Molecular disparities in colorectal cancers of White Americans, Alabama African Americans, and Oklahoma American Indians.

In the US, the majority of cancer samples analyzed are from white people, leading to biases in racial and ethnic treatment outcomes. Colorectal cancer (CRC) incidence and mortality rates are high in Alabama African Americans (AAs) and Oklahoma American Indians (AIs). We hypothesized that differences between racial groups may partially explain these disparities. Thus, we compared transcriptomic profiles of CRCs of Alabama AAs, Oklahoma AIs, and white people from both states. Compared to CRCs of white people, CRCs of AAs showed (a) higher expression of cytokines and vesicle trafficking toward modulated antitumor-immune activity, and (b) lower expression of the ID1/BMP/SMAD axis, IL22RA1, APOBEC3, and Mucins; and AIs had (c) higher expression of PTGS2/COX2 (an NSAID target/pro-oncogenic inflammation) and splicing regulators, and (d) lower tumor suppressor activities (e.g., TOB2, PCGF2, BAP1). Therefore, targeting strategies designed for white CRC patients may be less effective for AAs/AIs. These findings illustrate needs to develop optimized interventions to overcome racial CRC disparities.

Bayesian nonparametric inference for heterogeneously mixing infectious disease models.

SignificanceMathematical models of infectious disease transmission continue to play a vital role in understanding, mitigating, and preventing outbreaks. The vast majority of epidemic models in the literature are parametric, meaning that they contain inherent assumptions about how transmission occurs in a population. However, such assumptions can be lacking in appropriate biological or epidemiological justification and in consequence lead to erroneous scientific conclusions and misleading predictions. We propose a flexible Bayesian nonparametric framework that avoids the need to make strict model assumptions about the infection process and enables a far more data-driven modeling approach for inferring the mechanisms governing transmission. We use our methods to enhance our understanding of the transmission mechanisms of the 2001 UK foot and mouth disease outbreak.

Pair-based likelihood approximations for stochastic epidemic models.

Fitting stochastic epidemic models to data is a non-standard problem because data on the infection processes defined in such models are rarely observed directly. This in turn means that the likelihood of the observed data is intractable in the sense that it is very computationally expensive to obtain. Although data-augmented Markov chain Monte Carlo (MCMC) methods provide a solution to this problem, employing a tractable augmented likelihood, such methods typically deteriorate in large populations due to poor mixing and increased computation time. Here, we describe a new approach that seeks to approximate the likelihood by exploiting the underlying structure of the epidemic model. Simulation study results show that this approach can be a serious competitor to data-augmented MCMC methods. Our approach can be applied to a wide variety of disease transmission models, and we provide examples with applications to the common cold, Ebola, and foot-and-mouth disease.

Key questions for modelling COVID-19 exit strategies.

Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.

Modelling, Bayesian inference, and model assessment for nosocomial pathogens using whole-genome-sequence data.

Whole-genome sequencing of pathogens in outbreaks of infectious disease provides the potential to reconstruct transmission pathways and enhance the information contained in conventional epidemiological data. In recent years, there have been numerous new methods and models developed to exploit such high-resolution genetic data. However, corresponding methods for model assessment have been largely overlooked. In this article, we develop both new modelling methods and new model assessment methods, specifically by building on the work of Worby et al. Although the methods are generic in nature, we focus specifically on nosocomial pathogens and analyze a dataset collected during an outbreak of MRSA in a hospital setting.

Training in multiple breath washout testing for respiratory physiotherapists.

INTRODUCTION: The development of multiple breath washout (MBW) testing in respiratory disease highlights the need for increased awareness amongst respiratory physiotherapists and a potential opportunity for professional development in the use of an important outcome measure for clinical trials. OBJECTIVES: To rationalise how MBW may be a useful assessment tool for respiratory physiotherapists and to describe a local MBW training and certification programme for physiotherapists. RESULTS: The respiratory Multidisciplinary Team in the Belfast Health and Social Care Trust (BHSCT) identified a need for MBW testing to be available to facilitate clinical research and assessment. A 2day training programme consisting of prereading preparation, self-directed learning, theory presentations, practical demonstrations and hands-on practice was developed and delivered. All participants underwent a certification process. CONCLUSION: We have demonstrated the successful training and certification of clinical and research physiotherapists and encourage other respiratory physiotherapists to consider MBW test training.

Evaluating hospital infection control measures for antimicrobial-resistant pathogens using stochastic transmission models: Application to vancomycin-resistant enterococci in intensive care units.

