Model-based evaluation of school- and non-school-related measures to control the COVID-19 pandemic

Background: In autumn 2020, many countries, including the Netherlands, are experiencing a second wave of the COVID-19 pandemic. Health policymakers are struggling with choosing the right mix of measures to keep the COVID-19 case numbers under control, but still allow a minimum of social and economic activity. The priority to keep schools open is high, but the role of school-based contacts in the epidemiology of SARS-CoV-2 is incompletely understood. We used a transmission model to estimate the impact of school contacts on the transmission of SARS-CoV-2 and to assess the effects of school-based measures, including school closure, on controlling the pandemic at different time points during the pandemic. Methods and Findings: The age-structured model was fitted to age-specific seroprevalence and hospital admission data from the Netherlands during spring 2020. Compared to adults older than 60 years, the estimated susceptibility was 23% (95%CrI 20-28%) for children aged 0 to 20 years and 61% (95%CrI 50%-72%) for the age group of 20 to 60 years. The time points considered in the analyses were (i) August 2020 when the effective reproduction number (R_e) was estimated to be 1.31 (95%CrI 1.15-2.07), schools just opened after the summer holidays and measures were reinforced with the aim to reduce R_e to a value below 1, and (ii) November 2020 when measures had reduced R_e to 1.00 (95%CrI 0.94-1.33). In this period schools remained open. Our model predicts that keeping schools closed after the summer holidays, in the absence of other measures, would have reduced R_e by 10% (from 1.31 to 1.18 (95%CrI 1.04-1.83)) and thus would not have prevented the second wave in autumn 2020. Reducing non-school-based contacts in August 2020 to the level observed during the first wave of the pandemic would have reduced R_e to 0.83 (95%CrI 0.75-1.10). Yet, this reduction was not achieved and the observed R_e in November was 1.00. Our model predicts that closing schools in November 2020 could reduce R_e from the observed value of 1.00 to 0.84 (95%CrI 0.81-0.90), with unchanged non-school based contacts. Reductions in R_e due to closing schools in November 2020 were 8% for 10 to 20 years old children, 5% for 5 to 10 years old children and negligible for 0 to 5 years old children. Conclusions: The impact of measures reducing school-based contacts, including school closure, depends on the remaining opportunities to reduce non-school-based contacts. If opportunities to reduce R_e with non-school-based measures are exhausted or undesired and R_e is still close to 1, the additional benefit of school-based measures may be considerable, particularly among the older school children.</jats:p

Pathobionts in the Vaginal Microbiota: Individual Participant Data Meta-Analysis of Three Sequencing Studies

Sequencing studies have shown that optimal vaginal microbiota (VMB) are lactobacilli-dominated and that anaerobes associated with bacterial vaginosis (BV-anaerobes) are commonly present. However, they overlooked a less prevalent but more pathogenic group of vaginal bacteria: the pathobionts that cause maternal and neonatal infections and pelvic inflammatory disease. We conducted an individual participant data meta-analysis of three VMB sequencing studies that included diverse groups of women in Rwanda, South Africa, and the Netherlands (2,044 samples from 1,163 women in total). We identified 40 pathobiont taxa but only six were non-minority taxa (at least 1% relative abundance in at least one sample) in all studies: Streptococcus (54% of pathobionts reads), Staphylococcus, Enterococcus, Escherichia/Shigella, Haemophilus, and Campylobacter. When all pathobionts were combined into one bacterial group, the VMB of 17% of women contained a relative abundance of at least 1%. We found a significant negative correlation between relative abundances (ρ = −0.9234), but not estimated concentrations (r = 0.0031), of lactobacilli and BV-anaerobes; and a significant positive correlation between estimated concentrations of pathobionts and BV-anaerobes (r = 0.1938) but not between pathobionts and lactobacilli (r = 0.0436; although lactobacilli declined non-significantly with increasing pathobionts proportions). VMB sequencing data were also classified into mutually exclusive VMB types. The overall mean bacterial load of the ≥20% pathobionts VMB type (5.85 log10 cells/μl) was similar to those of the three lactobacilli-dominated VMB types (means 5.13–5.83 log10 cells/μl) but lower than those of the four anaerobic dysbiosis VMB types (means 6.11–6.87 log10 cells/μl). These results suggest that pathobionts co-occur with both lactobacilli and BV-anaerobes and do not expand as much as BV-anaerobes do in a dysbiotic situation. Pathobionts detection/levels were increased in samples with a Nugent score of 4–6 in both studies that conducted Nugent-scoring. Having pathobionts was positively associated with young age, non-Dutch origin, hormonal contraceptive use, smoking, antibiotic use in the 14 days prior to sampling, HIV status, and the presence of sexually transmitted pathogens, in at least one but not all studies; inconsistently associated with sexual risk-taking and unusual vaginal discharge reporting; and not associated with vaginal yeasts detection by microscopy. We recommend that future VMB studies quantify common vaginal pathobiont genera

