Matching Methods to Problems: Using Data Science and Transmission Modeling to Combat Antimicrobial Resistance

Abstract

Antimicrobial resistance is a growing worldwide crisis, declared by the World Health Organization as "one of the principal threats to global public health today." The emergence and spread of antimicrobial resistance is a multifaceted problem that spans all aspects of healthcare, and research efforts to advance the field must likewise employ investigators with a diverse set of expertise and a variety of approaches and study designs who recognize and address the unique challenges of infectious-disease and antimicrobial-resistance research. An understanding of transmission dynamics and externalities, both positive and negative, is critical to any assessment of the impact of an intervention or policy related to infectious disease, infection prevention, or antimicrobial stewardship, in order to create a more comprehensive and accurate estimate of the costs and outcomes associated with an intervention. These types of advanced studies are necessary if we are to significantly alter the course of this crisis and improve the outlook for our future.

Keywords: antimicrobial resistance; data science; transmission dynamics; transmission modeling.