Application of Pooled Testing Methodologies in Tackling the COVID-19 Pandemic

Abstract

The recent emergence of the COVID-19 pandemic has posed a healthcare challenge, as well as an economic threat to the world. The situation is even worse for the developing nations like India. Diagnostic tests are fundamental to the ability to detect and respond to the disease. However, finding adequate resources for that has proved to be a significant challenge. As a solution, a pooling approach for the diagnostic tests is proposed in the literature and the media. In this article, we explore several algorithms for pooling samples to reduce the number of such diagnostic tests. Through a comparative study, we look at their relative performance at different disease prevalence levels. We also discuss the impact of the sensitivity and specificity of the tests. In the context of using the quantitative reverse-transcription polymerase chain reaction (RT-qPCR) tests for diagnosing COVID-19 cases in India, we discuss the feasibility of using the pooling algorithms and possible avenues to improve their effectiveness.