Nosocomial pathogens such as methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE) are the cause of significant morbidity and mortality among hospital patients. It is important to be able to assess the efficacy of control measures using data on patient outcomes. In this paper, we describe methods for analysing such data using patient-level stochastic models which seek to describe the underlying unobserved process of transmission. The methods are applied to detailed longitudinal patient-level data on vancomycin-resistant Enterococci from a study in a US hospital with eight intensive care units (ICUs). The data comprise admission and discharge dates, dates and results of screening tests, and dates during which precautionary measures were in place for each patient during the study period. Results include estimates of the efficacy of the control measures, the proportion of unobserved patients colonized with vancomycin-resistant Enterococci, and the proportion of patients colonized on admission.

Modelling and Bayesian analysis of the Abakaliki smallpox data.

The celebrated Abakaliki smallpox data have appeared numerous times in the epidemic modelling literature, but in almost all cases only a specific subset of the data is considered. The only previous analysis of the full data set relied on approximation methods to derive a likelihood and did not assess model adequacy. The data themselves continue to be of interest due to concerns about the possible re-emergence of smallpox as a bioterrorism weapon. We present the first full Bayesian statistical analysis using data-augmentation Markov chain Monte Carlo methods which avoid the need for likelihood approximations and which yield a wider range of results than previous analyses. We also carry out model assessment using simulation-based methods. Our findings suggest that the outbreak was largely driven by the interaction structure of the population, and that the introduction of control measures was not the sole reason for the end of the epidemic. We also obtain quantitative estimates of key quantities including reproduction numbers.

Multi-Institutional FASTQ File Exchange as a Means of Proficiency Testing for Next-Generation Sequencing Bioinformatics and Variant Interpretation.

Next-generation sequencing is becoming increasingly common in clinical laboratories worldwide and is revolutionizing clinical molecular testing. However, the large amounts of raw data produced by next-generation sequencing assays and the need for complex bioinformatics analyses present unique challenges. Proficiency testing in clinical laboratories has traditionally been designed to evaluate assays in their entirety; however, it can be alternatively applied to separate assay components. We developed and implemented a multi-institutional proficiency testing approach to directly assess custom bioinformatics and variant interpretation processes. Six clinical laboratories, all of which use the same commercial library preparation kit for next-generation sequencing analysis of tumor specimens, each submitted raw data (FASTQ files) from four samples. These 24 file sets were then deidentified and redistributed to five of the institutions for analysis and interpretation according to their clinically validated approach. Among the laboratories, there was a high rate of concordance in the calling of single-nucleotide variants, in particular those we considered clinically significant (100% concordance). However, there was significant discordance in the calling of clinically significant insertions/deletions, with only two of seven being called by all participating laboratories. Missed calls were addressed by each laboratory to improve their bioinformatics processes. Thus, through our alternative proficiency testing approach, we identified the bioinformatic detection of insertions/deletions as an area of particular concern for clinical laboratories performing next-generation sequencing testing.

Reconstructing transmission trees for communicable diseases using densely sampled genetic data.

Whole genome sequencing of pathogens from multiple hosts in an epidemic offers the potential to investigate who infected whom with unparalleled resolution, potentially yielding important insights into disease dynamics and the impact of control measures. We considered disease outbreaks in a setting with dense genomic sampling, and formulated stochastic epidemic models to investigate person-to-person transmission, based on observed genomic and epidemiological data. We constructed models in which the genetic distance between sampled genotypes depends on the epidemiological relationship between the hosts. A data augmented Markov chain Monte Carlo algorithm was used to sample over the transmission trees, providing a posterior probability for any given transmission route. We investigated the predictive performance of our methodology using simulated data, demonstrating high sensitivity and specificity, particularly for rapidly mutating pathogens with low transmissibility. We then analyzed data collected during an outbreak of methicillin-resistant Staphylococcus aureus in a hospital, identifying probable transmission routes and estimating epidemiological parameters. Our approach overcomes limitations of previous methods, providing a framework with the flexibility to allow for unobserved infection times, multiple independent introductions of the pathogen, and within-host genetic diversity, as well as allowing forward simulation.

Transition of care for adolescents from paediatric services to adult health services.

