Showing posts with label Health Care. Show all posts
Showing posts with label Health Care. Show all posts

Friday, June 24, 2022

A look at Race/Ethnicity and South Central PA COVID Vaccination and Case Mortality Rates

I have been using the stat package R to create graphics. Above is a graph from R that uses the same variables in a graph from the last post: case mortality and the average number of mentally unhealthy days in the last month. I was able to add another layer to the graph by color coding each county by the full vaccination rate. Counties with higher vaccination rates are lighter colored and those with lower rates are darker colored. Graphics like these are useful for showing the effects of more than two variables. 

The main thrust of this post looks at correlations with COVID vaccination and Case Mortality rates in different ethnicities. If the rates by race/ethnicity are higher than overall rates, that suggests that there is more of an issue with that group in the 10 county region. If the rates are lower, then there is a potential confounding for this variable. Some counties do not have values for different ethnicities as they may have small populations of that group.

% Screened for a Mammogram

There was no overall correlation for vaccination or case mortality.  There was a significant negative correlation for white percent screened and case mortality (-0.92).  Only 6 out of the 10 counties had rates for whites and African Americans and 5 for Hispanics and Asians. For these counties, 84% of the variability in case mortality is accounted for by the % of whites screened. For the other groups the correlations were negative but not as strong. Those rates decreased the overall rate.

% Flu Vaccination

There was a significant positive correlation (0.704) for the flu and COVID vaccination rates and a negative correlation for flu vaccination and case mortality (-0.895) (pictured above with color codes for COVID vaccination rates). The white vaccination rates were virtually identical to the overall rates. All 10 counties had white rates while 6 had rates for Asians, 8 for African Americans, and 9 for Hispanics. Correlations were weakest for African Americans.

% Driving Alone to Work

There was a significant positive correlation between COVID case mortality rates and the % driving alone to work (0.73). Even though only five counties had rates for whites (pictured above), there was a significant positive correlation for them at 0.946. Centre county has a lower rate for driving alone to work for the overall and white rate due to better public transportation with Penn State University present. There were 4 counties with rates for Hispanics and African Americans and 2 for Asians. The rates were positive for the other groups but much weaker for Hispanics and African Americans.

These correlations for other groups highlight disparities within the counties. I have written before on racial disparities in Cambria County and presented at the Juneteenth celebrations. My slides from the presentations are presented below. This is just for one county. Other disparities are present in the other counties.

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Saturday, April 30, 2022

2022 County Health Rankings are Out: Cambria Still Ranks Low

The 2022 County Health Rankings for every county in the U.S. were released this week. Cambria County's Health Outcomes rank is 62nd out of 67 counties in Pennsylvania. This ranking is a composite of length of life measures (63rd out of 67 counties) and quality of life measures (60th out of 67 counties). 

There is another ranking where the Cambria fares better. Health factors (Cambria Ranks 40 out of 67 counties) is a composite of four sub-measures: health behaviors (33rd), clinical care (57th), social and economic factors (37th), and the physical environment (38th). These sub-measures are themselves a composite of dozens of government statistics which are more informative than the overall ranking.

The length of life ranking is determined by one statistic: Years of potential life lost or YPLL. This statistic is the number of years lost before age 75. For example, if someone dies at age 25, they have 50 years of potential life lost. Cambria County had 9,600 YPLL compared to 7,600 for PA and 7,300 for the U.S in 2019. For African Americans in Cambria County, the YPLL rate was 20,900 compared to 9,200 for Caucasians. These numbers do not include the effect of the pandemic. Life expectancy is not included in the rankings but is easier to understand.

For the years 2018-2020, Cambria's overall life expectancy was 75.8 years. This is 2.2 years shorter than the state rate of 78.0 years and the U.S. rate of 79 years. For Caucasians, it was 76.1 years and for African Americans it was 66.9 years. One factor driving this racial disparity is child mortality.

For child mortality in Cambria County, the overall rate was 50 deaths per 100,000 and was the same as the overall state rate. However for African Americans, the rate was 160 deaths per 100,000 which was tied for the 2nd highest rate in the state. This rate was 4 times higher than the county Caucasian rate of 40 per 100,000.

Finally the COVID mortality rate for Cambria was 119 per 100,000. This was the 6th highest rate in the state. The overall rate was 88 per 100,000 in Pennsylvania. This death rate occurred on top of the other health issues enumerated in the County Health Rankings. It will take some time to sift out the relevant numbers for our county, I look forward to finding them.

**Relevant Posts**

Friday, January 7, 2022

Changes in How Cases and Deaths in PA are Reported Due to the Omicron Variant

This week Anthony Fauci reported on ABC's This Week with George Stephanopoulus that cases were not as important as hospitalizations and deaths in measuring the severity of the coronavirus pandemic under the omicron variant.  This is because new Omicron variance of COVID-19 is believed to be more contagious but less severe.  With the advent of the new year, the Pennsylvania Department of Health has changed how it reports COVID cases and deaths at the county level.  

