Mass testing may be the answer to opening up the US economy and “getting back to normal.” Research done by teams at Stanford, in the US, Israel, India, Austria, Italy, Spain, and Germany, shows that mass testing could make it easier to eradicate COVID-19.
Advanced concepts like group testing, specimen pooling, linear algebra, and optimization make mass testing a reality. These models come from ideas published 80 years ago and have controlled various diseases, such as AIDS, HIV, and other STDs. These innovative testing measures group individuals to find out who among them has the disease, significantly improving our efficiency in this pandemic.
David Donoho is the Anne T. and Robert M. Bass Professor of Humanities and Sciences and Professor of Statistics at Stanford. He, along with Mahsa Lotfi and Batu Ozturkler, recently authored an article in Society for Industrial and Applied Mathematics (SIAM) News, talking about the importance of mass testing and the math behind this development.
With mass testing, scientists strive to make a puzzle out of data with a mathematical solution. In an interview with The Stanford Daily, Donoho explained, “You form pool specimens, where each pool has material from, say, seven people, combined into one pool sample and mixed together, then you test all of your pool specimens. You study which of those specimens get a positive result. Once you know which pools are positive, since you put the patients into the pools and you know which patients are in those pools, you now have a puzzle. Which patients must have been the ones who were infected? If you solve that puzzle, then you know who was infected. There are many ways to set it up and there are many mathematical approaches.”
Because this method revolves around 80-year-old models, researchers needed to find out if the test results would be accurate with a smaller sample amount of virus. In order to determine this, they need to find the sensitivity and specificity of the COVID-19 tests, after one does the math puzzles.
Researchers also had to figure out how the test behaves under dilution. Before research, there were concerns that a patient’s pool specimen would have too-small a percentage of COVID-19 to identify the disease when one test is used for many people. Dohono shared that “The underlying technology is called RT-qPCR and it can detect as little as ten virus particles in a sample. In general if someone were actually infected they would have many more than 10 particles in a sample. Even if there is some dilution, you would still see more than ten.” Potential issues could have arisen from this factor in testing; however, conclusive research has shown that dilution will not affect COVID-19 tests.
Research has created answers to all COVID-19 specific mass testing questions. Once math models identify if someone has COVID-19, that person can self-quarantine. If people are tested more frequently, through mass testing, we avoid the period in which people walk around in an infection state, spreading the disease.
Scientists can mass test because most people in testing groups are not likely to have COVID-19. However, if everyone in a test group has COVID-19, there are still applicable math models that will give patients accurate results. Donoho expanded, stating, “If we are in a situation with a low prevalence rate, then as a rule of thumb, we can get 10 [times] as many people as tests. As prevalence goes up you have to use more tests. There is still a benefit as prevalence goes up, but you have to use fancier and fancier math.” Therefore, testing, even with a higher prevalence of COVID-19, is possible.
On June 16 the FDA made mass testing on a large scale possible by approving pooling. Without FDA approval, only research organizations can perform such testing. As research organizations, Stanford and the University of Nebraska are both leaders in mass testing research. Donoho sighted the medRxiv server as a useful tool because it allowed researchers to share their discoveries quickly.
Following these discoveries, Israel and India have used mass testing to identify and reduce COVID-19 cases. In both places, this method has been very successful, integrating into hospitals and the public health systems there. In the fall, Cornell University plans to open its campus to in-person schooling and use mass testing with its students. Everyone on campus will get tested every five days, with specific high-risk groups, like those involved in healthcare, testing more frequently.
Explaining that mass testing will be possible, Dohono stated, “The response of various private businesses to producing tests has been really amazing, that we are now able to test several percent of the population per month. At low prevalence that means we can test almost the whole population every month, just using current capacity.” American testing capability is currently growing, showing hope for further improvement.
Overall, mass testing will allow America to open up safely. Paul Romer of NYU, who received the 2018 Nobel Prize in Economics, supports mass testing to open the economy and get people back to work. At the moment, with America facing a deep recession, failing businesses, and high unemployment rates, mass testing could be the solution to these issues. Mass testing could also be the solution to opening up schools. Donoho elaborated, stating that right now “students are just not learning. There is plenty of evidence that shows that online-is not working as an instructional technique. Many young people and children are not getting the benefit they should be getting from their formative years,” Donoho explained. “By having mass testing we can confidently reengage in the economy and education.”
(Sources: The Stanford Daily, SIAM News)
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