Coronavirus Death rates by State and Factors that Affect Mortality Rates

Coronavirus Death rates by State and Factors that Affect Mortality Rates

Correlations between States with High Coronavirus Mortality Rates

The CDC maintains a map of the U.S. showing the mortality rates (how many people per 100,000 of population) died from Coronavirus. The map at right is a snapshot from August 26, 2020.

This allows us to compare the death rates from Coronavirus between states. Of course, as Dr. Birx stated months ago, coroners were instructed to attribute any death to Coronavirus as long as the virus was detect in the person or there was even a suspicion that the victim had Covid19. This means the total number of fatalities attributed to Coronavirus are clearly exaggerated (it's like saying if you walked across the street and were hit and killed by a bus, and they detected the virus in your corpse's blood, you died from Coronavirus. )

But while the total numbers are exaggerated, the comparison between states should remove this and allow us to consider correlations to conditions that are likely causes.

Patterns within the states with the highest mortality rates

Notice in the chart that the highest rates occur in states with:

• High population densities, like large cities (NY, NJ, IL, IN, MI, MA, PA, CT, etc.)
• Aging populations (Florida, Arizona) and
• High rates of obesity (LA, SC, MS) and in general the Deep South and Midwest.

See below for references for these facts.

Now, we accept that this is a correlation. Causation is not proven by statistical correlations, a fact often misunderstood by non-scientists.

But the authorities who are studying Coronavirus have already established a causal effect between specific underlying conditions (called co-morbidities), specifically::

• age over 65
• obesity
• diabetes
• heart conditions
• respiratory problems

References

Obesity and COVID-19

See this page for detailed information about the connection between overweight, obesity and coronavirus risk.

 The Lancet: Increasing COVID-19 caseloads were associated with countries with higher obesity (adjusted rate ratio [RR]=1.06; 95%CI: 1.01–1.11), median population age (RR=1.10; 95%CI: 1.05–1.15) and longer time to border closures from the first reported case (RR=1.04; 95%CI: 1.01–1.08). Increased mortality per million was significantly associated with higher obesity prevalence (RR=1.12; 95%CI: 1.06–1.19)

Obesity is also high among another group at risk, the elderly

• Percent of noninstitutionalized persons with obesity (2013-2016)
  • Men aged 65-74: 40.2%
  • Men aged 75 and over: 28.0%
  • Women aged 65-74: 43.5%
  • Women aged 75 and over: 32.7%

Source: Health, United States, 2018, table 26 [PDF � 9.8 MB]

States with high elderly populations

The U.S. Census Bureau shows us which areas have the highest populations of elderly people. Examining these maps at right, we see that again, it correlates to those states with the higher mortality rates from Coronavirus, with the exception of Montana, which has a very low population density being a very rural and sparsely populated state..

U.S. Population Density

The Census Bureau also has population density maps, shown at right. Again, we see a high degree of correlation of the states with the highest mortality rates an d the states with the area of highest population density.

When you drill down to a county-by-county correlation between age and COVID mortality, the fit is very, very, close, implying that the virus spreads more when people are in close proximity, and this leads to higher death rates, as would be expected.