new coronavirus outbreak China, Korea, USA - mod warnings in OP (updated 24/02/20)

A statistical analysis of China’s coronavirus casualty data shows a near-perfect prediction model that data analysts say isn’t likely to naturally occur, casting doubt over the reliability of the numbers being reported to the World Health Organization. That’s aside from news on Thursday that health officials in the epicenter of the outbreak reported a surge in new infections after changing how they diagnose the illness.

…the number of cumulative deaths reported is described by a simple mathematical formula to a very high accuracy, according to a quantitative-finance specialist who ran a regression of the data for Barron’s. A near-perfect 99.99% of variance is explained by the equation, this person said.

Put in an investing context, that variance, or so-called r-squared value, would mean that an investor could predict tomorrow’s stock price with almost perfect accuracy. In this case, the high r-squared means there is essentially zero unexpected variability in reported cases day after day.

Barron’s re-created the regression analysis of total deaths caused by the virus, which first emerged in the central Chinese city of Wuhan at the end of last year, and found similarly high variance. We ran it by Melody Goodman, associate professor of biostatistics at New York University’s School of Global Public Health.

“I have never in my years seen an r-squared of 0.99,” Goodman says. “As a statistician, it makes me question the data.”

Real human data are never perfectly predictive when it comes to something like an epidemic, Goodman says, since there are countless ways that a person could come into contact with the virus.

For context, Goodman says a “really good” r-squared, in terms of public health data, would be a 0.7. “Anything like 0.99,” she said, “would make me think that someone is simulating data. It would mean you already know what is going to happen.”There’s one scenario where the data could be understandably jiggered, Goodman said. Because there are privacy concerns around public health data, it’s conceivable that someone would simulate the data based on real data, so as to make the individuals unidentifiable. But even then, the r-squared in this case is extraordinarily high. Moreover, says Goodman, when data are manipulated to protect privacy, it would need to be disclosed; there is no such disclosure on the WHO site.


https://www.macrobusiness.com.au/2020/02/parasite-vs-virus-tourism-demands-re-opening-to-china/
https://www.barrons.com/articles/chinas-economic-data-have-always-raised-questions-its-coronavirus-numbers-do-too-51581622840

Good graphs here, especially the ones with lag for deaths

https://nucleuswealth.com/articles/updated-coronavirus-statistics-cases-deaths-mortality-rate/