Analysis of Testing Accuracy Threshold for COVID-19 through an SIR Computational Model

About the Scholar: Nabo Yu attended The Webb Schools in Claremont, California, in the United States.

The Research:

Early in the COVID-19 pandemic, the accuracy of tests was so variable that some countries chose not to use tests at all, but instead isolate symptomatic individuals. Pioneer scholar Nabo thought computer simulations could shed light on the effects of testing accuracy on the spread of the disease. His SIR model computational calculations confirm that higher testing accuracy can result in reduced disease spread, and show that even lower accuracy testing is useful in slowing the transmission rate. According to Nabo, the model “has possibly offered a basic method of determining acceptable levels of testing accuracy based on the level of social isolation.”

ClientThe Car Rental Co
SkillsPhotography / Media Production
WebsiteGoodlayers.com

Project Title

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