National Institute for Mathematical and Biological Synthesis (NIMBioS) brings together researchers from around the world to collaborate across disciplinary boundaries to investigate solutions to basic and applied problems in the life sciences. NIMBioS is funded by the National Science Foundation in collaboration with the U.S. Department of Homeland Security and the U.S. Department of Agriculture, with additional support from The University of Tennessee, Knoxville.
For more information, contact Catherine Crawley at 865-974-9350 or ccrawley@nimbios.org
NIMBioS Working Group: SPIDER
Topic: Working Group for Synthesizing and Predicting Infectious Disease while Accounting for Endogenous Risk (SPIDER)
Organizers: Eli Fenichel (Arizona State University, School of Life Sciences); Carlos Castillo-Chavez (Arizona State University, Department of Mathematics and Statistics); Peter Daszak (Consortium for Conservation Medicine, New York, NY); Rick Horan (Michigan State University, Department of Agricultural, Food, and Resource Economics); Charles Perrings (Arizona State University, School of Life Sciences)
Meeting dates: June 7-9, 2009; November 9-11, 2009
Objectives: There is increasing interest in modeling risks associated with emerging infectious diseases (EIDs). Most EIDs are zoonotic in nature (Jones et al. 2008), and many infect valuable livestock and wildlife resources (Daszak et al. 2000). Disease risks, like the risks associated with invasive species, are endogenous – a function of human decisions (Finnoff et al. 2005; Horan and Fenichel 2007). However, most current attempts to model EID risks treat risk as exogenous and intrinsic. This comes from implicitly assuming that the probability of an event and the human self-protection decisions are additively separable in the consequence function (Shogren and Crocker 1999). In order to successfully manage, predict, and develop surveillance strategies for new emerging diseases, it is imperative that the human decision making processes that influence disease risks are formally included in the decision process. Recent mathematical advances offer new opportunities to do so. The SPIDER Working Group will bring together disease ecologists, economists, and mathematicians to facilitate the development of predictive models both to forecast the risks associated with EIDs in humans, livestock, wildlife, and plants, and to assist in the development of risk management strategies.
This project will assemble a working group to develop lines of research, share results and techniques, and provide capacity to unify models.
NIMBioS SPIDER Working Group: Meeting 1 Summary, June 6-9, 2009
Participants: Carlos Castillo-Chaves (Arizona State Univ.); Graziano Ceddia (Univ. of Reading, UK); Geradro Chowell-Puente (Arizona State Univ.); Peter Dazsak (Consortium for Conservation Medicine, NY); Eli Fenichel (Arizona State Univ.); David C. Finnoff (Univ. of Wyoming); Lynn Garrett (USAPHIS); Paula Gonzalez (Univ. of Texas-El Paso); Graham Hickling (Univ. of Tennessee); Garth Holloway (Univ. of Reading, UK); Rick Horan (Michigan State Univ.); Chris Jerde (Univ. of Notre Dame); Charles Perrings (Arizona State Univ.) Mike Springborn, (UC Davis); Leticia Velazquez (Univ. of Texas-El Paso); Christina Villalobos (Univ. of Texas-Pan American)
The first meeting of the SPIDER Working Group facilitated increased work on feedbacks between human behavior and emerging infectious disease risk. The group is employing a network motif to organize research combined with cross-cutting themes. The network motif organizes research themes to within nodes (e.g., countries, regions, or localities), on edges or pathways between nodes, and as a complex system. Cross-cutting themes include uncertainty and learning and computational issues. Each sub-group is developing a working paper and material for a synthesis paper. The Working Group meets next in early November, where the group will address issues associated with connecting the different sub-groups for the synthesis paper, resolving technical difficulties, and computing results.
NIMBioS SPIDER Working Group: Meeting 2 Summary, November 9-11, 2009
At the second meeting of the SPIDER Working Group, Nov. 9-11, progress continued on merging human behavioral and infectious disease models to improve understanding of disease risk and to build better predictive models. The working group clarified its definition of "prediction" in terms of the group's objective, which is to build models that can predict disease risk under alternative management strategies and policies. The group has also identified a modeling framework that is applicable to local, regional, national, and international scales. Thus far, two SPIDER-related manuscripts have been accepted for publication, and at least two more are almost ready for submission.
NIMBioS Working Groups are chosen to focus on major scientific questions at the interface between biology and mathematics. NIMBioS is particularly interested in questions that integrate diverse fields, require synthesis at multiple scales, and/or make use of or require development of new mathematical/computational approaches. NIMBioS Working Groups are relatively small (10-12 participants, with a maximum of 15), focus on a well-defined topic, and have well-defined goals and metrics of success. Working Groups will typically meet 2-4 times over a two-year period, with each meeting lasting 3-5 days; however, the number of participants, number of meetings, and duration of each meeting is flexible, depending on the needs and goals of the Group.
