Prevalence of SARS-CoV-2 antibodies among Belgian nursing home residents and staff during the primary COVID-19 vaccination campaign.

BACKGROUND: Nursing home residents (NHR) and staff have been disproportionally affected by the COVID-19 pandemic and were therefore prioritised in the COVID-19 vaccination strategy. However, frail older adults, like NHR, are known to have decreased antibody responses upon vaccination targeting other viral antigens. OBJECTIVES: As real-world data on vaccine responsiveness, we assessed the prevalence of SARS-CoV-2 antibodies among Belgian NHR and staff during the primary COVID-19 vaccination campaign. METHODS: In total, we tested 1629 NHR and 1356 staff across 69 Belgian NHs for the presence of SARS-CoV-2 IgM/IgG antibodies using rapid tests. We collected socio-demographic and COVID-19-related medical data through questionnaires. Sampling occurred between 1 February and 24 March 2021, in a randomly sampled population that received none, one or two BNT162b2 vaccine doses. RESULTS: We found that during the primary vaccination campaign with 59% of the study population fully vaccinated, 74% had SARS-CoV-2 antibodies. Among fully vaccinated individuals only, fewer residents tested positive for SARS-CoV-2 antibodies (77%) than staff (98%), suggesting an impaired vaccine-induced antibody response in the elderly, with lowest seroprevalences observed among infection naïve residents. COVID-19 vaccination status and previous SARS-CoV-2 infection were predictors for SARS-CoV-2 seropositivity. Alternatively, age ≥ 80 years old, the presence of comorbidities and high care dependency predicted SARS-CoV-2 seronegativity in NHR. CONCLUSION: These findings highlight the need for further monitoring of SARS-CoV-2 immunity upon vaccination in the elderly population, as their impaired humoral responses could imply insufficient protection against COVID-19. TRIAL REGISTRATION: This study was retrospectively registered on ClinicalTrials.gov (NCT04738695).

Prospective Performance Evaluation of the miDiagnostics COVID-19 PCR Test for Rapid SARS-CoV-2 Detection on Nasopharyngeal Swabs.

Rapid diagnosis or exclusion of SARS-CoV-2 infection is essential for correct medical management decisions regarding COVID-19. High-throughput laboratory-based reverse transcriptase (RT)-PCR testing is accurate with longer turnaround times, while rapid antigen tests show moderate sensitivity. In search of a fast and reliable COVID-19 test, we aimed to validate the rapid miDiagnostics COVID-19 PCR test. We recruited symptomatic and asymptomatic participants in a mobile COVID-19 test center in Belgium. We collected three nasopharyngeal samples from each participant. The index sample was tested on the miDiagnostics COVID-19 PCR reader, the reference sample was tested on the reference TaqPath COVID-19 PCR test in the Belgian Reference Center for Respiratory Pathogens of University Hospitals Leuven, and a third sample was collected for discordance testing with the PerkinElmer SARS-CoV-2 PCR kit. A total of 770 participants yielded 763 sets of included nasopharyngeal samples. Overall positive percent agreement and negative percent agreement of the miDiagnostics COVID-19 PCR test were 95.5% (92.6% to 97.4%) and 94.9% (92.3 to 96.8%), rising to 98.6% (96.5% to 99.6%) and 96.5% (92.6% to 98.7%) in symptomatic patients. Discordance testing reclassified 15 of 21 false-positive cases as true positive. A retest of the miDiagnostics PCR test was performed in 61 tests (7.4%) due to a technical error. The miDiagnostics COVID-19 PCR test showed excellent clinical accuracy. The fast and reliable results allow for rapid correct diagnosis and tailored medical management decisions regarding COVID-19.

Antibody tests for identification of current and past infection with SARS-CoV-2.

