What Data Did Health Experts Use in Their Alarming COVID Forecasts in 2021?
viewed each new variant as the Death Star for all
THUNDER BAY, ONTARIO ~~~~~ November 9, 2022 (LSNews) When the world moved into the second month of the second year of the COVID pandemic, in February of 2021, we heard a lot about the modelling public health officials used to project COVID case numbers going forward. One of the prime purposes of this modelling, we were told, was to ensure COVID cases didn’t overwhelm the healthcare system. We weren’t told what data or systems they used for this modelling, only that it was key to determining what measures and restrictions should be put in place to achieve the neverending goal of “flattening the curve”.
Models Seem to Over Forecast
What has become clear is that most models vastly over-estimated COVID numbers. The World Health Organization (WHO), for example, vastly over-estimated the lethality of the virus, causing panic and unprecedented lockdowns, in the early weeks of the pandemic. Despite the fact that most modelling to predict COVID spread, and deaths, and hospitalizations, has continued to over forecast COVID numbers, governments still insisted on using them, maintaining that they are “following the science”.
The modelling released by Federal Chief Health Officer Dr. Theresa Tam, in February of 2021, predicted such a drastic rise in COVID cases by mid-March (2021) that she described it as literally “off the charts”. This left many experts scratching their heads including Dr. Martha Fulford, an Infectious Disease Physician at Hamilton Health Sciences and Assistant Professor at McMaster University, in Hamilton, Ontario. She told the Sun newspaper, “For me the model is only as good as the data imputed and we need to know what the underlying assumptions and data are.
Dr. Tam’s February modelling chart, note the yellow and light grey lines predicting an extreme rise in COVID cases.
Health officials can't explain Dr. Tam's 'rocket ship' modelling | Toronto Sun
Opposition MPs, upon the release of Dr. Tam’s new modelling, did question Public Health Agency of Canada (PHAC) experts in that regard during a meeting of the Parliamentary Health Committee, but received no clear answers on what the modelling was based on, except that it seemed highly focused on the new “variants”.
This was not the first example of Tam’s penchant for “extreme case” scenarios. Her models released in the previous three months all fell short of a predicted dramatic rise in COVID cases. Yet, again she was predicting more dire circumstances on the horizon, while Canada had seen COVID cases declining since mid-January. Of course, our health officials and government’s liked to attribute this to the lockdowns imposed in many provinces in December. Yet, statistics from other countries, including the US, where some states actually began reopening in January, and states like Florida and South Dakota, that never locked down, experienced the same downward trends from mid-January and continuing into February. This same trend was occurring in virtually every western country in the world. This included Sweden, which didn’t lockdown and the United Kingdom (UK), which did, and was also one of first countries to report new COVID variants.
Given these statistics, it is hard to believe lockdowns made any great difference in COVID’s case trajectory. Did Dr. Tam’s team take any of this data into consideration when developing the model? Here in Ontario we, again, don’t know what “science” was followed in the modelling released in early January 2021 that predicted such a massive increase in daily COVID cases. So much so, that it led the government to impose an extended province-wide lockdown, coupled with a stern “stay at home order.” Now, as cases diminish, Premier Doug Ford, will no doubt attribute it to the lockdown, despite the downward trending of COVID cases in other countries. Did health experts wilfully ignore certain factors in their modelling process to produce such dire scenarios?
Some COVID 19 vaccines became available, in Canada, in January 2021 and we were told that they were the ‘silver bullet’ to get us out of this pandemic (another lie). That being said, the Liberal government initially, did a woefully poor job of acquiring vaccines for Canadians. This was partly due to the fact that they entered into a partnership with China to produce a boatload of vaccines back in June of 2020. Except the deal fell through when China refused to send vaccine samples to Canada to conduct trials, leaving the Liberal government placing late vaccine orders with other suppliers. Still, were told that this dearth in vaccines was coming to an end and soon we would be awash in doses. (and we were, except at the time, we–meaning the public–had no idea that they hadn’t even been tested for their efficacy) Did Dr. Tam not have faith in the government’s ability to actually acquire vaccines? That was what her modelling seemed to reflect.
