Tuesday
Organizers:
Dave Smith, NIH, [email protected]
Ramanan Laxminarayan, Resources for the Future, [email protected]
Presented under the auspices of the of the Special Focus on Computational and Mathematical Epidemiology.
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Workshop Announcement:
The emergence and spread of resistance to antimicrobial agents is a complex interplay between economics, human behavior, and disease ecology. Mathematical models can help make sense of the complexity and vastly improve our understanding of the interplay between these factors. The DIMACS workshop on economic epidemiology is planned as the first of a series of consultations between economists and biologists working on issues of infectious diseases modeling and policy. A special focus of this first workshop will be on the management of antimicrobial resistance. Economic incentives play an important role in determining antibiotic use, infection control and the evolution of resistance. At first glance, one notes that those who use or prescribe antibiotics have few or no incentives to consider the impact of their decisions on the rest of society. On further reflection, it is evident that this problem of missing incentives extends to institutions such as hospitals and the pharmaceutical industry. Hospitals operating in the vicinity of many other medical care institutions that share patients may have fewer incentives to invest in hospital infection control to manage resistance if the benefits of their actions mainly accrue to other institutions. Drug firms that are involved in the manufacture of antibiotics similarly may fail to consider the impact of their aggressive antibiotic marketing campaigns on cross-resistance with other antibiotics that are being used. Understanding the role of incentives in the evolution of drug resistance, and the implications for the management of resistance will form the agenda of the first workshop. The broad purpose of the Workshop is to encourage greater application of economic intuition and analytical methods to mathematical models of disease evolution.