BACKGROUND: The diagnostic challenges associated with the COVID-19 pandemic resulted in rapid development of diagnostic test methods for detecting SARS-CoV-2 infection. Serology tests to detect the presence of antibodies to SARS-CoV-2 enable detection of past infection and may detect cases of SARS-CoV-2 infection that were missed by earlier diagnostic tests. Understanding the diagnostic accuracy of serology tests for SARS-CoV-2 infection may enable development of effective diagnostic and management pathways, inform public health management decisions and understanding of SARS-CoV-2 epidemiology. OBJECTIVES: To assess the accuracy of antibody tests, firstly, to determine if a person presenting in the community, or in primary or secondary care has current SARS-CoV-2 infection according to time after onset of infection and, secondly, to determine if a person has previously been infected with SARS-CoV-2. Sources of heterogeneity investigated included: timing of test, test method, SARS-CoV-2 antigen used, test brand, and reference standard for non-SARS-CoV-2 cases. SEARCH METHODS: The COVID-19 Open Access Project living evidence database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) was searched on 30 September 2020. We included additional publications from the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre) 'COVID-19: Living map of the evidence' and the Norwegian Institute of Public Health 'NIPH systematic and living map on COVID-19 evidence'. We did not apply language restrictions. SELECTION CRITERIA: We included test accuracy studies of any design that evaluated commercially produced serology tests, targeting IgG, IgM, IgA alone, or in combination. Studies must have provided data for sensitivity, that could be allocated to a predefined time period after onset of symptoms, or after a positive RT-PCR test. Small studies with fewer than 25 SARS-CoV-2 infection cases were excluded. We included any reference standard to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR), clinical diagnostic criteria, and pre-pandemic samples). DATA COLLECTION AND ANALYSIS: We use standard screening procedures with three reviewers. Quality assessment (using the QUADAS-2 tool) and numeric study results were extracted independently by two people. Other study characteristics were extracted by one reviewer and checked by a second. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test and, for meta-analysis, we fitted univariate random-effects logistic regression models for sensitivity by eligible time period and for specificity by reference standard group. Heterogeneity was investigated by including indicator variables in the random-effects logistic regression models. We tabulated results by test manufacturer and summarised results for tests that were evaluated in 200 or more samples and that met a modification of UK Medicines and Healthcare products Regulatory Agency (MHRA) target performance criteria. MAIN RESULTS: We included 178 separate studies (described in 177 study reports, with 45 as pre-prints) providing 527 test evaluations. The studies included 64,688 samples including 25,724 from people with confirmed SARS-CoV-2; most compared the accuracy of two or more assays (102/178, 57%). Participants with confirmed SARS-CoV-2 infection were most commonly hospital inpatients (78/178, 44%), and pre-pandemic samples were used by 45% (81/178) to estimate specificity. Over two-thirds of studies recruited participants based on known SARS-CoV-2 infection status (123/178, 69%). All studies were conducted prior to the introduction of SARS-CoV-2 vaccines and present data for naturally acquired antibody responses. Seventy-nine percent (141/178) of studies reported sensitivity by week after symptom onset and 66% (117/178) for convalescent phase infection. Studies evaluated enzyme-linked immunosorbent assays (ELISA) (165/527; 31%), chemiluminescent assays (CLIA) (167/527; 32%) or lateral flow assays (LFA) (188/527; 36%). Risk of bias was high because of participant selection (172, 97%); application and interpretation of the index test (35, 20%); weaknesses in the reference standard (38, 21%); and issues related to participant flow and timing (148, 82%). We judged that there were high concerns about the applicability of the evidence related to participants in 170 (96%) studies, and about the applicability of the reference standard in 162 (91%) studies. Average sensitivities for current SARS-CoV-2 infection increased by week after onset for all target antibodies. Average sensitivity for the combination of either IgG or IgM was 41.1% in week one (95% CI 38.1 to 44.2; 103 evaluations; 3881 samples, 1593 cases), 74.9% in week two (95% CI 72.4 to 77.3; 96 evaluations, 3948 samples, 2904 cases) and 88.0% by week three after onset of symptoms (95% CI 86.3 to 89.5; 103 evaluations, 2929 samples, 2571 cases). Average sensitivity during the convalescent phase of infection (up to a maximum of 100 days since onset of symptoms, where reported) was 89.8% for IgG (95% CI 88.5 to 90.9; 253 evaluations, 16,846 samples, 14,183 cases), 92.9% for IgG or IgM combined (95% CI 91.0 to 94.4; 108 evaluations, 3571 samples, 3206 cases) and 94.3% for total antibodies (95% CI 92.8 to 95.5; 58 evaluations, 7063 samples, 6652 cases). Average sensitivities for IgM alone followed a similar pattern but were of a lower test accuracy in every time slot. Average specificities were consistently high and precise, particularly for pre-pandemic samples which provide the least biased estimates of specificity (ranging from 98.6% for IgM to 99.8% for total antibodies). Subgroup analyses suggested small differences in sensitivity and specificity by test technology however heterogeneity in study results, timing of sample collection, and smaller sample numbers in some groups made comparisons difficult. For IgG, CLIAs were the most sensitive (convalescent-phase infection) and specific (pre-pandemic samples) compared to both ELISAs and LFAs (P < 0.001 for differences across test methods). The antigen(s) used (whether from the Spike-protein or nucleocapsid) appeared to have some effect on average sensitivity in the first weeks after onset but there was no clear evidence of an effect during convalescent-phase infection. Investigations of test performance by brand showed considerable variation in sensitivity between tests, and in results between studies evaluating the same test. For tests that were evaluated in 200 or more samples, the lower bound of the 95% CI for sensitivity was 90% or more for only a small number of tests (IgG, n = 5; IgG or IgM, n = 1; total antibodies, n = 4). More test brands met the MHRA minimum criteria for specificity of 98% or above (IgG, n = 16; IgG or IgM, n = 5; total antibodies, n = 7). Seven assays met the specified criteria for both sensitivity and specificity. In a low-prevalence (2%) setting, where antibody testing is used to diagnose COVID-19 in people with symptoms but who have had a negative PCR test, we would anticipate that 1 (1 to 2) case would be missed and 8 (5 to 15) would be falsely positive in 1000 people undergoing IgG or IgM testing in week three after onset of SARS-CoV-2 infection. In a seroprevalence survey, where prevalence of prior infection is 50%, we would anticipate that 51 (46 to 58) cases would be missed and 6 (5 to 7) would be falsely positive in 1000 people having IgG tests during the convalescent phase (21 to 100 days post-symptom onset or post-positive PCR) of SARS-CoV-2 infection. AUTHORS' CONCLUSIONS: Some antibody tests could be a useful diagnostic tool for those in whom molecular- or antigen-based tests have failed to detect the SARS-CoV-2 virus, including in those with ongoing symptoms of acute infection (from week three onwards) or those presenting with post-acute sequelae of COVID-19. However, antibody tests have an increasing likelihood of detecting an immune response to infection as time since onset of infection progresses and have demonstrated adequate performance for detection of prior infection for sero-epidemiological purposes. The applicability of results for detection of vaccination-induced antibodies is uncertain.

Rapid, point-of-care antigen tests for diagnosis of SARS-CoV-2 infection.

