tetano
Editor, Senior Moderator
Vaccine. 2014 May 17. pii: S0264-410X(14)00699-9. doi: 10.1016/j.vaccine.2014.05.032. [Epub ahead of print]
Monitoring receipt of seasonal influenza vaccines with BRFSS and NHIS data: Challenges and solutions.
Burger AE1, Reither EN2.
Author information
Abstract
Despite the availability of vaccines that mitigate the health risks associated with seasonal influenza, most individuals in the U.S. remain unvaccinated. Monitoring vaccination uptake for seasonal influenza, especially among disadvantaged or high-risk groups, is therefore an important public health activity. The Behavioral Risk Factor Surveillance System (BRFSS) - the largest telephone-based health surveillance system in the world - is an important resource in monitoring population health trends, including influenza vaccination. However, due to limitations in the question that measures influenza vaccination status, difficulties arise in estimating seasonal vaccination rates. Although researchers have proposed various methodologies to address this issue, no systematic review of these methodologies exists. By subjecting these methods to tests of sensitivity and specificity, we identify their strengths and weaknesses and advance a new method for estimating national and state-level vaccination rates with Behavioral Risk Factor Surveillance (BRFSS) data. To ensure that our findings are not anomalous to the BRFSS, we also analyze data from the National Health Interview Survey (NHIS). For both studies, we find that restricting the sample to interviews conducted between January and September offers the best balance of sensitivity (>90% on average), specificity (>90% on average), and statistical power (retention of 92.3% of vaccinations from the target flu season) over other proposed methods. We conclude that including survey participants from these months will provide the best estimates of seasonal influenza vaccination rates with BRFSS and NHIS data, and we discuss potential ways to better estimate vaccination rates in future epidemiologic surveys.
Copyright ? 2014. Published by Elsevier Ltd.
KEYWORDS:
Flu seasons, Health disparities, Influenza, Methodology, Vaccination
PMID:
24844152
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/24844152
Monitoring receipt of seasonal influenza vaccines with BRFSS and NHIS data: Challenges and solutions.
Burger AE1, Reither EN2.
Author information
Abstract
Despite the availability of vaccines that mitigate the health risks associated with seasonal influenza, most individuals in the U.S. remain unvaccinated. Monitoring vaccination uptake for seasonal influenza, especially among disadvantaged or high-risk groups, is therefore an important public health activity. The Behavioral Risk Factor Surveillance System (BRFSS) - the largest telephone-based health surveillance system in the world - is an important resource in monitoring population health trends, including influenza vaccination. However, due to limitations in the question that measures influenza vaccination status, difficulties arise in estimating seasonal vaccination rates. Although researchers have proposed various methodologies to address this issue, no systematic review of these methodologies exists. By subjecting these methods to tests of sensitivity and specificity, we identify their strengths and weaknesses and advance a new method for estimating national and state-level vaccination rates with Behavioral Risk Factor Surveillance (BRFSS) data. To ensure that our findings are not anomalous to the BRFSS, we also analyze data from the National Health Interview Survey (NHIS). For both studies, we find that restricting the sample to interviews conducted between January and September offers the best balance of sensitivity (>90% on average), specificity (>90% on average), and statistical power (retention of 92.3% of vaccinations from the target flu season) over other proposed methods. We conclude that including survey participants from these months will provide the best estimates of seasonal influenza vaccination rates with BRFSS and NHIS data, and we discuss potential ways to better estimate vaccination rates in future epidemiologic surveys.
Copyright ? 2014. Published by Elsevier Ltd.
KEYWORDS:
Flu seasons, Health disparities, Influenza, Methodology, Vaccination
PMID:
24844152
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/24844152