(e.g., hair loss following receipt of hepatitis B vaccine) or a change in the rate of reporting of previously known adverse events associated with vaccines (e.g., decreased numbers of reports of both serious and less serious events after receipt of the acellular pertussis vaccine versus receipt of the whole-cell vaccine. Confusing peaks in the reporting of adverse events can also stem from recent publicity about an adverse event associated with a vaccine. It is difficult to ascertain whether these peaks in adverse event reports are due to a true increase in adverse events related to the vaccine or result only from increased awareness of a potential problem. Spurious peaks in VAERS reports may also occur from changes in the background rate of adverse events. A recent study has shown, for instance, that an increase in VAERS reports of Guillain-Barré syndrome (GBS) during the 1993–1994 influenza vaccination season was due largely to an increase in the rate of GBS in the general population (Lasky, 1997).

Large Linked Databases6

To improve detection of adverse events associated with vaccination and to conduct more active surveillance studies to assess the causality of adverse events, CDC established LLDB in 1990. This database is a CDC-coordinated linkage of large databases of four large health maintenance organizations. Comprising automated data from more than 500,000 children (ages 0 to 6 years) in Oregon, Washington, and California, LLDB enables researchers to link vaccine exposures to medical outcomes and thereby to estimate the rates of occurrence of adverse events following vaccination as well as the background incidence. An elevated rate following vaccination, in comparison with the rate at other times, would suggest a possible causal relation to vaccination. Over the next 5 years, LLDB will also be expanded to include adolescents and adults. Unlike VAERS, LLDB contains all of the information necessary for epidemiologic studies of vaccine adverse effects (vaccination exposures, outcomes among vaccinated and unvaccinated person times, and potential confounders).

The large size of LLDB improves the ability to detect rare adverse events, and extensive quality control of the clinical and immunization data in the system increases its reliability. LLDB also allows for the study of confounding variables and for the exploration of groups at risk for adverse events following vaccination.


 The material in this section is adapted from a presentation by Robert Davis.

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