BACKGROUND: Accurate rapid diagnostic tests for SARS-CoV-2 infection would be a useful tool to help manage the COVID-19 pandemic. Testing strategies that use rapid antigen tests to detect current infection have the potential to increase access to testing, speed detection of infection, and inform clinical and public health management decisions to reduce transmission. This is the second update of this review, which was first published in 2020. OBJECTIVES: To assess the diagnostic accuracy of rapid, point-of-care antigen tests for diagnosis of SARS-CoV-2 infection. We consider accuracy separately in symptomatic and asymptomatic population groups. Sources of heterogeneity investigated included setting and indication for testing, assay format, sample site, viral load, age, timing of test, and study design. SEARCH METHODS: We searched the COVID-19 Open Access Project living evidence database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) on 08 March 2021. We included independent evaluations from national reference laboratories, FIND and the Diagnostics Global Health website. We did not apply language restrictions. SELECTION CRITERIA: We included studies of people with either suspected SARS-CoV-2 infection, known SARS-CoV-2 infection or known absence of infection, or those who were being screened for infection. We included test accuracy studies of any design that evaluated commercially produced, rapid antigen tests. We included evaluations of single applications of a test (one test result reported per person) and evaluations of serial testing (repeated antigen testing over time). Reference standards for presence or absence of infection were any laboratory-based molecular test (primarily reverse transcription polymerase chain reaction (RT-PCR)) or pre-pandemic respiratory sample. DATA COLLECTION AND ANALYSIS: We used standard screening procedures with three people. Two people independently carried out quality assessment (using the QUADAS-2 tool) and extracted study results. Other study characteristics were extracted by one review author and checked by a second. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test, and pooled data using the bivariate model. We investigated heterogeneity by including indicator variables in the random-effects logistic regression models. We tabulated results by test manufacturer and compliance with manufacturer instructions for use and according to symptom status. MAIN RESULTS: We included 155 study cohorts (described in 166 study reports, with 24 as preprints). The main results relate to 152 evaluations of single test applications including 100,462 unique samples (16,822 with confirmed SARS-CoV-2). Studies were mainly conducted in Europe (101/152, 66%), and evaluated 49 different commercial antigen assays. Only 23 studies compared two or more brands of test. Risk of bias was high because of participant selection (40, 26%); interpretation of the index test (6, 4%); weaknesses in the reference standard for absence of infection (119, 78%); and participant flow and timing 41 (27%). Characteristics of participants (45, 30%) and index test delivery (47, 31%) differed from the way in which and in whom the test was intended to be used. Nearly all studies (91%) used a single RT-PCR result to define presence or absence of infection. The 152 studies of single test applications reported 228 evaluations of antigen tests. Estimates of sensitivity varied considerably between studies, with consistently high specificities. Average sensitivity was higher in symptomatic (73.0%, 95% CI 69.3% to 76.4%; 109 evaluations; 50,574 samples, 11,662 cases) compared to asymptomatic participants (54.7%, 95% CI 47.7% to 61.6%; 50 evaluations; 40,956 samples, 2641 cases). Average sensitivity was higher in the first week after symptom onset (80.9%, 95% CI 76.9% to 84.4%; 30 evaluations, 2408 cases) than in the second week of symptoms (53.8%, 95% CI 48.0% to 59.6%; 40 evaluations, 1119 cases). For those who were asymptomatic at the time of testing, sensitivity was higher when an epidemiological exposure to SARS-CoV-2 was suspected (64.3%, 95% CI 54.6% to 73.0%; 16 evaluations; 7677 samples, 703 cases) compared to where COVID-19 testing was reported to be widely available to anyone on presentation for testing (49.6%, 95% CI 42.1% to 57.1%; 26 evaluations; 31,904 samples, 1758 cases). Average specificity was similarly high for symptomatic (99.1%) or asymptomatic (99.7%) participants. We observed a steady decline in summary sensitivities as measures of sample viral load decreased. Sensitivity varied between brands. When tests were used according to manufacturer instructions, average sensitivities by brand ranged from 34.3% to 91.3% in symptomatic participants (20 assays with eligible data) and from 28.6% to 77.8% for asymptomatic participants (12 assays). For symptomatic participants, summary sensitivities for seven assays were 80% or more (meeting acceptable criteria set by the World Health Organization (WHO)). The WHO acceptable performance criterion of 97% specificity was met by 17 of 20 assays when tests were used according to manufacturer instructions, 12 of which demonstrated specificities above 99%. For asymptomatic participants the sensitivities of only two assays approached but did not meet WHO acceptable performance standards in one study each; specificities for asymptomatic participants were in a similar range to those observed for symptomatic people. At 5% prevalence using summary data in symptomatic people during the first week after symptom onset, the positive predictive value (PPV) of 89% means that 1 in 10 positive results will be a false positive, and around 1 in 5 cases will be missed. At 0.5% prevalence using summary data for asymptomatic people, where testing was widely available and where epidemiological exposure to COVID-19 was suspected, resulting PPVs would be 38% to 52%, meaning that between 2 in 5 and 1 in 2 positive results will be false positives, and between 1 in 2 and 1 in 3 cases will be missed. AUTHORS' CONCLUSIONS: Antigen tests vary in sensitivity. In people with signs and symptoms of COVID-19, sensitivities are highest in the first week of illness when viral loads are higher. Assays that meet appropriate performance standards, such as those set by WHO, could replace laboratory-based RT-PCR when immediate decisions about patient care must be made, or where RT-PCR cannot be delivered in a timely manner. However, they are more suitable for use as triage to RT-PCR testing. The variable sensitivity of antigen tests means that people who test negative may still be infected. Many commercially available rapid antigen tests have not been evaluated in independent validation studies. Evidence for testing in asymptomatic cohorts has increased, however sensitivity is lower and there is a paucity of evidence for testing in different settings. Questions remain about the use of antigen test-based repeat testing strategies. Further research is needed to evaluate the effectiveness of screening programmes at reducing transmission of infection, whether mass screening or targeted approaches including schools, healthcare setting and traveller screening.

