Estimating the effect of the 2005 change in BCG policy in England:a retrospective cohort study, 2000 to 2015

BackgroundIn 2005 in England, universal Bacillus Calmette-Guérin (BCG) vaccination of school-age children was replaced by targeted BCG vaccination of high-risk neonates.AimEstimate the impact of the 2005 change in BCG policy on tuberculosis (TB) incidence rates in England.MethodsWe conducted an observational study by combining notifications from the Enhanced Tuberculosis Surveillance system, with demographic data from the Labour Force Survey to construct retrospective cohorts relevant to both the universal and targeted vaccination between 1 January 2000 and 31 December 2010. We then estimated incidence rates over a 5-year follow-up period and used regression modelling to estimate the impact of the change in policy on TB.ResultsIn the non-United Kingdom (UK) born, we found evidence for an association between a reduction in incidence rates and the change in BCG policy (school-age incidence rate ratio (IRR): 0.74; 95% credible interval (CrI): 0.61 to 0.88 and neonatal IRR: 0.62; 95%CrI: 0.44 to 0.88). We found some evidence that the change in policy was associated with an increase in incidence rates in the UK born school-age population (IRR: 1.08; 95%CrI: 0.97 to 1.19) and weaker evidence of an association with a reduction in incidence rates in UK born neonates (IRR: 0.96; 95%CrI: 0.82 to 1.14). Overall, we found that the change in policy was associated with directly preventing 385 (95%CrI: -105 to 881) cases.ConclusionsWithdrawing universal vaccination at school age and targeting vaccination towards high-risk neonates was associated with reduced incidence of TB. This was largely driven by reductions in the non-UK born with cases increasing in the UK born

The transmissibility of novel Coronavirus in the early stages of the 2019-20 outbreak in Wuhan: Exploring initial point-source exposure sizes and durations using scenario analysis.

Background: The current novel coronavirus outbreak appears to have originated from a point-source exposure event at Huanan seafood wholesale market in Wuhan, China. There is still uncertainty around the scale and duration of this exposure event. This has implications for the estimated transmissibility of the coronavirus and as such, these potential scenarios should be explored.   Methods: We used a stochastic branching process model, parameterised with available data where possible and otherwise informed by the 2002-2003 Severe Acute Respiratory Syndrome (SARS) outbreak, to simulate the Wuhan outbreak. We evaluated scenarios for the following parameters: the size, and duration of the initial transmission event, the serial interval, and the reproduction number (R0). We restricted model simulations based on the number of observed cases on the 25th of January, accepting samples that were within a 5% interval on either side of this estimate. Results: Using a pre-intervention SARS-like serial interval suggested a larger initial transmission event and a higher R0 estimate. Using a SARs-like serial interval we found that the most likely scenario produced an R0 estimate between 2-2.7 (90% credible interval (CrI)). A pre-intervention SARS-like serial interval resulted in an R0 estimate between 2-3 (90% CrI). There were other plausible scenarios with smaller events sizes and longer duration that had comparable R0 estimates. There were very few simulations that were able to reproduce the observed data when R0 was less than 1. Conclusions: Our results indicate that an R0 of less than 1 was highly unlikely unless the size of the initial exposure event was much greater than currently reported. We found that R0 estimates were comparable across scenarios with decreasing event size and increasing duration. Scenarios with a pre-intervention SARS-like serial interval resulted in a higher R0 and were equally plausible to scenarios with SARs-like serial intervals

‘So they hit each other’: Gendered constructions of domestic abuse in the YouTube commentary of the Depp v Heard Trial

