SARS-CoV-2 has surged across the globe causing the ongoing COVID-19 pandemic. Systematic testing to facilitate index case isolation and contact tracing is needed for efficient containment of viral spread. The major bottleneck in leveraging testing capacity has been the lack of diagnostic resources. Pooled testing is a potential approach that could reduce cost and usage of test kits. This method involves pooling individual samples and testing them ‘ en bloc ’. Only if the pool tests positive, retesting of individual samples is performed. Upon reviewing recent articles on this strategy employed in various SARS-CoV-2 testing scenarios, we found substantial diversity emphasizing the requirement of a common protocol. In this article, we review various theoretically simulated and clinically validated pooled testing models and propose practical guidelines on applying this strategy for large scale screening. If implemented properly, the proposed approach could contribute to proper utilization of testing resources and flattening of infection curve.

BackgroundThe early diagnosis of tuberculosis using novel non-sputum-based biomarkers is of high priority in the End TB strategy. MicroRNAs (miRNAs) are significant regulators of TB pathogenesis and their differential expression pattern among healthy, latent, and active TB population has revealed their potentiality as biomarkers in recent studies. Thus, we systematically reviewed and performed a meta-analysis on the role of host miRNAs in TB diagnosis. We also reviewed the involvement of miRNAs in the immune response to Mycobacterium tuberculosis (Mtb).MethodsPubmed, Ovid and Cochrane databases were searched to retrieve published literature from 2000 to 2020 using predefined keywords. We screened relevant studies based on inclusion and exclusion criteria and the included studies were assessed for their quality using STARD guidelines and QUADAS-2 tool. Funnel plots were constructed to assess the publication bias. The heterogeneity of studies and overall pooled results of sensitivity, specificity and DOR were determined using forest plots.ResultsWe retrieved a total of 447 studies collectively from all the databases, out of which 21 studies were included for qualitative analysis. In these studies, miR-29, miR-31, miR-125b, miR146a and miR-155 were consistently reported. The overall sensitivity, specificity and DOR of these miRNAs were found to be 87.9% (81.7-92.2), 81.2% (74.5-86.5) and 43.1(20.3-91.3) respectively. Among these, miR-31 had the maximum diagnostic accuracy, with a sensitivity of 96% (89.7-98.5), specificity of 89% (81.2-93.8) and DOR of 345.9 (90.2-1326.3), meeting the minimal target product profile (TPP) for TB diagnostics.ConclusionmiRNAs can thus be exploited as potential biomarkers for rapid detection of tuberculosis as evident from their diagnostic performance. Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021226559 PROSPERO (CRD42021226559).

Background The positive predictive value of Tuberculin Skin Test and current generation Interferon Gamma Release Assays are very low leading to high numbers needed to treat. Therefore, it is critical to identify new biomarkers with high predictive accuracy to identify individuals bearing high risk of progression to active tuberculosis. Methods We used stored QuantiFERON supernatants from 14 household contacts of index TB patients who developed incident active TB during a two-year follow-up and 20 age and sex-matched non-progressors. The supernatants were tested for an expanded panel of 45 cytokines, chemokines and growth factors using the Luminex Multiplex Array kit. Results We found significant differences in the levels of TB-antigen induced production of several analytes between progressors and non-progressors. Dominance analysis identified 15 key predictive biomarkers based on relative percentage importance. Principal component analysis revealed that these biomarkers could robustly distinguish between the two groups. Receiver operating characteristic analysis identified IP-10, CCL19, IFN-γ, IL-1ra, CCL3 and GM-CSF as the most promising predictive markers, with AUC ≥90. IP-10/CCL19 ratio exhibited maximum sensitivity and specificity (100%) in predicting progression. Through Classification and Regression Tree analysis, a cut-off of 0.24 for IP-10/CCL19 ratio was found to be ideal for predicting short-term risk of progression to TB disease with a positive predictive value of 100 (95% CI 85.8-100). Conclusion The biomarkers identified in this study will pave way for the development of a more accurate test that can identify individuals at high risk for immediate progression to TB disease for targeted intervention.