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FDA authorizes $5 COVID-19 antigen test that's the size of a credit card

FOX News

Fox News Flash top headlines are here. Check out what's clicking on The Food and Drug Administration granted Abbott Technologies emergency use authorization for its $5 COVID-19 antigen test Wednesday saying it's an "important addition to available tests." The test -- which is said to be the size of a credit card -- is the first antigen test where results can be read directly from the testing card, according to the FDA's Wednesday announcement. With no equipment needed, Abbott said, "The device will be an important tool to manage risk by quickly identifying infectious people so they don't spread the disease to others."

COVID-19 testing shifts focus from precision to rapidity

FOX News

Fox News Flash top headlines are here. Check out what's clicking on Public health officials increasingly argue that it is better to get fast and frequent COVID-19 test results that are reasonably accurate than more delayed, precise conclusions. The Wall Street Journal reported Tuesday that diagnostic companies are hurrying to develop quicker and more affordable tests, and those that can be done in offices and nursing homes are becoming more prevalent. Several companies have also started to work on rapid at-home tests, although none are currently authorized for individual use. The U.S. Food and Drug Administration has authorized four antigen-based rapid tests thus far, and test-makers have vowed to produce tens of millions in the next few months.

Using Mathematical Modeling to Simulate an Epidemic


In this article, we'll explore and visualize a classic mathematical model used for modeling the spread of infectious disease: the SIR model. Our goal is to model how these compartments fluctuate over time, and so we'll consider them to be functions with respect to time: The SIRD model considers another compartment (D) for deceased individuals. In the SIR model, the transition between compartments takes the following path: susceptible infectious recovered. Each transition happens at a different rate. The rate at which susceptible individuals come into contact with infectious individuals, thus contracting the disease, is called the infectious rate (β).

Japan eyes introduction of quick coronavirus antigen test

The Japan Times

The health ministry is considering introducing an antigen test to more quickly screen for the new coronavirus amid a rise in the number of people who need testing, government sources said Wednesday. The ministry may approve an antigen test kit in May that uses mucus taken from nose. But as the new test is less precise than the existing polymerase chain reaction test, the dominant testing method which takes hours before results come out, officials will study under what circumstances to use it, they said. The antigen test detects protein unique to the virus and does not need to be conducted at labs like the PCR test, which involves amplifying small amounts of DNA sequences of the virus, a process that conventionally requires four to six hours to produce a result. While methods to shorten the length of the PCR test to about an hour have been developed, there is a growing demand for a simpler and quicker test as the number of people who need to undergo the test has surged in parts of the nation amid the epidemic.

A Partially Observable MDP Approach for Sequential Testing for Infectious Diseases such as COVID-19 Machine Learning

The outbreak of the novel coronavirus (COVID-19) is unfolding as a major international crisis whose influence extends to every aspect of our daily lives. Effective testing allows infected individuals to be quarantined, thus reducing the spread of COVID-19, saving countless lives, and helping to restart the economy safely and securely. Developing a good testing strategy can be greatly aided by contact tracing that provides health care providers information about the whereabouts of infected patients in order to determine whom to test. Countries that have been more successful in corralling the virus typically use a ``test, treat, trace, test'' strategy that begins with testing individuals with symptoms, traces contacts of positively tested individuals via a combinations of patient memory, apps, WiFi, GPS, etc., followed by testing their contacts, and repeating this procedure. The problem is that such strategies are myopic and do not efficiently use the testing resources. This is especially the case with COVID-19, where symptoms may show up several days after the infection (or not at all, there is evidence to suggest that many COVID-19 carriers are asymptotic, but may spread the virus). Such greedy strategies, miss out population areas where the virus may be dormant and flare up in the future. In this paper, we show that the testing problem can be cast as a sequential learning-based resource allocation problem with constraints, where the input to the problem is provided by a time-varying social contact graph obtained through various contact tracing tools. We then develop efficient learning strategies that minimize the number of infected individuals. These strategies are based on policy iteration and look-ahead rules. We investigate fundamental performance bounds, and ensure that our solution is robust to errors in the input graph as well as in the tests themselves.