SARS-CoV-2 Testing Strategies in the Diagnosis and Management of COVID-19 Patients in Low-Income Countries: A Scoping Review

Abstract

The accuracy of diagnostic laboratory tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can impact downstream clinical procedures in managing and controlling the outbreak of coronavirus disease 2019 (COVID-19). To assess the effectiveness of laboratory tools for managing COVID-19 patients in low-income countries (LICs), we systematically searched the PubMed, Embase, Scopus and CINHAL databases for reports published between January 2020 and June 2022. We found that 22 of 1303 articles reported the performance of various SARS-CoV-2 detection tools across 10 LICs. These tools were (1) real-time reverse transcriptase polymerase chain reaction (RT-PCR); (2) reverse transcription loop-mediated isothermal amplification (RT-LAMP); (3) rapid diagnostic tests (RDTs); (4) enzyme-linked immunosorbent assay (ELISA); and (5) dot-blot immunoassay. The detection of COVID-19 is largely divided into two main streams—direct virus (antigen) detection and serology (immunoglobulin)-based detection. Point-of-care testing using antigen-based RDTs is preferred in LICs because of cost effectiveness and simplicity in the test procedures. The nucleic acid amplification technology (RT-PCR and RT-LAMP) has the highest diagnostic performance among the available tests, but it is not broadly used in this context due to costs and shortage of facilities/trained staff. The serology-based test method is affected by antibody interferences and varying amounts of SARS-CoV-2 immunoglobulins expressed at different stages of disease onset. We further discuss the effectiveness and shortcomings of each of these tools in the diagnosis and management of COVID-19. Using the LICs as the study model, our findings highlight ways to improve the quality and turnaround time of COVID-19 testing in resource-constrained settings, notably through local/international collaborative efforts to refine the molecular-based or immunoassay-based testing technologies.