Instead of providing daily pdfs with case and death counts for each county which can easily be entered into a spreadsheet, these numbers are only provided on the state's dashboard.  This makes it more difficult for me to enter statewide numbers into a spreadsheet.  Having to enter it manually makes it easier to make errors of entry.  

I am still able to enter numbers for just Cambria and Somerset Counties from the dashboard and show they trend as in the above graph.  Here, the 7 day average for new cases (198.14) is the highest it has been since Dec 12, 2020.  So far there has not been a corresponding increase in hospitalizations or deaths (the dotted black line in the graph above).  If this increase in cases is due to the omicron variant, then there should not be a similar rise in deaths in a few weeks.  

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Thursday, June 10, 2021

Medicaid Expansion Update: What is its Impact on Uninsured Rates?

In the early days of this blog, I wrote extensively on how states were rolling out Medicaid expansion under the Affordable Care Act (aka Obamacare or ACA).  The 2012 Supreme Court decision that upheld the ACA made Medicaid expansion optional for the states.  This expansion allows states to raise the income eligibility level from 100% of the federal poverty level to 133%.

The above map shows that 12 states still refuse to expand Medicaid 11 years after the ACA was passed while 31 states have expanded and 8 states have used different methods to expand.  The map below shows where each state stood on expansion in 2012.  

The census bureau has 2018 as the most recent year where estimates of the uninsured are available.  Thus, to assess the impact of Medicaid expansion, I will compare uninsured rates at the state level between 2010 (the year the ACA was passed) and 2018.  The states will be grouped by whether they refused to expand it in 2018 (19 states), implemented expansion by 2018 (26 states), or implemented it with other methods (6 states).

Expanded by 2018



Change in %



























The table above shows the mean uninsured rates for each group of states with respect to Medicaid expansion.  There was a significant decrease in the uninsured in all three groups due to the implementation of other parts of the ACA.  The states that did not expand Medicaid had higher baseline mean or average uninsured rates at 18.6% compared to 14.6% for those that expanded traditionally and 16.0% for those who expanded using modified methods by 2018.  The uninsured rates for 2018 showed a wider gap in uninsured rates between states that did not expand (12.5%) and the other two groups (7.6% and 8.7% respectively). The standard deviation or SD's show less variability in uninsured rates in all three groups by 2018.

These numbers show that the ACA is having an impact on uninsured rates throughout the U.S.  Medicaid expansion increases this effect in states that have implemented it.  There is still a group of uninsured even in states that have implemented expansion.  A much harder number to measure is the number of uninsured individuals in then U.S.  Further steps will be needed to reach universal coverage.

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Tuesday, May 25, 2021

PBS Program on Data and Pandemics

PBS has a good series on how medicine has learned to fight pandemics.  This particular episode focuses on how data is used to understand and limit pandemics.  It starts with how William Farr used data to track a cholera outbreak.  I've embedded this episode here for your enjoyment and information.

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Income and Life Expectancy. What does it Tell Us About US?

Friday, April 16, 2021

Some Clues for Racial Disparities for Cambria County

Last week I posted on the racial disparities in health outcomes in Cambria County.  These disparities are primarily what is driving the low rankings for the county in the County Health Rankings.

County Health Rankings provides a wealth of statistics called health factors which provide clues to these disparities.  Here is a list:

  • 9% of the live births in the county from 2013-2019 are low birthweight which is 1% higher then the state rate. 16% of African American births are low birthweight compared to 12% of Hispanic and 6% of Caucasian births. in the county
  • The teen birth rate is 20 per 1,000 live births from 2013-2019 compared to 17/1,000 for PA.  For African Americans it is 54/1,000, 19/1,000 for Hispanics, and 18/1,000 in the county.
  • The drug overdose death rate from 2017-2019 was 52 per 100,000 for the county.  For Pennsylvania it is 37/100,000.  For African-Americans the rate was 112/100,000  and for Caucasians it was 50/100,000.  According to the website Overdose free PA, there were 18 overdose deaths among African Americans (orange bar in the above graph) in the county from 2017-2019 out of 204 total overdose deaths or 8% of the total.

