Cause, correlation and Covid: Excess life

November 16, 2020. When there are 'excess deaths' in any time period, does that mean that the rest of the time there is a shortage of deaths? I mean, did Covid just cause earlier than they otherwise might have, especially for this over the age of eighty, the people expected to have died earlier? Does anyone who lives longer than the contrived number we call "life expectancy" mean that they have "excess life"?

Consider three types of deaths, two of them ‘with’ Covid either confirmed with a RT-PCR test or assumed from symptoms present at death.

1. death from Covid (alone)

2. death with Covid (including those accompanied by pre-existing co-morbidities)

3. death without Covid (‘natural’ and lifestyle-related).

What ‘caused’ death? Did the Covid virus cause death, or was it present or inferred?

The idea that "correlation implies causation" is an example of a questionable-cause logical fallacy, in which two events occurring together are taken to have established a cause-and-effect relationship. This fallacy is also known by the Latin phrase cum hoc ergo propter hoc ('with this, therefore because of this').[1]

Consider the way a death certificate can be completed, as to the cause (or causes), immediate or underlying, of death on a death certificate

1. Immediate cause of death: The final disease or injury causing the death.

2. Intermediate cause of death: A disease or condition that preceded and caused the immediate cause of death.

3. Underlying cause of death: A disease or condition present before, and leading to, the intermediate or immediate cause of death.[2]

Consider this hypothetical: A person high on fentanyl had previously tested positive for the SARS-Covid virus is shot by a handgun and rushed to a hospital. An emergency room doctor treats him but fails to stem internal bleeding. The bleeding continues, an infection develops and sepsis results. The question: What caused this person’s death?

Are there marginal or conditional probabilities as to the cause(s) of death? Marginal probability is the probability of an event irrespective of the outcome of another variable. Conditional probability is the probability of one event occurring in the presence of a second event.[3]

One approach might be to ask: Does the presence of Covid cause the likelihood of death to increase? What is the marginal probability of death due to Covid? Or is there, in fact, a difference in death rates between those with Covid and those without Covid in their system at the time of death? Let’s look at data for both death rates.

Per SSA.gov,[4] the American death rate figure climbs monotonically to 0.00999% at age 19, or about 0.01%. The death rate continues to climb monotonically and at age 44, the figure is 0.30%. The rate changes from 1.6% at 65 to 0.32 at age 74. The likelihood that a seventy-year-old American will die in the current year is about 2.28%. At 75, it’s 3.56%. For an eighty-year-old, the likelihood is 5.8%. At 85, it’s 10.8%. And this percentage continues to climb exponentially with age, 16.5% at 90, 35.4% at 100.

Now contrast these above death rates with the SARS-Covid death rates in the USA in 2020, using the table below.

With Covid All causes

Age 65-74 2.7% 1.6% (65) to 3.2% (74)

Age 75-84 4.3% 3.5% (75) to 8.8% (84)

Age 85+ 10.4% > 9.78% (85)

Reflections

1. The number of Americans over the age of 65 has increased fifteen-fold, from 3.1 million in 1900 to 49.2 million in 2016. And the older population is increasingly older, with the number of people 85 or older increasing from 122,362 to 6,400,000 in that period, a more than fifty-fold increase.[5]

2. Covid death rates generally parallel ‘normal’ (pre-Covid) death rates across all age groups. The confirmed presence of Covid in one’s system at death might have accelerated an expected death, but not enough to increase death rates from Covid.

3. The seasonal flu has had a vaccine available yet still shows a strong impact on the elderly, with about 85% of 2017-18 flu deaths among those over age 65.[6]

4. In 1900, America had 202 pneumonia or influenza deaths per 100,000 population. In 2018, that rate had dropped amost 94%, to 14.9 deaths per 100,000.[7]

My takeaways – what works, what doesn’t

These are my conclusions and recommendations based on digesting multiple scientific and statistically sound reports, not on the opinions of experts or politicians. Take them for what you will. I am not a doctor or an epidemiologist, but I understand data, statistics and evidence much better than 99.5% of reporters and politicians.

1. Washing your hands works – if done properly.

2. Maintaining a healthy diet, weight, sleep schedule helps your immunity system, a key to stopping and surviving a developed case of Covid.

3. Masks work in the right places if of good quality and used properly.

a. Masks are not necessary outdoors among asymptomatic people.

4. Social distancing works.

a. The critical factor is to not spend more than a few minutes in close proximity to a person, especially if the person is symptomatic.

5. Lockdowns don’t work for many reasons.

a. Some activities can’t be locked down.

b. Some activities that need to be locked down don’t get locked down.

c. People don’t follow the lockdown demands for many reasons, from personal liberty, to lack of knowledge or lack of understanding of the rules, to pressing personal needs that warrant self-justification or rationalization to violate the conditions. I.e., some activities should not be locked down in any case.

d. The experts and political leaders don’t suffer from or sometimes even follow the lockdown – the lockdown is for the other guy.

e. Lockdowns disproportionately hit the poor and marginalized.

f. What happens when the lockdown ends? Transmission can pick up again.

g. When all is said and done, Sweden has handled Covid fine with no lockdown, much better than the experts predicted would happen with no lockdown, and much better economically, emotionally, and socially.

6. Asymptomatic transmission remains uncertain. Stay home if you’re sick and not expose others when you are symptomatic. This is not new advice.

7. Think critically: Why did the media shift from reporting deaths and ICU bed use to reporting

a. the number of (often faulty) tests administered,

b. the number of ‘positive’ tests (also subject to false positives and oversensitivity to previous case of beating the virus), and

c. the number of hospitalizations (if that is of those testing positive, it is different than if it measures all hospitalizations, regardless of reason; also, hospitals are desperate for patients to avoid bankruptcy so ‘Covid’ hospitalizations can be for people with mild, curable cases)?

The 94% mysteries

a. 94% decline in lung-related infection and virus deaths (per 100,000) since 1900.

b. 94% of Covid victims over age 65 survive.

c. 94% of Covid deaths are accompanied by an average of 2.6 co-morbidities.

[1] https://en.wikipedia.org/wiki/Correlation_does_not_imply_causation [2] https://www.mdedge.com/familymedicine/article/60314/cause-death-certification-not-easy-it-seems [3] https://machinelearningmastery.com/joint-marginal-and-conditional-probability-for-machine-learning/ [4] https://www.ssa.gov/oact/STATS/table4c6.html [5] https://acl.gov/sites/default/files/Aging%20and%20Disability%20in%20America/2017OlderAmericansProfile.pdf [6] https://www.statista.com/statistics/1127698/influenza-us-deaths-by-age-group/ [7] https://www.statista.com/statistics/235703/major-causes-of-death-in-the-us/