Antimicrobial resistance is a major threat to human health. Since the 2000s, computational tools for predicting infectious diseases have been greatly advanced; however, efforts to develop real-time forecasting models for antimicrobial-resistant organisms (AMROs) have been absent. In this perspective, we discuss the utility of AMRO forecasting at different scales, highlight the challenges in this field, and suggest future research priorities. We also discuss challenges in scientific understanding, access to high-quality data, model calibration, and implementation and evaluation of forecasting models. We further highlight the need to initiate research on AMRO forecasting using currently available data and resources to galvanize the research community and address initial practical questions.
Keywords: Blumberg S; Cascante Vega J; Medford RJ; Robin T; Suggested citation for this article: Pei S; Zhang Y; antimicrobial resistance; et al. Challenges in forecasting antimicrobial resistance. Emerg Infect Dis. 2023 Apr [date cited]. https://doi.org/10.3201/eid2904.221552; healthcare-associated infections; infectious disease forecasting.