Digital tools for the fight against COVID-19: Can a second wave be avoided?

Sinds het begin van de covid-19-epidemie zijn verschillende digitale middelen ontwikkeld, zoals apps die kunnen helpen bij de bestrijding van SARS-CoV-2. Met een app kunnen GGD’en de contacten van mensen die positief zijn getest op SARS-CoV-2 sneller traceren en daarmee verdere verspreiding van het virus beperken. Is een tweede golf hiermee te voorkomen

Model-based evaluation of school- and non-school-related measures to control the COVID-19 pandemic

The role of school-based contacts in the epidemiology of SARS-CoV-2 is incompletely understood. We use an age-structured transmission model fitted to age-specific seroprevalence and hospital admission data to assess the effects of school-based measures at different time points during the COVID-19 pandemic in the Netherlands. Our analyses suggest that the impact of measures reducing school-based contacts depends on the remaining opportunities to reduce non-school-based contacts. If opportunities to reduce the effective reproduction number (Re) with non-school-based measures are exhausted or undesired and Re is still close to 1, the additional benefit of school-based measures may be considerable, particularly among older school children. As two examples, we demonstrate that keeping schools closed after the summer holidays in 2020, in the absence of other measures, would not have prevented the second pandemic wave in autumn 2020 but closing schools in November 2020 could have reduced Re below 1, with unchanged non-school-based contacts

Digitale middelen in de strijd tegen covid-19: Is een tweede golf te voorkomen?

Sinds het begin van de covid-19-epidemie zijn verschillende digitale middelen ontwikkeld, zoals apps die kunnen helpen bij de bestrijding van SARS-CoV-2. Met een app kunnen GGD’en de contacten van mensen die positief zijn getest op SARS-CoV-2 sneller traceren en daarmee verdere verspreiding van het virus beperken. Is een tweede golf hiermee te voorkomen

Interventions to control nosocomial transmission of SARS-CoV-2: a modelling study

