Secondly, the “enormous numbers of deaths and illnesses” were predicted on a mathematical model that used false assumptions – it was not based on the behavior of the virus as observed in the population. Instead, it was based on extrapolated statistics based on false assumptions about viruses and how they cause disease.
This modeling was flawed because it was based on generic assumptions about the behavior of the virus that ignored the variations in factors between countries - environmental, host, and cultural factors that are determinants of disease from infectious agents.
Infectious agents do not cause disease on their own. Viruses are not living organisms. Their ability to cause disease varies with the environmental and host characteristics of each country as well as the quality of their health care systems.
The US Surgeon-General, Jerome Adams, admitted this fact when he dumped the prediction model on 13 April 2020, stating that the predictions were not based on ‘real data.’ In other words, countries had locked down the healthy populations and brought in social distancing rules based on statistics that were “predictions without actual evidence.”
There is no scientific basis for social distancing and lockdowns in the outbreak of this current disease. In my video, I described how disease statistics can be manipulated to give the appearance of an increase in a new disease by:
i) changing the classification of influenza-disease
ii) by providing financial incentives for diagnosing COVID19 without laboratory confirmation of the virus and
iii) by extra surveillance of the disease in healthy people using a generic test for the common coronaviruses and not a test that identifies the specific new mutated virus. Thereby, creating ‘cases’ of this disease in healthy people without explaining what a positive test actually means.
Statistics can hide many things and in the case of COVID19 disease, the ‘cases’ of disease reported in the media are not an indication of the risk of this disease to the community. This is because the ‘cases’ represent healthy people without symptoms as well as people with mild flu symptoms - people who are testing positive to a test that does not identify the new virus.
The media and government are using these ‘cases’ to frighten the public about the risk of this virus, even though they are not identifying the virus in these cases. The risk of this virus to the community can only be provided by reporting on the deaths to this disease, where the virus has been identified as well as the cases that are hospitalized. In addition, the reporting must provide the context of each case - the age and
co-morbidity of the patient.
In previous years, the co-morbidity of elderly patients, for example, those with cancer, heart disease, lung disease, diabetes, pneumonia etc, would have been listed as the cause of death for these patients. But in 2020 they are being labeled as ‘COVID19’ without proof of causality.
This is fraudulent reporting by the well primed media and government health officials as described at ‘Event 201’ that prepared for the pandemic in October 2019 – five months before the ‘pandemic’. Accurate statistics require context. However, the media is not providing the context surrounding the definition of the ‘cases’ or what is meant by an ‘active’ case of this disease.