Discrepancy In Covid-19 Testing Numbers?
A few weeks ago, the woman who was in charge of creating the Florida corona virus website and maintaining an accurate count was fired. She was fired because she started asking questions about the accuracy of the Florida virus numbers and about the their sources to her superiors. She started to suspect was awry when her superiors told her to downplay the reported numbers. She indicated that this manipulation of the numbers showed the counts less than was actually reported.
Since the virus stats are all in the numbers being reported from testing sites, hospitals, and other sources, manipulation of numbers could happen depending on who is in charge and perhaps, their political beliefs. Florida has a Republican Governor, a stout Trump supporter, and Republican Senators. They are team players and want to keep their state "open for business". They refuse to consider rolling back phases of reopening despite the state having more than 200,000 positive cases with an average increase of 6500-11,500 cases daily. They will not even mandate masks when in public. Texas is another Republican state mocking the CDC. If you look at Democratic led states, you will find better success in controlling the virus numbers.
One has to wonder about the numbers being reported. Some reports have indicated that each test for the virus consists of two tests: the virus test and the antibody blood test. This would be two tests for one person. If this is true, then the numbers being reported as positive would be halved to reflect the actual head count.
Others state that while there are two tests, they are NOT given at the same time. The virus nose swab is used to detect if the person has the virus or not at that time, while the antibody test is given only to those who did have the virus after the incubation period. The question remains, are the positive cases including or excluding those with the antibody test? Is a person counted more than once if they go get the tests at different times, weeks apart?
Most stats indicate the number of positive cases since the last count, indicating how the virus is spreading or not. The death count may decrease simply because the group in the positive cases may be the age group that seldom get seriously ill and they recover. But, eventually, as the virus spread across all population groups, more deaths will increase.
One can see how tracking the numbers of the virus could be tampered with or just incorrectly ascertained since there is the human error factor in reporting. The numbers could either be far worse or less worse than presented to the public.