Background: Emergence of more transmissible SARS-CoV-2 variants requires more efficient control measures to limit nosocomial transmission and maintain healthcare capacities during pandemic waves. Yet the relative importance of different strategies is unknown. Methods: We developed an agent-based model and compared the impact of personal protective equipment (PPE), screening of healthcare workers (HCWs), contact tracing of symptomatic HCWs and restricting HCWs from working in multiple units (HCW cohorting) on nosocomial SARS-CoV-2 transmission. The model was fit on hospital data from the first wave in the Netherlands (February until August 2020) and assumed that HCWs used 90% effective PPE in COVID-19 wards and self-isolated at home for 7 days immediately upon symptom onset. Intervention effects on the effective reproduction number (RE), HCW absenteeism and the proportion of infected individuals among tested individuals (positivity rate) were estimated for a more transmissible variant. Results: Introduction of a variant with 56% higher transmissibility increased — all other variables kept constant — RE from 0.4 to 0.65 (+ 63%) and nosocomial transmissions by 303%, mainly because of more transmissions caused by pre-symptomatic patients and HCWs. Compared to baseline, PPE use in all hospital wards (assuming 90% effectiveness) reduced RE by 85% and absenteeism by 57%. Screening HCWs every 3 days with perfect test sensitivity reduced RE by 67%, yielding a maximum test positivity rate of 5%. Screening HCWs every 3 or 7 days assuming time-varying test sensitivities reduced RE by 9% and 3%, respectively. Contact tracing reduced RE by at least 32% and achieved higher test positivity rates than screening interventions. HCW cohorting reduced RE by 5%. Sensitivity analyses show that our findings do not change significantly for 70% PPE effectiveness. For low PPE effectiveness of 50%, PPE use in all wards is less effective than screening every 3 days with perfect sensitivity but still more effective than all other interventions. Conclusions: In response to the emergence of more transmissible SARS-CoV-2 variants, PPE use in all hospital wards might still be most effective in preventing nosocomial transmission. Regular screening and contact tracing of HCWs are also effective interventions but critically depend on the sensitivity of the diagnostic test used

Guidance for the design and reporting of studies evaluating the clinical performance of tests for present or past SARS-CoV-2 infection

Testing for SARS-CoV-2 infection is key in managing the current pandemic. More than 1700 preprints and peer reviewed journal articles evaluating tests for SARS-CoV-2 infection have been published as of January 2021. However, evaluations of these studies have identified many methodological issues, leading to a high risk of bias and difficulties applying the results in practice. Better guidance is urgently needed on the conduct and interpretation of these studies. This article outlines the principles for defining the intended purpose of the test; study population selection; reference standard, test timing; and other critical considerations for the design, reporting, and interpretation of diagnostic accuracy studies. The implementation and accuracy of SARSCoV-2 tests have major implications for individuals and communities, balancing the potential consequences of continued infection against the need for public health measures, such as the restriction of movements and social activities. Decision making in the current pandemic requires a clear understanding of the clinical performance and limitations of testing. This article provides guidance to assist researchers design robust diagnostic accuracy studies, assist publishers and peer reviewers to assess such studies, and support clinicians and policy makers in their evaluation of the evidence on SARS-CoV-2 testing for clinical and public health decisions. The guidance aims to ensure that studies evaluating the diagnostic accuracy of SARS-CoV-2 tests are conducted as rigorously as possible, in an efficient and timely way

BCG Vaccination of Health Care Workers Does Not Reduce SARS-CoV-2 Infections nor Infection Severity or Duration: a Randomized Placebo-Controlled Trial.

Bacillus Calmette-Guerin (BCG) vaccination has been hypothesized to reduce severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, severity, and/or duration via trained immunity induction. Health care workers (HCWs) in nine Dutch hospitals were randomized to BCG or placebo vaccination (1:1) in March and April 2020 and followed for 1 year. They reported daily symptoms, SARS-CoV-2 test results, and health care-seeking behavior via a smartphone application, and they donated blood for SARS-CoV-2 serology at two time points. A total of 1,511 HCWs were randomized and 1,309 analyzed (665 BCG and 644 placebo). Of the 298 infections detected during the trial, 74 were detected by serology only. The SARS-CoV-2 incidence rates were 0.25 and 0.26 per person-year in the BCG and placebo groups, respectively (incidence rate ratio, 0.95; 95% confidence interval, 0.76 to 1.21; P = 0.732). Only three participants required hospitalization for SARS-CoV-2. The proportions of participants with asymptomatic, mild, or moderate infections and the mean infection durations did not differ between randomization groups. In addition, unadjusted and adjusted logistic regression and Cox proportional hazards models showed no differences between BCG and placebo vaccination for any of these outcomes. The percentage of participants with seroconversion (7.8% versus 2.8%; P = 0.006) and mean SARS-CoV-2 anti-S1 antibody concentration (13.1 versus 4.3 IU/mL; P = 0.023) were higher in the BCG than placebo group at 3 months but not at 6 or 12 months postvaccination. BCG vaccination of HCWs did not reduce SARS-CoV-2 infections nor infection duration or severity (ranging from asymptomatic to moderate). In the first 3 months after vaccination, BCG vaccination may enhance SARS-CoV-2 antibody production during SARS-CoV-2 infection. IMPORTANCE While several BCG trials in adults were conducted during the 2019 coronavirus disease epidemic, our data set is the most comprehensive to date, because we included serologically confirmed infections in addition to self-reported positive SARS-CoV-2 test results. We also collected data on symptoms for every day during the 1-year follow-up period, which enabled us to characterize infections in detail. We found that BCG vaccination did not reduce SARS-CoV-2 infections nor infection duration or severity but may have enhanced SARS-CoV-2 antibody production during SARS-CoV-2 infection in the first 3 months after vaccination. These results are in agreement with other BCG trials that reported negative results (but did not use serological endpoints), except for two trials in Greece and India that reported positive results but had few endpoints and included endpoints that were not laboratory confirmed. The enhanced antibody production is in agreement with prior mechanistic studies but did not translate into protection from SARS-CoV-2 infection

