COVID-19 Vaccination Propensity in New Hampshire
PORTSMOUTH: As of 16 July 2021, more than 4 million people worldwide have lost their lives due to the novel coronavirus SARS-CoV-2 (COVID-19). Vaccines that induce spike protein-specific neutralizing antibodies induce immunity with extremely high efficacy for the original wild-type COVID-19. However, the emergence of more transmissive mutations, in particular the Delta variant, combined with relaxing layered public health strategies to prevent transmission, have caused case spikes in regions where vaccination rates are low. To reduce transmission in these regions, it is imperative to understand the factors that influence vaccine hesitancy.
Of particular concern is this fall rural towns may be more impacted by school transmission, as schools are a unifying place for town activities (i.e., town meetings, voting, sports, and other activities). Schools are a location for mixing between age groups within communities. Implementation of public health strategies, (i.e., masking, social distancing and improved facility HVAC systems) vary since they are locally controlled, so understanding patterns of vaccination is a critical need here and in other states with similar rural characteristics.
The proportions of fully immunized individuals (more than 2 weeks from two doses of Pfizer/BioNTech, Moderna, or Janssen vaccines) vary widely across the state on a per town basis from 11.3% to 100% (Figure 1a).
We understood that political worldviews may be a factor in vaccination rates in New Hampshire. According to surveys, New Hampshire residents who voted for Donald Trump are more than 5 times more likely to say they don’t plan to be vaccinated for COVID-19 (UNH Survey Center, 2021). Other studies have found that perceived risk, along with sociodemographic factors including age, sex, income, and political ideology influence vaccine propensity (Baumgaertner, et al., 2020).
Comparing the geographic distribution of vaccination rates (Figure 1a) with the democratic performance index (DPI) (Figure 1b) suggests that political persuasion may be an important but not the sole factor influencing vaccine hesitancy. In some cases, towns with higher DPIs (designated as blue/Biden) have lower vaccination rates and vice versa, where some towns with lower DPIs (designated red/Trump) have higher vaccination rates (Figure 1b). The proportions of fully vaccinated individuals for eight cities and towns are below 30% while in 33 cities and towns between 30 and 40% of individuals are fully vaccinated.
We used statistical techniques to evaluate the associations between vaccination rates and independent variables including DPI, median household income, population density, median age, sex, and race.
Our dependent variable, vaccination rate, was calculated for each of the 233 cities and towns where data were available, using estimated 2019 population data obtained from New Hampshire Office of Strategic Initiatives (NHOSI, 2020) (see Figure 1a). Data were obtained from DHHS through June 23, 2021, on fully vaccinated individuals (defined as more than 2 weeks from two doses of Pfizer, Moderna, or Johnson and Johnson vaccines). Vaccination data for 26 towns with less than 100 residents were not made available by DHHS.
A Spearman’s rank correlation indicated a strong positive correlation between vaccination rate and DPI, which was statistically significant, rs = 0.67, p <0.0000 and a statistically significant relationship between vaccination rate and median household income (rs = 0.36, p <0.0000), proportion of females, rs = 0.30, p <0.0000 and weaker, but statistically significant relationships with population density (rs = 0.19, p = 0.003) and increasing age (rs = 0.15, p = 0.02). Vaccination rate and race (rs = -0.013, p = 0.89) was not a significant predictor of vaccination rate. Together, the six independent variables accounted for 53% of the variance in vaccination rate.
A stepwise hierarchical regression determined that vaccination rate was significantly related to DPI (F(1,231) = 172.91, p<0.0000) and accounted for 42.81% of the variation in vaccination rate. Introducing sex into the model explained an additional 3% of the variance in vaccination rate as towns with a higher proportion of women tended to have higher vaccination rates. When introduced, other independent variables were not significant predictors of vaccination rate.
Mindi Messmer, Co-Founder of NH Science and Public Health says:
“While our work shows that political identity at the town-level is an important factor in vaccination rates, our results also suggest there are other important factors, perhaps sex, social influence, education, risk perception, or access, that influence vaccine hesitancy.”
However, some of the towns and cities that are outliers. For example, vaccination rates in Durham and Eaton are very low (31.7% and 58%, respectively) with relatively high DPIs (76% and 61%, respectively).
Mindi Messmer, Co-Founder of NH Science and Public Health says:
“The vaccination rate in Eaton is similar to the vaccination rates in low DPI towns like Benton, Unity, Groton, and Dalton; these towns are likely influenced by DPI, but also lack of access to vaccines since they are in more remote, rural areas of the state. Conversely towns with moderate DPIs but varying population density such as Newington, Hebron, Center Harbor, Hale’s Location and Hooksett have relatively high vaccination rates. Additional pockets of low vaccination rates identified in northern, western, and southern regions of the state are also likely due to access limitations.”
Understanding the geographic distribution of vaccination rates and factors that contribute to vaccine propensity are important steps in addressing the COVID-19 pandemic. In this paper, we found political ideology and sociodemographic factors such as median income, gender, and age influenced vaccine propensity. While there is more work needed to understand the factors causing variance in vaccination rates, access to vaccinations and messaging from trusted sources within or across political ideologies could improve vaccination rates.
Mindi Messmer, Co-Founder of NH Science and Public Health says:
“Additionally, more consistent, and transparent public health messaging about case counts, long COVID risk, and mortality and other morbidity risks may improve vaccine uptake. Initial efforts should be targeted on improving access in communities where vaccination rates are low but where access to healthcare has historically been limited. Trusted communicators also include local health care providers and public health professionals.”
Dr. Nora Traviss, Co-Founder of NH Science and Public Health says:
“Efforts should immediately be expanded in those rural pocket areas where vaccination rates are low. Availability of vaccinations in medical offices would also promote conversations between health care providers and patients and would likely improve vaccination rates.”
Controlling the spread of COVID-19 is an important step in limiting the development of new mutations of the disease which could in the future evade vaccines, presenting as more contagious and/or more deadly. Rising cases from the Delta variant are currently challenging hospitals in other states with low vaccinated rural populations such as Missouri. A precautionary approach, which employs a layered strategy, which we know work (masking, social distancing, and ventilation and filtration of air) is imperative to control community transmission.
Dr. Nora Traviss, Co-Founder of NH Science and Public Health says:
“Younger children, who need to be in school, cannot be vaccinated and will likely not be able to receive a vaccination before school starts in the fall of 2021. We must take precautions, which includes improving vaccination rates in rural areas, to allow children to stay in school safely and to protect them from infection since the impacts of long COVID are poorly understood.”
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