Update 17-Jan-2021: This is too important to let politics or vested interests get in the way! The real roadblock is getting validated data from hospitals and other testing facilities. Apparently arguments about ethics, privacy and other topics are gumming up the works. To me, this is sounds like an excuse. If you want to find a solution to this problem, you can! I have updated the appeal to include calls to health authorities and the researchers to find ways to make this happen. How can you cooperate more effectively? How can you crowdsource validated data without official cooperation?
In December, health authorities in Canton Graubunden announced that they were able to reduce the number of weekly infections by 73% in just one week! 
Imagine if we could do that everywhere, every week. For Switzerland, a weekly 73% drop would mean going from 20,000 new cases per week  to under 10 cases per week in just 7 weeks. Even the USA could go from 1.8 million cases per week  to under 10 cases per week in just 11 weeks!
Today that seems like an impossible dream. The data confirms our attempts to combat the spread of the COVID have not been very successful. For lack of better alternatives, slowdowns, shutdowns and lockdowns seem to be the only tools available to our health authorities, even though they come at huge cost to society.
We can make this dream a reality. This article identifies the “points of light” that will make it possible. All we have to do is connect the dots.
The “R-Values” measure how effectively the virus spreads. A value of 1 means the virus passes itself itself on to one other person. Its population remains constant. A value greater than 1 means the virus is spreading, and a value below one means the virus is dying out.
In February, COVID was spreading in Switzerland without resistance. Each infected person passed the disease to up to four other people! To avert a total breakdown of the health care system, the government first asked people to (1) wash their hands and observe other hygiene measures, then, two weeks later, (2) ordered a complete shutdown.
What impact did these measures have on the spread of Corona? Very little! The trend in R-Values was already going down before the measures were put into effect, and continued to decline at the same rate afterwards, until hitting a floor around 1.0, where, except for some blips, the level has stabilized.
The measures were not totally without impact. In particular, the reopening of schools and businesses (4) had some effect, and allowing large events (5) caused the R-Values to go up way up, due to super-spreader events they enabled. The evidence is strong that big events should be curtailed.
What’s not working? Wearing masks, contact tracing, the COVID app and our current approach to testing don’t seem to be up to the task of eradicating the virus. Most of the time, we are keeping the R-Value close to one, but just barely. When the measure fail, the R-Values go up, and the infection numbers go quickly through the roof. Most likely, the reaction times are too slow for these measures to be really effective. If people are contacted, by the time they are contacted, they have already spread the disease.
In short, slowdowns, shutdowns and lockdowns are barely sufficient to contain the disease now, and the new “English” variant looks even more contagious. How can we beat this disease?
In Switch, How to Change When Change is Hard, authors Chip Heath and Dan Heath described a case about solving the problem of child malnutrition in Vietnam, which was once widespread. By identifying children who weren’t malnourished, the social workers could identify ways to properly nourish children that were both viable, that is they worked, and acceptable, that is would be accepted as “our” solution by Vietnamese parents rather than an alien approach imposed from outside. Heath and Heath called this approach “Points of Light.”
I have been following the developments around COVID-19 since it broke on the scene in March. I believe I have identified two points of light. If we can connect the dots, we can eliminate COVID, and we can do it quickly!
In December, health authorities in Graubunden, Switzerland reported that they had reduced daily infections by 73% in one week! How did they do it? They tested the entire population. Many people had no symptoms but were contagious anyway. They isolated everybody who tested positive.
This is a point of light in an otherwise dark, depressing landscape. We’ve done it before. We can do it again. Test everybody. Isolate those who are infected. If we could do this everywhere, every week, we could virtually eliminate the disease in no time!
What would happen if this success could be repeated everywhere, every week? In Switzerland, the virus would be virtually eliminated in about 7 weeks. In the USA, with about 1’800’000 new infections per week, it would take about 11 weeks.
What makes it hard to do this everywhere? Tests are expensive and need specialists to perform them. If each test costs $200 and takes 24 hours (the current list price at the University Hospital in Zurich), the cost of testing the entire population even just once is prohibitive; the cost to do it on a weekly or daily basis would be unsustainable. Such tests cannot be used at the turnstile, both because of the costs and because the response times are too slow.
What if a COVID test were so cheap and so easy that anybody could give the test as often as needed? What if it were so fast, you could use it like a ticket at the turnstile? Only let people get close to you if they are free of the disease.
With a fast, cheap, and easy test, you could test anybody, any time. You could check guests before you let them in your home. You could check passengers before they board an airplane. You could check staff before they start work. If you had high confidence that the people around you were free of COVID, you could meet, sing, party, conduct business and travel normally. COVID wouldn’t have a chance and life would go back to normal.
According to various news reports, there is an app for that. Researchers from at least three major universities (EPFL , MIT  and CMU ) have created AI-based programs that listen to your cough and diagnose whether your have COVID. The MIT project has reported accuracy comparable to the $200-PCR test. The apps should be just around the corner. They could be installed on your phone. They could be free.