Diagnostic accuracy of rapid antigen tests in asymptomatic and presymptomatic close contacts of individuals with confirmed SARS-CoV-2 infection: Cross sectional study

AbstractObjective To assess the diagnostic test accuracy of two rapid antigen tests in asymptomatic and presymptomatic close contacts of people with SARS-CoV-2 infection on day 5 after exposure. Design Prospective cross sectional study. Setting Four public health service covid-19 test sites in the Netherlands. Participants 4274 consecutively included close contacts (identified through test-and-trace programme or contact tracing app) aged 16 years or older and asymptomatic for covid-19 when requesting a test. Main outcome measures Sensitivity, specificity, and positive and negative predictive values of Veritor System (Beckton Dickinson) and Biosensor (Roche Diagnostics) rapid antigen tests, with reverse-transcriptase polymerase chain reaction (RT-PCR) testing as reference standard. The viral load cut-off above which 95% of people with a positive RT-PCR test result were virus culture positive was used as a proxy of infectiousness. Results Of 2678 participants tested with Veritor, 233 (8.7%) had a RT-PCR confirmed SARS-CoV-2 infection of whom 149 were also detected by the rapid antigen test (sensitivity 63.9%, 95% confidence interval 57.4% to 70.1%). Of 1596 participants tested with Biosensor, 132 (8.3%) had a RT-PCR confirmed SARS-CoV-2 infection of whom 83 were detected by the rapid antigen test (sensitivity 62.9%, 54.0% to 71.1%). In those who were still asymptomatic at the time of sampling, sensitivity was 58.7% (51.1% to 66.0%) for Veritor (n=2317) and 59.4% (49.2% to 69.1%) for Biosensor (n=1414), and in those who developed symptoms were 84.2% (68.7% to 94.0%; n=219) for Veritor and 73.3% (54.1% to 87.7%; n=158) for Biosensor. When a viral load cut-off was applied for infectiouness (≥5.2 log10 SARS-CoV-2 E gene copies/mL), the overall sensitivity was 90.1% (84.2% to 94.4%) for Veritor and 86.8% (78.1% to 93.0%) for Biosensor, and 88.1% (80.5% to 93.5%) for Veritor and 85.1% (74.3% to 92.6%) for Biosensor, among those who remained asymptomatic throughout. Specificities were >99%, and positive and negative predictive values were >90% and >95%, for both rapid antigen tests in all analyses. Conclusions The sensitivities of both rapid antigen tests in asymptomatic and presymptomatic close contacts tested on day 5 onwards after close contact with an index case were more than 60%, increasing to more than 85% after a viral load cut-off was applied as a proxy for infectiousness