Monthly Archives: March 2020

Corona New York – it’s *really* extreme..!

Posted on March 31, 2020 by swdevperestroika

New York is hit very hard by Corona, we know that. But exactly how hard…? Turns out it’s extremely hard: the number of confirmed corona cases per million habitants in New York is 6 (!) standard deviations over US mean…! … Continue reading →

Posted in Bayes, Data Analytics, Epidemics, PYMC, Society, Statistics | Tagged , , , , | Leave a comment

Corona – New York compared to 10 Countries

Posted on March 31, 2020 by swdevperestroika

New York has been hit hard by Corona. However, it seems that the growth rate  as well as the death rate are now quickly slowing down.

Posted in Data Analytics, Epidemics, Society, Statistics | Tagged , , , | Leave a comment

Bayesian Inference – Corona (Technical)

Posted on March 30, 2020 by swdevperestroika

[This is a technical post. Those of you mainly interested in the daily Corona numbers may want to skip this] Now, after about a month of basically full time Data Analysis of the Corona statistics, perhaps it’s a good point … Continue reading →

Posted in Bayes, Data Analytics, Epidemics, Probability, PYMC, Statistics | Tagged , , , , , | Leave a comment

Corona – estimation of true mortality rate, as of 2020-03-29

Posted on March 29, 2020 by swdevperestroika

Courtesy of my friend Joe Marasco, here’s an update to the Nomogram previously explained here.  

Posted in Data Analytics, Epidemics | Tagged , | Leave a comment

Corona – Trends for 10 selected countries

Posted on March 29, 2020 by swdevperestroika

[Data up until yesterday, GMT, all data from Johns Hopkins CSSE]

Posted in Data Analytics, Epidemics | Tagged , | Leave a comment

Corona – Sweden and Netherlands – the Anomalies

Posted on March 28, 2020 by swdevperestroika

[UPDATE: Added Germany + Canada] [All data from Johns Hopkins CSSE] Noticed a couple of interesting patterns when I put the growth rates for Confirmed and Deceased on the same chart, for a set of countries: Let’s start by looking … Continue reading →

Posted in Bayes, Culture, Data Analytics, Epidemics, Politik, Probability, PYMC, Simulation, Society, Statistics, Sverige | Tagged , , , , , , , , | 2 Comments

Corona Sweden & some selected countries – trends

Posted on March 28, 2020 by swdevperestroika

[All data  obtained from Johns Hopkins CSSE] Data up including yesterday (GMT): Summary: It still looks like the current strategy is working, and the jump in number of deceased over the past few days lead to the limit on people … Continue reading →

Posted in Data Analytics, Epidemics, Research, Statistics | Tagged , , , | Leave a comment

Corona – estimated true mortality rate presented using a Nomogram

Posted on March 27, 2020 by swdevperestroika

My old friend, mentor and former manager Joe Marasco has devised a very cool way to present information on the estimated true mortality rate, using a technique I’d expect very few people under 60 years of age will ever have … Continue reading →

Posted in Data Analytics, Epidemics, Statistics | Tagged , , | 1 Comment

Corona – the “true” mortality rate…?

Posted on March 26, 2020 by swdevperestroika

A new Markov Chain Monte Carlo run on current data, to figure out the likely mortality rate, and the factor of under-estimation of the number of infected. For more info on what this is all about, see my earlier post. … Continue reading →

Posted in Bayes, Data Analytics, Epidemics, Probability, PYMC, Statistics | Tagged , , , , | Leave a comment

Corona Sweden – day of reckoning coming up!

Posted on March 26, 2020 by swdevperestroika

A couple of days ago I pointed out that thus far, Sweden was an anomaly in the Corona dataset: – despite almost no restrictions on daily life – the restaurants and shops are still open, public transportation operates as normally … Continue reading →

Posted in Bayes, Data Analytics, Epidemics, Organization, Politik, Probability, PYMC, Research, Society, Statistics, Sverige | Tagged , , , , , , , , | Leave a comment