Recapture or precapture? Fallibility of standard capture-recapture methods in the presence of referrals between sources.

Capture-recapture methods, largely developed in ecology, are now commonly used in epidemiology to adjust for incomplete registries and to estimate the size of difficult-to-reach populations such as problem drug users. Overlapping lists of individuals in the target population, taken from administrative data sources, are considered analogous to overlapping "captures" of animals. Log-linear models, incorporating interaction terms to account for dependencies between sources, are used to predict the number of unobserved individuals and, hence, the total population size. A standard assumption to ensure parameter identifiability is that the highest-order interaction term is 0. We demonstrate that, when individuals are referred directly between sources, this assumption will often be violated, and the standard modeling approach may lead to seriously biased estimates. We refer to such individuals as having been "precaptured," rather than truly recaptured. Although sometimes an alternative identifiable log-linear model could accommodate the referral structure, this will not always be the case. Further, multiple plausible models may fit the data equally well but provide widely varying estimates of the population size. We demonstrate an alternative modeling approach, based on an interpretable parameterization and driven by careful consideration of the relationships between the sources, and we make recommendations for capture-recapture in practice

Evaluation of the Neonatal Resuscitation Program\u27s Recommended Chest Compression Depth Using Computerized Tomography Imaging.

BACKGROUND: Neonatal Resuscitation Program (NRP) guidelines recommend chest compression depths of 1/3 the anterior-posterior (AP) chest depth. Appropriateness of this recommendation has not been rigorously assessed. OBJECTIVE: To compare the efficacy and safety of neonatal chest compression depths of 1/4, 1/3, and 1/2 AP chest depth during cardiopulmonary resuscitation. DESIGN/METHODS: Anterior-posterior internal and external chest depth, heart dimensions, and non-cardiac thoracic tissue depth were measured from neonatal chest CTs. Using these measurements, residual internal chest depth, the remaining depth of the chest between the sternum and spine after external compression, was calculated for compression depths of 1/4, 1/3 and 1/2 anterior-posterior chest depth. Compression sufficient to compress the chest tomodel, an estimated ejection fraction (EF) was calculated for each chest compression depth. Compression inadequate to obtain a predicted 50% EF was defined as under-compression. Descriptive statistics, Fisher\u27s exact test and Student\u27s t-test were used to analyze data, where appropriate. RESULTS: Fifty-four neonatal chest CT scans were evaluated. Estimated chest compression induced EF increased incrementally with increasing chest compression depth (EF was 51+/-3% with 1/4 AP chest depth vs 69+/-3% with 1/3 AP chest depth, and 106% with 1/2 AP chest depth, p CONCLUSIONS: Mathematical modeling based upon neonatal chest CT scan dimensions suggests that current NRP chest compression recommendations of 1/3 AP chest depth should be more effective than 1/4 compression depth, and safer than 1/2 AP compression depth

Estimating the prevalence of problem drug use from drug-related mortality data.

BACKGROUND AND AIMS: Indirect estimation methods are required for estimating the size of populations where only a proportion of individuals are observed directly, such as problem drug users (PDUs). Capture-recapture and multiplier methods are widely used, but have been criticized as subject to bias. We propose a new approach to estimating prevalence of PDU from numbers of fatal drug-related poisonings (fDRPs) using linked databases, addressing the key limitations of simplistic 'mortality multipliers'. METHODS: Our approach requires linkage of data on a large cohort of known PDUs to mortality registers and summary information concerning additional fDRPs observed outside this cohort. We model fDRP rates among the cohort and assume that rates in unobserved PDUs are equal to rates in the cohort during periods out of treatment. Prevalence is estimated in a Bayesian statistical framework, in which we simultaneously fit regression models to fDRP rates and prevalence, allowing both to vary by demographic factors and the former also by treatment status. RESULTS: We report a case study analysis, estimating the prevalence of opioid dependence in England in 2008/09, by gender, age group and geographical region. Overall prevalence was estimated as 0.82% (95% credible interval = 0.74-0.94%) of 15-64-year-olds, which is similar to a published estimate based on capture-recapture analysis. CONCLUSIONS: Our modelling approach estimates prevalence from drug-related mortality data, while addressing the main limitations of simplistic multipliers. This offers an alternative approach for the common situation where available data sources do not meet the strong assumptions required for valid capture-recapture estimation. In a case study analysis, prevalence estimates based on our approach were surprisingly similar to existing capture-recapture estimates but, we argue, are based on a much more objective and justifiable modelling approach

Trust, guilds and kinship in London, 1330-1680

How was trust created and reinforced between the inhabitants of medieval and early modern cities? And how did the social foundations of trusting relationships change over time? Current research highlights the role of kinship, neighbourhood and associations, particularly guilds, in creating ‘relationships of trust’ and social capital in the face of high levels of migration, mortality and economic volatility, but tells us little about their relative importance or how they developed. We uncover a profound shift in the contribution of family and guilds to trust networks among the middling and elite of one of Europe’s major cities, London, over three centuries, from the 1330s to the 1680s. We examine the networks of sureties created to secure the inheritances of children whose fathers died while they were minors, surviving in the records of London’s Orphans Court. Our analysis of almost fifteen thousand networks evaluates the presence of trusting relationships connected with guild membership, family and place over several centuries. We show a profound increase in the role of kinship – a re-embedding of trust within the family - and a decline of the importance of shared guild membership in connecting Londoner’s who secured orphans’ inheritances together. We suggest these developments are best explained as a result of the impact of the Reformation on the form and intensity of sociability fostered by guilds and the enormous growth of the metropolis

