SARS-CoV-2 Testing Disparities in Massachusetts

ObjectiveEarly deficiencies in testing capacity contributed to poor control of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the context of marked improvement in SARS-CoV-2 testing infrastructure, we sought to examine the alignment of testing with epidemic intensity to mitigate subsequent waves of COVID-19 in Massachusetts.MethodsWe compiled publicly available weekly SARS-CoV-2 molecular testing data for period (May 27 to October 14, 2020) following the initial COVID-19 wave. We defined testing intensity as weekly SARS-CoV-2 tests performed per 100,000 population and used weekly test positivity (percent of tests positive) as a measure of epidemic intensity. We considered optimal alignment of testing resources to be matching community ranks of testing and positivity. In communities with a lower rank of testing than positivity in a given week, the testing gap was calculated as the additional tests required to achieve matching ranks. Multivariable Poisson modeling was utilized to assess for trends and association with community characteristics.ResultsDuring the observation period, 4,262,000 tests were reported in Massachusetts and the misalignment of testing with epidemic intensity increased. The weekly testing gap increased 9.0% per week (adjusted rate ratio [aRR]: 1.090, 95% confidence interval [CI]: 1.08-1.10). Increasing levels of community socioeconomic vulnerability (aRR: 1.35 per quartile increase, 95% CI: 1.23-1.50) and the highest quartile of minority and language vulnerability (aRR: 1.46, 95% CI 0.96-1.49) were associated with increased testing gaps, but the latter association was not statistically significant. Presence of large university student population (>10% of population) was associated with a marked decrease in testing gap (aRR 0.21, 95% CI: 0.12-0.38).ConclusionThese analyses indicate that despite objectives to promote equity and enhance epidemic control in vulnerable communities, testing resources across Massachusetts have been disproportionally allocated to more affluent communities. Worsening structural inequities in access to SARS-CoV-2 testing increase the risk for another intense wave of COVID-19 in Massachusetts, particularly among vulnerable communities.

Development of MAST: A Microscopy-Based Antimicrobial Susceptibility Testing Platform

Antibiotic resistance is compromising our ability to treat bacterial infections. Clinical microbiology laboratories guide appropriate treatment through antimicrobial susceptibility testing (AST) of patient bacterial isolates. However, increasingly, pathogens are developing resistance to a broad range of antimicrobials, requiring AST of alternative agents for which no commercially available testing methods are available. Therefore, there exists a significant AST testing gap in which current methodologies cannot adequately address the need for rapid results in the face of unpredictable susceptibility profiles. To address this gap, we developed a multicomponent, microscopy-based AST (MAST) platform capable of AST determinations after only a 2 h incubation. MAST consists of a solid-phase microwell growth surface in a 384-well plate format, inkjet printing–based application of both antimicrobials and bacteria at any desired concentrations, automated microscopic imaging of bacterial replication, and a deep learning approach for automated image classification and determination of antimicrobial minimal inhibitory concentrations (MICs). In evaluating a susceptible strain set, 95.8% were within ±1 and 99.4% were within ±2, twofold dilutions, respectively, of reference broth microdilution MIC values. Most (98.3%) of the results were in categorical agreement. We conclude that MAST offers promise for rapid, accurate, and flexible AST to help address the antimicrobial testing gap.