Ying-Chun Li1, Edward C Norton, William H Dow. 1. Department of Health Policy and Management, School of Public Health, Harvard University, Cambridge MA 02138, USA.
Abstract
OBJECTIVE: To test the hypothesis that individuals are more likely to receive a vaccination against influenza or pneumonia as the perceived disease threat increases. DATA SOURCES: This study uses two different national datasets. Individual-level information about the vaccination rates of 38,768 elderly persons are from the Behavioral Risk Factor Surveillance System, 1993-1998. Information on the combined influenza and pneumonia state mortality rates are measured from the Compressed Mortality File. STUDY DESIGN: Using both cross-sectional and state fixed-effects panel data estimators, we model an individual's probability of having an influenza or pneumococcal vaccination as a function of the lagged state mortality rate. Multiyear lags are specified in order to estimate the duration of the effect of disease mortality on individual vaccination behavior. PRINCIPAL FINDINGS: Results support our hypothesis that influenza vaccination behavior responds positively to disease mortality, even after a one-year lag. We further find that cross-sectional estimators used in previous work yield downward-biased estimates, although even for our preferred panel data models, the estimated effects are small. CONCLUSIONS: The findings indicate that behavioral demand responses can help to limit infectious disease epidemics, and suggest further research on how public awareness campaigns can mediate this disease threat responsiveness behavior.
OBJECTIVE: To test the hypothesis that individuals are more likely to receive a vaccination against influenza or pneumonia as the perceived disease threat increases. DATA SOURCES: This study uses two different national datasets. Individual-level information about the vaccination rates of 38,768 elderly persons are from the Behavioral Risk Factor Surveillance System, 1993-1998. Information on the combined influenza and pneumonia state mortality rates are measured from the Compressed Mortality File. STUDY DESIGN: Using both cross-sectional and state fixed-effects panel data estimators, we model an individual's probability of having an influenza or pneumococcal vaccination as a function of the lagged state mortality rate. Multiyear lags are specified in order to estimate the duration of the effect of disease mortality on individual vaccination behavior. PRINCIPAL FINDINGS: Results support our hypothesis that influenza vaccination behavior responds positively to disease mortality, even after a one-year lag. We further find that cross-sectional estimators used in previous work yield downward-biased estimates, although even for our preferred panel data models, the estimated effects are small. CONCLUSIONS: The findings indicate that behavioral demand responses can help to limit infectious disease epidemics, and suggest further research on how public awareness campaigns can mediate this disease threat responsiveness behavior.
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