Rapid evidence review to inform safe return to campus in the context of coronavirus disease 2019 (COVID-19)

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is transmitted predominantly through the air in crowded and unventilated indoor spaces, especially among unvaccinated people. Universities and colleges are potential settings for its spread. Methods: An interdisciplinary team from public health, virology, and biology used narrative methods to summarise and synthesise evidence on key control measures, taking account of mode of transmission. Results: Evidence from a wide range of primary studies supports six measures. Vaccinate (aim for > 90% coverage and make it easy to get a jab). Require masks indoors, especially in crowded settings. If everyone wears well-fitting cloth masks, source control will be high, but for maximum self-protection, respirator masks should be worn. Masks should not be removed for speaking or singing. Space people out by physical distancing (but there is no “safe” distance because transmission risk varies with factors such as ventilation, activity levels and crowding), reducing class size (including offering blended learning), and cohorting (students remain in small groups with no cross-mixing). Clean indoor air using engineering controls—ventilation (while monitoring CO2 levels), inbuilt filtration systems, or portable air cleaners fitted with high efficiency particulate air [HEPA] filters). Test asymptomatic staff and students using lateral flow tests, with tracing and isolating infectious cases when incidence of coronavirus disease 2019 (COVID-19) is high. Support clinically vulnerable people to work remotely. There is no direct evidence to support hand sanitising, fomite controls or temperature-taking. There was no evidence that freestanding plastic screens, face visors and electronic air-cleaning systems are effective. Conclusions: The above evidence-based measures should be combined into a multi-faceted strategy to maximise both student safety and the continuation of in-person and online education provision. Those seeking to provide a safe working and learning environment should collect data (e.g. CO2 levels, room occupancy) to inform their efforts.

Test to release from isolation after testing positive for SARS-CoV-2

The rapid spread and high transmissibility of the Omicron variant of SARS-CoV-2 is likely to lead to a significant number of key workers testing positive simultaneously. Under a policy of self-isolation after testing positive, this may lead to extreme staffing shortfalls at the same time as e.g. hospital admissions are peaking. Using a model of individual infectiousness and testing with lateral flow tests (LFT), we evaluate test-to-release policies against conventional fixed-duration isolation policies in terms of excess days of infectiousness, days saved, and tests used. We find that the number of infectious days in the community can be reduced to almost zero by requiring at least 2 consecutive days of negative tests, regardless of the number of days' wait until testing again after initially testing positive. On average, a policy of fewer days' wait until initiating testing (e.g 3 or 5 days) results in more days saved vs. a 10-day isolation period, but also requires a greater number of tests. Due to a lack of specific data on viral load progression, infectivity, and likelihood of testing positive by LFT over the course of an Omicron infection, we assume the same parameters as for pre-Omicron variants and explore the impact of a possible shorter proliferation phase.

‘Variant fatigue’? Public attitudes to COVID-19 18 months into the pandemic: A qualitative study

Objectives: Qualitative study exploring public attitudes to COVID-19 18 months into the pandemic, specifically focused on adherence to infection-reducing behaviours and policy measures during a period of the emergence of a new variant (Omicron)Study design: Qualitative online focus group study Methods: Focus groups were conducted with a diverse sample of 22 adults in the United Kingdom to explore their views. Data were analysed using a framework approach.Findings: Analysis revealed two main groups based on participants’ perceived concern over Omicron: variant fatigue (n=16 (73%)) and deja vu (n=6 (27%)). Those exhibiting variant fatigue reported not adopting any additional caution or infection-reducing behaviours as a result of the new variant. They tended to describe Omicron as ‘just another variant’ and expressed a need to ‘get on’ and ‘live with’ the virus. Those exhibiting deja vu suggested that Omicron was of additional concern to them and for some posed a threat not seen since ‘last year’ (second wave). No demographic patterns emerged, although there was a high amount of variant fatigue (absence of additional caution) (n=5 (83%)) amongst the unvaccinated participants. Those who were concerned about Omicron tended to report reducing social contacts. Few participants reported taking lateral flow tests regularly, except for those required to by their employers. Stated compliance with facemask rules was high. Nearly all participants stated an intention to comply with any future potential policy measures to reduce transmission of COVID-19, including more stringent measures such as lockdowns. Implications: 18 months into the pandemic, there may be habituation to the risk posed by COVID-19, despite the increased risk posed by the new variant Omicron. Due to this risk habituation (‘variant fatigue’) and due to a general decline in engagement with news related to COVID-19, many people may not be, or might be reluctant to, voluntarily adopt additional caution and infection-reducing behaviours. This poses a challenge for public health communication, since a sense of being ‘relaxed’ about, or ‘living with’ COVID-19 may undermine efforts to encourage voluntary adherence to infection-reducing behaviours. However, findings suggest that most people intend to comply (albeit reluctantly) with policy measures (as opposed to ‘advice’)- including stringent measures such as lockdown - if they were required in future.

