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Editorial Commentary: Network Models, Patient Transfers, and Infection Control

  1. Alberto M. Segre2
  1. 1Departments of Internal Medicine and Epidemiology
  2. 2Department of Computer Science, University of Iowa, Iowa City
  1. Correspondence: P. M. Polgreen, Carver College of Medicine, Department of Internal Medicine, University of Iowa, Iowa City, Iowa 52242 (philip-polgreen{at}uiowa.edu).

Key words

(See the Major Article by Ray et al on pages 889–93.)

Residents of long-term care facilities are at high risk for acquiring multidrug-resistant organisms [15]. These individuals are often admitted to acute-care hospitals, promoting the propagation of multidrug-resistant (and other) infections to other patients. Thus, hospital transfers represent an important potential point of intervention, where informed decisions can be made to control the spread of multidrug-resistant organisms, if only one could sufficiently understand the complex interactions that enable the spread of infections. Ray et al's article “Spread of Carbapenem-Resistant Enterobacteriaceae Among Illinois Healthcare Facilities: The Role of Patient Sharing” in the current issue of Clinical Infectious Diseases uses a model constructed from healthcare data to help elucidate the relationship between multidrug-resistant organisms and the sharing of patients between long-term care facilities and acute-care hospitals [6].

Scientists and engineers use models to understand the behavior of complex systems in many fields. Obviously, any resulting model-based predictions are only as good as their underlying models are faithful to reality; in general, finer-grained models support more refined predictions. In epidemiology, relatively coarse epidemiological models based on random mixing (ie, the assumption that every member of the population is at similar risk) have long been used to predict how infections spread across large populations [7]. In reality, interactions between healthcare workers are not uniformly random [8], individual healthcare workers come into contact with diverse sets of patients [911], and some hospitals are much more likely to transfer patients to or from other hospitals …

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