Emergence of a Deadly Coronavirus

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REMIND ME AGAIN WHY WE WENT INTO TOTAL LOCKDOWN QUARANTINE MODE!

The Covid-19 modelling that sent Britain into lockdown, shutting the economy and leaving millions unemployed, has been slammed by a series of experts.

Professor Neil Ferguson's computer coding was derided as “totally unreliable” by leading figures, who warned it was “something you wouldn’t stake your life on".

The model, credited with forcing the Government to make a U-turn and introduce a nationwide lockdown, is a “buggy mess that looks more like a bowl of angel hair pasta than a finely tuned piece of programming”, says David Richards, co-founder of British data technology company WANdisco.

“In our commercial reality, we would fire anyone for developing code like this and any business that relied on it to produce software for sale would likely go bust.”

The comments are likely to reignite a row over whether the UK was right to send the public into lockdown, with conflicting scientific models having suggested people may have already acquired substantial herd immunity and that Covid-19 may have hit Britain earlier than first thought. Scientists have also been split on what the fatality rate of Covid-19 is, which has resulted in vastly different models.

Up until now, though, significant weight has been attached to Imperial's model, which placed the fatality rate higher than others and predicted that 510,000 people in the UK could die without a lockdown.

It was said to have prompted a dramatic change in policy from the Government, causing businesses, schools and restaurants to be shuttered immediately in March. The Bank of England has predicted that the economy could take a year to return to normal, after facing its worst recession for more than three centuries.

The Imperial model works by using code to simulate transport links, population size, social networks and healthcare provisions to predict how coronavirus would spread. However, questions have since emerged over whether the model is accurate, after researchers released the code behind it, which in its original form was “thousands of lines” developed over more than 13 years.

In its initial form, developers claimed the code had been unreadable, with some parts looking “like they were machine translated from Fortran”, an old coding language, according to John Carmack, an American developer, who helped clean up the code before it was published online. Yet, the problems appear to go much deeper than messy coding.

Many have claimed that it is almost impossible to reproduce the same results from the same data, using the same code. Scientists from the University of Edinburgh reported such an issue, saying they got different results when they used different machines, and even in some cases, when they used the same machines.

“There appears to be a bug in either the creation or re-use of the network file. If we attempt two completely identical runs, only varying in that the second should use the network file produced by the first, the results are quite different,” the Edinburgh researchers wrote on the Github file.

After a discussion with one of the Github developers, a fix was later provided. This is said to be one of a number of bugs discovered within the system. The Github developers explained this by saying that the model is “stochastic”, and that “multiple runs with different seeds should be undertaken to see average behaviour”.

However, it has prompted questions from specialists, who say “models must be capable of passing the basic scientific test of producing the same results given the same initial set of parameters...otherwise, there is simply no way of knowing whether they will be reliable.”

It comes amid a wider debate over whether the Government should have relied more heavily on numerous models before making policy decisions.

Writing for telegraph.co.uk, Sir Nigel Shadbolt, Principal at Jesus College, said that “having a diverse variety of models, particularly those that enable policymakers to explore predictions under different assumptions, and with different interventions, is incredibly powerful”.

Like the Imperial code, a rival model by Professor Sunetra Gupta at Oxford University works on a so-called "SIR approach" in which the population is divided into those that are susceptible, infected and recorded. However, while Gupta made the assumption that 0.1pc of people infected with coronavirus would die, Ferguson placed that figure at 0.9pc.

That led to a dramatic reversal in government policy from attempting to build “herd immunity” to a full-on lockdown. Experts remain baffled as to why the government appeared to dismiss other models.

“We’d be up in arms if weather forecasting was based on a single set of results from a single model and missed taking that umbrella when it rained,” says Michael Bonsall, Professor of Mathematical Biology at Oxford University.

Concerns, in particular, over Ferguson’s model have been raised, with Konstantin Boudnik, vice-president of architecture at WANdisco, saying his track record in modelling doesn’t inspire confidence.

