Regular as clockwork, the flu arrives every year. And, according to the national Centers for Disease Control and Prevention, 5 to 20 percent of the
In a report to be published in the peer-reviewed journal PLoS Computational Biology and currently available online, Sally Blower, a professor at the Semel Institute for Neuroscience and Human Behavior at UCLA, and Romulus Breban and Raffaele Vardavas, postdoctoral fellows in Blowers research group, used novel mathematical modeling techniques to predict that current health policy based on voluntary vaccinations is not adequate to control severe flu epidemics and pandemics unless vaccination programs offer incentives to individuals.
According to the researchers, the severity of such a health crisis could be reduced if programs were to provide several years of free vaccinations to individuals who pay for only one year. Interestingly, however, some incentive programs could have the opposite effect. Providing free vaccinations for entire families, for example, could actually increase the frequency of severe epidemics. This is because when the head of the household makes a choice flu shots or no flu shots on behalf of all the other household members, there is no individual decision-making, and adaptability is decreased.
While other models have determined what proportion of the population would need to be vaccinated in order to prevent a pandemic, none of these models have shown whether this critical coverage can actually be reached. What has been missing, according to Blower, a mathematical and evolutionary biologist, is the human factor.
The human factor involves two biological characteristics, memory and how adaptable people can be, Blower said. These characteristics drive human behavior.
Blower and her group used peoples attitudes toward the seasonal flu to construct their model. With seasonal flu, protective immunity a flu shot lasts only one year. Thus, individuals must decide each year whether or not to participate in a vaccination program.
The model Blowers team developed is inspired by game theory, used in economics to predict how non-communicating, selfish individuals reach a collective behavior with respect to a common dilemma by adapting to what they think are other peoples decisions. The group modeled each individuals strategy for making yearly vaccination decisions as an adaptive process of trial and error. They tracked both individual-level decisions and population-level variables that is, the yearly vaccine coverage level and influenza prevalence, where prevalence is defined as the proportion of the population that is infected. The individual-level model was based on the human biological attributes of memory and adaptability.
We assume that the decision of each individual is based upon self-interest, that people wish to avoid coming down with the flu, preferably without having to vaccinate, said Breban.
It is the adaptive decision-making by the individual, the researchers say, that may be an important and previously overlooked causal factor in driving influenza epidemiology.
Including cognitive and personality factors into epidemic models can dramatically change our understanding of why flu epidemics occur. said Vardavas.
The research was supported by a National Institutes of Health grant. Blowers lab uses mathematical modeling as a health policy tool to design epidemic control strategies for a variety of infectious diseases. The focus of her research is to develop the study of infectious diseases into a predictive science.
The Semel Institute for Neuroscience and Human Behavior is an interdisciplinary research and education institute devoted to the understanding of complex human behavior, including the genetic, biological, behavioral and sociocultural underpinnings of normal behavior and the causes and consequences of neuropsychiatric disorders. In addition to conducting fundamental research, the institute faculty seeks to develop effective treatments for neurological and psychiatric disorders, to improve access to mental health services, and to shape national health policy regarding neuropsychiatric disorders.