This study presents a critical discourse analysis of YouTube comments below five videos of the Johnny Depp v Amber Heard trial, which was live streamed by the platform in April and May 2022. The analysis examines the discursive resources used by commenters to construct domestic abuse. Commenters draw on three interpretive repertoires: ‘Perfect Victim’, ‘Mutual Abuse’ and ‘Dangerous Women’. The analysis explores the way these repertoires are used to rebut Heard’s allegations of abuse by mobilising the perfect victim repertoire to refute any claim she has to this experience, and the mutual abuse repertoire to implicate Heard in the abuse and minimise blame for Depp. Through establishing gender-symmetry in domestic abuse and drawing on traditional gender norms for each party, commenters construct the dangerous women repertoire to depict Heard as crazy, pathological and violent. The key implication of this study is that public constructions of domestic abuse can directly impact the attitudes and treatment of both victims and perpetrators. In this instance, they serve to maintain the oppression and control of women within anti-feminist narratives of female dominance, currently led by men’s rights activists and conservative outlets

Scoring epidemiological forecasts on transformed scales

Forecast evaluation is essential for the development of predictive epidemic models and can inform their use for public health decision-making. Common scores to evaluate epidemiological forecasts are the Continuous Ranked Probability Score (CRPS) and the Weighted Interval Score (WIS), which can be seen as measures of the absolute distance between the forecast distribution and the observation. However, applying these scores directly to predicted and observed incidence counts may not be the most appropriate due to the exponential nature of epidemic processes and the varying magnitudes of observed values across space and time. In this paper, we argue that transforming counts before applying scores such as the CRPS or WIS can effectively mitigate these difficulties and yield epidemiologically meaningful and easily interpretable results. Using the CRPS on log-transformed values as an example, we list three attractive properties: Firstly, it can be interpreted as a probabilistic version of a relative error. Secondly, it reflects how well models predicted the time-varying epidemic growth rate. And lastly, using arguments on variance-stabilizing transformations, it can be shown that under the assumption of a quadratic mean-variance relationship, the logarithmic transformation leads to expected CRPS values which are independent of the order of magnitude of the predicted quantity. Applying a transformation of log(x + 1) to data and forecasts from the European COVID-19 Forecast Hub, we find that it changes model rankings regardless of stratification by forecast date, location or target types. Situations in which models missed the beginning of upward swings are more strongly emphasised while failing to predict a downturn following a peak is less severely penalised when scoring transformed forecasts as opposed to untransformed ones. We conclude that appropriate transformations, of which the natural logarithm is only one particularly attractive option, should be considered when assessing the performance of different models in the context of infectious disease incidence

Reassessing the evidence for universal school-age BCG vaccination in England and Wales: re-evaluating and updating a modelling study

OBJECTIVES: In 2005, England and Wales switched from universal BCG vaccination against tuberculosis (TB) disease for school-age children to targeted vaccination of neonates. We aimed to recreate and re-evaluate a previously published model, the results of which informed this policy change. DESIGN: We recreated an approach for estimating the impact of ending the BCG schools scheme, correcting a methodological flaw in the model, updating the model with parameter uncertainty and improving parameter estimates where possible. We investigated scenarios for the assumed annual decrease in TB incidence rates considered by the UK's Joint Committee on Vaccination and Immunisation and explored alternative scenarios using notification data. SETTING: England and Wales. OUTCOME MEASURES: The number of vaccines needed to prevent a single notification and the average annual additional notifications caused by ending the policy change. RESULTS: The previously published model was found to contain a methodological flaw and to be spuriously precise. It greatly underestimated the impact of ending school-age vaccination compared with our updated, corrected model. The updated model produced predictions with wide CIs when parameter uncertainty was included. Model estimates based on an assumption of an annual decrease in TB incidence rates of 1.9% were closest to those estimated using notification data. Using this assumption, we estimate that 1600 (2.5; 97.5% quantiles: 1300, 2000) vaccines would have been required to prevent a single notification in 2004. CONCLUSIONS: The impact of ending the BCG schools scheme was found to be greater than previously thought when notification data were used. Our results highlight the importance of independent evaluations of modelling evidence, including uncertainty, and evaluating multiple scenarios when forecasting the impact of changes in vaccination policy