  • The rate of preventable hospital stays per 100,000 Medicare enrollees for 2018 is 5,762 in the county compared 4464 for PA.  The African American Rate is 6,154 while it is 5,779 for Caucasians in the county.
  • The rate of mammography screening is 42% for the county for Medicare enrollees for 2018 while it is 45% for the county.  For African Americans it is 31% compared to 38% for Asians, 50% for Hispanics, and 42% of Caucasians in the county.
  • The rate of flu vaccinations is 41% overall for the county for Medicare enrollees in 2018 compared to 53% for PA.  For African Americans the rate was 36% in the county while it was 45% for Asians and Hispanics and 41% for Caucasians.
  • The overall rate of child poverty was 23% for the county for 2019 while it was 17% for PA.  For African Americans it was 67% in the county while it was 19% for Asians, 42% for Hispanics, and 20% for Caucasians.
  • Median income in the county was $48,800 for 2019 while it was $63,500 in PA.  For African Americans it was 18,900 in the county while for Asians it was $90,000, for Hispanics it was $35,100, and for Caucasians it was $48,100.
  • The injury death rate was 128 per 100,000 for the county from 2015-2019 while it was 89/100,000 for PA.  For African-Americans it was 221/100,000 and 126/100,000 for Caucasians in the county.
  • The homicide death rate was 6/100,000 for the county from 2013-2019 while it was 5/100,000 from 2013-2019.  For African Americans it was 50/100,000 while it was 4/100,000 for Caucasians in the county.
  • For firearm fatalities the rate was 16/100,000 from 2015-2019 while it was 12/100,000 for PA.  For African Americans it was 41/100,000 and 15/100,000 for Caucasians in the county.
  • For reading scores, the average grade level was 3.1 for 3rd graders in both the County and PA in 2018.  For African Americans it was at a 2.2 grade level and 3.2 for Caucasians in the county.
  • For math scores, the average grade level for 3rd graders was 3.1 for both the county and PA in 2018.  For African Americans it was at a 2.0 grade level and 3.2 for Caucasians in the county
  • Finally the % of residents who drive alone to work for the county was 82% from 2015-2019 while it was 76% for PA.  For African Americans, 62% drives alone to work in the county while it was 65% for Hispanics and 84% for Caucasians.  This could be due to African Americans and Hispanics being more likely to rely on public transportation to get to work.
These 14 statistics provide some clues to the nature of the racial/ethnic disparities in Cambria County.  They suggest violence and poverty as the main explanatory factors.  One must be careful not to assume that they tell the whole story.  They do provide some clues to where public health resources need to be allocated.  It remains to be seen how the Coronavirus pandemic will interact with these health issues.

**Related Posts**

The 2021 County Health Rankings are Out

County Health Rankings and Corona Virus Cases: Lower ranked counties have fewer cases in PA (except for Philly)

Holiday Poverty Estimates for Johnstown and Cambria County

Friday, December 25, 2020

Testing and New Cases Declined in Cambria County While The Positive Test Rate Remains High

The graph above shows how the rise in cases appears to be levelling off in Cambria County since Donald Trump came here on October 13. The 7 day average for new cases reached a high of 214.29 on Dec 11 and has steadily decreased to 96.57 on Dec 25 (a 54.7% decrease) as can be seen in the solid black line in the graph below.

Also in the graph above we see that the 7 day average number of test results presented per day in the county (dotted red line in the graph) also decreased from 335 per day on Dec 11 and also decreased to 182 per day on Dec 25, a decrease of 45.7% over the same period.  This is a 9% smaller rate of decrease than that of cases in the county.

This graph above shows how the cumulative positive testing rates for the county (dotted blue line), Pennsylvania (red line), and the U.S. (yellow line).  The 7 day average for positive tests peaked at 68.29% on Dec 8 to 53.14% on Dec 25.  This is only a 22.2% decrease which is smaller than the decrease in cases and testing.  

On December 13 I posted on how the % of test results (46.8% today) for Greater Johnstown (zip codes 15901 thru 15909) was higher than the % of positive cases there (41.1% today).  This suggests that the cumulative testing rate for Johnstown is 31.48% while it is 35.74% for the rest of the county, a 13.53% increase outside of Johnstown.  The cumulative positive testing rate is 16.71% for Greater Johnstown while for the rest of the county it is 21.15%, a 26.54% increase.

While it is encouraging to watch the number of new positive cases decrease in Cambria County, the smaller decrease in the positive cases suggests that there may be more cases that are being missed, especially outside of Greater Johnstown.  The 7 day average for deaths in the county peaked at 8.14 per day on December 17 and decreased to 5 per day this Christmas day.  The peak in deaths came 6 days after the peak in cases in the county.  Lets hope the trend continues.  The Governor's order against dine in restaurant eating and gym us appears to be curtailing the rise in cases.  I wish I had better news this Christmas night.


Dave Sutor of the Tribune Democrat has tweeted that Conemaugh Memorial hospital has rented refrigerator trailers to handle possible over crowding at the morgue.

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Monday, October 12, 2020

A Wave of Deaths in Blair County

I have written extensively about the surge in corona virus cases in Cambria County.  Recently there has been a surge in cases and deaths in in Blair County as can be seen in the image above (22 since July 21).  Centre County has seen a larger surge in cases since the Penn State students have come back but has had only four deaths since July 21.  

