Here is a simple SIR model — Susceptible- Infected- Removed: Here, “removed” can be by recovery or death. Obviously parameters are not exact so the next level would explore randomised changes in possible values and time varying models; noting particular clusters that give dramatic outcomes. The S(t) line is an inverted cumulative case curve — if people don’t flee. So C(t) = 1 – S(t) is cumulative cases, a logistic curve. C(t) will at first look exponential until resistance and running out of susceptible population leads to saturation. A supplementary equation could partition recovery vs death, and we can work back from observed patterns with infection and deaths. Further analysis could stratify the population as susceptibility varies with factors such Read More ›

What is going on? I don’t understand the hysteria that is going on. What am I missing? Let’s get some numbers out there. According to the CDC, from September of last year until the end of February this year, 180 days, 18,000 Americans died of the seasonal flu. Starting with March, we have been on high alert, we have been exercising greater hygiene, and, for the last week, we have been quarantining ourselves and spacing ourselves out (a new meaning to the words “being spaced out”). Yet, the CDC just released new numbers, and, over the last roughly 20 days, 4,000 Americans died of the seasonal flu, while only 140 Americans died of the corona virus. That’s a 30 to Read More ›