Scientists can only make good conclusions and recommendations after testing or using good quality data from good sources. There’s an old IT saying of “garbage in, garbage out” – if you put garbage data into a program, it will give you garbage results!

Similarly, doctors, politicians and the general public can only make good decisions based on good quality data. But sadly the data we are seeing in this pandemic is not of good quality, and yet the governments of the world are making massive decisions (and many new restrictive laws) which have a significant impact on people, people’s health and stresses, peoples’ livelihoods, jobs, businesses, education, companies, our rights and freedoms, and the economy (which sadly seems to be a more important factor in their eyes).

In science, the data is everything! Or more correctly, the quality of the data is everything. Without good quality data, we are only guessing. Guessing is not good enough. We need accurate information in order to justify the decisions our politicians and medical experts are making.

Dr John Ioannidis, a Professor of Medicine and a world leading expert in health research and policy, has given the following statements:

• “In the coronavirus pandemic, we’re making decisions without reliable data.”
• “The current coronavirus disease, Covid-19, has been called a once-in-a-century pandemic. But it may also be a once-in-a-century evidence fiasco.”
• “At a time when everyone needs better information, from disease modellers and governments to people quarantined or just social distancing, we lack reliable evidence on how many people have been infected with SARS-Co-V-2 or who continue to become infected.”
• “The data collected so far on how many people are infected and how the epidemic is evolving are utterly unreliable.”
• “If we had not known about a new virus out there, and had not checked individuals with PCR tests, the number of total deaths due to “influenza-like illness” would not seem unusual this year.”
• “Adding these extra sources of uncertainty, reasonable estimates for the case of fatality ratio in the general U.S. population vary from 0.05% to 1%.”

There are many reasons why we cannot believe the statistics (ie data) about this pandemic:

• China is a secretive communist country, and they didn’t give out accurate or realistic statistics of incidences and deaths when the infection broke out there. Their official data showed a nice linear growth rate of incidences and deaths, but as we know with the coronavirus, it has a much higher transmission rate than the flu, and infected people are transmitting the virus to 2-3+ more people, which actually causes an exponential increase in numbers, not a linear increase. We are seeing that now the exponential growth in the “official’ statistics, since the infection spread to other countries. China’s data sucked.
• Other countries have different testing criteria, with some testing more people and some testing not many at all
• In Australia, there is a specific criteria which is used to determine if you get tested or not. Testing isn’t being done on everyone who shows with a respiratory infection
• There is a lack of test kits, or laboratory staff or equipment to process all the tests, which has lead to the restriction of those who can actually get tested
• There is no central register of case incidences and mortality
• Recording of cases is open to bias or assumption
• People who die with one or more chronic health conditions are being classified as dying as a primary result of the virus and not of their existing health conditions
• The COVID-19 PCR testing used to confirm infection isn’t accurate!

Governments and health authorities have also made very basic (ie, pathetic IMHO) recommendations for reducing your risks of getting the virus and transmitting it, based on NO accurate scientific data whatsoever. They are only using the above inaccurate and biased reporting data.

Here’s some more data from Australian officials as at March 26 2020: (Australian Government Department of Health, 2020)

Australian NCOVID-19 Incidences 3966 (as at 29 March, 2020)
Australian NCOVID-19 Deaths 16
Australian Mortality Rate 0.4%

Are these statistics worth shutting down the entire country for?

Let’s compare our statistics to that of the country with the highest mortality rate – Italy:

Italian NCOVID-19 Incidences 92,472 (as at 29 March, 2020)
Italian NCOVID-19 Deaths 10,023
Italian Mortality Rate 10.8%

What did Italy do, or what other factors have lead to such a high mortality rate, compared to other countries?

A report by the Centre for Evidence Based Medicine (2020) investigated the incidence and mortality rates in Italy compared to other countries and found a higher aging population (2nd highest in the world), a high prevalence of men who smoke (28% compared to 15% in UK), the highest rate of antibiotic resistance deaths in Europe, and how deaths are recorded. Their ministry of health reported that only 12% of deaths being reported as being caused by the coronavirus had any direct causality to the virus. Hence more people are dying WITH the coronavirus, but not OF the coronavirus.

But this situation is not new in Italy, with studies published on flu infections and mortality in previous years, showing that Italy (because of a high aging population) has a much higher mortality rate amongst the elderly compared to other European countries (Rosano, A. et al, 2019).

And lastly, since the medical authorities and governments of the world are making vast changes to laws and restrictions to your rights and freedoms to try and reduce your risk of the virus, why don’t they know that the COVID-19 test is only 20% accurate?!

Yes, a recent published study shows that the COVID-19 pathology test is reporting up to 80% false positive results in asymptomatic people (those showing no symptoms at all) (Zhuang et al., 2020). In many cases, people have tested positive for COVID-19, but a day or so later, testing negative, then positive again. This shouldn’t happen.

All this disruption to our personal and work lives, to our families, finances, companies and the economy, and more, are based on a VERY low mortality rate in healthy people, and on a test that is only 20% accurate and data that is totally inaccurate…

If an infection, like this coronavirus, gives only mild symptoms in healthy people, then it is a MILD infection! If it causes more serious symptoms in some people, it’s because of something else going on with that person. As we now know, those other reasons include having one or more chronic health condition which has already weakened their immune system and their body’s ability to deal with the infection.

In short, the testing for coronavirus is inadequate as well as inaccurate, the reporting of cases is inaccurate, the reporting of deaths being too quick to lay blame at the virus, and therefore the overall statistics are essentially useless, but they make for great fuel for the fire that is the media coverage of this infection. Don’t buy into the media scare campaign!

Heed the warnings, but do more to support your immune system as well, as per my previous articles.

Stay healthy!

Centre for Evidence-Based Medicine. (2020). Global Covid-19 Case Fatality Rates. Retrieved 29th March 2020 from https://www.cebm.net/covid-19/global-covid-19-case-fatality-rates/

Rosano, A. Bella, A., Gesualdo, F., Acampora, A., Pezzotti, P., Marchetti, S., Ricciardi, W., Rizzo, C. (2019). Investigating the impact of influenza on excess mortality in all ages in Italy during recent seasons (2013/14-2016/17 seasons). International Journal of Infectious Diseases 88: 127-34. doi: 10.1016/j.ijid.2019.08.003

World o Meter. (2020). COVID-19 Coronavirus Pandemic statistics. Retrieved 29th March 2020 from https://www.worldometers.info/coronavirus/

Zhuang, G.H., Shen, M.W., Zeng, L.X., Mi, B.B., Chen, F.Y., Liu, W.J., Pei, L.L., Qi, X., & Li, C. (2020). Potential False-Positive Rate Among the ‘Asymptomatic Infected Individuals’ in Close Contacts of COVID-19 Patients. Zhonghua Liu Xing Bing Xue Za Zhi, 41 (4), 485-488. DOI: 10.3760/cma.j.cn112338-20200221-00144.

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This content was originally published here.