Declining Prevalence of SARS-CoV-2 Antibodies among Vaccinated Nursing Home Residents and Staff Six Months after the Primary BNT162b2 Vaccination Campaign in Belgium: A Prospective Cohort Study.

In the SCOPE study, we monitored SARS-CoV-2 antibodies in a national sample of residents and staff from Belgian nursing homes. Here, we report the seroprevalence among infected and infection-naive residents and staff after the primary COVID-19 vaccination campaign. Among 1554 vaccinated nursing home residents and 1082 vaccinated staff from 69 nursing homes in Belgium, we assessed the proportion having SARS-CoV-2 antibodies approximately two (April 2021), four (June 2021), and six months (August 2021) after a two-dose regimen of the BNT162b2 vaccine. We measured the seroprevalence using SARS-CoV-2 antibody rapid tests and collected socio-demographic and COVID-19 medical data using an online questionnaire. Two months after vaccination (baseline), we found a seroprevalence of 91% (95% CI: 89-93) among vaccinated residents and 99% (95% CI: 98-99) among vaccinated staff. Six months after vaccination, the seroprevalence significantly decreased to 68% (95% CI: 64-72) among residents and to 89% (95% CI; 86-91) among staff (p < 0.001). The seroprevalence was more likely to decrease among infection-naive residents, older residents, or residents with a high care dependency level. These findings emphasize the need for close monitoring of nursing home residents, as a substantial part of this population fails to mount a persistent antibody response after BNT162b2 vaccination.

Accuracy of routine laboratory tests to predict mortality and deterioration to severe or critical COVID‐19 in people with SARS‐CoV‐2

Objectives This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To assess the accuracy of routine blood‐based laboratory tests to predict mortality and deterioration to severe or critical (from mild or moderate) COVID‐19 in people with SARS‐CoV‐2 infection. Secondary objectives Where data are available, we will investigate whether prognostic accuracy varies according to a specific measurement or test, reference standard, timing of outcome verification, sample type, study design, and setting, including prevalence of the target condition (either by stratified analysis or meta‐regression).

