Perceptions on undertaking regular asymptomatic self-testing for COVID-19 using lateral flow tests: a qualitative study of university students and staff.

OBJECTIVES: Successful implementation of asymptomatic testing programmes using lateral flow tests (LFTs) depends on several factors, including feasibility, acceptability and how people act on test results. We aimed to examine experiences of university students and staff of regular asymptomatic self-testing using LFTs, and their subsequent behaviours. DESIGN AND SETTING: A qualitative study using semistructured remote interviews and qualitative survey responses, which were analysed thematically. PARTICIPANTS: People who were participating in weekly testing feasibility study, between October 2020 and January 2021, at the University of Oxford. RESULTS: We interviewed 18 and surveyed 214 participants. Participants were motivated to regularly self-test as they wanted to know whether or not they were infected with SARS-CoV-2. Most reported that a negative test result did not change their behaviour, but it did provide them with reassurance to engage with permitted activities. In contrast, some participants reported making decisions about visiting other people because they felt reassured by a negative test result. Participants valued the training but some still doubted their ability to carry out the test. Participants were concerned about safety of attending test sites with lots of people and reported home testing was most convenient. CONCLUSIONS: Clear messages highlighting the benefits of regular testing for family, friends and society in identifying asymptomatic cases are needed. This should be coupled with transparent communication about the accuracy of LFTs and how to act on either a positive or negative result. Concerns about safety, convenience of testing and ability to do tests need to be addressed to ensure successful scaling up of asymptomatic testing.

Feasibility and Acceptability of Community Coronavirus Disease 2019 Testing Strategies (FACTS) in a University Setting.

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic in 2020, the UK government began a mass severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing program. This study aimed to determine the feasibility and acceptability of organized regular self-testing for SARS-CoV-2. METHODS: This was a mixed-methods observational cohort study in asymptomatic students and staff at University of Oxford, who performed SARS-CoV-2 antigen lateral flow self-testing. Data on uptake and adherence, acceptability, and test interpretation were collected via a smartphone app, an online survey, and qualitative interviews. RESULTS: Across 3 main sites, 551 participants (25% of those invited) performed 2728 tests during a follow-up of 5.6 weeks; 447 participants (81%) completed at least 2 tests, and 340 (62%) completed at least 4. The survey, completed by 214 participants (39%), found that 98% of people were confident to self-test and believed self-testing to be beneficial. Acceptability of self-testing was high, with 91% of ratings being acceptable or very acceptable. A total of 2711 (99.4%) test results were negative, 9 were positive, and 8 were inconclusive. Results from 18 qualitative interviews with students and staff revealed that participants valued regular testing, but there were concerns about test accuracy that impacted uptake and adherence. CONCLUSIONS: This is the first study to assess feasibility and acceptability of regular SARS-CoV-2 self-testing. It provides evidence to inform recruitment for, adherence to, and acceptability of regular SARS-CoV-2 self-testing programs for asymptomatic individuals using lateral flow tests. We found that self-testing is acceptable and people were able to interpret results accurately.

A real-world way to manage real options.

Each corporate growth project is an option, in the sense that managers face choices--push ahead or pull back--along the way. Yet many companies hesitate to apply options theory to initiatives such as R&D and geographic expansion, partly because these "real" options are highly complex. In this article, the authors make the case that the complexity of real options can be eased through the use of a binomial valuation model. Many of the problems with real-options analysis stem from the use of the Black-Scholes-Merton model, which isn't suited to real options. Binomial models, by contrast, are simpler mathematically, and you can tinker with a binomial model until it closely reflects the project you wish to value. Suppose your company is considering investing in a new plant. To use the binomial model, you must create an "event tree" to figure out the full range of possible values for the plant during the project's lifetime--next year, at the end of the design phase, upon completion. Then you work backward from the value at completion, factoring in the various investments, to determine the value of the project today. These calculations provide you with numbers for all the possible future values of the option at the various points where a decision needs to be made on whether to continue with the project. The authors also address another criticism of real options: that gaps often arise between theoretical and realized values of options of all types. Such gaps may be largely the result of managers exercising options at the wrong time. To improve the way it manages its real options, a company can look out for the decision trigger points that correspond to the nodes on a binomial decision tree. The trigger points should not only tell managers when they need to decide on exercise but also specify rules governing the exercise decisions.