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Volume 29, Number 4—April 2023
Perspective

Challenges in Forecasting Antimicrobial Resistance

Sen PeiComments to Author , Seth Blumberg, Jaime Cascante Vega, Tal Robin, Yue Zhang, Richard J. Medford, Bijaya Adhikari, Jeffrey Shaman, and for the CDC MIND-Healthcare Program
Author affiliations: Columbia University, New York, New York, USA (S. Pei, J. Cascante Vega, T. Robin, J. Shaman); University of California, San Francisco, California, USA (S. Blumberg); University of Utah, Salt Lake City, Utah, USA (Y. Zhang); University of Texas Southwestern Medical Center, Dallas, Texas, USA (R.J. Medford); University of Iowa, Iowa City, Iowa, USA (B. Adhikari)

Main Article

Figure

Open questions for predictive modeling of MRSA. Example questions at the facility level, the population level, and across scales are listed. The upper left panel depicts population-level and facility-level MRSA transmission. The lower left panel represents the uncertainty about the roles of co-selection and competition with MSSA in affecting the dynamics of MRSA. MRSA, methicillin-resistant Staphylococcus aureus; MSSA, methicillin-susceptible S. aureus.

Figure. Open questions for predictive modeling of MRSA. Example questions at the facility level, the population level, and across scales are listed. The upper left panel depicts population-level and facility-level MRSA transmission. The lower left panel represents the uncertainty about the roles of co-selection and competition with MSSA in affecting the dynamics of MRSA. MRSA, methicillin-resistant Staphylococcus aureus; MSSA, methicillin-susceptible S. aureus.

Main Article

Page created: February 07, 2023
Page updated: March 20, 2023
Page reviewed: March 20, 2023
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