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Background: Seasonal influenza vaccination is an important behavior with significant individual and public health consequences, yet fewer than half of individuals in the USA are vaccinated annually. To promote vaccination adherence, it is important to understand the factors that affect vaccination behavior., Purpose: In this research, we focused on one such factor, an individual's vaccination history. We gathered longitudinal data to track and understand the relationship between an individual's vaccination history and their current behaviors., Methods: U.S. adults completed multiple surveys over an 8 year period, which asked about whether they had received the influenza vaccination during the previous flu season. We analyzed the data to determine the strength of the relationship between vaccination decisions across single-year and multiyear intervals. Additionally, we fitted two mathematical models to the data to determine whether individuals were better characterized as having a stable propensity to vaccinate or a stable propensity to repeat their previous decisions., Results: Individuals exhibited highly consistent behavior across adjacent years, yet, across the complete extent of the longitudinal study, they were far more likely to repeat the earlier decision to vaccinate. Surprisingly, the results of the mathematical model suggest that individuals are better characterized as having a stable propensity to repeat their previous decisions rather than a stable propensity to vaccinate per se. Although most individuals had an extremely strong tendency to repeat the previous decision, some had a far weaker propensity to do so., Conclusions: This suggests that interventions intended to increase vaccination uptake might be most impactful for those individuals with only a weak tendency to vaccinate or not to vaccinate., (© Society of Behavioral Medicine 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Influenza vaccination decisions may be influenced by perceived risk reduction related to herd immunity., Purpose: This paper examines how free-riding (i.e., foregoing vaccination because of reduced risk perceptions related to herd immunity) or protective benefits to the community affect vaccination decisions., Methods: A survey of a nationally representative panel of U.S. adults (N=442 respondents; data collected and analyzed during 2012) asked about how respondents made vaccination decisions, including whether and how vaccination among the members of respondents' social networks influenced their own vaccination decisions., Results: Most individuals (61%) reported that vaccination in the social network would not influence their decision. Among those perceiving being influenced by vaccination in their social network, most stated that an increase in network vaccination coverage would make them more likely to get vaccinated, rather than less. Overall, only 6% (28 of 442) gave a response consistent with the reduced-risk logic of herd immunity, which was more common among those stating that they would be less likely to get vaccinated (emphasizing free-riding) than among those more likely to get vaccinated (emphasizing social protection; 33% vs 11%, two-sided, p=0.0005). The reduced-risk logic of herd immunity, and more specifically free-riding, is consciously considered by relatively few individuals. Far more common are social influences bolstering personal vaccination, such as peer pressure and social learning (6% vs 11%, two-sided, p=0.015)., Conclusions: Interventionists may be more successful by capitalizing on existing social-influence considerations than by trying to combat the conscious lure of free-riding., (Copyright © 2013 American Journal of Preventive Medicine.)

The COVID-19 pandemic required significant public health interventions from local governments. Although nonpharmaceutical interventions often were implemented as decision rules, few studies evaluated the robustness of those reopening plans under a wide range of uncertainties. This paper uses the Robust Decision Making approach to stress-test 78 alternative reopening strategies, using California as an example. This study uniquely considers a wide range of uncertainties and demonstrates that seemingly sensible reopening plans can lead to both unnecessary COVID-19 deaths and days of interventions. We find that plans using fixed COVID-19 case thresholds might be less effective than strategies with time-varying reopening thresholds. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower. The approach used in this paper could also prove useful for other public health policy problems in which policymakers need to make robust decisions in the face of deep uncertainty. [ABSTRACT FROM AUTHOR]

Previous modeling studies have identified the vaccination coverage level necessary for preventing influenza epidemics, but have not shown whether this critical coverage can be reached. Here we use computational modeling to determine, for the first time, whether the critical coverage for influenza can be achieved by voluntary vaccination. We construct a novel individual-level model of human cognition and behavior; individuals are characterized by two biological attributes (memory and adaptability) that they use when making vaccination decisions. We couple this model with a population-level model of influenza that includes vaccination dynamics. The coupled models allow individual-level decisions to influence influenza epidemiology and, conversely, influenza epidemiology to influence individual-level decisions. By including the effects of adaptive decision-making within an epidemic model, we can reproduce two essential characteristics of influenza epidemiology: annual variation in epidemic severity and sporadic occurrence of severe epidemics. We suggest that individual-level adaptive decision-making may be an important (previously overlooked) causal factor in driving influenza epidemiology. We find that severe epidemics cannot be prevented unless vaccination programs offer incentives. Frequency of severe epidemics could be reduced if programs provide, as an incentive to be vaccinated, several years of free vaccines to individuals who pay for one year of vaccination. Magnitude of epidemic amelioration will be determined by the number of years of free vaccination, an individuals' adaptability in decision-making, and their memory. This type of incentive program could control epidemics if individuals are very adaptable and have long-term memories. However, incentive-based programs that provide free vaccination for families could increase the frequency of severe epidemics. We conclude that incentive-based vaccination programs are necessary to control influenza, but some may be detrimental. Surprisingly, we find that individuals' memories and flexibility in adaptive decision-making can be extremely important factors in determining the success of influenza vaccination programs. Finally, we discuss the implication of our results for controlling pandemics. [ABSTRACT FROM AUTHOR]

The Affordable Care Act changed the regulations governing small firms' health insurance premiums. However, small businesses can avoid many of the new regulations by self-insuring or maintaining grandfathered plans. If small firms with healthy and lower-cost enrollees avoid the regulations, premiums for coverage sold through insurance exchanges could be unaffordable. In this analysis we used the RAND Comprehensive Assessment of Reform Efforts microsimulation model to predict the effects of self-insurance and grandfathering exemptions on coverage and premiums available through the exchanges. We estimate that Affordable Care Act regulations restricting employers' ability to offer grandfathered plans will result in lower premiums on plans available through the exchanges and will have small negative effects on enrollment in the exchanges. Our results suggest that these regulations are essential to keeping premiums on the Small Business Health Options Program (SHOP) exchanges affordable. Our analysis also found that Affordable Care Act regulations limiting self-insurance will reduce enrollment in the exchanges somewhat, without substantially affecting exchange premiums. [ABSTRACT FROM AUTHOR]