Seasonal Flu Statistics?
Was the drastic drop in seasonal influenza cases factored into these modelling scenarios? This trend surfaced early in 2020 once the coronavirus began spreading across Canada. A Health Canada Flu Watch Report for the week of March 15, 2020 noted a sharp decrease in laboratory detections of the flu and a reduction in hospitalizations in both the adult and pediatric populations. A later Health Canada Flu Watch Report for the week of February 7, 2021 continued to report that influenza activity remained low across the country. One would think such modelling would have taken into consideration the fact that hospital admissions for seasonal flu dropped dramatically over the course of 2020 and the pattern was continuing in 2021. Thus, the fewer hospital beds occupied by flu patients, meant more for potential COVID patients, should they be required.
COVID Case Statistical Comparisons?
One would also think that, given we had been in pandemic mode for over a year, that looking at past COVID statistics and comparing them to ongoing and current data would have been useful to such predictive modelling. Statistics deal in numbers and percentages and when one looks at the percentages, recorded by Health Canada, in terms of COVID deaths and hospitalizations, those numbers have remained constant throughout the course of the pandemic. Would such consistencies not have been of value in predictive modelling exercise as it might relate to allocating medical resources?
COVID Deaths: A comparison of the percentages of total COVID deaths from October 2020 (no lockdown) and from February 2021 (post lockdown), reveal that rates in various age groups remained remarkably constant as the chart below illustrates. The overall percent of COVID deaths in those aged 50 and under was 0.9% in October compared to 1.2% in February—a .03 difference. Meanwhile, those over the age of 70 account for a whopping 90 percent of COVID deaths. Given that this trend of the elderly accounting for the vast majority of deaths, which became clear three months into the pandemic, one would think more effort would have been focused on targeted measures to protect this group of people, particularly those in retirement facilities. Instead our governments seemed to prefer an approach of rotating and revolving lockdowns that impacted everything from mental and physical health, to educating our children and weakening our economy. Did health experts ever take these other impacts into account when they went through their modelling process, or was it pure tunnel vision on cases and only cases?
Oct. 17 - 0% Ages 0 -19 Feb. 12 - 0%
Oct. 17 - 0.1% Ages 20-29 Feb. 12 - 0.1%
Oct. 17 - 0.2% Ages 30-39 Feb. 12 - 0.3%
Oct. 17 - 0.6% Ages 40-49 Feb. 12 - 0.8%
Oct. 17 - 2.4 % Ages 50-59 Feb. 12 - 2.6%
Oct. 17 - 7.3% Ages 60-69 Feb. 12 - 7.6%
Oct. 17 - 18.1% Ages 70-79 Feb. 12 - 18.9%
Oct. 17 - 73.8% Ages 80+ Feb. 12 - 69.7%
COVID Hospitalizations: The percent of COVID patients admitted to hospital for the same two periods had also remained consistent. The percentage of admissions in those under the age of 50 in October was 17.3%, and in February the percentage was 16.7%, a difference of 0.6%. Would such information, if factored in with the drop in flu hospitalizations, have been of value in determining medical resources needed, as they relate to COVID, rather than looking solely at overall positive case numbers, which seem, largely to be, what the models were been based on?