BACKGROUND: There is evidence that the process of transition from paediatric (child) to adult health services is often associated with deterioration in the health of adolescents with chronic conditions.Transitional care is the term used to describe services that seek to bridge this care gap. It has been defined as 'the purposeful, planned movement of adolescents and young adults with chronic physical and medical conditions from child-centred to adult-oriented health care systems'. In order to develop appropriate services for adolescents, evidence of what works and what factors act as barriers and facilitators of effective interventions is needed. OBJECTIVES: To evaluate the effectiveness of interventions designed to improve the transition of care for adolescents from paediatric to adult health services. SEARCH METHODS: We searched The Cochrane Central Register of Controlled Trials 2015, Issue 1, (including the Cochrane Effective Practice and Organisation of Care Group Specialised Register), MEDLINE, EMBASE, PsycINFO, and Web of Knowledge to 19 June 2015. We also searched reference lists of included studies and relevant reviews, and contacted experts and study authors for additional studies. SELECTION CRITERIA: We considered randomised controlled trials (RCTs), controlled before- and after-studies (CBAs), and interrupted time-series studies (ITSs) that evaluated the effectiveness of any intervention (care model or clinical pathway), that aimed to improve the transition of care for adolescents from paediatric to adult health services. We considered adolescents with any chronic condition that required ongoing clinical care, who were leaving paediatric services and going on to receive services in adult healthcare units, and their families. Participating providers included all health professionals responsible for the care of young people. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data from included papers, assessed the risk of bias of each study, and assessed the certainty of the evidence for the main comparisons using GRADE. Discrepancies were resolved by discussion. Authors were contacted for missing data. We reported the findings of the studies as pre- and post-intervention means and calculated the unadjusted absolute change from baseline with 95% confidence intervals (CI). MAIN RESULTS: We included four RCTs (N = 238 participants) that explored: a two-day workshop-based transition preparation training for adolescents with spina bifida; a nurse-led, one-on-one, teaching session with the additional support of a 'health passport' for adolescents with heart disease; a web- and SMS-based educational intervention for adolescents with a range of different conditions; and a structured comprehensive transition programme with a transition co-ordinator for adolescents with type 1 diabetes.One study evaluating a one-on-one nurse-led intervention, and one evaluating a technology-based intervention suggested that these interventions may lead to slight improvements in transitional readiness and chronic disease self-management measured at six- to eight-month follow-ups (low certainty evidence). Results with the TRAQ self-management tool were: MD 0.20; 95% CI -0.16 to 0.56 and MD 0.43; 95% CI; -0.09 to 0.95; with the TRAQ self-advocacy tool: MD 0.37; 95% CI -0.06 to 0.80; and with the PAM tool were: MD 10; 95% CI 2.96 to 17.04. In contrast, transition-preparation training delivered via a two-day workshop for patients with spina bifida may lead to little or no difference in measures of self-care practice and general health behaviours when measured using the DSCPI-90©.Two studies evaluated the use of health services. One study evaluated a technology-based intervention and another a comprehensive transition programme; these interventions may lead to slightly more young people taking positive steps to initiate contact with health professionals themselves (Relative risk (RR): 4.87; 95% CI 0.24 to 98.12 and RR 1.50; 95% CI 0.32 to 6.94, respectively; low certainty evidence.Young people's knowledge of their disease may slightly improve with a nurse-led, one-on-one intervention to prepare young people for transition to an adult congenital heart programme (MD 14; 95% CI 2.67 to 25.33; one study; low certainty evidence).Disease-specific outcome measures were reported in two studies, both of which led to little or no difference in outcomes (low certainty evidence). One study found little or no difference between intervention and control groups. A second study found that follow-up HbA1c in young people with type 1 diabetes mellitus increased by 1.2% for each percentage increase in baseline HbA1c, independent of treatment group (1.2%; 95% CI 0.4 to 1.9; P = 0.01).Transition interventions may lead to little or no difference in well-being or quality of life as measured with the PARS III or PedsQ (two studies; low certainty evidence). Both the technology-based intervention and the two-day workshop for young people with spina bifida found little or no difference between intervention and control groups (MD 1.29; 95% CI -4.49 to 7.07). One study did not report the data.Four telephone support calls from a transition co-ordinator may lead to little or no difference in rates of transfer from paediatric to adult diabetes services (one study; low certainty evidence). At 12-month follow-up, there was little or no difference between groups of young people receiving usual care or a telephone support (RR 0.80; 95% CI 0.59 to 1.08)). They may slightly reduce the risk of disease-related hospital admissions at 12-month follow-up (RR 0.29; 95% CI 0.03 to 2.40). AUTHORS' CONCLUSIONS: The available evidence (four small studies; N = 238), covers a limited range of interventions developed to facilitate transition in a limited number of clinical conditions, with only four to 12 months follow-up. These follow-up periods may not be long enough for any changes to become apparent as transition is a lengthy process. There was evidence of improvement in patients' knowledge of their condition in one study, and improvements in self-efficacy and confidence in another, but since few studies were eligible for this review, and the overall certainty of the body of this evidence is low, no firm conclusions can be drawn about the effectiveness of the evaluated interventions. Further research is very likely to have an important impact on our confidence in the intervention effect and likely could change our conclusions. There is considerable scope for the rigorous evaluation of other models of transitional care, reporting on clinical outcomes with longer term follow-up.

Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes.

This paper considers novel Bayesian non-parametric methods for stochastic epidemic models. Many standard modeling and data analysis methods use underlying assumptions (e.g. concerning the rate at which new cases of disease will occur) which are rarely challenged or tested in practice. To relax these assumptions, we develop a Bayesian non-parametric approach using Gaussian Processes, specifically to estimate the infection process. The methods are illustrated with both simulated and real data sets, the former illustrating that the methods can recover the true infection process quite well in practice, and the latter illustrating that the methods can be successfully applied in different settings.

Stochastic epidemic models featuring contact tracing with delays.

This paper is concerned with a stochastic model for the spread of an SEIR (susceptible → exposed (=latent) → infective → removed) epidemic with a contact tracing scheme, in which removed individuals may name some of their infectious contacts, who are then removed if they have not been already after some tracing delay. The epidemic is analysed via an approximating, modified birth-death process, for which a type-reproduction number is derived in terms of unnamed individuals, that is shown to be infinite when the contact rate is sufficiently large. We obtain explicit results under the assumption of either constant or exponentially distributed infectious periods, including the epidemic extinction probability in the former case. Numerical illustrations show that, while the distributions of latent periods and delays have an effect on the spread of the epidemic, the assumption of whether the delays experienced by individuals infected by the same individual are of the same or independent length makes little difference.

Bayesian model choice for epidemic models with two levels of mixing.

This paper considers the problem of choosing between competing models for infectious disease final outcome data in a population that is partitioned into households. The epidemic models are stochastic individual-based transmission models of the susceptible-infective-removed type. The main focus is on various algorithms for the estimation of Bayes factors, of which a path sampling-based algorithm is seen to give the best results. We also explore theoretical properties in the case where the within-model prior distributions become increasingly uninformative, which show the need for caution when using Bayes factors as a model choice tool. A suitable form of deviance information criterion is also considered for comparison. The theory and methods are illustrated with both artificial data, and influenza data from the Tecumseh study of illness.

Estimation of vaccine efficacy and critical vaccination coverage in partially observed outbreaks.

Classical approaches to estimate vaccine efficacy are based on the assumption that a person's risk of infection does not depend on the infection status of others. This assumption is untenable for infectious disease data where such dependencies abound. We present a novel approach to estimating vaccine efficacy in a Bayesian framework using disease transmission models. The methodology is applied to outbreaks of mumps in primary schools in the Netherlands. The total study population consisted of 2,493 children in ten primary schools, of which 510 (20%) were known to have been infected, and 832 (33%) had unknown infection status. The apparent vaccination coverage ranged from 12% to 93%, and the apparent infection attack rate varied from 1% to 76%. Our analyses show that vaccination reduces the probability of infection per contact substantially but not perfectly ([Formula: see text] = 0.933; 95CrI: 0.908-0.954). Mumps virus appears to be moderately transmissible in the school setting, with each case yielding an estimated 2.5 secondary cases in an unvaccinated population ([Formula: see text] = 2.49; 95%CrI: 2.36-2.63), resulting in moderate estimates of the critical vaccination coverage (64.2%; 95%CrI: 61.7-66.7%). The indirect benefits of vaccination are highest in populations with vaccination coverage just below the critical vaccination coverage. In these populations, it is estimated that almost two infections can be prevented per vaccination. We discuss the implications for the optimal control of mumps in heterogeneously vaccinated populations.

Estimating the effectiveness of isolation and decolonization measures in reducing transmission of methicillin-resistant Staphylococcus aureus in hospital general wards.

Infection control for hospital pathogens such as methicillin-resistant Staphylococcus aureus (MRSA) often takes the form of a package of interventions, including the use of patient isolation and decolonization treatment. Such interventions, though widely used, have generated controversy because of their significant resource implications and the lack of robust evidence with regard to their effectiveness at reducing transmission. The aim of this study was to estimate the effectiveness of isolation and decolonization measures in reducing MRSA transmission in hospital general wards. Prospectively collected MRSA surveillance data from 10 general wards at Guy's and St. Thomas' hospitals, London, United Kingdom, in 2006-2007 were used, comprising 14,035 patient episodes. Data were analyzed with a Markov chain Monte Carlo algorithm to model transmission dynamics. The combined effect of isolation and decolonization was estimated to reduce transmission by 64% (95% confidence interval: 37, 79). Undetected MRSA-positive patients were estimated to be the source of 75% (95% confidence interval: 67, 86) of total transmission events. Isolation measures combined with decolonization treatment were strongly associated with a reduction in MRSA transmission in hospital general wards. These findings provide support for active methods of MRSA control, but further research is needed to determine the relative importance of isolation and decolonization in preventing transmission.

