April 10, 2020
“New York is Flattening the Curve”…[here]
Computer models should always be treated with a certain amount of circumspection. Especially when decisions of huge importance are mooted.
Of late, we have been treated to a plethora of projections for the likely, and possible unlikely, outcomes for deaths due to the covid-19 virus. The widely varying predictions depend greatly on the algorithms running on the computer and the values of the parameters being used to produce predictions.
The output is simply that—a prediction. Not data. Further, the predictions can vary between huge limits depending on the input. They can and do also vary hugely because the output is hugely sensitive to the values of R-naught, the infection parameter, which is not simply a function of the pathogen, but of human behavior and the social response to the spread.
The graphs above show how wide the variations can be. What does this mean? Basically, nobody really knows what is going to happen. However, some of the data tends to support the notion that this won’t turn out to be as bad as the most dire predictions projected. That may be because the fraction of the population that has antibodies is much higher than previously believed. According to some very recent work may be 30 to 50% of the population has antibodies. If so, then there are large numbers of people who are ready to be de-isolated and get back to work. However, massive antibody testing is required to really determine this. Ideally, of course, a DIY pin-prick blood test that can be done at home is required. Centralized testing is definitely not the way to go, as shown by the British NHS failure. That failure should lead to a massive re-think concerning a government-centralized health system.
For current updates and access to the best science work see the MRC Centre for Global Infectious Disease Analysis at Imperial College, London,…[here]
For world-wide data and modeling and detailed hospital data see IMHE, the Institute for Health Metrics and Evaluation: https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/covid-19-weekly-forecasts/week-07-04-2020/ to download it all in Excel format.
For the latest preprints see bioRxiv at https://connect.biorxiv.org/relate/content/181
On the politics front, there is a very revealing article on politico.eu https://www.politico.eu/article/coronavirus-europe-failed-the-test/?utm_source=pocket-newtab (believe it or not) about the colossal failure of the EU bureaucracy to appreciate the oncoming tsunami, despite intensive warning from medical professionals. The focus of the politicians is always on fantasy, always on the slogans of the self-assured, the “science is settled” Al Gore types, rather than on the facts in the real world. They, and we, are all paying the price now.
And lastly, for your enjoyment, a list of the many Fake News media lies in their attempts to denigrate President Trump…[here]
And from Brad Spellberg in Clinical Infectious Diseases, July 2008,
Dr. William H. Stewart was the US Surgeon General during 1965–1969 . Despite his significant accomplishments, Dr. Stewart is remembered primarily for his infamous statement: “It is time to close the book on infectious diseases, and declare the war against pestilence won” . Depending on the source, the quote is dated to 1967 or 1969. Infectious diseases specialists, including myself [3, 4], have repeated this quote innumerable times to underscore how wrong it was.
Famous last words.