Validation of rapid, molecular testing for COVID-19 and integration with TB diagnostics

We are living in a world severely disrupted by the COVID-19 pandemic, but it is critical we do not neglect other diseases that persist outside of the global spotlight. Losing progress against the worldwide tuberculosis (TB) epidemic would mean adding to the 1.5 million TB-related deaths reported each year, but it is not inevitable. The symptoms for COVID-19 and TB are similar, with fever and cough both frequently observed. As such, integrating COVID-19 and TB testing is an opportunity to improve the quality of patient care by taking advantage of already-existing infrastructure. One example is GeneXpert, a diagnostic platform proven to be effective in low- and middle-income countries (LMICs) for TB diagnosis. The TB test, Xpert MTB/RIF, rapidly detects TB with high accuracy. Recently, a COVID-19 test, Xpress SARS-CoV-2, received FDA emergency use authorization for use on the GeneXpert platform. This is a promising development, particularly for LMICs with extensive GeneXpert networks already in place, but the test's diagnostic accuracy is unknown. We propose a validation study of Xpress SARS-CoV-2 to evaluate its diagnostic accuracy in Peru, a middle-income country already using GeneXpert. After obtaining an estimate of the test's performance, we will assess the feasibility of integrating testing for COVID-19 and TB on the GeneXpert platform. Namely, we will collect one sputum sample from individuals presenting with clinical symptoms typical to COVID-19 and TB, and test them using Xpress SARS-CoV-2 and Xpert MTB/RIF, respectively. We expect that the amount of COVID-19 and TB detected will be similar to what we would have detected with complete but time-consuming diagnostic work-ups for each disease. Testing for two diseases with common symptoms in one clinical interaction will be convenient for patients and healthcare workers. Having rapidly available diagnostic data will facilitate a more timely response for patient care and, ultimately, population-level planning.