Analytical evaluation of thirty-two SARS-CoV-2 lateral flow antigen tests demonstrates sensitivity remains with the SARS-CoV-2 Gamma lineage

The limit of detection (LOD) of thirty-two antigen lateral flow tests (Ag-RDT) were evaluated with the SARS-CoV-2 Gamma variant. Twenty-eight of thirty-two Ag-RDTs exceeded the World Health Organization criteria of an LOD of 1.0×106 genome copy numbers/ml and performance was equivalent as with the 2020 B.1 lineage and Alpha variant.

In vitro characterisation and clinical evaluation of the diagnostic accuracy of a new antigen test for SARS-CoV-2 detection.

Background and aims: Quick, user-friendly and sensitive diagnostic tools are the key to controlling the spread of the SARS-CoV-2 pandemic in the new epidemiologic landscape. The aim of this work is to characterise a new Covid-19 antigen test that uses an innovative chromatographic Affimer-based technology designed for the qualitative detection of SARS-CoV-2 antigen. As rapid technology to detect Covid-19, the test was extensively characterised in vitro. Once the analytical parameters of performance were set, the test system was challenged in a test field study. The aim of this study was to evaluate its diagnostic accuracy, as compared by the gold standard RT-PCR and other existing lateral flow tests. The study was approved by MiRNAX corporate review board to ensure i) that the test complied with all the ethical requirements, ii) that the rights of participants were protected, and iii) that donors were fully informed about the likelihood that they would not personally benefit from the research. The tests were completed under the frame of Project SENSORNAS RTC-20176501 in collaboration with MiRNAX Biosens Ltd. and Hospital Carlos III and are currently under submission and review from the Ethics Committee of Universidad Autonoma de Madrid. Keywords: respiratory disease COVID-19; SARS-CoV-2; ELISA; RT-PCR; antigen lateral flow test.

Rapid evidence review to inform safe return to campus in the context of coronavirus disease 2019 (COVID-19)

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is transmitted predominantly through the air in crowded and unventilated indoor spaces among unvaccinated people. Universities and colleges are potential settings for its spread. Methods: An interdisciplinary team from public health, virology, and biology used narrative methods to summarise and synthesise evidence on key control measures, taking account of mode of transmission. Results: Evidence from a wide range of primary studies supports six measures. Vaccinate (aim for > 90% coverage and make it easy to get a jab). Require masks indoors, especially in crowded settings. If everyone wears well-fitting cloth masks, source control will be high, but for maximum self-protection, respirator masks should be worn. Masks should not be removed for speaking or singing. Space people out by physical distancing (but there is no “safe” distance because transmission risk varies with factors such as ventilation, activity levels and crowding), reducing class size (including offering blended learning), and cohorting (students remain in small groups with no cross-mixing). Clean indoor air using engineering controls—ventilation (while monitoring CO2 levels), inbuilt filtration systems, or portable air cleaners fitted with high efficiency particulate air [HEPA] filters). Test asymptomatic staff and students using lateral flow tests, with tracing and isolating infectious cases when incidence of coronavirus disease 2019 (COVID-19) is high. Support clinically vulnerable people to work remotely. There is no direct evidence to support hand sanitising, fomite controls or temperature-taking. There is evidence that freestanding plastic screens, face visors and electronic air-cleaning systems are ineffective. Conclusions: The above six evidence-based measures should be combined into a multi-faceted strategy to maximise both student safety and the continuation of in-person and online education provision. Staff and students seeking to negotiate a safe working and learning environment should collect data (e.g. CO2 levels, room occupancy) to inform conversations.