Protocol non-adherence is common and poses unique challenges in the interpretation of trial outcomes, especially in non-inferiority trials. We performed simulations of a non-inferiority trial with a time-fixed treatment and a binary endpoint in order to: i) explore the impact of various patterns of non-adherence and analysis methods on treatment effect estimates; ii) quantify the probability of claiming non-inferiority when the experimental treatment effect is actually inferior; and iii) evaluate alternative methods such as inverse probability weighting and instrumental variable estimation. We found that the probability of concluding non-inferiority when the experimental treatment is actually inferior depends on whether non-adherence is due to confounding or non-confounding factors, and the actual treatments received by the non-adherent participants. With non-adherence, intention-to-treat analysis has a higher tendency to conclude non-inferiority when the experimental treatment is actually inferior under most patterns of non-adherence. This probability of concluding non-inferiority can be increased to as high as 0.1 from 0.025 when the adherence is relatively high at 90%. The direction of bias for the per-protocol analysis depends on the directions of influence the confounders have on adherence and probability of outcome. The inverse probability weighting approach can reduce bias but will only eliminate it if all confounders can be measured without error and are appropriately adjusted for. Instrumental variable estimation overcomes this limitation and gives unbiased estimates even when confounders are not known, but typically requires large sample sizes to achieve acceptable power. Investigators need to consider patterns of non-adherence and potential confounders in trial designs. Adjusted analysis of the per-protocol population with sensitivity analyses on confounders and other approaches, such as instrumental variable estimation, should be considered when non-compliance is anticipated. We provide an online power calculator allowing for various patterns of non-adherence using the above methods.
\n \n\n \n \n[This corrects the article DOI: 10.1371/journal.pntd.0009657.].
\n \n\n \n \nBackgroundA nationwide Movement Control Order (MCO) was enforced in Malaysia on 18 March 2020 in view of the global COVID-19 pandemic. Malaysia implemented various public health measures and later raced against time to administer COVID-19 vaccines when they became available. As a result of various public health measures to curb the spread of the virus, people in Malaysia faced unprecedented circumstances and new challenges. This study addressed the knowledge gap in our understanding the experiences, coping strategies and perspectives of the people in Malaysia about infection countermeasures by investigating their experiences during the COVID-19 pandemic.MethodsA sequential mixed method approach was used to conduct an online survey and in-depth interviews among residents in Malaysia. A total of 827 respondents participated in the online survey from 1st May to 30th June 2020. Nineteen in-depth interviews were conducted online and by phone with key informants and members of the public, who were selected through maximum variation purposive sampling between 2nd May 2020 to 20th December 2021. The semi-structured interviews employed a phenomenological approach and transcripts were analysed using thematic analysis. The survey data were analysed using descriptive statistics in Stata 15.0.ResultsThe survey reflected significant economic impacts of the pandemic, the maximum number of days that people could cope during the MCO, and their coping strategies, which generally entailed changes in lifestyle. The internet and social media were vital platforms to mitigate against the impact of public health measures. Thematic analysis of the interview data revealed participant experiences and perceptions of COVID-19 and public health measures in four main themes: (1) work and business; (2) emotional impact (3) coping with change and (4) the COVID-19 vaccine.ConclusionsThis study provides insights into the experiences, coping strategies and perspectives of people in Malaysia living through the first-ever MCO during the COVID-19 pandemic. Such insights into COVID-19-related public health measures are pertinent for successfully planning and implementing future responses to pandemics.
\n \n\n \n \nGenetic studies associate killer cell immunoglobulin-like receptors (KIRs) and their HLA class I ligands with a variety of human diseases. The basis for these associations and the relative contribution of inhibitory and activating KIR to NK cell responses are unclear. Because KIR binding to HLA-I is peptide dependent, we performed systematic screens, which totaled more than 3500 specific interactions, to determine the specificity of five KIR for peptides presented by four HLA-C ligands. Inhibitory KIR2DL1 was largely peptide sequence agnostic and could bind ~60% of hundreds of HLA-peptide complexes tested. Inhibitory KIR2DL2, KIR2DL3, and activating KIR2DS1 and KIR2DS4 bound only 10% and down to 1% of HLA-peptide complexes tested, respectively. Activating KIR2DS1, previously described as weak, had high binding affinity for HLA-C, with high peptide sequence specificity. Our data revealed MHC-restricted peptide recognition by germline-encoded NK receptors and suggest that NK cell responses can be shaped by HLA-I\u2013bound immunopeptidomes in the context of disease or infection.