Impact of a web based interactive simulation game (PULSE) on nursing students' experience and performance in life support training--a pilot study.

The delivery of effective life support measures is highly associated with the quality, design and implementation of the education that underpins it. Effectively responding to a critical event is a requirement for all nurses illustrating the need for effective educational approaches from pre-registration training through to enhancing and maintaining life support skills after qualification. This paper reports the findings of utilising a web-based multimedia simulation game PULSE (Platform for Undergraduate Life Support Education). The platform was developed to enhance the student experience of life support education, to motivate on-going learning and engagement and to improve psychomotor skills associated with the provision of Intermediate Life Support (ILS) training. Pre training participants played PULSE and during life support training data was collected from an intervention and a control group of final year undergraduate nursing students (N=34). Quantitative analysis of performance took place and qualitative data was generated from a questionnaire assessing the learning experience. A statistically significant difference was found between the competence the groups displayed in the three skills sets of checking equipment, airway assessment and the safe/effective use of defibrillator at ILS level, and PULSE was positively evaluated as an educational tool when used alongside traditional life support training.

Introduction and snapshot review: relating infectious disease transmission models to data.

Disease transmission models are becoming increasingly important both to public health policy makers and to scientists across many disciplines. We review some of the key aspects of how and why such models are related to data from infectious disease outbreaks, and identify a number of future challenges in the field.

Extensive use of torpor in 13-lined ground squirrels in the fall prior to cold exposure.

Mammalian hibernation is characterized by profound reductions in body temperature (T(b)) and metabolic, heart and respiratory rates. These reductions are characteristic of torpor, which is temporally confined to winter. Hibernators including ground squirrels are heterothermic in winter, cycling between multiday periods of torpor with low T(b) and brief periods of rewarming. In contrast, ground squirrels remain homeothermic during summer, like non-hibernating mammals. The transition between the homeothermic and heterothermic phases of the circannual rhythm of hibernation is often overlooked in hibernation studies. Here, we examined the use of torpor throughout the fall transition in laboratory-housed 13-lined ground squirrels by recording core body temperature with an implanted data logger. As is typical of laboratory-based hibernation studies, animals were kept in standard housing prior to being moved into a cold, dark room to simulate natural hibernation conditions. Significantly, the vast majority of both male and female ground squirrels expressed torpor in the fall while still housed conventionally and prior to cold exposure. The expression of torpor was not predicted by body weight or age, rather it appears to be preprogrammed in a time-dependent manner that is independent of, yet enhanced by, environmental cues. The timing and duration of these torpor bouts occurring prior to cold exposure were also remarkably sporadic. Thus, it is not possible to know with certainty which animals are torpor-naive before cold exposure in the absence of continuous measurement of body temperature. We conclude that fall animals encompass variable points in the transition between summer and winter phases of the circannual cycle of hibernation, thereby confounding studies in which they are used as non-hibernating controls. Conversely, these fall transition animals offer unique opportunities to define the molecular changes that accompany and enable hibernation.

Estimation of measles vaccine efficacy and critical vaccination coverage in a highly vaccinated population.

Measles is a highly infectious disease that has been targeted for elimination from four WHO regions. Whether and under which conditions this goal is feasible is, however, uncertain since outbreaks have been documented in populations with high vaccination coverage (more than 90%). Here, we use the example of a large outbreak in a German public school to show how estimates of key epidemiological parameters such as the basic reproduction number (R(0)), vaccine efficacy (VE(S)) and critical vaccination coverage (p(c)) can be obtained from partially observed outbreaks in highly vaccinated populations. Our analyses rely on Bayesian methods of inference based on the final size distribution of outbreak size, and use data which are easily collected. For the German public school the analyses indicate that the basic reproduction number of measles is higher than previously thought (R(0) = 30.8, 95% credible interval: 23.6-40.4), that the vaccine is highly effective in preventing infection (VE(S) = 0.997, 95% credible interval: 0.993-0.999), and that a vaccination coverage in excess of 95 per cent may be necessary to achieve herd immunity (p(c) = 0.971, 95% credible interval: 0.961-0.978). We discuss the implications for measles elimination from highly vaccinated populations.