Publication:
Responding to Vaccine Safety Signals during Pandemic Influenza: A Modeling Study

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2014

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Public Library of Science
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Maro, Judith C., Dennis G. Fryback, Tracy A. Lieu, Grace M. Lee, and David B. Martin. 2014. “Responding to Vaccine Safety Signals during Pandemic Influenza: A Modeling Study.” PLoS ONE 9 (12): e115553. doi:10.1371/journal.pone.0115553. http://dx.doi.org/10.1371/journal.pone.0115553.

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Abstract

Background: Managing emerging vaccine safety signals during an influenza pandemic is challenging. Federal regulators must balance vaccine risks against benefits while maintaining public confidence in the public health system. Methods: We developed a multi-criteria decision analysis model to explore regulatory decision-making in the context of emerging vaccine safety signals during a pandemic. We simulated vaccine safety surveillance system capabilities and used an age-structured compartmental model to develop potential pandemic scenarios. We used an expert-derived multi-attribute utility function to evaluate potential regulatory responses by combining four outcome measures into a single measure of interest: 1) expected vaccination benefit from averted influenza; 2) expected vaccination risk from vaccine-associated febrile seizures; 3) expected vaccination risk from vaccine-associated Guillain-Barre Syndrome; and 4) expected change in vaccine-seeking behavior in future influenza seasons. Results: Over multiple scenarios, risk communication, with or without suspension of vaccination of high-risk persons, were the consistently preferred regulatory responses over no action or general suspension when safety signals were detected during a pandemic influenza. On average, the expert panel valued near-term vaccine-related outcomes relative to long-term projected outcomes by 3∶1. However, when decision-makers had minimal ability to influence near-term outcomes, the response was selected primarily by projected impacts on future vaccine-seeking behavior. Conclusions: The selected regulatory response depends on how quickly a vaccine safety signal is identified relative to the peak of the pandemic and the initiation of vaccination. Our analysis suggested two areas for future investment: efforts to improve the size and timeliness of the surveillance system and behavioral research to understand changes in vaccine-seeking behavior.

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Biology and Life Sciences, Computational Biology, Population Modeling, Infectious Disease Modeling, Immunology, Vaccination and Immunization, Vaccines, Plant Science, Plant Pathology, Disease Surveillance, Infectious Disease Surveillance, Infectious Disease Epidemiology, Engineering and Technology, Management Engineering, Decision Analysis, Medicine and Health Sciences, Epidemiology, Health Care, Health Care Policy, Infectious Diseases, Viral Diseases, Influenza, Infectious Disease Control, Pharmaceutics, Therapeutic Drug Monitoring, Public and Occupational Health, Preventive Medicine

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