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Abstract #162632

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David M. Abramson, PhD MPH¹, Daniel Bienstock, PhD², Stephen S. Morse, PhD¹, Andrew Garrett, MD MPH¹, Gregory A. Thomas, MS³, Elizabeth Fuller, MPH¹, and Lisa Soloff³. (1) National Center for Disaster Preparedness, Columbia University, 722 West 168th Street, Room 1014-E, New York, NY 10032, 212-305-1929, dma3@columbia.edu, (2) Operations Research, School of Engineering, Columbia University, 342 Mudd Building, Columbia University, New York, NY 10025, (3) National Center for Disaster Preparedness, Mailman School of Public Health, Columbia University, 722 West 168th Street, 10th Floor, New York, NY 10032

Public health interventions to address a potential pandemic flu – whether pharmaceutical or non-pharmaceutical – may be regarded as a predictable first-order response. The operational success of contingency plans for the containment and treatment of pandemic flu may be tracked by measurable process outcomes (e.g., numbers of individuals or health care workers vaccinated, numbers of intensive care beds opened up) as well as health outcomes (e.g., flu-related morbidity and mortality, transmission rates, and attack rates). Less well-known or researched is the “second order response,” the social consequences of the first-order interventions. This could include health outcomes such as excess morbidity and mortality from untreated or under-treated illness and injury distinct from influenza, and social outcomes related to such issues as increased crowding, health system congestion, increasing scarcity of resources (including monetary resources), major population shifts, and degradation of various workforces (health care, urban infrastructure such as police and sanitation, critical infrastructure,etc.) with their consequent effects. This presentation will review available evidence and theoretical frameworks, as well as preliminary computer modeling using stochastic and robust optimization designs, to consider these “unanticipated consequences.” In particular, we will focus upon the following major themes: (1) Critical infrastructure loss; (2) Consequences of specific transportation shutdowns; (3) Consequences of school closures; (4) Social behavior related to elements of a pandemic, including historical evidence, survey research on population attitudes and anticipated behavior, and workforce-related issues; and (5) Health and social consequences of crowding and health system congestion, directly or indirectly associated with pandemic flu and first-order responses.

Learning Objectives:

• Identify health and social consequences of non-pharmaceutical public health interventions to contain pandemic flu.
• Apply theoretical framework and historical data to computer modeling of pandemic flu consequences, using both stochastic and robust optimization designs.

Keywords: Infectious Diseases, Public Health Research

Presenting author's disclosure statement:

Any relevant financial relationships? No
Any institutionally-contracted trials related to this submission?

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.

• Audio (mp3) recording
• Slides (pdf) or Handout
• Multimedia recording