Except that was months ago. Why aren’t these testing tools available? When can we download them to our phones? There are many possible explanations. The teams might challenged by actually creating a releasable product. The regulatory authorities might be dragging their feet on approval. Pharma companies looking to make billions on tests and vaccines might be putting sand in the gears of the regulators. Maybe the tech giants are wrestling for control over the data to be generated. Maybe the tests don’t actually work that well.
I have since received information about the real impediments to success from one of the research projects. Getting validated data (cough samples and confirmed test results) is a challenge. The health institutions seem interested, but can’t get past various internal objections, so the cooperation doesn’t happen. No sample data, no AI-based app. No app, and Corona rages on.
It’s time to connect the dots! These apps can change the course of the pandemic. We need them, and we need them now!
If you are working on one of these research projects, I call on you to focus on getting the fruits of your research into the app stores. If the institutions won’t cooperate, get creative and look for alternatives, like crowdsourcing, to get the data you need. Above all, ask for the help! The right people can open doors for you. Make sure people understand why this work is so important!
If you are a public health agency, I call on you to reach out to these research projects and find out how they can help you and us eliminate COVID now! Support their work, and incorporate these ideas into your planning. Forget lockdowns – test often! Employ strategies that bring results quickly without shutting down the economy.
The whole world can become a COVID test center, at virtually no cost.
If these apps are free then anybody can use them. If these apps respect patient privacy, people can use them without fear. The more people can protect themselves, their families and their schools just by using an app, the quicker Coronavirus will disappear from our radar screen.
Preventing the virus from spreading from one individual to another takes away the air it needs to survive. If someone contracts the disease, either they recover or they die from it. Either way, that instance of the virus dies. The only way for the virus survive is to infect other hosts.
If every smartphone can become a free testing center, then everyone can test themselves or the people who come into their homes, stores and office. Just ask them to cough into the phone — if you get a green light, it’s okay to let them in. Get a red light, then ask them to go home and take care of themselves. If you test positive, stay home.
This is mass testing with all the dials turned up to eleven! This will take away the air from the virus and it will die quickly.
We can shut down COVID in time for Spring vacation, Summer vacation at the latest. We have the tools. We just need to make them happen.
 Corona-Zahlen sinken nach Flächentests, (all sources retrieved January 14, 2021)
 Die neusten Zahlen zur Corona-Pandemie
 United States COVID-19 Cases and Deaths by State
 Die neusten Zahlen zur Corona-Pandemie
 Artificial intelligence model detects asymptomatic Covid-19 infections through cellphone-recorded coughs
 Coronavirus Detected By Voice? Carnegie Mellon Researchers Develop App To ‘Listen’ For Signs Of COVID-19
 COVID-19 Artificial Intelligence Diagnosis using only Cough Recordings
|cookielawinfo-checkbox-advertisement||1 year||Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Advertisement" category .|
|cookielawinfo-checkbox-analytics||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".|
|cookielawinfo-checkbox-functional||11 months||The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".|
|cookielawinfo-checkbox-necessary||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".|
|cookielawinfo-checkbox-others||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.|
|cookielawinfo-checkbox-performance||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".|
|mailchimp_landing_site||1 month||The cookie is set by MailChimp to record which page the user first visited.|
|CONSENT||2 years||YouTube sets this cookie via embedded youtube-videos and registers anonymous statistical data.|
|_ga||2 years||The _ga cookie, installed by Google Analytics, calculates visitor, session and campaign data and also keeps track of site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognize unique visitors.|
|_gat_gtag_UA_42152348_1||1 minute||Set by Google to distinguish users.|
|_gcl_au||3 months||Provided by Google Tag Manager to experiment advertisement efficiency of websites using their services.|
|_gid||1 day||Installed by Google Analytics, _gid cookie stores information on how visitors use a website, while also creating an analytics report of the website's performance. Some of the data that are collected include the number of visitors, their source, and the pages they visit anonymously.|
|NID||6 months||NID cookie, set by Google, is used for advertising purposes; to limit the number of times the user sees an ad, to mute unwanted ads, and to measure the effectiveness of ads.|
|test_cookie||15 minutes||The test_cookie is set by doubleclick.net and is used to determine if the user's browser supports cookies.|
|VISITOR_INFO1_LIVE||5 months 27 days||A cookie set by YouTube to measure bandwidth that determines whether the user gets the new or old player interface.|
|YSC||session||YSC cookie is set by Youtube and is used to track the views of embedded videos on Youtube pages.|
|yt-remote-connected-devices||never||YouTube sets this cookie to store the video preferences of the user using embedded YouTube video.|
|yt-remote-device-id||never||YouTube sets this cookie to store the video preferences of the user using embedded YouTube video.|
|COMPASS||1 hour||No description|
|cookies.js||session||No description available.|
|S||1 hour||No description available.|