In the early 2000s, Ferguson’s models incorrectly predicted up to 136,000 deaths from mad cow disease, 200 million from bird flu and 65,000 from swine flu.

“The facts from the early 2000s are just yet another confirmation that their modeling approach was flawed to the core,” says Dr Boudnik. “We don't know for sure if the same model/code was used, but we clearly see their methodology wasn't rigourous then and surely hasn't improved now.”

Source: Modelling That Led To Lockdown Was ‘Totally Unreliable’ And A ‘Buggy Mess’, Say Experts

In the history of the expensive software mistakes, Mariner 1 was probably the most notorious. The unmanned spacecraft was destroyed seconds after launch from Cape Canaveral in 1962 when it veered dangerously off-course due to a line of dodgy code.

But nobody died and the only hits were to NASA’s budget and pride. Imperial College’s modelling of non-pharmaceutical interventions for Covid-19 which helped persuade the UK and other countries to bring in draconian lockdowns will supersede the failed Venus space probe could go down in history as the most devastating software mistake of all time, in terms of economic costs and lives lost.

Since publication of Imperial’s microsimulation model, those of us with a professional and personal interest in software development have studied the code on which policymakers based their fateful decision to mothball our multi-trillion pound economy and plunge millions of people into poverty and hardship. And we were profoundly disturbed at what we discovered. The model appears to be totally unreliable and you wouldn’t stake your life on it.

First though, a few words on our credentials. I am David Richards, founder and chief executive of WANdisco, a global leader in Big Data software that is jointly headquartered in Silicon Valley and Sheffield. My co-author is Dr Konstantin ‘Cos’ Boudnik, vice-president of architecture at WANdisco, author of 17 US patents in distributed computing and a veteran developer of the Apache Hadoop framework that allows computers to solve problems using vast amounts of data.

Imperial’s model appears to be based on a programming language called Fortran, which was old news 20 years ago and, guess what, was the code used for Mariner 1. This outdated language contains inherent problems with its grammar and the way it assigns values, which can give way to multiple design flaws and numerical inaccuracies. One file alone in the Imperial model contained 15,000 lines of code.

Try unravelling that tangled, buggy mess, which looks more like a bowl of angel hair pasta than a finely tuned piece of programming. Industry best practice would have 500 separate files instead. In our commercial reality, we would fire anyone for developing code like this and any business that relied on it to produce software for sale would likely go bust.

The approach ignores widely accepted computer science principles known as "separation of concerns", which date back to the early 70s and are essential to the design and architecture of successful software systems. The principles guard against what developers call CACE: Changing Anything Changes Everything.

Without this separation, it is impossible to carry out rigorous testing of individual parts to ensure full working order of the whole. Testing allows for guarantees. It is what you do on a conveyer belt in a car factory. Each and every component is tested for integrity in order to pass strict quality controls.

Only then is the car deemed safe to go on the road. As a result, Imperial’s model is vulnerable to producing wildly different and conflicting outputs based on the same initial set of parameters. Run it on different computers and you would likely get different results. In other words, it is non-deterministic.

As such, it is fundamentally unreliable. It screams the question as to why our Government did not get a second opinion before swallowing Imperial's prescription.

Ultimately, this is a computer science problem and where are the computer scientists in the room? Our leaders did not have the grounding in computer science to challenge the ideas and so were susceptible to the academics. I suspect the Government saw what was happening in Italy with its overwhelmed hospitals and panicked.

It chose a blunt instrument instead of a scalpel and now there is going to be a huge strain on society. Defenders of the Imperial model argue that because the problem - a global pandemic - is dynamic, then the solution should share the same stochastic, non-deterministic quality.

We disagree. Models must be capable of passing the basic scientific test of producing the same results given the same initial set of parameters. Otherwise, there is simply no way of knowing whether they will be reliable.

Indeed, many global industries successfully use deterministic models that factor in randomness. No surgeon would put a pacemaker into a cardiac patient knowing it was based on an arguably unpredictable approach for fear of jeopardising the Hippocratic oath. Why on earth would the Government place its trust in the same when the entire wellbeing of our nation is at stake?

