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Background In clinical research, there is an increasing interest in joint modelling of longitudinal and time-to-event data, since it reduces bias in parameter estimation and increases the efficiency of statistical inference. Inference and prediction from frequentist approaches of joint models have been extensively reviewed, and due to the recent popularity of data-driven Bayesian approaches, a review on current Bayesian estimation of joint model is useful to draw recommendations for future researches. Methods We have undertaken a comprehensive review on Bayesian univariate and multivariate joint models. We focused on type of outcomes, model assumptions, association structure, estimation algorithm, dynamic prediction and software implementation. Results A total of 89 articles have been identified, consisting of 75 methodological and 14 applied articles. The most common approach to model the longitudinal and time-to-event outcomes jointly included linear mixed effect models with proportional hazards. A random effect association structure was generally used for linking the two sub-models. Markov Chain Monte Carlo (MCMC) algorithms were commonly used (93% articles) to estimate the model parameters. Only six articles were primarily focused on dynamic predictions for longitudinal or event-time outcomes. Conclusion Methodologies for a wide variety of data types have been proposed; however the research is limited if the association between the two outcomes changes over time, and there is also lack of methods to determine the association structure in the absence of clinical background knowledge. Joint modelling has been proved to be beneficial in producing more accurate dynamic prediction; however, there is a lack of sufficient tools to validate the prediction.

The diagnosis of inflammatory bowel disease (IBD) in children and the need to distinguish between subtypes (Crohn’s disease (CD) and ulcerative colitis (UC)) requires lengthy investigative and invasive procedures. Non-invasive, rapid, and cost-effective tests to support these diagnoses are needed. Faecal volatile organic compounds (VOCs) are distinctive in IBD. VOC profiles can be rapidly determined using a gas chromatography–sensor device (OdoReader©). In an inception-cohort of children presenting with suspected IBD, we directly compared the diagnostic fidelity of faecal calprotectin (FCP, a non-specific protein marker of intestinal inflammation) with OdoReader© VOC profiles of children subsequently diagnosed with IBD with matched controls diagnosed with other gastrointestinal conditions. The OdoReader© was 82% (95% confidence interval 75–89%) sensitive and 71% (61–80%) specific but did not outperform FCP (sensitivity 93% (77–99%) and specificity 86% (67–96%); 250 µg/g FCP cut off) in the diagnosis of IBD from other gastrointestinal conditions when validated in a separate sample from the same cohort. However, unlike FCP and better than other similar technologies, the OdoReader© could distinguish paediatric CD from UC (up to 88% (82–93%) sensitivity and 80% (71–89%) specificity in the validation set) and justifies further validation in larger studies. A non-invasive test based on VOCs could help streamline and limit invasive investigations in children.

The social brain hypothesis, an explanation for the unusually large brains of primates, posits that the size of social group typical of a species is directly related to the volume of its neocortex. To test whether this hypothesis also applies at the within-species level, we applied the Cavalieri method of stereology in conjunction with point counting on magnetic resonance images to determine the volume of prefrontal cortex (PFC) subfields, including dorsal and orbital regions. Path analysis in a sample of 40 healthy adult humans revealed a significant linear relationship between orbital (but not dorsal) PFC volume and the size of subjects' social networks that was mediated by individual intentionality (mentalizing) competences. The results support the social brain hypothesis by indicating a relationship between PFC volume and social network size that applies within species, and, more importantly, indicates that the relationship is mediated by social cognitive skills.

ObjectivesTo evaluate the effectiveness of localised Tier 3 restrictions, implemented in England in December 2020, on reducing COVID-19 hospitalisations compared with less stringent Tier 2 measures and the variations by neighbourhood deprivation and the prevalence of Alpha (B.1.1.7) variant, the primary variant of concern then, to measure hospital services’ burden and inequalities across different communities.DesignObservational study using a synthetic control method, comparing weekly hospitalisation rates in Tier 3 areas to a synthetic control from Tier 2 areas.SettingEngland between 4 October 2020 and 21 February 2021.Participants23 million people under Tier 3 restrictions, compared with a synthetic control group derived from 29 million people under Tier 2 restrictions.InterventionsTier 3 restrictions in designated areas were implemented from 7 December 2020, imposing stricter limits on gatherings and hospitality than Tier 2, followed by a national lockdown on 6 January 2021.Primary and secondary outcome measuresWeekly COVID-19-related hospitalisations for neighbourhoods in England over 11 weeks following the interventions.ResultsImplementing Tier 3 restrictions were associated with a 17% average reduction in hospitalisations compared with Tier 2 areas (95% CI 13% to 21%; 8158 (6286 to 9981) in total). The effects were similar across different levels of neighbourhood deprivation and prevalence of the Alpha variant.ConclusionsRegionally targeted Tier 3 restrictions in England had a moderate but significant effect on reducing hospitalisations. The impact did not exacerbate socioeconomic inequalities during the pandemic. Our findings suggest that regionally targeted restrictions can be effective in managing infectious diseases.

