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Background: Automated, high throughput assays are required to quantify the immune response after infection with or vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study on the Roche Elecsys ® Anti-SARS-CoV-2 S (ACOV2S) assay provides insights on the assay design and performance., Methods: The ACOV2S assay quantifies antibodies to the receptor-binding domain of the SARS-CoV-2 spike protein. The assigned units and the underlying standardization were compared to the international reference standard in BAU/mL. Assay specificity was assessed in samples (n=5981) collected prior to the COVID-19 pandemic and in samples from patients with non-COVID-19 respiratory infections (n=697) or other infectious diseases (n=771). Sensitivity was measured in 1313 samples from patients with mild COVID-19 and 297 samples from patients hospitalized with COVID-19. Comparison of results was performed to a comparator semi-quantitative anti-S1 assay of indirect detection format as well as a commercially available and an in-house version of a surrogate neutralization assay (ACE2-RBD)., Results: The originally assigned units for the ACOV2S assay were shown to be congruent to the units of the First International WHO Standard for anti-SARS-CoV-2 immunoglobulins. Overall specificity was 99.98% with no geographical differences noted and no loss of specificity in samples containing potentially cross-reacting antibodies. High sensitivity was observed, with 98.8% of samples reported to be reactive >14 days after infection and sustained detection of antibodies over time. For all samples, ACOV2S titers and neutralization capacities developed with comparable dynamics. Robust standardization and assay setup enable excellent reproducibility of results, independent of lot or analyzer used., Conclusion: The results from this study confirmed that ACOV2S is a highly sensitive and specific assay and correlates well with surrogate neutralization assays. The units established for ACOV2S are also interchangeable with the units of the First International WHO Standard for anti-SARS-CoV-2 immunoglobulins. Worldwide availability of the assay and analyzers render ACOV2S a highly practical tool for population-wide assessment and monitoring of the humoral response to SARS-CoV-2 infection or vaccination., Competing Interests: This study received funding from Roche Diagnostics. The funder was involved in the study design, analysis, interpretation of data, the writing of this article and the decision to submit it for publication. Editorial support was provided by Steph Carter and Jade Drummond of inScience Communications, Springer Healthcare Ltd, UK, and was funded by Roche Diagnostics International Ltd (Rotkreuz, Switzerland). ELECSYS and COBAS are trademarks of Roche. All other product names and trademarks are the property of their respective owners. All authors (KT, MW, PM, JK, SP, and SJ) are employees of Roche Diagnostics., (Copyright © 2022 Taffertshofer, Walter, Mackeben, Kraemer, Potapov and Jochum.)

Background: The COVID-19 pandemic has led to an avalanche of scientific studies, drawing on many different types of data. However, studies addressing the effectiveness of government actions against COVID-19, especially non-pharmaceutical interventions, often exhibit data problems that threaten the validity of their results. This review is thus intended to help epidemiologists and other researchers identify a set of data issues that, in our view, must be addressed in order for their work to be credible. We further intend to help journal editors and peer reviewers when evaluating studies, to apprise policy-makers, journalists, and other research consumers about the strengths and weaknesses of published studies, and to inform the wider debate about the scientific quality of COVID-19 research., Results: To this end, we describe common challenges in the collection, reporting, and use of epidemiologic, policy, and other data, including completeness and representativeness of outcomes data; their comparability over time and among jurisdictions; the adequacy of policy variables and data on intermediate outcomes such as mobility and mask use; and a mismatch between level of intervention and outcome variables. We urge researchers to think critically about potential problems with the COVID-19 data sources over the specific time periods and particular locations they have chosen to analyze, and to choose not only appropriate study designs but also to conduct appropriate checks and sensitivity analyses to investigate the impact(s) of potential threats on study findings., Conclusions: In an effort to encourage high quality research, we provide recommendations on how to address the issues we identify. Our first recommendation is for researchers to choose an appropriate design (and the data it requires). This review describes considerations and issues in order to identify the strongest analytical designs and demonstrates how interrupted time-series and comparative longitudinal studies can be particularly useful. Furthermore, we recommend that researchers conduct checks or sensitivity analyses of the results to data source and design choices, which we illustrate. Regardless of the approaches taken, researchers should be explicit about the kind of data problems or other biases that the design choice and sensitivity analyses are addressing., (© 2022. The Author(s).)

