| County | % COVID Fully Vaccinated | Case Mortality | COVID Case Rate | COVID Mortality /100,000 | County Health Outcomes Rank | County Health Factors Rank |
| Bedford | 38.21% | 2.26% | 26757.90 | 604.31 | 38 | 34 |
| Blair | 52.36% | 1.96% | 28913.02 | 566.55 | 44 | 26 |
| Cambria | 56.20% | 1.87% | 33358.91 | 624.57 | 64 | 41 |
| Centre | 63.58% | 0.90% | 27468.20 | 247.74 | 2 | 5 |
| Clearfield | 51.09% | 1.62% | 31090.03 | 503.36 | 52 | 55 |
| Fayette | 56.60% | 1.94% | 30231.18 | 586.98 | 66 | 65 |
| Huntingdon | 50.38% | 2.02% | 30931.44 | 624.65 | 29 | 53 |
| Indiana | 46.01% | 1.80% | 26191.35 | 471.21 | 50 | 43 |
| Somerset | 49.90% | 1.99% | 30397.87 | 603.98 | 39 | 52 |
| Westmoreland | 59.84% | 1.57% | 28552.24 | 449.36 | 20 | 14 |
| Pennsylvania | 65.37% | 1.43% | 27313.10 | 391.15 |
For me to describe the new county health rankings fully, I need to do it in a piecemeal fashion. Above is a table showing area rankings in health outcomes, factors, and COVID. Health outcomes are a composite of length and quality of life measures. Health factors are a composite of health behaviors, clinical care, social and economic factors, and physical environment. These factors are things that contribute to the health outcomes.
The map above shows that of the ten counties listed in the table above, only Centre County is in the in the upper tier (rank 1-17) in health outcomes. Cambria, Clearfield, and Fayette are in the lower tier (rank 51-67). Huntingdon and Westmoreland are in the second tier (rank 18-34). The remaining 5 counties are in the third tier (rank 35-50).
Correlations
The health factors and health outcomes rankings were both most strongly correlated with COVID population adjusted mortality. Higher numbered rakings are worse. In the linear models, these models accounted for 49% and 46% for health factors and outcomes respectively. Looking at the scatterplots for this correlation, a nonlinear relationship is apparent. A sixth order polynomial relationship provides the best fit for the data accounting for 99% of the variability in COVID mortality. Likewise, similar relationship is seen in the plot for health factors and COVID mortality. Next I will look at the sub-measures for area rankings in health outcomes and the other COVID variables.
**Update**
My mentor Lloyd Stires asked me if I had an explanation for the 6th order polynomial fit for the above graph. I do not. As the rankings are lower the overall trend is upward but there are twists and turns along the way. The health outcomes ranking is a composite of length and quality of life measures. Looking at the individual measures in the next post may provide some clues.
Do you have any explanation for that sixth order polynomial relationship? Since Centre and Indiana counties are well below the predicted COVID mortality rate, I thought it might have something to do with education, but that doesn’t seem to explain the success of Clearfield County.