Background: Health care–associated infections (HAIs) are a global health burden because of their significant impact on patient health and health care systems. Mechanistic simulation modeling that captures the dynamics between patients, pathogens, and the environment is increasingly being used to improve understanding of epidemiological patterns of HAIs and to facilitate decisions on infection prevention and control (IPC). The purpose of this review is to present a systematic review to establish (1) how simulation models have been used to investigate HAIs and their mitigation and (2) how these models have evolved over time, as well as identify (3) gaps in their adoption and (4) useful directions for their future development. Methods: The review involved a systematic search and identification of studies using system dynamics, discrete event simulation, and agent-based model to study HAIs. Results: The complexity of simulation models developed for HAIs significantly increased but heavily concentrated on transmission dynamics of methicillin-resistant Staphylococcus aureus in the hospitals of high-income countries. Neither HAIs in other health care settings, the influence of contact networks within a health care facility, nor patient sharing and referring networks across health care settings were sufficiently understood. Conclusions: This systematic review provides a broader overview of existing simulation models in HAIs to identify the gaps and to direct and facilitate further development of appropriate models in this emerging field.
Nguyen, L. K. N., Megiddo, I., & Howick, S. (2019). Simulation models for transmission of health care–associated infection: A systematic review. American Journal of Infection Control. Mosby Inc. https://doi.org/10.1016/j.ajic.2019.11.005