How to Determine When SARS-CoV-2 Antibody Testing Is or Is Not Useful for Population Screening: A Tutorial

Extensive testing lies at the heart of any strategy to effectively combat the SARS-COV-2 pandemic. In recent months, the use of enzyme-linked immunosorbent assay–based antibody tests has gained a lot of attention. These tests can potentially be used to assess SARS-COV-2 immunity status in individuals (e.g., essential health care personnel). They can also be used as a screening tool to identify people that had COVID-19 asymptomatically, thus getting a better estimate of the true spread of the disease, gain important insights on disease severity, and to better evaluate the effectiveness of policy measures implemented to combat the pandemic. But the usefulness of these tests depends not only on the quality of the test but also, critically, on how far disease has already spread in the population. For example, when only very few people in a population are infected, a positive test result has a high chance of being a false positive. As a consequence, the spread of the disease in a population as well as individuals’ immunity status may be systematically misinterpreted. SARS-COV-2 infection rates vary greatly across both time and space. In many places, the infection rates are very low but can quickly skyrocket when the virus spreads unchecked. Here, we present two tools, natural frequency trees and positive and negative predictive value graphs, that allow one to assess the usefulness of antibody testing for a specific context at a glance. These tools should be used to support individual doctor-patient consultation for assessing individual immunity status as well as to inform policy discussions on testing initiatives.Peer Reviewe

Germany’s fourth COVID-19 wave was mainly driven by the unvaccinated

Background While the majority of the German population was fully vaccinated at the time (about 65%), COVID-19 incidence started growing exponentially in October 2021 with about 41% of recorded new symptomatic cases aged twelve or above being symptomatic breakthrough infections, presumably also contributing to the dynamics. So far, it remained elusive how significant this contribution was and whether targeted non-pharmaceutical interventions (NPIs) may have stopped the amplification of the crisis. Methods We develop and introduce a contribution matrix approach based on the next-generation matrix of a population-structured compartmental infectious disease model to derive contributions of respective inter- and intragroup infection pathways of unvaccinated and vaccinated subpopulations to the effective reproduction number and new infections, considering empirical data of vaccine efficacies against infection and transmission. Results Here we show that about 61%–76% of all new infections were caused by unvaccinated individuals and only 24%–39% were caused by the vaccinated. Furthermore, 32%–51% of new infections were likely caused by unvaccinated infecting other unvaccinated. Decreasing the transmissibility of the unvaccinated by, e. g. targeted NPIs, causes a steeper decrease in the effective reproduction number R than decreasing the transmissibility of vaccinated individuals, potentially leading to temporary epidemic control. Reducing contacts between vaccinated and unvaccinated individuals serves to decrease R in a similar manner as increasing vaccine uptake. Conclusions A minority of the German population—the unvaccinated—is assumed to have caused the majority of new infections in the fall of 2021 in Germany. Our results highlight the importance of combined measures, such as vaccination campaigns and targeted contact reductions to achieve temporary epidemic control.Peer Reviewe

Explaining the Mechanism Behind mRNA Vaccines Influences Perceived Vaccine Effectiveness but not Vaccination Intentions

Vaccine effectiveness and safety concerns can prevent people from receiving their first Covid-19 vaccines or boosters. Understanding the vaccine mechanism may lead people to perceive vaccine effectiveness appropriately. This study tested whether helping people understand the vaccine’s mechanism could improve their perceived vaccine safety and effectiveness. In a preregistered study, N = 1,548 unvaccinated or non-boosted participants were randomly presented with one of three communication formats: a fact box (a benefit-risk profile in tabular format; control condition), an expository text (i.e., a purely factual explanation) plus fact box, or an analogy plus fact box. Participants rated the vaccine’s effectiveness in preventing a Covid-19 disease, their perceived risk of getting vaccinated, and their intention to get vaccinated or boosted (depending on their vaccination status). Reading either additional text about the vaccines’ mechanism increased participants’ effectiveness ratings for the vaccine to prevent Covid-19 but did not affect risk ratings or vaccination intentions. The participants’ vaccine-related perceptions and intentions did not differ between the two text types. Elaborating on the vaccine’s mechanism of protection, in addition to presenting the benefit-risk profile of a vaccine, can lead people to perceive the vaccine effectiveness as slightly higher, yet it is insufficient to increase vaccination intentions

Kommunikationsempfehlungen zur Verbesserung des Verhaltens bei der Verwendung von PoC Antigen-Schnelltests und Selbsttests