Rapid, point‐of‐care antigen tests for diagnosis of SARS‐CoV‐2 infection

Background Accurate rapid diagnostic tests for SARS‐CoV‐2 infection would be a useful tool to help manage the COVID‐19 pandemic. Testing strategies that use rapid antigen tests to detect current infection have the potential to increase access to testing, speed detection of infection, and inform clinical and public health management decisions to reduce transmission. This is the second update of this review, which was first published in 2020. Objectives To assess the diagnostic accuracy of rapid, point‐of‐care antigen tests for diagnosis of SARS‐CoV‐2 infection. We consider accuracy separately in symptomatic and asymptomatic population groups. Sources of heterogeneity investigated included setting and indication for testing, assay format, sample site, viral load, age, timing of test, and study design. Search methods We searched the COVID‐19 Open Access Project living evidence database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) on 08 March 2021. We included independent evaluations from national reference laboratories, FIND and the Diagnostics Global Health website. We did not apply language restrictions. Selection criteria We included studies of people with either suspected SARS‐CoV‐2 infection, known SARS‐CoV‐2 infection or known absence of infection, or those who were being screened for infection. We included test accuracy studies of any design that evaluated commercially produced, rapid antigen tests. We included evaluations of single applications of a test (one test result reported per person) and evaluations of serial testing (repeated antigen testing over time). Reference standards for presence or absence of infection were any laboratory‐based molecular test (primarily reverse transcription polymerase chain reaction (RT‐PCR)) or pre‐pandemic respiratory sample. Data collection and analysis We used standard screening procedures with three people. Two people independently carried out quality assessment (using the QUADAS‐2 tool) and extracted study results. Other study characteristics were extracted by one review author and checked by a second. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test, and pooled data using the bivariate model. We investigated heterogeneity by including indicator variables in the random‐effects logistic regression models. We tabulated results by test manufacturer and compliance with manufacturer instructions for use and according to symptom status. Main results We included 155 study cohorts (described in 166 study reports, with 24 as preprints). The main results relate to 152 evaluations of single test applications including 100,462 unique samples (16,822 with confirmed SARS‐CoV‐2). Studies were mainly conducted in Europe (101/152, 66%), and evaluated 49 different commercial antigen assays. Only 23 studies compared two or more brands of test. Risk of bias was high because of participant selection (40, 26%);interpretation of the index test (6, 4%);weaknesses in the reference standard for absence of infection (119, 78%);and participant flow and timing 41 (27%). Characteristics of participants (45, 30%) and index test delivery (47, 31%) differed from the way in which and in whom the test was intended to be used. Nearly all studies (91%) used a single RT‐PCR result to define presence or absence of infection. The 152 studies of single test applications reported 228 evaluations of antigen tests. Estimates of sensitivity varied considerably between studies, with consistently high specificities. Average sensitivity was higher in symptomatic (73.0%, 95% CI 69.3% to 76.4%;109 evaluations;50,574 samples, 11,662 cases) compared to asymptomatic participants (54.7%, 95% CI 47.7% to 61.6%;50 evaluations;40,956 samples, 2641 cases). Average sensitivity was higher in the first week after symptom onset (80.9%, 95% CI 76.9% to 84.4%;30 evaluations, 2408 cases) than in the second week f symptoms (53.8%, 95% CI 48.0% to 59.6%;40 evaluations, 1119 cases). For those who were asymptomatic at the time of testing, sensitivity was higher when an epidemiological exposure to SARS‐CoV‐2 was suspected (64.3%, 95% CI 54.6% to 73.0%;16 evaluations;7677 samples, 703 cases) compared to where COVID‐19 testing was reported to be widely available to anyone on presentation for testing (49.6%, 95% CI 42.1% to 57.1%;26 evaluations;31,904 samples, 1758 cases). Average specificity was similarly high for symptomatic (99.1%) or asymptomatic (99.7%) participants. We observed a steady decline in summary sensitivities as measures of sample viral load decreased. Sensitivity varied between brands. When tests were used according to manufacturer instructions, average sensitivities by brand ranged from 34.3% to 91.3% in symptomatic participants (20 assays with eligible data) and from 28.6% to 77.8% for asymptomatic participants (12 assays). For symptomatic participants, summary sensitivities for seven assays were 80% or more (meeting acceptable criteria set by the World Health Organization (WHO)). The WHO acceptable performance criterion of 97% specificity was met by 17 of 20 assays when tests were used according to manufacturer instructions, 12 of which demonstrated specificities above 99%. For asymptomatic participants the sensitivities of only two assays approached but did not meet WHO acceptable performance standards in one study each;specificities for asymptomatic participants were in a similar range to those observed for symptomatic people. At 5% prevalence using summary data in symptomatic people during the first week after symptom onset, the positive predictive value (PPV) of 89% means that 1 in 10 positive results will be a false positive, and around 1 in 5 cases will be missed. At 0.5% prevalence using summary data for asymptomatic people, where testing was widely available and where epidemiological exposure to COVID‐19 was suspected, resulting PPVs would be 38% to 52%, meaning that between 2 in 5 and 1 in 2 positive results will be false positives, and between 1 in 2 and 1 in 3 cases will be missed. Authors' conclusions Antigen tests vary in sensitivity. In people with signs and symptoms of COVID‐19, sensitivities are highest in the first week of illness when viral loads are higher. Assays that meet appropriate performance standards, such as those set by WHO, could replace laboratory‐based RT‐PCR when immediate decisions about patient care must be made, or where RT‐PCR cannot be delivered in a timely manner. However, they are more suitable for use as triage to RT‐PCR testing. The variable sensitivity of antigen tests means that people who test negative may still be infected. Many commercially available rapid antigen tests have not been evaluated in independent validation studies. Evidence for testing in asymptomatic cohorts has increased, however sensitivity is lower and there is a paucity of evidence for testing in different settings. Questions remain about the use of antigen test‐based repeat testing strategies. Further research is needed to evaluate the effectiveness of screening programmes at reducing transmission of infection, whether mass screening or targeted approaches including schools, healthcare setting and traveller screening. Plain language summary How accurate are rapid antigen tests for diagnosing COVID‐19? Key messages • Rapid antigen tests are most accurate when they are used in people who have signs or symptoms of COVID‐19, especially during the first week of illness. People who test negative may still be infected. • Rapid antigen tests are considerably less accurate when they are used in people with no signs or symptoms of infection, but do perform better in people who have been in contact with someone who has confirmed COVID‐19. • The accuracy of rapid antigen tests varies between tests that are produced by different manufacturers and there is a lack of evidence for many commercially available tests. What are rapid point‐of‐care antigen tests for COVID⠐19? Rapid point‐of‐care tests aim to confirm or rule out COVID‐19 infection in people with or without COVID‐19 symptoms. They: • are portable, so they can be used wherever the patient is (at the point‐of‐care) or in non‐healthcare settings such as in the home;• are easy to perform, with a minimum amount of extra equipment or complicated preparation steps;• are less expensive than standard laboratory tests;• do not require a specialist operator or setting;and • provide results ‘while you wait’. For this review we were interested in rapid antigen tests, sometimes referred to as ‘lateral flow tests’. These tests identify proteins on the virus in samples taken from the nose or throat. They come in disposable plastic cassettes, similar to over‐the‐counter pregnancy tests. Why is this question important? People with suspected COVID‐19 need to know quickly whether they are infected, so that they can self‐isolate, receive treatment, and inform close contacts. Currently, COVID‐19 infection is confirmed by a laboratory test called RT‐PCR, which uses specialist equipment and often takes at least 24 hours to produce a result. In many places, rapid antigen tests have opened access to testing for many more people, with and without symptoms, and in locations other than healthcare settings. Faster diagnosis of COVID‐19 infection could allow people to take appropriate action more quickly, with the potential to reduce the spread of COVID‐19, but it is important to understand how accurate they are and the best way to use them. What did we want to find out? We wantedto know whether commercially available, rapid point‐of‐care antigen tests are accurate enough to diagnose COVID‐19 infection reliably, and to find out if accuracy differs in people with and without symptoms. What did we do? We looked for studies that measured the accuracy of any commercially produced rapid antigen test in people who were also tested for COVID‐19 using RT‐PCR. People could be tested in hospital, in the community or in their own homes. Studies could test people with or without symptoms. What did we find? We included 155 studies in the review. The main results are based on 152 studies investigating a total of 100,462 nose or throat samples;COVID‐19 was confirmed in 16,822 of these samples. Studies investigated 49 different antigen tests. Around 60% of studies took place in Europe. Main results In people with confirmed COVID‐19, antigen tests correctly identified COVID‐19 infection in an average of 73% of people with symptoms, compared to 55% of people without symptoms. Tests were most accurate when used in the first week after symptoms began (an average of 82% of confirmed cases had positive antigen tests). This is likely to be because people have the most virus in their system in the first days after they are infected. For people with no symptoms, tests were most accurate in people likely to have been in contact with a case of COVID‐19 infection (an average of 64% of confirmed cases had positive antigen tests). In people who did not have COVID‐19, antigen tests correctly ruled out infection in 99.6% of people with symptoms and 99.7% of people without symptoms. Different brands of tests varied in accuracy. Summary results (combined from more than one study per test brand) for seven tests met World Health Organization (WHO) standards as ‘acceptable’ for confirming and ruling out COVID‐19 in people with signs and symptoms of COVID‐19. Two more tests met the WHO acceptable standard in one study each. No test met this standard when evaluated in people without symptoms. Using summary results for symptomatic people tested during the first week after symptoms began, if 1000 people with symptoms had the antigen test, and 50 (5%) of them really had COVID‐19: • 45 people would test positive for COVID‐19. Of these, 5 people (11%) would not have COVID‐19 (false positive result). • 955 people would test negative for COVID‐19. Of these, 10 people (1.0%) would actually have COVID‐19 ( alse negative result). In people with no symptoms of COVID‐19 the number of confirmed cases is expected to be much lower than in people with symptoms. Using summary results for people with no known exposure to COVID‐19 in a bigger population of 10,000 people with no symptoms, where 50 (0.5%) of them really had COVID‐19: • 62 people would test positive for COVID‐19. Of these, 30 people (48%) would not have COVID‐19 (false positive result). • 9938 people would test negative for COVID‐19. Of these, 18 people (0.2%) would actually have COVID‐19 (false negative result). What are the limitations of the evidence? In general, studies used relatively rigorous methods, particularly for selecting participants and performing the tests. Sometimes studies did not perform the test on the people for whom it was intended and did not follow the manufacturers’ instructions for using the test. Sometimes the tests were not carried out at the point of care. Studies used less rigorous methods for confirming the presence or absence of COVID‐19 infection;91% of studies relied on a single negative RT‐PCR result as evidence of no COVID‐19 infection. Results from different test brands varied, and relatively few studies directly compared one test brand with another. Finally, not all studies gave enough information about their participants for us to judge how long they had had symptoms, or even whether or not they had symptoms. What does this mean? In people with symptoms, some rapid antigen tests are accurate enough to replace RT‐PCR, especially for ruling in the presence of infection. Alternatively, where RT‐PCR is available, rapid antigen tests could be used to select which people with symptoms require further testing with RT‐PCR, thereby reducing the burden on laboratory services. This would be most useful when quick decisions are needed about patient care, to identify outbreaks, to allow people to self‐isolate more quickly, or to initiate contact tracing. Rapid antigen tests are less good at ruling out infection in symptomatic people ‐ individuals who receive a negative rapid antigen test result may still be infected. Rapid antigen tests are less accurate when used in people with no symptoms of COVID‐19. More evidence is needed to understand the accuracy of rapid testing in people without symptoms and the extent to which repeated testing strategies can lead to reduced transmission, either for tests carried out at home or in non‐healthcare settings such as schools. There is no independent evidence to support the use of many test brands. More direct comparisons of test brands are needed, with testers following manufacturers’ instructions. How up‐to‐date is this review? This review updates our previous review and includes evidence published up to 8 March 2021.

