Implementing the COVID-19 Rapid Community Assessment on Vaccine Confidence: Lessons Learned from Alabama and Georgia

Strengthening COVID-19 vaccine confidence & demand during the US COVID-19 emergency response

In October 2020, the CDC's Vaccinate with Confidence strategy specific to COVID-19 vaccines rollout was published. Adapted from an existing vaccine confidence framework for childhood immunization, the Vaccinate with Confidence strategy for COVID-19 aimed to improve vaccine confidence, demand, and uptake of COVID-19 vaccines in the US. The objectives for COVID-19 were to 1. build trust, 2. empower healthcare personnel, and 3. engage communities and individuals. This strategy was implemented through a dedicated unit, the Vaccine Confidence and Demand (VCD) team, which collected behavioral insights; developed and disseminated toolkits and best practices in collaboration with partners; and collaborated with health departments and community-based organizations to engage communities and individuals in behavioral interventions to strengthen vaccine demand and increase COVID-19 vaccine uptake. The VCD team collected and used social and behavioral data through establishing the Insights Unit, implementing rapid community assessments, and conducting national surveys. To strengthen capacity at state and local levels, the VCD utilized "Bootcamps," a rapid training of trainers on vaccine confidence and demand, "Confidence Consults", where local leaders could request tailored advice to address local vaccine confidence challenges from subject matter experts, and utilized surge staffing to embed "Vaccine Demand Strategists" in state and local public health agencies. In addition, collaborations with Prevention Research Centers, the Institute of Museum and Library Services, and the American Psychological Association furthered work in behavioral science, community engagement, and health equity. The VCD team operationalized CDC's COVID-19 Vaccine with Confidence strategy through behavioral insights, capacity building opportunities, and collaborations to improve COVID-19 vaccine confidence, demand, and uptake in the US. The inclusion of applied behavioral science approaches were a critical component of the COVID-19 vaccination program and provides lessons learned for how behavioral science can be integrated in future emergency responses.

Social Determinants of COVID-19 Vaccination Rates: A Time-Constrained Multiple Mediation Analysis

Objective To estimate the multiple direct/indirect effects of social, environmental, and economic factors on COVID-19 vaccination rates (series complete) in the 3109 continental counties in the United States (U.S.). Study design  The dependent variable was the COVID-19 vaccination rates in the U.S. (April 15, 2022). Independent variables were collected from reliable secondary data sources, including the Census and CDC. Independent variables measured at two different time frames were utilized to predict vaccination rates. The number of vaccination sites in a given county was calculated using the geographic information system (GIS) packages as of April 9, 2022. The Internet Archive (Way Back Machine) was used to look up data for historical dates. Methods  A chain of temporally-constrained least absolute shrinkage and selection operator (LASSO) regressions was used to identify direct and indirect effects on vaccination rates. The first regression identified direct predictors of vaccination rates. Next, the direct predictors were set as response variables in subsequent regressions and regressed on variables that occurred before them. These regressions identified additional indirect predictors of vaccination. Finally, both direct and indirect variables were included in a network model. Results  Fifteen variables directly predicted vaccination rates and explained 43% of the variation in vaccination rates in April 2022. In addition, 11 variables indirectly affected vaccination rates, and their influence on vaccination was mediated by direct factors. For example, children in poverty rate mediated the effect of (a) median household income, (b) children in single-parent homes, and (c) income inequality. For another example, median household income mediated the effect of (a) the percentage of residents under the age of 18, (b) the percentage of residents who are Asian, (c) home ownership, and (d) traffic volume in the prior year. Our findings describe not only the direct but also the indirect effect of variables. Conclusions  A diverse set of demographics, social determinants, public health status, and provider characteristics predicted vaccination rates. Vaccination rates change systematically and are affected by the demographic composition and social determinants of illness within the county. One of the merits of our study is that it shows how the direct predictors of vaccination rates could be mediators of the effects of other variables.

Approaches to enabling rapid evaluation of innovations in health and social care: a scoping review of evidence from high-income countries

OBJECTIVE

The COVID-19 pandemic increased the demand for rapid evaluation of innovation in health and social care. Assessment of rapid methodologies is lacking although challenges in ensuring rigour and effective use of resources are known. We mapped reports of rapid evaluations of health and social care innovations, categorised different approaches to rapid evaluation, explored comparative benefits of rapid evaluation, and identified knowledge gaps.

DESIGN

Scoping review.

DATA SOURCES

MEDLINE, EMBASE and Health Management Information Consortium (HMIC) databases were searched through 13 September 2022.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

We included publications reporting primary research or methods for rapid evaluation of interventions or services in health and social care in high-income countries.

DATA EXTRACTION AND SYNTHESIS

Two reviewers developed and piloted a data extraction form. One reviewer extracted data, a second reviewer checked 10% of the studies; disagreements and uncertainty were resolved through consensus. We used narrative synthesis to map different approaches to conducting rapid evaluation.

RESULTS

We identified 16 759 records and included 162 which met inclusion criteria.We identified four main approaches for rapid evaluation: (1) Using methodology designed specifically for rapid evaluation; (2) Increasing rapidity by doing less or using less time-intensive methodology; (3) Using alternative technologies and/or data to increase speed of existing evaluation method; (4) Adapting part of non-rapid evaluation.The COVID-19 pandemic resulted in an increase in publications and some limited changes in identified methods. We found little research comparing rapid and non-rapid evaluation.

CONCLUSIONS

We found a lack of clarity about what 'rapid evaluation' means but identified some useful preliminary categories. There is a need for clarity and consistency about what constitutes rapid evaluation; consistent terminology in reporting evaluations as rapid; development of specific methodologies for making evaluation more rapid; and assessment of advantages and disadvantages of rapid methodology in terms of rigour, cost and impact.