Game theory and economics show how to steer evolution in a better
direction

Date:
November 16, 2021
Source:
PLOS
Summary:
Human behavior drives the evolution of biological organisms in ways
that can profoundly adversely impact human welfare. Understanding
people's incentives when they do so is essential to identify
policies and other strategies to improve evolutionary outcomes. In
a new study, researchers bring the tools of economics and game
theory to evolution management.



FULL STORY ========================================================================== Human behavior drives the evolution of biological organisms in ways that
can profoundly adversely impact human welfare. Understanding people's incentives when they do so is essential to identify policies and other strategies to improve evolutionary outcomes. In a new study publishing
November 16thin 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 evolution management.


==========================================================================
From antibiotic-resistant bacteria that endanger our health to control- resistant crop pests that threaten to undermine global food production,
we are now facing the harmful consequences of our failure to efficiently
manage the evolution of the biological world. As Day explains, "By
modelling the joint economic and evolutionary consequences of people's
actions we can determine how best to incentivize behavior that is evolutionarily desirable." The centerpiece of the new analysis is a
simple mathematical formula that determines when physicians, farmers,
and other "evolution managers" will have sufficient incentive to steward
the biological resources that are under their control, trading off
the short-term costs of stewardship against the long-term benefits of
delaying adverse evolution.

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

The researchers take the mathematical model further by implementing game theory, which analyzes how individuals' decisions are interconnected
and can impact each other -- such as physicians in the same facility
whose patients can infect each other or corn farmers with neighboring
fields. Their game-theoretic analysis identifies 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
like community contact tracing," McAdams says. "This would entail
additional costs and, alone, a hospital would likely not have an
incentive to do so. But if every hospital took this additional step,
they might all collectively benefit from slowing the spread of these
bacteria. Game theory gives you a systematic way to think through
those possibilities and maximize overall welfare." "Evolutionary
change in response to human interventions, such as the evolution of
resistance in response to drug treatment or evolutionary change in
response to harvesting, can have significant economic repercussions,"
Day adds. "We determine the conditions under which it is economically beneficial to employ costly strategies that limit evolution and
thereby preserve the value of biological resources for longer." ========================================================================== Story Source: Materials provided by PLOS. Note: Content may be edited
for style and length.


========================================================================== Journal Reference:
1. Troy Day, David A. Kennedy, Andrew F. Read, David McAdams. The
economics
of managing evolution. PLOS Biology, 2021; 19 (11): e3001409 DOI:
10.1371/journal.pbio.3001409 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/11/211116144811.htm

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