Vaccine Hesitancy towards the COVID-19 Vaccine in a Random National Sample of Belgian Nursing Home Staff Members.

In Belgium, nursing home staff (NHS) and residents were prioritised for COVID-19 vaccination. However, vaccine hesitancy may have impacted vaccination rates. In this study, a random stratified sample of NHS (N = 1142), vaccinated and unvaccinated, completed an online questionnaire on COVID-19 vaccine hesitancy (between 31 July and 15 November 2021). NHS who hesitated or refused the vaccine were asked for the main reason for their hesitation/refusal. Those who hesitated, but eventually accepted vaccination, were asked why they changed their minds. Overall, 29.5% of all respondents hesitated before accepting vaccination, were still hesitating, or refused vaccination. Principal reasons were fear of unknown future effects (55.1% of vaccinated participants that hesitated and 19.5% who refused), fear of side-effects (12.7% of vaccinated participants that hesitated and 12.2% who refused), and mistrust in vaccination (10.5% of vaccinated participants that hesitated and 12.2% who refused). For vaccinated participants who hesitated initially, protecting the vulnerable was the main reason they changed their minds. Given this degree of fear and proposals to mandate vaccination among healthcare workers, communicating with NHS on the safety and efficacy of the vaccine should be prioritised.

Prevalence and incidence of antibodies against SARS-CoV-2 among primary healthcare providers in Belgium during 1 year of the COVID-19 epidemic: prospective cohort study protocol.

INTRODUCTION: National SARS-CoV-2 seroprevalence data provide essential information about population exposure to the virus and help predict the future course of the epidemic. Early cohort studies have suggested declines in levels of antibodies in individuals associated with, for example, illness severity, age and comorbidities. This protocol focuses on the seroprevalence among primary healthcare providers (PHCPs) in Belgium. PHCPs manage the vast majority of (COVID-19) patients and therefore play an essential role in the efficient organisation of healthcare. Currently, evidence is lacking on (1) how many PHCPs get infected with SARS-CoV-2 in Belgium, (2) the rate at which this happens, (3) their clinical spectrum, (4) their risk factors, (5) the effectiveness of the measures to prevent infection and (6) the accuracy of the serology-based point-of-care test (POCT) in a primary care setting. METHODS AND ANALYSIS: This study will be set up as a prospective cohort study. General practitioners (GPs) and other PHCPs (working in a GP practice) will be recruited via professional networks and professional media outlets to register online to participate. Registered GPs and other PHCPs will be asked at each testing point (n=9) to perform a capillary blood sample antibody POCT targeting IgM and IgG against the receptor-binding domain of SARS-CoV-2 and complete an online questionnaire. The primary outcomes are the prevalence and incidence of antibodies against SARS-CoV-2 in PHCPs during a 12-month follow-up period. Secondary outcomes include the longevity of antibodies against SARS-CoV-2. ETHICS AND DISSEMINATION: Ethical approval has been granted by the ethics committee of the University Hospital of Antwerp/University of Antwerp (Belgian registration number: 3002020000237). Alongside journal publications, dissemination activities include the publication of monthly reports to be shared with the participants and the general population through the publicly available website of the Belgian health authorities (Sciensano). TRIAL REGISTRATION NUMBER: NCT04779424.

