When people “treat” a biological population, e.g., when a doctor prescribes an antibiotic, a farmer sprays an herbicide, or a homeowner mows their lawn, they create a selective pressure favoring organisms that can better survive and/or recover from treatment. It might therefore seem that rising resistance to treatment is inevitable. In this week’s conversation, Duke economics professor David McAdams discussed why this is not necessarily the case—how the traditional logic of rising resistance hinges on an assumption of ignorance about the biological population. If the “evolution manager” has multiple treatment options and can observe the state of the population before deciding which treatment to prescribe, e.g., by conducting a rapid resistance diagnostic of an infecting pathogen or visually inspecting an unruly lawn, their subsequent informed treatment may then shape the fitness landscape in ways that serve human needs and, indeed, enhance the population’s future treatability. But there are important limitations, as the population may be impacted by the choices of other evolution managers (creating a “game” among managers) and some strategies with the potential to select against resistant organisms may only be feasible when resistance is sufficiently rare.
Resources discussed:
- McAdams et al. 2019, “Resistance diagnostics as a public health tool to combat antibiotic resistance: A model-based evaluation”
- McAdams 2017, “Resistance diagnosis and the changing epidemiology of antibiotic resistance”
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