The one thing we want to know as the COVID19 virus circumnavigates the globe and ravages the world, is how bad it will get. Risk consequence sits at the forefront of our thoughts as we think about our loved ones, our friends, our neighbours, our lives, and the world at large. How many people will get sick? How many people will die? What’s going to happen? What will happen to the economy?
I had already posted my predictions for the economy back in February, and my next post will likely deal with the economic factors we are facing. I had also created a qualitative risk assessment tool that you can read here. For now, I’d like to focus on the inaccurate science of predictability on COVID19, and how bad this is going to get for us here in the west, as we see the tidal wave moving towards us.
The truth is, it’s impossible to predict with 100 percent accuracy. For that that you’d need a working crystal ball, though I am yet to find one. Algorithmic results are as good as the available data, and the best you can do is use the available data to make the best predictions. Currently the data is very new and still evolving, and there are so many versions of the truth it is virtually impossible to sift through the melee. So, let’s do that here, together.
Predictions are based on the available information we currently have, and we don’t have it all. A lack of rigorous testing in the USA means we do not have an accurate number of Confirmed Cases, which would generally be our jumping off point, to understand the Case Fatality Rate (CFR), but there are other metrics to consider also. We must look at populations, demographics, contact tracing, decision making, and other variables to make good predictions and outcome determinations.
It’s also important to understand that predictions will change dependent on many variables, such as containment measures, availability of health care workers, availability of medical equipment, incubation period, etc. And asymptomatic spreading only amplifies our problem with data variability.
Thus far many are making statistical and mathematical inferences based on assumptions as the data is still emerging and evolving. The danger in dealing with assumptions is it easily leads to hyperbolic or spurious reasoning, without hard facts.
At the same time, we need some indication on how serious this problem really is, how serious it will get, and what will happen.
Here’s a simple mathematical calculation based on available information that illustrates how bad this will get if we do nothing.
Epidemiologist and Professor Dr. Marc Lipsitch, Director of the Center for Communicable Disease Dynamics at Harvard’s School of Public Health stated in February that 40% to 70% of the world’s population is likely to become infected with COVID19 this year. Many are using this metric to gauge the rate of infection.
Taking the median rate of 55% (mid point between 40 and 70), and with the US population being approximately 329.4 million, that would mean over 181 million people would become infected.
A US CDC Report on the management of patients with confirmed COVID19 stated that of the first 44,000 cases in China, 19% of patients were severely or critically ill.
This would mean that of the over 181 million US citizens who would become infected with COVID19, 34.4 million would become severely or critically ill, requiring hospitalization.
An additional insight that prepares us for the coming deluge is to know how many people will die. This statistic, the Case Fatality Rate (CFR) indicates the severity of a disease and is defined as the proportion of reported cases which are fatal within a specified timeframe. The World Health Organization reported the CFR for COVID19 to be 3.4%.
Using the predicted 34.4 million severe cases at a CFR of 3%, this would mean that over 1 million people in the United States would die. Note that the Case Fatality Rate changes based on several factors and can vary greatly among countries.
|Country||Population||Rate of Infection||Severe Cases Requiring Hospitalization||Mortality|
The prediction according to this basic mathematical model and many others’ models is that 1 million people will die in the USA alone. This is the simple math, highly alarming, I agree. And if we were to look at the numbers coming out of China or South Korea, it did not get as bad as the numbers predicted, based on population. And at this date China is not seeing an increase in cases. So, what did they do?
What Can We Do?
let’s build in some measures that will bring down the CFR by reducing the number of infected. By now we’ve all heard of Social Distancing. I’m not a doctor or epidemiologist, but as a layperson we understand the definition and we’ve all seen the following video, which is a great visualization of how to curb the spread.
Quarantine measures and social distancing will help reduce the R-Naught value (R0). The R0 value is defined as the number of people that 1 person can infect. This also varies based on several factors, one of them is social distancing, another is quarantine measures.
The R0 for COVID19 has been estimated to be as high as 2.5.
If we take a simple mathematical calculation using an assumed number of 1000 confirmed cases, by week 10 with a 7 day replication at a R0 of 2.5, we’d have more than 3.8 million infected cases. This would as expected, increase the number of severe cases to just over 724,000 and at a 3% CFR would mean that over 21,700 people would die. By week 15, without any containment or mitigation measures, mortality jumps to over 2 million. Unimaginable!
|NO CONTAINMENT MEASURES|
The Good News
Employing social distancing and quarantine measures will make a huge difference. Let’s say those measures reduce the R0 by 50% down to 1.25. This would make an enormous difference by week 10 in the number of confirmed cases 7,450, severe cases requiring hospitalization 1,415 and deaths down to 42. That is a massive change. A whopping 21,701 lives would be saved.
By week 15, containment measures will save 2 million lives accordingly to this assumptive mathematical model. And therefore, it is a good argument for why we need containment and quarantine measures. The numbers show they work. And they have worked in practice in countries like China and South Korea.
Using the same variables, South Korea based on a population of 51.2 million would have seen a total of over 160,000 deaths. However, South Korea implemented early testing and rigorous containment and mitigation measures. To date (Mar. 17), South Korea has had 8,320 Confirmed Cases and 81 deaths.
So, the good news is, it doesn’t have to get as bad as the mathematical models predict. We must make note of the fact that we are working with unstable data that has many assumptions built in and has considerable variability. Employing containment, social distancing, and other similar measures will shift the R0 considerably and therefore reduce spread, leading to much fewer deaths.
What Could Happen?
Worst case scenario, countries do not take strong measures, thus allowing the virus to run rampant through the population. This action will cause deaths in the millions, destroy the economy, devastate systems as we know it, collapse health care, and create turmoil that will take decades to recover from.
Mid case scenario, we implement strong containment measures to reduce risk to high risk populations, find new ways to manage our lives, online shopping, online work, online education etc. More isolating, but also good risk prevention. The virus will move in waves for a year or so and then dissipate. There will be major disruptions, but not major collapse of our current systems, depending of course on the severity and duration of the pandemic.
Best case scenario, the virus will weaken as it moves through the population and thus become less lethal? Yes, there is a good possibility of that. Viruses, specifically coronaviruses mutate relatively quickly. As they mutate, they often become less lethal and become part of the cycle of illness we are accustomed to, such as the common cold or flu.
According to this study
researchers have identified two separate strains of the virus. The S type being a less aggressive strain having evolved from the more aggressive L strain. The S strain is now more commonly found in patients. However as with all studies and research, there are the debunkers, and this paper has been debunked by other professionals due to its limited scope in the number of patients. Though it does offer a glimmer of hope.
Another pre-print offers similar findings
Though this is not a peer-reviewed paper, and more work is needed, it also offers some hope. According to the science here, COVID19 appears to be following the same evolutionary trajectory as SARS and MERS, which means it will essentially burn itself out as it mutates.
Let’s plan for the worst case scenario, but hope for the best case scenario! What do you foresee on how bad the COVID19 pandemic will get?