Encephalitis, brain inflammation and swelling, most often caused by an infection or the body's immune defences, can have devastating consequences, especially if diagnosed late. We looked for clinical predictors of different types of encephalitis to help clinicians consider earlier treatment. We conducted a multicentre prospective observational cohort study (ENCEPH-UK) of adults (> 16 years) with suspected encephalitis at 31 UK hospitals. We evaluated clinical features and investigated for infectious and autoimmune causes. 341 patients were enrolled between December 2012 and December 2015 and followed up for 12 months. 233 had encephalitis, of whom 65 (28%) had HSV, 38 (16%) had confirmed or probable autoimmune encephalitis, and 87 (37%) had no cause found. The median time from admission to 1.sup.st dose of aciclovir for those with HSV was 14 hours (IQR 5-50); time to 1.sup.st dose of immunosuppressant for the autoimmune group was 125 hours (IQR 45-250). Compared to non-HSV encephalitis, patients with HSV more often had fever, lower serum sodium and lacked a rash. Those with probable or confirmed autoimmune encephalitis were more likely to be female, have abnormal movements, normal serum sodium levels and a cerebrospinal fluid white cell count < 20 cells x10.sup.6 /L, but they were less likely to have a febrile illness. Initiation of treatment for autoimmune encephalitis is delayed considerably compared with HSV encephalitis. Clinical features can help identify patients with autoimmune disease and could be used to initiate earlier presumptive therapy.

Background Our study examines if SARS-CoV-2 infections varied by vaccination status, if an individual had previously tested positive and by neighbourhood socioeconomic deprivation across the Delta and Omicron epidemic waves of SARS-CoV-2. Methods Population cohort study using electronic health records for 2.7 M residents in Cheshire and Merseyside, England (3rd June 2021 to 1st March 2022). Our outcome variable was registered positive test for SARS-CoV-2. Explanatory variables were vaccination status, previous registered positive test and neighbourhood socioeconomic deprivation. Cox regression models were used to analyse associations. Results Originally higher SARS-CoV-2 rates in the most socioeconomically deprived neighbourhoods changed to being higher in the least deprived neighbourhoods from the 1st September 2021, and were inconsistent during the Omicron wave. Individuals who were fully vaccinated (two doses) were associated with fewer registered positive tests (e.g., individuals engaged in testing between 1st September and 27th November 2021—Hazards Ratio (HR) = 0.48, 95% Confidence Intervals (CIs) = 0.47–0.50. Individuals with a previous registered positive test were also less likely to have a registered positive test (e.g., individuals engaged in testing between 1st September and 27th November 2021—HR = 0.16, 95% CIs = 0.15–0.18. However, the Omicron period saw smaller effect sizes for both vaccination status and previous registered positive test. Conclusions Changing patterns of SARS-CoV-2 infections during the Delta and Omicron waves reveals a dynamic pandemic that continues to affect diverse communities in sometimes unexpected ways.

