Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, United States
Michael L Barnett
Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, United States; Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, United States
Derek R MacFadden
Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, Canada
John S Brownstein
Boston Children’s Hospital, Boston, United States; Harvard Medical School, Boston, United States
Sonia Hernández-Díaz
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, United States
Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, United States; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, United States; Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, United States
Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, United States; Division of Infectious Diseases, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, United States
Antibiotic use is a primary driver of antibiotic resistance. However, antibiotic use can be distributed in different ways in a population, and the association between the distribution of use and antibiotic resistance has not been explored. Here, we tested the hypothesis that repeated use of antibiotics has a stronger association with population-wide antibiotic resistance than broadly-distributed, low-intensity use. First, we characterized the distribution of outpatient antibiotic use across US states, finding that antibiotic use is uneven and that repeated use of antibiotics makes up a minority of antibiotic use. Second, we compared antibiotic use with resistance for 72 pathogen-antibiotic combinations across states. Finally, having partitioned total use into extensive and intensive margins, we found that intense use had a weaker association with resistance than extensive use. If the use-resistance relationship is causal, these results suggest that reducing total use and selection intensity will require reducing broadly distributed, low-intensity use.
