China lab matters

The revelation that Dr. Fauci was warned about the possibility of a Chinese lab accident causing the release of the Wuhan Virus is bad enough but the efforts to undermine any serious investigation is even worse.

This reflects on something possibility deeper, the foreign policy, scientific class and political class refusal to confront China. Pointing out China responsibility was declared racist but now it is time to accept the reality, China is responsible. It is not racist to point out who started this pandemic, it is truth.

How you can tell a fraudulent Climate science argument.

First rule of telling a fraudulent climate science argument. They use the word denier. There are two things about this phrase. First, it is attempt to compare those who disagree with their view that the world is about to end due to global warming to Nazis. Second, it is scientifically inaccurate.

There are four schools dealing with climate science but there is one important idea, all of the schools of thoughts agree that climate is changing and mostly likely warming. No serious scientists disagree that climate is changing or vast majority view the long term trend is warming.

First school is the alarmist school that global warming is man-made and very bad. The end of the world is near, bla, bla, bla. This is the school the media pays the most attention but the science is totally wrong since much of their predictions have proven to be wrong. For the past three decades, the planet is getting greener, we are feeding more people healthier diets than ever before and every major economic and health metrics have improved. None of this was even predicated because of human ability to adopt and come up with solutions.

Second school believes humans are to blame for present warming but we have plenty of time to deal with the issues. They oppose the use of some fossil fuels but will work with natural gas and are big advocates of nuclear energy. Michael Shellenberger is a example of this school. They don’t buy into replacing our present energy choices with wind and solar since they correctly understand that wind and solar by themselves are incapable of keeping a modern day economy going.

Third school is that human are involved with changing climate but there are natural events that have to be considered. They rely on many solid science to back their concern including the history of this planet. They are not certain that human involvement is that bad. Some within this group view that CO2 levels maybe good for the planet (William Happier is an example of this.) They don’t oppose the use of different mix of energy and like group two, will support a move away from oil and coal toward nuclear energy and natural gas. Think Judith Curry as example of this group.

Fourth school view that much of the climate change is a natural event that has been part of this planet for millions of years and don’t view human contribution as significant. The late Fred Singer is example of this group.

I alternate between the third and fourth school. As I stated in a soon to be published book, that the only way we will get the economic depression, massive starvation and the negative impact of droughts if we actually restrict economic growth to “to save the planet.” Pass the Green New Deal, depend upon wind and solar as oppose to fossil fuels and Nuclear and you will see massive starvation as our economy will go back to a 19th century economy that barely fed one seventh of our present world population.

We have seen a scientific class that has allowed personal agendas and political views to impact the science. Political operatives and activist determine the science not the science helping to determine policies. We saw this in the recent Wuhan virus pandemics.

If a person uses the word denier, he or she is either ill informed or just plain demagogues. The consensus is that the planet climate is changing and we may be in a warmer trend. The real debate is why and what is proper mix of economic policies to ensure our continue economic growth and not set our present economy to a more primitive economy where billions will die.

Lessons From the pandemic

2017 Covers.pdf (amermaj.org)

Data-Efficacy.pdf (amermaj.org)

An-Ignored-Cost.pdf (amermaj.org)

We reviewed from different angles the failure of the lockdown. As the data shows that non-lockdown states and red states outperformed lockdown states and blues states.

  1. We found that there were no significant differences in death between non-lockdown and red states versus lockdown and blue states.
  2. That minorities were more likely to die from Corona virus in lockdown and blue states.
  3. As mention, economic growth and job growth were superior in Red and non-lockdown states.
  4. That other data referenced in our study, that more people have or will die from the lockdown than saved from the virus.
  5. We saw these trends from our data and others from the past year.
  6. Lockdowns were a failure.

stats: Covid death Red vs Blue states

Total deaths eight populous states and note more deaths in Blue state

Total death of Red vs Blue states

Death per state and note Red states less death.

more death per capita in blue states

less death, less unemployment less need for unemployment
death from thanksgiving
weekly death from thanksgiving and note more from blue states

Counting Covid’s Death

Here is interesting thought. How much of the deaths reported are not necessarily caused by Covid but people who die with Covid? In Colorado, they have two set of numbers, one number they report and a second they try more accurately to determine if Covid was the cause.

Colorado data may show 20% of deaths not caused by Covid. Florida is now estimating as high as 40% If they are both right, we are talking 180,000 deaths to 240,000 deaths. Still high by past flu pandemic past decade. 2018 flu based on similar infection and population, would be 160,000.

Tweets on death

Considering that I have been 90 percent plus correct with many of my numbers in March and April on the Lockdown impact on the economy, IFR, the number of undiagnosed cases of Covid outnumbering diagnose case and the number of mild cases far higher than was being reported in April.

The one area I underestimated was the number of infections. Past flu season, we have seen seen 45 to 60 million infected, which means 20% or less of the population infected before the virus disappeared. According to CDC, we may have 100 to 110, 000 infected.

That is a third of the population. There are many reasons including novelty of the virus or the lockdown delaying the normal transmission or the virus but Covid has infected nearly double of the flu season normally does.

This could account for the half of the deaths we have seen. Thoughts? I underestimated how many people would get infected. So this is part of the 10% or less I got wrong. Still impressive track record and better than 80% of those commenting on this.

Data

Data  unemployment through May and claims % of civilian Population June 13 Democrats average include DC and not include DC.

 

May unemployment Claims % of civilian population
Dem average/DC 14.1 13.8
Dem average 14.3 13.6
Rep average 11.4 9.5

Deaths per capital

Death per capita death per million
Dem average/DC 418.3
Dem average 404
Rep average 210

 

 

data top 25 with Lowest unemployment claims by percentage and death per capita

may 2nd may 23rd May 30th June 6th Death per capita
South Dakota 6% 5.60% 4.50% 4.60% 83
Utah 6.20% 5.30% 5.10% 5.10% 40
Idaho 8.70% 6.70% 5.90% 5.60% 48
Nebraska 6.90% 6.40% 6.10% 6.10% 101
Arizona 7% 7% 6.20% 6.20% 155
Wyoming 7.20% 7.20% 6.50% 6.30% 31
Indiana 9.60% 8.50% 7.80% 7.40% 354
Kansas 9.70% 8.20% 7.90% 7.60% 83
Missouri 9.40% 9.20% 8.20% 8% 142
Maryland 8.80% 8.60% 8.30% 8.50% 476
Alabama 10.60% 9.50% 8.90% 8.50% 154
Colorado 8.10% 8.80% 8.10% 8.70% 276
Arkansas 9.50% 9.30% 8.80% 8.80% 55
Montana 12.40% 9.80% 9.40% 8.90% 17
Wisconsin 11.40% 10% 9.50% 9.10% 115
North Dakota 11% 9.60% 9.50% 9.30% 97
Texas 9.80% 10% 10.80% 9.30% 66
Ohio 13.20% 11.30% 10% 9.40% 211
Virginia 9.80% 9.80% 9.60% 9.50% 178
Tennessee 11.10% 10.40% 10% 9.70% 64
South Carolina 12.70% 11.10% 10% 9.70% 112
Iowa 11.90% 11.30% 9.90% 9.80% 203
Florida 5.70% 6.50% 7.80% 10% 122
Oklahoma 12.10% 9.10% 11.20% 10.90% 90
North Carolina 13.10% 11.80% 11.30% 11% 105