Looking at the numbers for Blair County more in depth, there are 887 total cases (31 probable +856 confirmed) and 18,865 total negative results.  This gives a total of 19,752 total tests and a positive rate of 4.49%.  The case rate of 728.07 per 100,000 ranks 39th in the state out of 67 counties.

The county's case mortality rate of 2.59% ranks 38th in the state.  The mortality rate of 18.88 deaths per 100,000 ranks 36th in the state.  

One hundred fifty three of the 887 cases are in a nursing home (17.2% of the total) in 13 facilities.  One hundred and ten of these nursing home cases are residents and 43 are staff members.  Thirteen of the 23 deaths or 56.5% of the total are in nursing homes.  By comparison, 10.49% of Cambria County's cases are in a nursing home and no deaths have been reported there.

The PA Department of Health reports that 8 cases are hospitalized and 4 are on ventilators.  The hospitalization rate is 6.57 per 100,00 ranking 16th in the state.  The ventilator rate is 3.28 per 100,000 and ranks third in the state.

The high rate of hospitalization, nursing home cases and deaths, and ventilator use relative to the number of cases in Blair County suggests a greater severity of these cases.  Without access to contact tracing data, it's hard to say why this is the case.

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Saturday, August 22, 2020

Testing Rates Have Decreased in Cambria County as Cases Keep Rising

One week ago, Cambria County surpassed 400 cases of COVID-19.  This can be seen in the graph above.  Since then the number of new cases has tapered off.

On August 11 the 7 day average for new cases in the county was 11.14 cases per day.  As of today, it is 7.29 cases per day.  The graph above shows that the positive testing rate has increased in the county while it has decreased or remained the same for the US and Pennsylvania.  

The graph above shows the trend in the cumulative cases (red line), the number of tests per day (blue bars), and the 7 day average of tests per day.  The decrease in the testing average occurred after August 5 when the number of cases passed 300 (with a brief spike on August 10).  That day there was an increase of 30 cases.  The increase was primarily at the federal prison in Loretto

I don't have a very good explanation for the decrease in testing after the outbreak at the prison.  Carnegie Mellon's COVID Cast website has indicators to predict future cases such as doctor visits, and survey's of symptoms on Facebook.  The graph at the left shows that the composite of indicators has remained relatively steady.  I hope that the decrease is just an aberration.

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Wednesday, July 15, 2020

A Look at Positive COVID-19 Testing Rates in Cambria, PA, and the US

There have been recent media reports about positive testing rates increasing in Pennsylvania.  I thought I would take a closer look at positive test rates since they were reported by the state on April 17. The positive testing rate is simply the number of positive tests divided by the total number of tests.  The graph above shows the cumulative positive test rates for the US (orange line), PA (red line), and Cambria County (blue dotted line).  The black line shows the daily positive testing rate for Cambria County.  

The positive rate for the state has been consistently higher than the US and county rates.  Both rates have been decreasing as testing has become more readily available.  Cambria's positivity rate has been consistently lower than the state and US rates.  The daily testing rate for the county on April 13 was high because on that day there were three positive tests out of 16 total tests (18.25%).  

Since June 24, the cumulative positive test rate increased from 1.02% to 1.28% as of today.  This rise may not sound like much but the solid black line shows positive rates that were consistently at or above the cumulative rates for this period with one day being higher than 5% on July 11.  

The graph above is from the Johns-Hopkins Univeristy site tracking the Corona Virus Pandemic.  It shows the trend in testing for the US during the pandemic.  The blue line shows the seven day average of positive test % with a steady decrease from early April (21.9%) until the middle of June (4.4%) with an increase to 8.7% today.

This graph shows the trend in testing for the state of Pennsylvania for the same period.  Here, we see that there was a corresponding peak in mid April in the positive rate at 27.8% to 3.4% around June 21.  This decrease was followed by an increase to 5.5% as of today.  We can see that testing has risen at a slower rate in the state than in the US as a whole.

The black line in the graph at the top was replaced with the 7 day moving average in testing which does show a rise in positive tests after June 24.  I did not have the same access to 
testing data that Johns-Hopkins had.  I used publicly available data that the PA health department provided beginning on April 17.  

The graph below shows the comparison of the positive testing rate (in the red line) to the testing rate as a percentage of the population for six Johnstown zip codes, the overall rates for Greater Johnstown, Cambria County, Pennsylvania, and the US. These rates are cumulative.  The numbers at the top of each bar are the cumulative testing rates as a percentage of the population.  It's interesting that the state has a higher cumulative positive rate (10.08%) than its testing rate (7.57%).  Johns-Hopkins testing tracker has the state ranked 47th in the testing rates over the last two weeks (1.1 per 1,000) while it ranks 37th in the two week average positive testing rate (5.5%).  At the bottom is a summary of testing data for Pennsylvania.  How one frames the statistics makes all the difference.

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