Prospective SARS-CoV-2 cohort study among primary health care providers during the second COVID-19 wave in Flanders, Belgium.

BACKGROUND: Primary health care providers (PHCPs) are assumed to be at high risk of a COVID-19 infection, as they are exposed to patients with usually less personal protective equipment (PPE) than other frontline health care workers (HCWs). Nevertheless, current research efforts focussed on the assessment of COVID-19 seroprevalence rates in the general population or hospital HCWs. OBJECTIVE: We aimed to determine the seroprevalence in PHCPs during the second SARS-CoV-2 wave in Flanders (Belgium) and compared it to the seroprevalence in the general population. We also assessed risk factors, availability of PPE and attitudes towards the government guidelines over time. METHODS: A prospective cohort of PHCPs (n = 698), mainly general practitioners, was asked to complete a questionnaire and self-sample capillary blood by finger-pricking at five distinct points in time (June-December 2020). We analysed the dried blood spots for IgG antibodies using a Luminex multiplex immunoassay. RESULTS: The seroprevalence of PHCPs remained stable between June and September (4.6-5.0%), increased significantly from October to December (8.1-13.4%) and was significantly higher than the seroprevalence of the general population. The majority of PHCPs were concerned about becoming infected, had adequate PPE and showed increasing confidence in government guidelines. CONCLUSIONS: The marked increase in seroprevalence during the second COVID-19 wave shows that PHCPs were more at risk during the second wave compared to the first wave in Flanders. This increase was only slightly higher in PHCPs than in the general population suggesting that the occupational health measures implemented provided sufficient protection when managing patients.

Routine laboratory testing to determine if a patient has COVID-19.

BACKGROUND: Specific diagnostic tests to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and resulting COVID-19 disease are not always available and take time to obtain results. Routine laboratory markers such as white blood cell count, measures of anticoagulation, C-reactive protein (CRP) and procalcitonin, are used to assess the clinical status of a patient. These laboratory tests may be useful for the triage of people with potential COVID-19 to prioritize them for different levels of treatment, especially in situations where time and resources are limited. OBJECTIVES: To assess the diagnostic accuracy of routine laboratory testing as a triage test to determine if a person has COVID-19. SEARCH METHODS: On 4 May 2020 we undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. SELECTION CRITERIA: We included both case-control designs and consecutive series of patients that assessed the diagnostic accuracy of routine laboratory testing as a triage test to determine if a person has COVID-19. The reference standard could be reverse transcriptase polymerase chain reaction (RT-PCR) alone; RT-PCR plus clinical expertise or and imaging; repeated RT-PCR several days apart or from different samples; WHO and other case definitions; and any other reference standard used by the study authors. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data from each included study. They also assessed the methodological quality of the studies, using QUADAS-2. We used the 'NLMIXED' procedure in SAS 9.4 for the hierarchical summary receiver operating characteristic (HSROC) meta-analyses of tests for which we included four or more studies. To facilitate interpretation of results, for each meta-analysis we estimated summary sensitivity at the points on the SROC curve that corresponded to the median and interquartile range boundaries of specificities in the included studies. MAIN RESULTS: We included 21 studies in this review, including 14,126 COVID-19 patients and 56,585 non-COVID-19 patients in total. Studies evaluated a total of 67 different laboratory tests. Although we were interested in the diagnotic accuracy of routine tests for COVID-19, the included studies used detection of SARS-CoV-2 infection through RT-PCR as reference standard. There was considerable heterogeneity between tests, threshold values and the settings in which they were applied. For some tests a positive result was defined as a decrease compared to normal vaues, for other tests a positive result was defined as an increase, and for some tests both increase and decrease may have indicated test positivity. None of the studies had either low risk of bias on all domains or low concerns for applicability for all domains. Only three of the tests evaluated had a summary sensitivity and specificity over 50%. These were: increase in interleukin-6, increase in C-reactive protein and lymphocyte count decrease. Blood count Eleven studies evaluated a decrease in white blood cell count, with a median specificity of 93% and a summary sensitivity of 25% (95% CI 8.0% to 27%; very low-certainty evidence). The 15 studies that evaluated an increase in white blood cell count had a lower median specificity and a lower corresponding sensitivity. Four studies evaluated a decrease in neutrophil count. Their median specificity was 93%, corresponding to a summary sensitivity of 10% (95% CI 1.0% to 56%; low-certainty evidence). The 11 studies that evaluated an increase in neutrophil count had a lower median specificity and a lower corresponding sensitivity. The summary sensitivity of an increase in neutrophil percentage (4 studies) was 59% (95% CI 1.0% to 100%) at median specificity (38%; very low-certainty evidence). The summary sensitivity of an increase in monocyte count (4 studies) was 13% (95% CI 6.0% to 26%) at median specificity (73%; very low-certainty evidence). The summary sensitivity of a decrease in lymphocyte count (13 studies) was 64% (95% CI 28% to 89%) at median specificity (53%; low-certainty evidence). Four studies that evaluated a decrease in lymphocyte percentage showed a lower median specificity and lower corresponding sensitivity. The summary sensitivity of a decrease in platelets (4 studies) was 19% (95% CI 10% to 32%) at median specificity (88%; low-certainty evidence). Liver function tests The summary sensitivity of an increase in alanine aminotransferase (9 studies) was 12% (95% CI 3% to 34%) at median specificity (92%; low-certainty evidence). The summary sensitivity of an increase in aspartate aminotransferase (7 studies) was 29% (95% CI 17% to 45%) at median specificity (81%) (low-certainty evidence). The summary sensitivity of a decrease in albumin (4 studies) was 21% (95% CI 3% to 67%) at median specificity (66%; low-certainty evidence). The summary sensitivity of an increase in total bilirubin (4 studies) was 12% (95% CI 3.0% to 34%) at median specificity (92%; very low-certainty evidence). Markers of inflammation The summary sensitivity of an increase in CRP (14 studies) was 66% (95% CI 55% to 75%) at median specificity (44%; very low-certainty evidence). The summary sensitivity of an increase in procalcitonin (6 studies) was 3% (95% CI 1% to 19%) at median specificity (86%; very low-certainty evidence). The summary sensitivity of an increase in IL-6 (four studies) was 73% (95% CI 36% to 93%) at median specificity (58%) (very low-certainty evidence). Other biomarkers The summary sensitivity of an increase in creatine kinase (5 studies) was 11% (95% CI 6% to 19%) at median specificity (94%) (low-certainty evidence). The summary sensitivity of an increase in serum creatinine (four studies) was 7% (95% CI 1% to 37%) at median specificity (91%; low-certainty evidence). The summary sensitivity of an increase in lactate dehydrogenase (4 studies) was 25% (95% CI 15% to 38%) at median specificity (72%; very low-certainty evidence). AUTHORS' CONCLUSIONS: Although these tests give an indication about the general health status of patients and some tests may be specific indicators for inflammatory processes, none of the tests we investigated are useful for accurately ruling in or ruling out COVID-19 on their own. Studies were done in specific hospitalized populations, and future studies should consider non-hospital settings to evaluate how these tests would perform in people with milder symptoms.

