Online Program

Evaluating Ebola Response Alternatives in the VA Healthcare System using a Computational Epidemiological Control Model

Tuesday, November 3, 2015 : 9:10 a.m. - 9:30 a.m.

Patrick Finley, Sandia National Laboratories, Albuquerque, NM
Walt Beyeler, Sandia National Laboratories, Albuquerque, NM
Michael Mitchell, Sandia National Laboratories, Albuquerque NM
Richard Kaslow, MD, Office of Public Health (10P3), US Department of Veterans Affairs, Washington, DC
Richard Martinello, MD, Public Health, VACHS, Washington, DC
Victoria Davey, PhD, MPH, RN, Office of Research and Development, US Department of Veterans Affairs, Washington, DC
Managing Ebola virus-infected patients presents major challenges to US hospitals. Strict isolation protocols are required to prevent spread of Ebola virus disease (EVD) to health care personnel (HCP), other patients and the community. Implementing these protocols requires rapid reallocation of scarce resources including facility space, HCP, personal protective equipment (PPE), and laboratory capacity while placing new burdens on hospital administrative and medical leadership. A systems-level analysis of EVD patient management processes can help decision makers develop contingency plans for managing EVD patients within hospital networks by anticipating resource constraints, coordination challenges, and critical dependencies on other systems.

We have designed a computational model as a tool to analyze the potential impact of managing EVD patients at VA hospitals. The agent-based model applies well-established epidemiological principles within an innovative model construct. The model calculates potential EVD containment probabilities for alternative response strategies reflecting various staffing and resource provision levels, uncertainties regarding PPE effectiveness, HCP capabilities, and pathogen infectivity. The model enables measurement of risk tradeoffs associated with alternative protocols, such as implementing pre-emergency-department (ED) triage. The model can track co-occurring pathogens, thereby allowing evaluation of response to surges in patients seeking care for, e.g., seasonal influenza during an EVD incident.

Model performance was evaluated for a tiered treatment protocol for EVD patients. Tier 1 facilities provide an EVD patient with full isolation and definitive care. Tier 2 facilities maintain isolation until the patient can be transferred to a Tier 1 bed.  Tier 3 facilities provide brief triage and isolation for rare cases. Differential effects of management alternatives were evaluated using metrics including deaths from EVD, number of patients and HCP infected, and illness from concurrent influenza. We found that a pre-ED triage system would reduce EVD cases by preventing transmission in the ED. This system would also expedite admission of EVD patients to isolation, reducing opportunity for transmission.  Presentation of EVD patients during an influenza outbreak increases the prospective number of EVD cases since projected ED crowding leads to additional person-person contacts and delays in diagnosis. This generates additional opportunities to spread EVD to HCP and throughout the community. This agent based model can be used to guide policy and processes to mitigate risk of EVD transmission in a healthcare system.

Learning Areas:

Administration, management, leadership
Other professions or practice related to public health
Protection of the public in relation to communicable diseases including prevention or control
Systems thinking models (conceptual and theoretical models), applications related to public health

Learning Objectives:
Identify benefits of pre-hospital screening in managing the spread of EVD. Discuss challenges of managing EVD treatment and disease spread during an influenza outbreak. Evaluate tradeoffs involved in organizing care for Ebola patients Explain benefits of computational modeling for management of EVD treatment and prevention.

Keyword(s): Epidemiology, Public Health Policy

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I serve as technical lead for public health modeling at Sandia National Laboratories. My organization models complex public health and healthcare processes such as disease spread, practice translation, medical logistics, treatment efficacy, healthcare management to support policy makers. I have decades of experience in this field and am considered an authority in the public health modeling community.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.