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Challenges in Forecasting Antimicrobial Resistance

Sen Pei, Seth Blumberg, Jaime E. Cascante Vega, Tal Robin, Yue Zhang, Richard J Medford, Bijaya Adhikari, Jeffrey Shaman, for the CDC MIND-Healthcare Program

2023Emerging infectious diseases44 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Data scienceComputer scienceAntibiotic resistancePerspective (graphical)Field (mathematics)Clinical microbiologyRisk analysis (engineering)Management scienceBiologyMedicineArtificial intelligenceMicrobiologyAntibioticsMathematicsPure mathematicsEconomicsAntibiotic Use and ResistanceBacterial Identification and Susceptibility TestingAntibiotic Resistance in Bacteria
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