Source: Neil Ferguson's Computer Model Could Be The Most Devastating Modelling Mistake Of All Time

The weather is about perfect right now for me. 82 degrees outside and 75 degrees inside with a humidity of 51%. Right in the middle of the 45 to 55 percent range suggested by that article.

Every business needs to look at the demographics of its work force. Those that depend on skilled older workers have to be much more cautious than those who don't have to spend months looking for suitable replacments.

NEW INNOVATIVE TECHNOLOGY NOT WRAPPED INTO LATEST CDC GUIDELINES

The Centers for Disease Control and Prevention released a set of documents on Thursday designed to provide guidance on how child care centers, schools, restaurants and bars, and other establishments could begin the process of reopening in the face of the coronavirus.

The "decision tools" the agency released recommend that all workplaces hold off on reopening unless they are ready to protect employees at higher risk for severe illness, including those 65 and older and people of all ages with underlying medical conditions.

But the guidelines fall short because it failed to incorporate technology and industry solutions:

They could upgrade to antimicrobial surfaces, including doorknobs, computer keyboards, handrails and other frequently touched surfaces.

Numerous studies show how viral traces deposited on a doorknob can be spread by touch, infecting many people in just a few hours.

Copper naturally destroys viruses and bacteria. Several manufacturers produce molded polymer products embedded with copper, including desktops, keyboards and chair arms.

Antimicrobial coatings can also be painted on existing floors, furniture and equipment. All of these high-tech approaches are already used in hospitals. Now is the time to inform the public about their usefulness in combatting the coronavirus.

The CDC also recommends that schools, offices and other venues open windows and doors to increase air circulation.

Research finds that air conditioning can spread viral droplets from an infected person to other people across the room, depending on the direction of the airflow. Bringing in fresh air is better.

Makes sense, but opening the windows is not always an option. The agency should at least mention that there are more effective options available, including continuous, nontoxic disinfection devices [UVC Light Sanitizers] that can be installed in the HVAC system.

These technologies are already used by professional sports teams in their locker rooms, and by manufacturers and hospitals. They deactivate viruses in the air and reduce traces of virus or bacteria on surfaces.

The CDC guidelines never once mention public restrooms. But reducing the risk of viral spread when toilets are flushed is important. The key is to be sure all toilets have lids.

Research indicates that coronavirus is carried in feces. When a toilet is flushed, the virus can become aerosolized. New findings in the journal Emerging Infectious Diseases suggest the virus is found in heavy concentrations in restrooms.

Source: Latest CDC coronavirus guidelines shun technology and industry solutions

How do convince management to invest in things like copper railings if they don't believe in science?
We are talking about a capital investment that has to be approved by the bean counters.

China confirms US accusations that it destroyed early samples of the novel coronavirus, but says it was done for 'biosafety reasons'

China has confirmed that it had ordered unauthorized laboratories to destroy samples of the new coronavirus but insisted that it was due to "biosafety reasons."

The announcement comes after Secretary of State Mike Pompeo has repeatedly said that China refused to give virus samples taken from patients infected with COVID-19 in late December last year and that officials had destroyed early samples, according to South China Morning Post.

Liu Dengfeng, an official with the Chinese National Health Commission's science and education department, said in a Beijing briefing on Friday that the samples were destroyed to "prevent the risk to laboratory biological safety and prevent secondary disasters caused by unidentified pathogens."

He insisted that this was not done to cover-up or hide samples from other countries, but was done strictly for biosafety reasons."The remarks made by some US officials were taken out of context and intended to confuse," Liu said.

https://www.businessinsider.com/china-c ... rus-2020-5

I believe it and I know about medical malpractice from personal experience and my mom's anecdotes, my XH's mom's first-born was also delivered with what was believed to be totally avoidable issues at birth, malpractice, that affected his brain --doctor later caught and suspended for malpractice having done it to many others and finally having a case against them

what she is relaying sounds like 100% intentional malpractice.