Friday, January 14, 2022

PA County Factors that Predict Full COVID Vaccination Rates

Last month I posted on which county health ranking variables were most strongly correlated with COVID case mortality rates.  Granted these posts were made just as the omicron variant was arriving on the scene.  This month, I thought I would take a look at which variables were the best predictors of full vaccination rates.  Full vaccination means receiving the first two shots.  As of today, only 51.8% of the state population has received the first two shots.  This includes Philadelphia County and individuals who are ineligible to receive the shots.

Univariately, the average number of mentally unhealthy days had the strongest negative correlation with the full vaccination rate.  Not surprisingly, the flu vaccination rate at the county level had the highest positive correlation.  These and other variables were entered into a multiple regression model to find the most robust predictors.  The flu vaccination rate was not significant in the presence of other variables but others were and are presented below.  These variables accounted for 62% of the variability in the full vaccination rate.  Philadelphia county was a problematic outlier and was excluded from the data set.

Full vaccination rate = 0.585 - 0.006(social assoc rate) - 0.044(avg # mentally unhealthy days) + 0.003(% with access to exercise opportunities) + 0.001(Primary Care Physician Rate)


The rate of social associations in a county was negatively associated with the full vaccination rate.  In the model, for every unit increase in the association rate there is a 0.6% decrease in the full vaccination rate.  Univariately this relationship accounts for 22.8% of the variability in this relationship.  Montour county, with the highest vaccination rate in the state is an outlier for this relationship as well as other variables.

The average number of mentally unhealthy days in the last month is also negatively associated with the full vaccination rate.  For every increase of one day in this variable there is a predicted 4.4% decline in the full vaccination rate.  Univariately this relationship accounts for 34.9% of the variability in the rate.  


Access to exercise opportunities is positively associated with the full vaccination rate.  For every 1% increase in the rate, there is a predicted 0.3% increase in the full vaccination rate.  Univariately, this variable accounts for 33.9% of the variability in the full vaccination rate.
















The fourth variable is the primary care physician rate in the county which is positively associated with the full vaccination rate.  For every unit increase in the physician rate, there is a predicted 0.1% increase in the vaccination rate.  Univariately this variable accounts for 20.8% of the variability in the vaccination rate.  Montour County (where Geisinger Hospital is located), is influential in this relationship but not poorly fit.

When I looked at which County Healthy Ranking variables predicted COVID case mortality rate, the social association rate, the rate of mentally unhealthy days, and access to exercise opportunities were significantly associated with the outcome.  The PCP rate was not significant for case mortality and the % smoking did not hold up in variable selection for the vaccination rate.  

The correspondence is high for the models for these two dependent variables.  These predictors may provide clues as to crafting strategies for improving vaccination rates and thus decreasing COVID mortality.

**Related Posts**

Rates of Smoking and Social Associations Predict PA County COVID Case Mortality



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