Dear Colleagues,
A friendly reminder. Today (April 14th, 4:10pm, @1100 Social Sciences) Carl Bergstrom from the University of Washington will present the Ecology and Evolution seminar. Carl’s research applies mathematical models and computer simulations to study population biology, animal behavior, and evolutionary theory and especially information flow in biological systems and the infectious disease. Carl’s seminar is titled "Anthropogenic evolution, externalities, and public health" and a summary of his talk is copied below.
Seminar abstract: Humans today have a major impact on the evolution of species ranging from pathogenic bacteria to charismatic megafauna. In some cases, such as conservation efforts, humans deliberate influence the evolutionary process to bring about desired ends. In other cases, such as the overuse of antibiotics, undesirable evolutionary consequences result as a side-effect of other activities. One common element of these cases is that the consequences of anthropogenic evolution are rarely fully encompassed by existing economic markets. In other words, anthropogenic evolution can generate both positive and negative externalities, which can be managed by legislation, taxation, torts, and property rights much as are other externalities such as public works or pollution. After briefly summarizing some of these mechanisms, I will show how a public choice framework from economics can be adapted to think about the positive and negative externalities generated by the public health measures. Such activities as vaccination and antibiotic use influence can both the trajectory of a disease outbreak and the evolution of the pathogen in question, and we can adapt the economic theory of public finance to account for the externalities generated thusly. In the final part of the talk, I consider how antimicrobial use influences the evolution of antimicrobial resistance for epidemic diseases rather than for the typical endemic settings in which this problem is studied. To do so, I will use mathematical models to predict how the timing of antiviral use influences resistance evolution and drug efficacy in seasonal influenza and other epidemically spreading diseases.
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