From January to May 2021 the alpha variant (B.1.1.7) of SARS-CoV-2 was the most commonly detected variant in the UK. Following this, the Delta variant (B.1.617.2) then became the predominant variant. The UK COVID-19 vaccination programme started on 8th December 2020. Prior to the Delta variant, most vaccine effectiveness studies focused on the alpha variant. We therefore aimed to estimate the effectiveness of the BNT162b2 (Pfizer-BioNTech) and the ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines in preventing symptomatic and asymptomatic infection with respect to the Delta variant in a UK setting. We used anonymised public health record data linked to infection data (PCR) using the Combined Intelligence for Population Health Action resource. We then constructed an SIR epidemic model to explain SARS-CoV-2 infection data across the Cheshire and Merseyside region of the UK. Vaccines were assumed to be effective after 21 days for 1 dose and 14 days for 2 doses. We determined that the effectiveness of the Oxford-AstraZeneca vaccine in reducing susceptibility to infection is 39% (95% credible interval [34, 43]) and 64% (95% credible interval [61, 67]) for a single dose and a double dose respectively. For the Pfizer-BioNTech vaccine, the effectiveness is 20% (95% credible interval [10, 28]) and 84% (95% credible interval [82, 86]) for a single-dose and a double dose respectively. Vaccine effectiveness for reducing susceptibility to SARS-CoV-2 infection shows noticeable improvement after receiving two doses of either vaccine. Findings also suggest that a full course of the Pfizer-BioNTech provides the optimal protection against infection with the Delta variant. This reinforces the need to complete the full course programme to maximise individual protection and reduce transmission.

AbstractObjectiveTo analyse the impact of voluntary rapid testing for SARS-CoV-2 antigen in Liverpool city on covid-19 related hospital admissions.DesignSynthetic control analysis comparing hospital admissions for small areas in the intervention population with a group of control areas weighted to be similar for past covid-19 related hospital admission rates and sociodemographic factors.SettingLiverpool city, UK, 6 November 2020 to 2 January 2021, under the intervention of Covid-SMART (systematic meaningful asymptomatic repeated testing) voluntary, open access supervised self-testing with lateral flow devices, compared with control areas selected from the rest of England.PopulationGeneral population of Liverpool (n=498 042) and a synthetic control population from the rest of England.Main outcome measureWeekly covid-19 related hospital admissions for neighbourhoods in England.ResultsThe introduction of community testing was associated with a 43% (95% confidence interval 29% to 57%) reduction (146 (96 to 192) in total) in covid-19 related hospital admissions in Liverpool compared with the synthetic control population (non-adjacent set of neighbourhoods with aggregate trends in covid-19 hospital admissions similar to Liverpool) for the initial period of intensive testing with military assistance in national lockdown from 6 November to 3 December 2020. A 25% (11% to 35%) reduction (239 (104 to 333) in total) was estimated across the overall intervention period (6 November 2020 to 2 January 2021), involving fewer testing centres, before England’s national roll-out of community testing, after adjusting for regional differences in tiers of covid-19 restrictions from 3 December 2020 to 2 January 2021.ConclusionsThe city-wide pilot of community based asymptomatic testing for SARS-CoV-2 was associated with substantially reduced covid-19 related hospital admissions. Large scale asymptomatic rapid testing for SARS-CoV-2 could help reduce transmission and prevent hospital admissions.

BackgroundThe diagnosis and surveillance of urothelial bladder cancer (UBC) require cystoscopy. There is a need for biomarkers to reduce the frequency of cystoscopy in surveillance; urinary volatile organic compound (VOC) analysis could fulfil this role. This cross-sectional study compared the VOC profiles of patients with and without UBC, to investigate metabolomic signatures as biomarkers.MethodsUrine samples were collected from haematuria clinic patients undergoing diagnostic cystoscopy and UBC patients undergoing surveillance. Urinary headspace sampling utilised solid-phase microextraction and VOC analysis applied gas chromatography-mass spectrometry; the output underwent metabolomic analysis.ResultsThe median participant age was 70 years, 66.2% were male. Of the haematuria patients, 21 had a new UBC diagnosis, 125 had no cancer. In the surveillance group, 75 had recurrent UBC, 84 were recurrence-free. A distinctive VOC profile was observed in UBC patients compared with controls. Ten VOCs had statistically significant abundances useful to classify patients (false discovery rate range 1.9 × 10−7–2.8 × 10−2). Two prediction models were evaluated using internal validation. An eight-VOC diagnostic biomarker panel achieved AUROC 0.77 (sensitivity 0.71, specificity 0.72). A six-VOC surveillance biomarker panel obtained AUROC 0.80 (sensitivity 0.71 and specificity 0.80).ConclusionsUrinary VOC analysis could aid the diagnosis and surveillance of UBC.