Oct. 17 - 1.4% Ages 0 -19 Feb. 12 - 0%
Oct. 17 - 3.1% Ages 20-29 Feb. 12 - 0.1%
Oct. 17 - 5.1% Ages 30-39 Feb. 12 - 0.3%
Oct. 17 - 7.7% Ages 40-49 Feb. 12 - 0.8%
Oct. 17 - 13.9% Ages 50-59 Feb. 12 - 2.6%
Oct. 17 - 17.2% Ages 60-69 Feb. 12 - 12.1%
Oct. 17 - 20.6% Ages 70-79 Feb. 12 - 21.0%
Oct. 17 - 31.1% Ages 80+ Feb. 12 - 34.2%
COVID Intensive Care Unit Admissions: Again the pattern continues when comparing the percentage of ICU admissions for the same two periods. The difference in the under 50 age group is 1.5 percent more admissions in October, compared to February. With such information at their fingertips would it not have made sense for health experts to use it to determine the medical resources and facilities required to meet these numbers? Essentially, if you know from past experience that 1.3 percent of Canadians under the age of 19 who contract COVID will require ICU treatment, could you not plan accordingly given that the 1.3 percent average has remained constant for the past ten months? If you know, from statistical data that some 21 percent of Canadians between the ages of 70 and 79, who contract COVID will require hospitalization. Could you not plan for that by allotting beds accordingly?
Oct. 17 - 1.3% Ages 0 -19 Feb. 12 - 0%
Oct. 17 - 3.4% Ages 20-29 Feb. 12 - 0.1%
Oct. 17 - 4.9% Ages 30-39 Feb. 12 - 0.3%
Oct. 17 - 9.3% Ages 40-49 Feb. 12 - 0.8%
Oct. 17 - 20.4% Ages 50-59 Feb. 12 - 17.6%
Oct. 17 - 24.6% Ages 60-69 Feb. 12 - 26.0%
Oct. 17 - 23.5% Ages 70-79 Feb. 12 - 25.7%
Oct. 17 - 12.5% Ages 80+ Feb. 12 - 13.2%
Stoking Fear Never Stops
These percentages have remained constant throughout the pandemic, during lockdowns, during re-openings and during the peak of the pandemic waves. Yet, we seldom heard about this from the legacy media, instead they bombarded Canadians with COVID statistics, from alarming reports of rising case numbers to the daily death counts. At that time in 2021, they also had the new ‘more contagious’ variants from the UK, South Africa and Brazil to stir into the fear mix. Yet, when one looks at the statistics from these countries, the variants have had little impact on their COVID case numbers or deaths. The UK, as mentioned earlier, was in a downward trend, as was South Africa, whose numbers had been dropping consistently since mid-January. In Brazil, while there hadn’t been a significant drop in case numbers, neither has there been any dramatic spike. Did Dr. Tam look at this data while creating her models?
The models and the media’s unquestioning support of them all seem designed to stoke fear in people and it works. There were many Canadians that living in fear. Fear of going to work or going shopping, fear for their elderly parents lives, and fear of sending their healthy kids to school. But, it was also provokimg anger and cycicism in a growing number of people who, based on their own observations of who the disease most severely impacted, didn’t believe that COVID was the great threat to the entire population, as they had been told. This resulted in an increasing number of public protests against lockdowns, school closures and other rigid arbitrary restrictions such as stay-at-home orders, masking mandates, curfews and severe curtailment of outdoor activities.
Most people, by now, know that COVID killed the elderly, particularly those in long term care facilities (LTCF) where, once it enters such places, it spreads like wildfire. Over the course of the pandemic, our governments coudn’t seem to find away to fix this in an significant manner, other than shutting the entire province or country down. And using these mysterious modelling exercises carried out by our federal health experts, this trend to continued throughout 2021, despite, again, having any measurable effect on COVID spread and infections. The only downward trend was the number of deaths, partially due to vaccines, particularly in the elderly, but more due to milder versions of the virus, as it mutated over time. Which, based on the history of pandemics, is the natural trend of how they wind down and eventually end, or become endemic. Which, is something the modelling also missed, and instead viewed each new variant as the Death Star for all.
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|I am a retired journalist who served with the Canadian Armed Forces and for the last 13 years of my working career was a Senior Emergency Planning Analyst with the RCMP. I am a wife, mother and dog, cat and intrepid explorer
An Intrepid warrior exploring issues in today's strange new world.
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