Game theory and economics show how to direct th


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Human behavior drives the evolution of biological organisms in ways that can have a profound negative impact on human well-being. Understanding the motivations of people when doing so is critical to identifying policies and other strategies to improve scalable outcomes. In a new study published on November 16e in the open access journal, PLOS Biology, researchers led by Troy Day at Queens University and David McAdams at Duke University bring the tools of economics and game theory to the management of evolution.

From antibiotic-resistant bacteria that put our health at risk to control-resistant crop pests that threaten to undermine global food production, we now face the dire consequences of our inability to manage the evolution of the biological world. As Day explains, “By modeling the joint economic and evolutionary consequences of people’s actions, we can determine how best to encourage behavior that is evolutionarily desirable. “

The centerpiece of the new analysis is a simple mathematical formula that determines when physicians, farmers, and other “evolutionary managers” will be given enough incentive to manage the biological resources that are under their control, trading off short-term costs. of management against the long-term benefits of delaying adverse development.

For example, when a patient arrives at an emergency care facility, screening them to determine if they are colonized with a dangerous superbug is costly, but protects future patients by allowing the superbug carriers to be isolated from others. Whether the facility itself benefits from patient screening depends on how it balances these costs and benefits.

Researchers take the mathematical model one step further by implementing game theory, which analyzes how the decisions of individuals are interconnected and may influence each other – such as doctors at the same facility whose patients may become infected or corn growers with neighboring fields. Their game theory analysis identifies the conditions under which outcomes can be improved through policies that change incentives or facilitate coordination.

“In the example of antibiotic-resistant bacteria, hospitals could go above and beyond to control the spread of superbugs through methods such as community contact tracing,” McAdams said. “It would incur additional costs and, on its own, a hospital would probably not have the incentive to do so. But if each hospital took this extra step, they could all collectively benefit from slowing the spread of these bacteria. Game theory gives you a systematic way to think about these possibilities and maximize overall well-being. “

“Evolutionary change in response to human interventions, such as evolution of resistance in response to drug therapy or evolutionary change in response to harvest, can have significant economic implications,” adds Day. “We determine the conditions under which it is economically advantageous to employ expensive strategies which limit evolution and thus preserve the value of biological resources for longer.”


In your cover, please use these URLs to provide access to articles available free of charge in PLOS Biology:

Quote: Day T, Kennedy DA, Read AF, McAdams D (2021) The economics of evolutionary management. PLoS Biol 19 (11): e3001409.

Author countries: Canada, United States

Funding: This work was funded by the Research and Policy in Infectious Disease Dynamics (RAPIDD) program of the Science and Technology Directorate, Department of Homeland Security, Fogarty International Center, National Institutes of Health, and Natural Sciences and Engineering Research Council of Canada (TD) and the Institute of General Medical Sciences (R01GM105244 to AFR and R01GM140459 to DAK) under the joint NSF-NIH-USDA program on the ecology and evolution of infectious diseases. Funders played no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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