Trust, guilds and kinship in London, 1330-1680

How was trust created and reinforced between the inhabitants of medieval and early modern cities? And how did the social foundations of trusting relationships change over time? Current research highlights the role of kinship, neighbourhood and associations, particularly guilds, in creating ‘relationships of trust’ and social capital in the face of high levels of migration, mortality and economic volatility, but tells us little about their relative importance or how they developed. We uncover a profound shift in the contribution of family and guilds to trust networks among the middling and elite of one of Europe’s major cities, London, over three centuries, from the 1330s to the 1680s. We examine almost 15,000 networks of sureties created to secure orphans’ inheritances to measure the presence of trusting relationships connected by guild membership, family and place. We uncover a profound increase in the role of kinship – a re-embedding of trust within the family - and a decline of the importance of shared guild membership in connecting Londoner’s who secured orphans’ inheritances together. These developments indicate a profound transformation in the social fabric of urban society

Accuracy of UK Rapid Test Consortium (UK-RTC) "AbC-19 Rapid Test" for detection of previous SARS-CoV-2 infection in key workers: test accuracy study.

OBJECTIVE: To assess the accuracy of the AbC-19 Rapid Test lateral flow immunoassay for the detection of previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. DESIGN: Test accuracy study. SETTING: Laboratory based evaluation. PARTICIPANTS: 2847 key workers (healthcare staff, fire and rescue officers, and police officers) in England in June 2020 (268 with a previous polymerase chain reaction (PCR) positive result (median 63 days previously), 2579 with unknown previous infection status); and 1995 pre-pandemic blood donors. MAIN OUTCOME MEASURES: AbC-19 sensitivity and specificity, estimated using known negative (pre-pandemic) and known positive (PCR confirmed) samples as reference standards and secondly using the Roche Elecsys anti-nucleoprotein assay, a highly sensitive laboratory immunoassay, as a reference standard in samples from key workers. RESULTS: Test result bands were often weak, with positive/negative discordance by three trained laboratory staff for 3.9% of devices. Using consensus readings, for known positive and negative samples sensitivity was 92.5% (95% confidence interval 88.8% to 95.1%) and specificity was 97.9% (97.2% to 98.4%). Using an immunoassay reference standard, sensitivity was 94.2% (90.7% to 96.5%) among PCR confirmed cases but 84.7% (80.6% to 88.1%) among other people with antibodies. This is consistent with AbC-19 being more sensitive when antibody concentrations are higher, as people with PCR confirmation tended to have more severe disease whereas only 62% (218/354) of seropositive participants had had symptoms. If 1 million key workers were tested with AbC-19 and 10% had actually been previously infected, 84 700 true positive and 18 900 false positive results would be projected. The probability that a positive result was correct would be 81.7% (76.8% to 85.8%). CONCLUSIONS: AbC-19 sensitivity was lower among unselected populations than among PCR confirmed cases of SARS-CoV-2, highlighting the scope for overestimation of assay performance in studies involving only PCR confirmed cases, owing to "spectrum bias." Assuming that 10% of the tested population have had SARS-CoV-2 infection, around one in five key workers testing positive with AbC-19 would be false positives. STUDY REGISTRATION: ISRCTN 56609224.The study was commissioned by the UK Government’s Department of Health and Social Care. It was funded and implemented by Public Health England, supported by the NIHR Clinical Research Network (CRN) Portfolio. The Department of Health and Social Care received a report containing these data on 10/9/2020, but had no role in the study design, data collection, analysis, interpretation of results, writing of the manuscript, or the decision to publish. DW acknowledges support from the NIHR Health Protection Research Unit in Genomics and Data Enabling at the University of Warwick. HEJ, AEA, MH and IO acknowledge support from the NIHR Health Protection Research Unit in Behavioural Science and Evaluation at University of Bristol. STP is supported by an NIHR Career Development Fellowship (CDF-2016-09-018). Participants in the COMPARE study were recruited with the active collaboration of NHS Blood and Transplant (NHSBT) England (www.nhsbt.nhs.uk). Funding for COMPARE was provided by NHSBT and the NIHR Blood and Transplant Research Unit (BTRU) in Donor Health and Genomics (NIHR BTRU-2014-10024). The academic coordinating centre for COMPARE was supported by core funding from: NIHR BTRU, UK Medical Research Council (MR/L003120/1), British Heart Foundation (RG/13/13/30194) and the NIHR [Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust]. This work was supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Division), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome. JD holds a British Heart Foundation Professorship and a National Institute for Health Research Senior Investigator Award. The views expressed are those of the author(s) and not necessarily those of the NHS, NIHR or the Department of Health and Social Care

Proceedings of Patient Reported Outcome Measure’s (PROMs) Conference Oxford 2017: Advances in Patient Reported Outcomes Research

A33-Effects of Out-of-Pocket (OOP) Payments and Financial Distress on Quality of Life (QoL) of People with Parkinson’s (PwP) and their Carer