Exploring the impacts of neighborhood disadvantage on Medicare beneficiaries' early COVID-19 vaccine uptake.

A variety of factors influenced the American public's experiences with the COVID-19 pandemic and initial availability and uptake of COVID-19 vaccines. To examine variation in early COVID-19 vaccine uptake based on neighborhood disadvantage along with individual sociodemographic and health characteristics, we used Spring 2021 data from the Medicare Current Beneficiary Survey (MCBS), a nationally representative, longitudinal survey of the Medicare population conducted by the Centers for Medicare & Medicaid Services. Bivariate analyses showed that beneficiaries in disadvantaged neighborhoods were less likely to have received at least one vaccine dose than those in less disadvantaged neighborhoods (49.7%, SE = 1.6 versus 66.6%, SE = 1.0, p < 0.0001). After accounting for individual characteristics, the relationship between neighborhood disadvantage and vaccine uptake was not statistically significant. However, interaction effects of neighborhood disadvantage by urbanicity showed a more complex picture, where those in disadvantaged urban areas had the lowest odds of vaccine uptake (p < 0.01). The relationship between neighborhood disadvantage and vaccination is multifaceted, requiring further research to inform future vaccination efforts targeting the most vulnerable beneficiaries.

Optimizing Call Patterns for Landline and Cell Phone Surveys.

Cell phone surveys have become increasingly popular and researchers have noted major challenges in conducting cost-effective surveys while achieving high response rates. Previous work has shown that calling strategies that maximize both respondent contact and completed interviews for landline surveys may not be the most cost-effective for cell phone surveys. For example, Montgomery, et al. (2011) found important differences between landline and cell samples for best times to call and declines in contact rates after repeated dialing. Using paradata from the 2010 and 2011 National Flu Surveys (sponsored by the Centers for Disease Control and Prevention), we investigate differences in calling outcomes between landline and cell surveys. Specifically, we predict respondent contact and interview completion using logistic regression models that examine the impact of calling on particular days of the week, certain times of the day, number of previous calls, outcomes of previous calls and length of time between calls. We discuss how these differences can be used to increase the likelihood of contacting cooperative respondents and completing interviews for both sample types.