SIAM Mathematics of Data Science (MDS20) Distinguished Lecture Series: David L. Donoho

/ May 19, 2020/

A Mathematical Data Scientist’s perspective on Covid-19 Testing Scale-up

Abstract: Paul Romer, the former Chief Economist of the World Bank and
Nobel Prizewinner in Economics, wants to spend more than 100
billiion dollars this year to test every American for Covid-19 twice monthly.
This would require an unprecedented scaling up of our virus testing capability and
in Romer’s view require building out totally new national capabilities based on
unproven new technologies.

There is another way. During the peak of the Covid-19 shutdown
during March through April, a number of
talented and driven teams spread around the world demonstrated in principle
methods enabling existing testing technology based on RT-qPCR to
service significantly larger testing volumes by sophisticated multiplexing/pooling
methods involve combinatorial designs and mathematically minded
algorithms, in some situations delivering 10X as many patients evaluated
for a given base testing capability.

In my talk I will mention a number of the efforts going on, a number of the
approaches being tried, and the underlying technological issues that are important.

This is a survey talk, not concerning my own work.

David L. Donoho, Stanford University, U.S.

This is one of seven virtual plenary talks originally scheduled for the 2020 SIAM Conference on Mathematics of Data Science. For more information on this session, visit https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=69231. To view the virtual program and register for other invited plenary talks, minitutorial talks, and minisymposia, please visit the MDS20 website at https://www.siam.org/conferences/cm/conference/mds20