Can Influenza Epidemics Be Prevented by Voluntary Vaccination?

Abstract

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. Currently, a major public health concern is the next influenza pandemic; yet it remains unclear how to control such a crisis. By using novel mathematical modeling techniques, here we predict the likely impact of voluntary vaccination programs on controlling influenza epidemics and pandemics. We construct an individual-level model of human cognition and behavior that includes two important biological characteristics: memory and adaptability/flexibility. In each influenza season, each individual in the modeled population decides, using memory and adaptability/flexibility, whether to be vaccinated or not. We combine our individual-level model with an epidemic model to predict the impact of voluntary vaccination programs. We found that severe influenza 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. However, we found that a public health intervention program that focuses on vaccinating families is likely to increase the frequency of severe epidemics. Most importantly, we found that individuals' memories and adaptability/flexibility in decision-making are critical factors in determining the success of influenza vaccination programs. Our results are applicable both for the control of seasonal and pandemic influenza.