\n \n\n \n \nObjectiveTo evaluate blood-based biomarkers to detect endometriosis and/or adenomyosis across nine European centers (June 2014-April 2018).MethodsThis prospective, non-interventional study assessed the diagnostic accuracy of 54 blood-based biomarker immunoassays in samples from 919 women (aged 18-45\u2009years) with suspicion of endometriosis and/or adenomyosis versus symptomatic controls. Endometriosis was stratified by revised American Society for Reproductive Medicine stage. Symptomatic controls were \"pathologic symptomatic controls\" or \"pathology-free symptomatic controls\". The main outcome measure was receiver operating characteristic-area under the curve (ROC-AUC) and Wilcoxon P values corrected for multiple testing (q values).ResultsCA-125 performed best in \"all endometriosis cases\" versus \"all symptomatic controls\" (AUC 0.645, 95% confidence interval [CI] 0.600-0.690, q\u2009ConclusionThis study concluded that no biomarkers tested could diagnose or rule out endometriosis/adenomyosis with high certainty.
\n \n\n \n \nTesting for infection with SARS-CoV-2 is an important intervention in reducing onwards transmission of COVID-19, particularly when combined with the isolation and contact-tracing of positive cases. Many countries with the capacity to do so have made use of lab-processed Polymerase Chain Reaction (PCR) testing targeted at individuals with symptoms and the contacts of confirmed cases. Alternatively, Lateral Flow Tests (LFTs) are able to deliver a result quickly, without lab-processing and at a relatively low cost. Their adoption can support regular mass asymptomatic testing, allowing earlier detection of infection and isolation of infectious individuals. In this paper we extend and apply the agent-based epidemic modelling framework Covasim to explore the impact of regular asymptomatic testing on the peak and total number of infections in an emerging COVID-19 wave. We explore testing with LFTs at different frequency levels within a population with high levels of immunity and with background symptomatic PCR testing, case isolation and contact tracing for testing. The effectiveness of regular asymptomatic testing was compared with 'lockdown' interventions seeking to reduce the number of non-household contacts across the whole population through measures such as mandating working from home and restrictions on gatherings. Since regular asymptomatic testing requires only those with a positive result to reduce contact, while lockdown measures require the whole population to reduce contact, any policy decision that seeks to trade off harms from infection against other harms will not automatically favour one over the other. Our results demonstrate that, where such a trade off is being made, at moderate rates of early exponential growth regular asymptomatic testing has the potential to achieve significant infection control without the wider harms associated with additional lockdown measures.
\n \n\n \n \nContact tracing is an important tool for allowing countries to ease lockdown policies introduced to combat SARS-CoV-2. For contact tracing to be effective, those with symptoms must self-report themselves while their contacts must self-isolate when asked. However, policies such as legal enforcement of self-isolation can create trade-offs by dissuading individuals from self-reporting. We use an existing branching process model to examine which aspects of contact tracing adherence should be prioritized. We consider an inverse relationship between self-isolation adherence and self-reporting engagement, assuming that increasingly strict self-isolation policies will result in fewer individuals self-reporting to the programme. We find that policies which increase the average duration of self-isolation, or that increase the probability that people self-isolate at all, at the expense of reduced self-reporting rate, will not decrease the risk of a large outbreak and may increase the risk, depending on the strength of the trade-off. These results suggest that policies to increase self-isolation adherence should be implemented carefully. Policies that increase self-isolation adherence at the cost of self-reporting rates should be avoided.\nThis article is part of the theme issue \u2018Modelling that shaped the early COVID-19 pandemic response in the UK\u2019.
\n \n\n \n \nThe zoonotic Rift Valley fever virus (RVFV) can cause severe disease in humans and has pandemic potential, yet no approved vaccine or therapy exists. Here we describe a dual-mechanism human monoclonal antibody (mAb) combination against RVFV that is effective at minimal doses\u00a0in a lethal mouse model of infection. We structurally analyze and characterize the\u00a0binding mode of a prototypical potent Gn\u00a0domain-A-binding antibody that blocks attachment and of an antibody that inhibits infection by abrogating the fusion process as previously determined. Surprisingly, the Gn domain-A antibody does not directly block RVFV Gn interaction with the host receptor low density lipoprotein receptor-related protein 1 (LRP1) as determined by a competitive assay. This study identifies a rationally designed combination of human mAbs deserving of future investigation for use in humans against RVFV infection. Using a two-pronged mechanistic approach, we demonstrate the potent efficacy of a rationally designed combination mAb therapeutic.
\n \n\n \n \nBayesian methods are a popular choice for statistical inference in small-data regimes due to the regularization effect induced by the prior. In the context of density estimation, the standard nonparametric Bayesian approach is to target the posterior predictive of the Dirichlet process mixture model. In general, direct estimation of the posterior predictive is intractable and so methods typically resort to approximating the posterior distribution as an intermediate step. The recent development of quasi-Bayesian predictive copula updates, however, has made it possible to perform tractable predictive density estimation without the need for posterior approximation. Although these estimators are computationally appealing, they struggle on non-smooth data distributions. This is due to the comparatively restrictive form of the likelihood models from which the proposed copula updates were derived. To address this shortcoming, we consider a Bayesian nonparametric model with an autoregressive likelihood decomposition and a Gaussian process prior. While the predictive update of such a model is typically intractable, we derive a quasi-Bayesian update that achieves state-of-the-art results in small-data regimes.
\n \n\n \n \n