Organisation and quality monitoring for point-of-care testing (POCT) in Belgium: proposal for an expansion of the legal framework for POCT into primary health care.

BACKGROUND: There is a trend towards decentralisation of laboratory tests by means of Point-of-Care testing (POCT). Within hospitals, Belgian law requires a POCT policy, coordinated by the clinical laboratory. There is however no legal framework for POCT performed outside the hospital: no reimbursement, no compulsory quality monitoring and no limits nor control on the prices charged to the patient. Uncontrolled use of POCT can have negative consequences for individual and public health. PROPOSAL: We propose that POCT outside hospitals would only be reimbursed for tests carried out within a legal framework, requiring evidence-based testing and collaboration with a clinical laboratory, because clinical laboratories have procedures for test validation and quality monitoring, are equipped for electronic data transfer, are familiar with logistical processes, can provide support when technical issues arise and can organise and certify training. Under these conditions the government investment will be offset by health benefits, e.g. fall in antibiotic consumption with POCT for CRP in primary care, quick response to SARS-CoV2-positive cases in COVID-19 triage centres. PRIORITIES: 1° extension of the Belgian decree on certification of clinical laboratories to decentralised tests in primary care; 2° introduction of a separate reimbursement category for POCT; 3° introduction of reimbursement for a limited number of specified POCT; 4° setup of a Multidisciplinary POCT Advisory Council, the purpose of which is to draw up a model for reimbursement of POCT, to select tests eligible for reimbursement and to make proposals to the National Institute for Health and Disability Insurance (RIZIV/INAMI).

SARS-CoV-2 Infections and Impact of the COVID-19 Pandemic in Pregnancy and Breastfeeding: Results from an Observational Study in Primary Care in Belgium.

COVID-19 also affects pregnant and breastfeeding women. Hence, clinicians and policymakers require reliable evidence on COVID-19 epidemiology and consequences in this population. We aimed to assess the susceptibility of pregnant women to SARS-CoV-2 and women's perceived impact of the pandemic on their breastfeeding practices, medical counseling and social support. We performed a cross-sectional study using an online survey in primary care in Belgium. Pregnant and breastfeeding women and women who breastfed in the preceding four weeks were eligible to participate. The survey was distributed through social media in April 2020. In total, 6470 women participated (i.e., 2647 pregnant and 3823 breastfeeding women). Overall, 0.3% of all respondents reported to have tested positive for SARS-CoV-2, not indicating a higher susceptibility of pregnant women to contracting COVID-19. More than 90% refuted that the pandemic affected their breastfeeding practices, nor indicated that the coronavirus was responsible for breastfeeding cessation. Half of the women even considered giving longer breastmilk because of the coronavirus. In contrast, women's medical counseling and social support were negatively affected by the lockdown. Women without previous breastfeeding experience and in the early postpartum period experienced a higher burden in terms of reduced medical counseling and support. In the future, more consideration and alternative supportive measures such as tele-visits by midwives or perinatal organizations are required for these women.

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

OBJECTIVE: To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. DESIGN: Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. DATA SOURCES: PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. STUDY SELECTION: Studies that developed or validated a multivariable covid-19 related prediction model. DATA EXTRACTION: At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). RESULTS: 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. CONCLUSION: Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. SYSTEMATIC REVIEW REGISTRATION: Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. READERS' NOTE: This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.