Tests for Coronavirus disease 2019 (COVID-19) are intended for a disparate and shifting range of purposes: (1) diagnosing patients who present with symptoms to inform individual treatment decisions; (2) organizational uses such as "cohorting" potentially infected patients and staff to protect others; and (3) contact tracing, surveillance, and other public health purposes. Often lost when testing is encouraged is that testing does not by itself confer health benefits. Rather, testing is useful to the extent it forms a critical link to subsequent medical or public health interventions. Such interventions might be individual level, like better diagnosis, treatment, isolation, or quarantine of contacts. They might aid surveillance to understand levels and trends of disease within a defined population that enables informed decisions to implement or relax social distancing measures. In this article, we describe the range of available COVID-19 tests; their accuracy and timing considerations; and the specific clinical, organizational, and public health considerations that warrant different testing strategies. Three representative clinical scenarios illustrate the importance of appropriate test use and interpretation. The reason a patient seeks testing is often a strong indicator of the pretest probability of infection, and thus how to interpret test results. In addition, the level of population spread of the virus and the timing of testing play critical roles in the positive or negative predictive value of the test. We conclude with practical recommendations regarding the need for testing in various contexts, appropriate tests and testing methods, and the interpretation of test results., Competing Interests: Conflict of interest: None., (© Copyright 2021 by the American Board of Family Medicine.)

Background: Eliminating disparities in the burden of COVID-19 requires equitable access to control measures across socio-economic groups. Limited research on socio-economic differences in mobility hampers our ability to understand whether inequalities in social distancing are occurring during the SARS-CoV-2 pandemic., Objective: We aimed to assess how mobility patterns have varied across the United States during the COVID-19 pandemic and to identify associations with socioeconomic factors of populations., Methods: We used anonymized mobility data from tens of millions of devices to measure the speed and depth of social distancing at the county level in the United States between February and May 2020, the period during which social distancing was widespread in this country. Using linear mixed models, we assessed the associations between social distancing and socioeconomic variables, including the proportion of people in the population below the poverty level, the proportion of Black people, the proportion of essential workers, and the population density., Results: We found that the speed, depth, and duration of social distancing in the United States are heterogeneous. We particularly show that social distancing is slower and less intense in counties with higher proportions of people below the poverty level and essential workers; in contrast, we show that social distancing is intensely adopted in counties with higher population densities and larger Black populations., Conclusions: Socioeconomic inequalities appear to be associated with the levels of adoption of social distancing, potentially resulting in wide-ranging differences in the impact of the COVID-19 pandemic in communities across the United States. These inequalities are likely to amplify existing health disparities and must be addressed to ensure the success of ongoing pandemic mitigation efforts., (©Romain Garnier, Jan R Benetka, John Kraemer, Shweta Bansal. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.01.2021.)

Background and Aim: Testing represents one of the main pillars of public health response to SARS-CoV-2/COVID-19 pandemic. This paper shows how accuracy and utility of testing programs depend not just on the type of tests, but on the context as well., Methods: We describe the testing methods that have been developed and the possible testing strategies; then, we focus on two possible methods of population-wide testing, i.e., pooled testing and testing with rapid antigen tests. We show the accuracy of split-pooling method and how, in different pre-test probability scenarios, the positive and negative predictive values vary using rapid antigen tests., Results: Split-pooling, followed by retesting of negative results, shows a higher sensitivity than individual testing and requires fewer tests. In case of low pre-test probability, a negative result with antigen test could allow to rule out the infection, while, in case of a positive result, a confirmatory molecular test would be necessary., Conclusions: Test performance alone is not enough to properly choose which test to use; goals and context of the testing program are essential. We advocate the use of pooled strategies when planning population-wide screening, and the weekly use of rapid tests for close periodic monitoring in low-prevalence populations.