For other posts, visit my Commentary blog
In mid-May, my analysis of the COVID crisis lead me to make what many considered an outrageous prediction. After modeling and tracking coronavirus data for three months, I grew convinced the epidemic was winding down even though media and academic models were continuing to sensationalize the crisis. Based on the trends I was following and the data put out by the CDC, WHO, and IndexMundi, I predicted the crisis would be over on June 7th.
Those who follow my commentary blog recognize the above plot, which I updated daily in April and May to show the rise and fall of the coronavirus epidemic. The blue section of the curve shows the rise in COVID deaths up to the April 14th apex (which my model accurately predicted). The red section shows the steady decline in the death rate from mid-April to June 7th. Both these sections of the curve match CDC data and the area under the blue/red curve represents the number of COVID deaths, which unlike federal and academic models, my model accurately predicted. The yellow section was my June 7th prediction for future COVID deaths. Through June and July, this projection curve has been spot on, but that’s a topic for my end of month status review. Note: while the yellow curve appears to approach zero, it actually doesn’t, it asymptotically approaches zero.
Before we proceed, lets distinguish the difference between an epidemic and pandemic. According to Merriam Webster, the difference is;
- An epidemic is defined as: “an outbreak of disease that spreads quickly and affects many individuals at the same time.”
- A pandemic is: “a type of epidemic (one with greater range and coverage), an outbreak of a disease that occurs over a wide geographic area and affects an exceptionally high proportion of the population. While a pandemic may be characterized as a type of epidemic, you would not say that an epidemic is a type of pandemic.“
Pandemics are usually multi-continent while an epidemic is limited to a particular region or country. For example, an E.coli outbreak in southern California and Baja, Mexico might be considered an epidemic, but if it spreads to South America, it becomes a pandemic. Like an expanding and contracting balloon, an outbreak starts out as a small epidemic, expands into a larger pandemic, and then contracts again to smaller epidemic. Also, when we discuss a worldwide outbreak, it’s a pandemic. When we talk only about that outbreak within a confined region, such as the U.S., its an epidemic.
The term epidemic is derived from the Greek word epi, which means “upon or above,’ and demos, which means “people.” The term was first used by Homer, but took on its current meaning when Hippocrates used it to describe a collection of clinical syndromes, such as coughs or diarrheas, occurring and propagating in a given period at a given location. Epidemics tend to be short-lived (relative), while a constant presence of an infection or disease in a population is called Endemic; this is also referred to as a baseline, which is crucial for determining when an epidemic starts and when it ends.
With all the media coverage focused on COVID, you may not be aware that the CDC is currently tracking three outbreaks,
- Cyclospora Infections – from bagged salad mixes
- Salmonella Infections – from poultry
- Coronavirus Disease – from the Chinese government
How an epidemic starts: There is an official threshold defining the start of an epidemic. In general, epidemics occur when an infection/disease (i.e., agent) plus susceptible hosts are present in adequate numbers, and the agent can be effectively transmitted from a source to susceptible hosts. Epidemics result from:
- A recent increase in amount or virulence of the agent,
- The recent introduction of the agent into a setting where it has not been before,
- An enhanced mode of transmission so that more susceptible persons are exposed,
- A change in the susceptibility of the host response to the agent, and/or
- Factors that increase host exposure or involve introduction through new portals of entry. (1)
How an epidemic ends: an epidemic ends when “the number of new reported illnesses [/deaths] drops back to the number normally expected.” For the CDC, the end of an influenza outbreak is reached when the number of infections or deaths, depending on the metric you are measuring, drops to a level at or below the number for endemic influenza. For example, the death rate for an average flu season in the U.S. is 36,000 per year. That means when an influenza epidemic drops below 36,000 deaths per year the outbreak is over. This number can be adjusted to a seasonal rate, or an evenly distributed annual rate depending on the circumstances and whose doing the math.
In early July, the CDC quietly announced that upon a review of June COVID death count data, the epidemic was over. While the CDC did not point to a specific date, like June 7th, they pointed out that “Based on death certificate data, the percentage of deaths attributed to pneumonia, influenza or COVID-19 (PIC) decreased from 9.0% during week 25 to 5.9% during week 26, representing the tenth week of a declining percentage of deaths due to PIC.”
Assessing the baseline: The baseline death rate for COVID-19 and other diseases such as influenza and pneumonia typically range from 5% to 7% at the height of flu season. According to the CDC, the coronavirus epidemic is over when the death rate drops below 5.9%, which was achieved in June, which confirms my model’s projection.
The always wrong University of Washington model, that the media depends on for their over-sensationalized hysteria, predicted the epidemic would last past September. The scientific powerhouse known as the University of Pennsylvania’s Wharton School of Business and the federal FEMA models also predicted the epidemic would last into fall.
To be honest, I was a bit unsettled making my bold prediction in mid-May that the coronavirus epidemic would be over on June 7th. Think back to mid-May and the hysteria being propagated by media and agenda-ravaged politicians to get a sense for how outrageous my prediction was. Part of me worried this would be the Waterloo moment when my model betrayed me. But being a man of science, I knew my model was mathematically sound and so I reported my results and stood my ground against nay-sayers. I’m glad I trusted my math and feel vindicated to get confirmation from the CDC; an organization I’ve taken to the woodshed on numerous occasions during this crisis.
President Trump is right, schools should reopen and states that impose facemask mandates should end their shallow farce. The only part of the media and political hysteria I support, is banning professional sports, except hockey. I refuse to submit myself to a bunch of low-educated entertainers wanting to lecture me about my country and my social burdens. After they donate their multi-million dollar contracts to charity, then they can talk to me about social justice.
Ref (1): Kelsey JL, Thompson WD, Evans AS. Methods in observational epidemiology. New York: Oxford University Press; 1986. p. 216
