Estimating the Unanticipated Consequences of Pandemic Flu

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.