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Article Excerpt
I. Introduction
This paper describes an economic model for analyzing an individual's decision about whether or not to be vaccinated against influenza. It shows that based upon objective parameters, the vaccination rate should be high. Yet, this result is not consistent with empirical findings of low vaccination rates, for example for anti-influenza shots (MIV study group, 2005). Therefore, the second part of the paper uses the behavioral approach and subjective variables, such as perceived infection probability, time preference, subjective costs of vaccination, perceived vaccination effectiveness, and perceived severity of illness, to explain the empirical findings.
Previous economic studies that dealt with an individual's decision concerning preferred preventive behaviors (e.g., Brito et al., 1991, Francis, 1997) did not take into account subjective variables known to influence an individual's decision. For example, individuals might use the subjective probability of being infected rather than population-based epidemiological data (Mehrez and Gafni, 1987, Auld, 2003, Karni, 2003, Mullahy, 1999). Moreover, the Health Belief Model (HBM) (Rosenstock, 1988) can provide insight into why people participate in programs that prevent illness or detect disease. The HBM posits that behavior is a function of an individual's beliefs about the subjective value of an outcome and the subjective expectation that a particular behavior will achieve that outcome. Blue and Valley (2002), who employ the HBM, found that individuals who were vaccinated against influenza believed more strongly that they were susceptible to influenza and that influenza is a serious illness than did those who chose not to be vaccinated. In addition, Chapman and Coups (1999) provide some evidence that individuals' time preference patterns can explain preventive health behavior; in particular, monetary time preferences were found to predict whether people took flu shots. Since individuals' short-term discount rates are typically higher than market or social rates (West et al., 2003), the present value of the benefit from vaccination to those individuals is lower than to society.
Our paper integrates the above mentioned behavioral effects as well as known psychological biases into a theoretical economic model to explain an individual's decision regarding flu-shot vaccination as an example of preventive behavior. Because low vaccination rates have a negative externality on society, it is important to identify the decision-making process of the individual.
Our model refers to the demand side of the flu-shot, yet the supply side might also have an impact on vaccination rates. While a shortage of vaccine in certain years has reduced vaccination rates, we still observe low vaccination levels over a long period, even in years with no shortages. For example, according to the MIV study group (2005), data for the period 1997-2003 show consistently low vaccination rates, although improving over time, in developed as well as undeveloped countries. In 2002, for example, there was no shortage of flu vaccines, at least in the US (Harper et al., 2004). Yet, vaccination levels for that year (doses distributed/1000 population) in the US were 289, in Canada 328, in Japan 160 and in Germany 181, while other developed and undeveloped countries exhibited even lower vaccination levels (MIV study group, 2005).
The paper is organized as follows. Section II describes the vaccination decision model based on objective parameters. Section III uses the behavioral economic model and subjective evaluation parameters to explain empirical findings regarding vaccination. Section IV describes the policy implications, and Section V presents conclusions.
II. The Vaccination Decision-Making Model
In describing the economic model regarding an individual's decision whether or not to be vaccinated against a particular disease, we assume the use of "objective variables." We describe the case of an infectious disease such as the flu, which breaks out each year during period 1 and has an epidemiological (i.e., population-based) infection probability denoted by P. A vaccine against this disease is available to the public...
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