Dataset Information

Vaccination rates among the general adult population and high-risk groups in the United States.

ABSTRACT: BACKGROUND: In order to adequately assess the effectiveness of vaccination in helping to control vaccine-preventable infectious disease, it is important to identify the adherence and uptake of risk-based recommendations. METHODS: The current project includes data from five consecutive datasets of the National Health and Wellness Survey (NHWS): 2007 through 2011. The NHWS is an annual, Internet-based health questionnaire, administered to a nationwide sample of adults (aged 18 or older) which included items on vaccination history as well as high-risk group status. Vaccination rates and characteristics of vaccinees were reported descriptively. Logistic regressions were conducted to predict vaccination behavior from sociodemographics and risk-related variables. RESULTS: The influenza vaccination rate for all adults 18 years and older has increased significantly from 28.0% to 36.2% from 2007 to 2011 (ps<.05). Compared with those not at high risk (25.1%), all high-risk groups were vaccinated at a higher rate, from 36.8% (pregnant women) to 69.7% (those with renal/kidney disease); however, considerable variability among high-risk groups was observed. Vaccination rates among high-risk groups for other vaccines varied considerably though all were below 50%, with the exception of immunocompromised respondents (57.5% for the hepatitis B vaccine and 52.5% for the pneumococcal vaccine) and the elderly (50.4% for the pneumococcal). Multiple risk factors were associated with increased rate of vaccination for most vaccines. Significant racial/ethnic differences with influenza, hepatitis, and herpes zoster vaccination rates were also observed (ps<.05). CONCLUSIONS: Rates of influenza vaccination have increased over time. Rates varied by high-risk status, demographics, and vaccine. There was a pattern of modest vaccination rate increases for individuals with multiple risk factors. However, there were relatively low rates of vaccination for most risk-based recommendations and all fell below national goals.

SUBMITTER: Annunziata K

PROVIDER: S-EPMC3511565 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Vaccination rates among the general adult population and high-risk groups in the United States.

Annunziata Kathy K Rak Aaron A Del Buono Heather H DiBonaventura Marco M Krishnarajah Girishanthy G

PloS one 20121130 11

<h4>Background</h4>In order to adequately assess the effectiveness of vaccination in helping to control vaccine-preventable infectious disease, it is important to identify the adherence and uptake of risk-based recommendations.<h4>Methods</h4>The current project includes data from five consecutive datasets of the National Health and Wellness Survey (NHWS): 2007 through 2011. The NHWS is an annual, Internet-based health questionnaire, administered to a nationwide sample of adults (aged 18 or olde ...[more]

PMID: 23226312

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Project description:BackgroundPopulation-level vaccine efficacy is a critical component of understanding COVID-19 risk, informing public health policy, and mitigating disease impacts. Unlike individual-level clinical trials, population-level analysis characterizes how well vaccines worked in the face of real-world challenges like emerging variants, differing mobility patterns, and policy changes.MethodsIn this study, we analyze the association between time-dependent vaccination rates and COVID-19 health outcomes for 48 U.S. states. We primarily focus on case-hospitalization risk (CHR) as the outcome of interest, using it as a population-level proxy for disease burden on healthcare systems. Performing the analysis using Generalized Additive Models (GAMs) allowed us to incorporate real-world nonlinearities and control for critical dynamic (time-changing) and static (temporally constant) factors. Dynamic factors include testing rates, activity-related engagement levels in the population, underlying population immunity, and policy. Static factors incorporate comorbidities, social vulnerability, race, and state healthcare expenditures. We used SARS-CoV-2 genomic surveillance data to model the different COVID-19 variant-driven waves separately, and evaluate if there is a changing role of the potential drivers of health outcomes across waves.ResultsOur study revealed a strong and statistically significant negative association between vaccine uptake and COVID-19 CHR across each variant wave, with boosters providing additional protection during the Omicron wave. Higher underlying population immunity is shown to be associated with reduced COVID-19 CHR. Additionally, more stringent government policies are generally associated with decreased CHR. However, the impact of activity-related engagement levels on COVID-19 health outcomes varied across different waves. Regarding static variables, the social vulnerability index consistently exhibits positive associations with CHR, while Medicaid spending per person consistently shows a negative association. However, the impacts of other static factors vary in magnitude and significance across different waves.ConclusionsThis study concludes that despite the emergence of new variants, vaccines remain highly correlated with reduced COVID-19 harm. Therefore, given the ongoing threat posed by COVID-19, vaccines remain a critical line of defense for protecting the public and reducing the burden on healthcare systems.

Project description:BackgroundIn temperate regions, influenza epidemics occur annually with the highest activity occurring during the winter months. While seasonal dynamics of the influenza virus, such as time of onset and circulating strains, are well documented by the Centers for Disease Control and Prevention Influenza Surveillance System, an accurate prediction of timing, magnitude, and composition of circulating strains of seasonal influenza remains elusive. To facilitate public health preparedness for seasonal influenza and to obtain better insights into the spatiotemporal behavior of emerging strains, it is important to develop measurable characteristics of seasonal oscillation and to quantify the relationships between those parameters on a spatial scale. The objectives of our research were to examine the seasonality of influenza on a national and state level as well as the relationship between peak timing and intensity of influenza in the United States older adult population.Methodology/principal findingsA total of 248,889 hospitalization records were extracted from the Centers for Medicare and Medicaid Services for the influenza seasons 1991-2004. Harmonic regression models were used to quantify the peak timing and absolute intensity for each of the 48 contiguous states and Washington, DC. We found that individual influenza seasons showed spatial synchrony with consistent late or early timing occurring across all 48 states during each influenza season in comparison to the overall average. On a national level, seasons that had an earlier peak also had higher rates of influenza (r(s) = -0.5). We demonstrated a spatial trend in peak timing of influenza; western states such as Nevada, Utah, and California peaked earlier and New England States such as Rhode Island, Maine, and New Hampshire peaked later.Conclusions/significanceOur findings suggest that a systematic description of influenza seasonal patterns is a valuable tool for disease surveillance and can facilitate strategies for prevention of severe disease in the vulnerable, older adult population.

Dataset Information

Vaccination rates among the general adult population and high-risk groups in the United States.

Publications

Vaccination rates among the general adult population and high-risk groups in the United States.

Similar Datasets

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