Identifying trusted local sources and predicting behavior change pathways according to COVID-19 vaccination status: Results of a 2022 statewide survey of Alaskan adults.

BACKGROUND: Low rates of COVID-19 vaccination remain a substantial public health challenge. Despite early successes, vaccinations of Alaskans trail the US average, drawing attention to the need for better-designed and targeted vaccine confidence interventions. Our objective was to assess levels of community trust and theory-driven predictors of vaccination status to inform the design of future programs. METHODS: We conducted a cross-sectional, telephone-based survey of 940 Alaskan adults between May and June 2022. Data were collected on vaccination status (including initial vaccination and receipt of booster shots), trust in local community members, demographic characteristics, and thematic questions designed using the Capability, Opportunity, Motivation - Behavior (COM-B) model to examine possible predictors (barriers/facilitators) of vaccination status. FINDINGS: Among those who are not fully vaccinated and boosted, we observe significantly lower trust placed in many immediate community members, especially health workers (e.g., doctors, nurses, specialty care physicians, health administrators). Firefighters and emergency medical technicians enjoy the most community trust, followed by medical professionals. Among those who received only a primary vaccine series, we find that perceptions of whether close friends are vaccinated, a sense of professional responsibility, and age were the strongest predictors vaccination status. Among the unvaccinated, we find significant predictive power from the same variables, as well as perceptions of whether family members are vaccinated, perceived risks from non-vaccination and whether vaccination is a healthy choice. CONCLUSIONS: These findings will help inform the design and targeting of future vaccine promotion interventions to adult populations in Alaska. Interventions that leverage reflective motivation and social opportunity domains of the COM-B framework may be most effective. Local community members including firefighters and emergency medical technicians, as well as medical professionals may be perceived as the most trustworthy and influential messengers among those who are not fully vaccinated and boosted.

Application of COVIDTracer to Inform Public Health Workforce Planning in Alaska During the COVID-19 Pandemic.

The COVID-19 pandemic has caused social and economic disruption worldwide and spurred numerous mitigation strategies, including state investments in training a large contact tracing and case investigation workforce. A team at the University of Alaska Anchorage evaluated implementation of the COVID-19 contact tracing and case investigation program of the State of Alaska Department of Health and Social Services, Division of Public Health, Section of Public Health Nursing. As part of that evaluation, the team used COVIDTracer, a spreadsheet modeling tool. COVIDTracer generated projections of COVID-19 case counts that informed estimates of workforce needs and case prioritization strategies. Case count projections approximated the reported epidemiologic curve with a median 7% difference in the first month. The accuracy of case count predictions declined after 1 month with a median difference of 80% in the second month. COVIDTracer inputs included previous case counts, the average length of time for telephone calls to cases and outreach to identified contacts, and the average number of contacts per case. As each variable increased, so too did estimated workforce needs. Decreasing the average time from exposure to outreach from 10 to 5 days reduced case counts estimated by COVIDTracer by approximately 93% during a 5-month period. COVIDTracer estimates informed Alaska's workforce planning and decisions about prioritizing case investigation during the pandemic. Lessons learned included the importance of being able to rapidly scale up and scale down workforce to adjust to a dynamic crisis and the limitations of prediction modeling (eg, that COVIDTracer was accurate for only about 1 month into the future). These findings may be useful for future pandemic preparedness planning and other public health emergency response activities.

Compounding Effects of Social Vulnerability and Recurring Natural Disasters on Mental and Physical Health.

OBJECTIVE: This study evaluated the relationships between the occurrence of recent and recurring natural disasters on the incidence of acute and chronic health outcomes at the census tract level in 500 cities across the United States between 2001 and 2015. METHODS: Using the Centers for Disease Control and Prevention (CDC) 500 cities data set, the CDC Social Vulnerability Index, and the US Small Business Administration (SBA) Disaster Loan Database, we modeled the incidence of self-reported, poor mental and physical health, or a clinical diagnosis of high blood pressure or asthma in census tracts (N = 27 204 tracts in 500 cities) that had experienced recent or recurring natural disasters while controlling for social and environmental risk factors. RESULTS: Communities that experienced a natural disaster in the previous 5 years compared to those that had not had a higher incidence of poor mental health (RR: 1.02, 95% CI: 1.01-1.02), poor physical health (RR: 1.03, 95% CI: 1.02-1.04), high blood pressure (RR: 1.04, 95% CI: 1.02-1.05), and asthma (RR: 1.01, 95% CI: 1.01-1.02). The incidence of these poor health outcomes increased 1-2% with each additional year that a community experienced a disaster. CONCLUSIONS: Prevention and preparedness plans that work to build resilience in communities before disasters should focus on closing the gap in environmental and social determinants that have been linked with disproportionate health burdens and slow recovery post-disaster.