Modeling Infectious Diseases in Healthcare Network (MInD-Healthcare) Framework for Describing and Reporting Multidrug-resistant Organism and Healthcare-Associated Infections Agent-based Modeling Methods. (10th March 2020)

• Record Type: Journal Article
• Authors: Slayton, Rachel B; O'Hagan, Justin J; Barnes, Sean; Rhea, Sarah; Hilscher, Rainer; Rubin, Michael; Lofgren, Eric; Singh, Brajendra; Segre, Alberto; Paul, Prabasaj
• Is Part Of: Clinical infectious diseases. Volume 71:Number 9(2020)
• Page Start: 2527
• Page End: 2532
• Publication Date: 2020-03-10
• Subjects: healthcare-associated infections -- mathematical modeling -- antimicrobial resistance; Communicable diseases -- Periodicals; 616.905
• DOI: 10.1093/cid/ciaa234
• Languages: English
• ISSNs: 1058-4838

Abstract

Abstract: Mathematical modeling of healthcare-associated infections and multidrug-resistant organisms improves our understanding of pathogen transmission dynamics and provides a framework for evaluating prevention strategies. One way of improving the communication among modelers is by providing a standardized way of describing and reporting models, thereby instilling confidence in the reproducibility and generalizability of such models. We updated the Overview, Design concepts, and Details protocol developed by Grimm et al [11 ] for describing agent-based models (ABMs) to better align with elements commonly included in healthcare-related ABMs. The Modeling Infectious Diseases in Healthcare Network (MInD-Healthcare) framework includes the following 9 key elements: (1) Purpose and scope; (2) Entities, state variables, and scales; (3) Initialization; (4) Process overview and scheduling; (5) Input data; (6) Agent interactions and organism transmission; (7) Stochasticity; (8) Submodels; and (9) Model verification, calibration, and validation. Our objective is that this framework will improve the quality of evidence generated utilizing these models. Abstract : The MInD-Healthcare Framework was developed as a set of best practices for conducting and reporting transmission modeling studies, in particular those utilizing ABMs.