I first posted "Covid Math" on April 13th of 2020. These were using the statistics known at the time to determine the potential severity of #Coronavirus / #CoVid19 / Sars-CoV-2 / China-Virus, or whatever you want to call it. I am returning to this post in September, after five months, to see how things have held up as predictions. Feel free to read the previous posts and the comparative backgrounds of influenza and H1N1, as I won't be rehashing that data here.
"Finally, what we know of Coronavirus so far"
Again, we are going to use the same data point, but update it with what we know now. So, we still don't know the assumed cases, but we might be able to estimate it better. We have really accurate confirmed cases, hospitalizations, and deaths.
Note: There are still questions about the number of deaths. Some are saying many deaths are not attributable to Covid. Recently, the CDC made a statement that only 6% of recorded Covid deaths were strictly caused by Covid, and the other 94% had comorbidities. I will NOT be separating these at this time. My rationale is that we don't know with any high degree of certainty that those comorbidities would have killed the person if they had not contracted Covid. If they would have lived six months or six years with those other issues, then Covid hastened their demise, and I will not try to parse which issue was the ultimate cause of their death. For instance: an obese person with diabetes and heart issues is likely to die early. If they contract Covid and die, was it the Covid, the diabetes, or the heart issue? If they didn't have those other issues, would they have survived Covid? These are questions we are unable to answer at this time, and we likely will never have an answer. Deaths = deaths.
Covid-19 numbers (as of 9/9/2020):
Medical visits (confirmed tests) - 6,334,158
Hospitalizations - 379,866
Deaths - 189,972
Population (est.) - 318,000,000
In the previous post, I extrapolated out the hospitalizations for a year to be about 374,524. Yet here we are at only 8 months and we have already exceeded that estimate. If we (again) do a simple (linear) extrapolation to one year, we will have had 569,799 hospitalizations. That is nearly twice my original estimate.
If we had extrapolated, again simply (linear), the previous deaths of 22,154 would have been 88,616 deaths, which we are FAR past that number. So we see that the numbers we had early on had not proceeded in a linear fashion, which is to be expected with a virus with a Rate of Infection (R0) of greater than 1.0.
If we compare these numbers back to the H1N1 and seasonal flu, we need to compare the death rates:
Known cases:
Seasonal flu - 38,230 deaths / 29,220,523 cases = 0.13%
H1N1 - 12,469 deaths / 60,800,000 cases = 0.02%%
Covid - 189,972 / 6,334,158= 3.0%
Hospitalized deaths:
Seasonal flu - 38,230 deaths / 496,912 hospitalizations = 7.69%
H1N1 - 12,469 deaths / 274,304 hospitalizations = 4.55%
Covid - 189,972 / 379,866 = 50%
To compare this to the previous post's estimates, the Covid case mortality was previously calculated at 1.98%, and it is now at 3.0%. An additional one-percent morality is pretty serious.
If we continue to assume that cases will continue to increase for the remainder of the year (or until a widely accepted vaccine is available), then we will have to make an assumption of total cases. Again, I will use simple (linear) extrapolation, even though it has been shown to be inaccurate. The reason for this is because new cases appear to be trending downward, so hopefully the estimate will turn out to be higher than what we end up with. I hope.
Extrapolated 1-year total cases: 9,501,237
Extrapolated 1-year hospitalizations: 569,799
Extrapolated 1-year deaths: 284,958
This is FAR below the worst-case estimates of the April post. We will have far fewer than the 80 million cases predicted. It will be far below the H1N1 60 million cases. It will be fewer than the 29 million cases of seasonal influenza. But because the death rate is higher than anticipated, the case fatality rate will be higher than the original extrapolation, yet lower than the worst-case estimates.
source:
https://gis.cdc.gov/grasp/COVIDNet/COVID19_3.html
https://coronavirus.jhu.edu/map.html
https://ycharts.com/indicators/us_coronavirus_hospitalizations