Regional Healthcare Ecosystem Analyst (RHEA) Modeling the Environment (MODE): SARS-CoV-2

项目摘要

PROJECT SUMMARY ABSTRACT With the ongoing COVID-19 coronavirus pandemic, the potential environmental transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of significant concern, especially in hospitals. Choosing and coordinating the right approaches (e.g., environmental cleaning and monitoring, airflow regulation) in the complex hospital environment can be challenging, given frequent patient and staff turnover, limited resources, and the potential rapid spread of SARS-CoV-2. Further, developing new approaches requires guidance for design and implementation. Computational modeling with economic, operational, and epidemiologic components can assess the value of approaches with various features and efficacies to guide design and implementation in complex systems. Our Regional Healthcare Ecosystem Analyst (RHEA) Modeling the Environment (RHEA-MODE) project already will be developing agent-based models (ABMs) to help better understand and prevent the environmental transmission of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE), two pathogens that commonly cause healthcare-associated infections (HAIs). This offers a key opportunity to ask and answer similar questions about SARS-CoV-2. Therefore, the goal of this proposed RHEA-MODE: SARS-CoV-2 supplemental project is to develop ABMs of hospitals to help better understand the role of the hospital environment and environmental cleaning and monitoring methods in preventing and controlling the spread of SARS-CoV-2. While there may be some similarities with MRSA and VRE, the characteristics (e.g., contact, air transmission) and consequences (e.g., various COVID-19 outcomes) of SARS-CoV-2 are different, requiring different representations in the ABMs. The virus also requires different interventions (e.g., N95 mask use) and potentially different environmental cleaning (e.g., more aggressive standard disinfectant use, new procedures like ultraviolet light irradiation, air filtering) and monitoring (e.g., checking compliance with cleaning protocols and for the presence of virus in the air and on surfaces). Our team is led by Bruce Y. Lee, MD MBA, who has been part of the Models of Infectious Disease Agent Study (MIDAS) network for over 12 years and has over two decades of experience in industry and academia leading large mathematical and computational modeling projects to better understand, prevent, and control infectious diseases, including being embedded in the U.S. Department of Health Human Services during the H1N1 flu pandemic to assist the national response. Specific Aim 1 for this project will develop detailed computational representations of sample hospitals and their environments and determine the role of the hospital environment in the transmission of SARS-CoV-2 under various conditions and circumstances. Specific Aim 2 will explore how various environmental cleaning and monitoring products, methods, approaches, and strategies can reduce SARS-CoV-2 transmission, spread, and associated health and economic outcomes based upon the simulation models from Aim 1.