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 16ein 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 failure to manage the evolution of the biological world. As Day explains, âBy 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 the short costs. term 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.
âIn 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,â McAdams said. âIt 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 approach. 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 are determining 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.”
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