Die breitere Anwendung von Antigentests zum Auffinden einer akuten Infektion mit SARS-CoV-2 beinhaltet Chancen, aber auch Risiken und Limitationen. Die Tests können als einer von mehreren Bausteinen zur Pandemiekontrolle beitragen, indem sie die Erkennung von Infektionen und somit die Unterbrechung von Infektionsketten ermöglichen - insbesondere durch wiederholte, engmaschige Testungen derselben Personen. Der Beitrag fasst die wichtigsten Aspekte zusammen und gibt evidenzbasierte Tipps zur Kommunikation rund um die PoC Antigen-Schnelltests und Selbsttests

A modelling framework for the prediction of the herd-level probability of infection from longitudinal data

International audienceThe collective control programmes (CPs) that exist for many infectious diseases of farm animals rely on the application of diagnostic testing at regular time intervals for the identification of infected animals or herds. The diversity of these CPs complicates the trade of animals between regions or countries because the definition of freedom from infection differs from one CP to another. In this paper, we describe a statistical model for the prediction of herd-level probabilities of infection from longitudinal data collected as part of CPs against infectious diseases of cattle. The model was applied to data collected as part of a CP against bovine viral diarrhoea virus (BVDV) infection in Loire-Atlantique, France. The model represents infection as a herd latent status with a monthly dynamics. This latent status determines test results through test sensitivity and test specificity. The probability of becoming status positive between consecutive months is modelled as a function of risk factors (when available) using logistic regression. Modelling is performed in a Bayesian framework, using either Stan or JAGS. Prior distributions need to be provided for the sensitivities and specificities of the different tests used, for the probability of remaining status positive between months as well as for the probability of becoming positive between months. When risk factors are available, prior distributions need to be provided for the coefficients of the logistic regression, replacing the prior for the probability of becoming positive. From these prior distributions and from the longitudinal data, the model returns posterior probability distributions for being status positive for all herds on the current month. Data from the previous months are used for parameter estimation. The impact of using different prior distributions and model implementations on parameter estimation was evaluated. The main advantage of this model is its ability to predict a probability of being status positive in a month from inputs that can vary in terms of nature of test, frequency of testing and risk factor availability/presence. The main challenge in applying the model to the BVDV CP data was in identifying prior distributions, especially for test characteristics, that corresponded to the latent status of interest, i.e. herds with at least one persistently infected (PI) animal. The model is available on Github as an R package (https://github.com/AurMad/STOCfree) and can be used to carry out output-based evaluation of disease CPs

Long-Term Follow-Up of Newborns with 22q11 Deletion Syndrome and Low TRECs.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadBackground: Population-based neonatal screening using T-cell receptor excision circles (TRECs) identifies infants with profound T lymphopenia, as seen in cases of severe combined immunodeficiency, and in a subgroup of infants with 22q11 deletion syndrome (22q11DS). Purpose: To investigate the long-term prognostic value of low levels of TRECs in newborns with 22q11DS. Methods: Subjects with 22q11DS and low TRECs at birth (22q11Low, N=10), matched subjects with 22q11DS and normal TRECs (22q11Normal, N=10), and matched healthy controls (HC, N=10) were identified. At follow-up (median age 16 years), clinical and immunological characterizations, covering lymphocyte subsets, immunoglobulins, TRECs, T-cell receptor repertoires, and relative telomere length (RTL) measurements were performed. Results: At follow-up, the 22q11Low group had lower numbers of naïve T-helper cells, naïve T-regulatory cells, naïve cytotoxic T cells, and persistently lower TRECs compared to healthy controls. Receptor repertoires showed skewed V-gene usage for naïve T-helper cells, whereas for naïve cytotoxic T cells, shorter RTL and a trend towards higher clonality were found. Multivariate discriminant analysis revealed a clear distinction between the three groups and a skewing towards Th17 differentiation of T-helper cells, particularly in the 22q11Low individuals. Perturbations of B-cell subsets were found in both the 22q11Low and 22q11Normal group compared to the HC group, with larger proportions of naïve B cells and lower levels of memory B cells, including switched memory B cells. Conclusions: This long-term follow-up study shows that 22q11Low individuals have persistent immunologic aberrations and increased risk for immune dysregulation, indicating the necessity of lifelong monitoring. Clinical implications: This study elucidates the natural history of childhood immune function in newborns with 22q11DS and low TRECs, which may facilitate the development of programs for long-term monitoring and therapeutic choices. Keywords: 22q11.2 deletion syndrome; DiGeorge syndrome; T lymphopenia; TREC; long-term outcome; newborn screening; severe combined immunodeficiency.University of Gothenburg Regional research grant Region Halland Swedish Research Council European Commission Queen Silvia Jubilee Foundation Swedish Primary Immunodeficiency Organization Sparbanken Foundation Varberg Frimurare Barnhusdirektionen Foundation Gothenburg Medical Society Medical Faculty at Umea University Cancer Research Foundation in Northern Sweden Swedish government county councils, the ALF-agreement Umea University Vasterbottens County Counci