AI-defined COVID-19 testing strategy could lead to fewer infections
When the novel coronavirus pandemic spread across the globe, governments and institutions worldwide faced hard decisions about who to test for the virus and when with limited testing supplies.
Now, a new algorithm developed by researchers at Penn State’s College of Information Sciences and Technology could help leaders make better informed decisions on how many symptomatic and asymptomatic individuals to test with rationed daily tests, and at what stage of the pandemic. The model’s simulated testing strategies resulted in approximately 40% fewer infections.
“Our goal was to find out how do you distribute an allocation of tests that you have every day,” said Amulya Yadav, PNC Technologies Career Development Assistant Professor at the College of IST. “How do you distribute them among symptomatic and asymptomatic people? And how should this allocation change over time?”
AI-defined COVID-19 testing strategy could lead to fewer infections
A new algorithm developed by researchers at the College of Information Sciences and Technology could help leaders of governments and organizations make better informed decisions on how many symptomatic and asymptomatic individuals to test for COVID-19 with a limited supply of daily tests, and at what stage of the pandemic.
Image: Adobe Stock: Giovanni Cancemi
AI-defined COVID-19 testing strategy could lead to fewer infections
January 21, 2021
UNIVERSITY PARK, Pa. When the novel coronavirus pandemic spread across the globe, governments and institutions worldwide faced hard decisions about who to test for the virus and when with limited testing supplies.
Date Time
AI-defined COVID-19 testing strategy could lead to fewer infections
A new algorithm developed by researchers at the College of Information Sciences and Technology could help leaders of governments and organizations make better informed decisions on how many symptomatic and asymptomatic individuals to test for COVID-19 with a limited supply of daily tests, and at what stage of the pandemic.
Image: Adobe Stock: Giovanni Cancemi
When the novel coronavirus pandemic spread across the globe, governments and institutions worldwide faced hard decisions about who to test for the virus – and when – with limited testing supplies.
Now, a new algorithm developed by researchers at Penn State’s College of Information Sciences and Technology could help leaders make better informed decisions on how many symptomatic and asymptomatic individuals to test with rationed daily tests, and at what stage of the pandemic. The model’s simulated testing strategies resulted in approximately