>>12462190Lets compare to the 2010 H1N1 pandemic
CDC data:
https://www.cdc.gov/flu/about/burden/2010-2011.htmlOkay, now lets consider the terms used in the CDC COVID19 stats. "Infection Fatality Rate" is estimated by adding symptomatic + asymptomatic cases. Essentially, to determine the IFR you have to make a projection on how many people are actually getting infected regardless of symptom onset and test results. The "Survival Rate" is a measure of fatalities vs positively confirmed cases. So while the IFR is an inferential statistic, the survival rate is an empirical statistic insofar as we can rely on the accuracy of the testing method. We shall assume PCR testing is generally reliable as it is not relevant to the comparison being made here.
For the 2010-2011 CDC Influenza season stats, we have "Illness Rate" and "Mortality Rate". Illness rate is an estimate (projection) of influenza cases vs 100,000 population. Mortality rate is determined by comparing deaths with positive influenza diagnoses vs 100,000 population.
So the stats on mortality we have here are slightly different. It would not make sense to compare COVID19 "Survival Rate" with influenza "Mortality Rate", as in this case the "Mortality Rate" of influenza also includes an estimate of asymptomatic or unaccounted (non-treated) cases, which the COVID19 "Survival Rate" does not.
Thus we must compare the COVID19 IFR vs 2010-2011 Influenza mortality rate, as both of these statistics include factor in the estimate for unaccounted (i.e. asymptomatic, non-treated) cases.
In so doing, we see that the COVID19 IFR for ages 70+ is 0.054%, or 54 out of 100,000. The mortality rate for influenza is 62.4 out of 100,000 - meaning, the 2010-2011 influenza was estimated to be MORE DEADLY for older people than COVID19 is currently estimated to be.
"Trust the science" libtards.
Source: data scientist
