Abstract | BACKGROUND: There currently are no population-based systems in the United States to rapidly detect adverse events after newly introduced vaccines. To evaluate the feasibility of developing such systems, we used 5 years of data from 4 health maintenance organizations within the Centers for Disease Control and Prevention (CDC) Vaccine Safety Datalink. METHODS: Within every year, each week's vaccinated children were followed for 4 weeks, and rates of adverse events were compared with rates among children of similar ages before the introduction of the new vaccine. We assessed risks for intussusception after rotavirus vaccination and risks for fever, seizures, and other neurologic adverse events after the change from whole cell diphtheria- tetanus- pertussis (DTPw) to acellular DTP vaccine ( DTPa). We used sequential probability ratio testing, adjusted for age, sex, calendar time, season, and HMO, and with a stopping value based on the probability of an adverse event under the null hypothesis and under a preset alternative hypothesis. RESULTS: CONCLUSIONS: We conclude that it is feasible to develop systems for rapid and routine population-based assessments of new vaccine safety.
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Authors | Robert L Davis, Margarette Kolczak, Edwin Lewis, James Nordin, Michael Goodman, David K Shay, Richard Platt, Steven Black, Henry Shinefield, Robert T Chen |
Journal | Epidemiology (Cambridge, Mass.)
(Epidemiology)
Vol. 16
Issue 3
Pg. 336-41
(May 2005)
ISSN: 1044-3983 [Print] United States |
PMID | 15824549
(Publication Type: Journal Article, Research Support, U.S. Gov't, P.H.S.)
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Chemical References |
- Diphtheria-Tetanus-Pertussis Vaccine
- Rotavirus Vaccines
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Topics |
- Databases, Factual
- Diphtheria-Tetanus-Pertussis Vaccine
(adverse effects)
- Fever
(chemically induced, epidemiology)
- Health Maintenance Organizations
(statistics & numerical data)
- Humans
- Infant
- Intussusception
(chemically induced, epidemiology)
- Product Surveillance, Postmarketing
(methods)
- Rotavirus Vaccines
(adverse effects)
- Seasons
- United States
(epidemiology)
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