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Abstract The mpox epidemic in the UK began in May 2022, with rates of new cases unexpectedly and rapidly declining during August 2022. Interpreting trends in infection requires disentangling the underlying growth rate of cases from the delay from symptom onset to presenting to healthcare. We developed a nowcasting Bayesian method which incorporates time-varying delays (EpiLine) to quantify the changes in the delay from symptom onset to healthcare presentation and the underlying mpox growth rate over the period May-August 2022 in the UK. We show that the mean delay between symptom onset and healthcare presentation for mpox in the UK decreased from 22 days in early May 2022 to 10 days by early June and 8 days in August 2022. When we account for these dynamic delays, the time-varying growth rate declined gradually and continuously in the UK during the May-August 2022 period. Not accounting for varying time delays would have incorrectly characterised the growth rate by a sharp increase followed by a rapid decline in mpox cases. Our results highlight the importance of correctly quantifying the delay between symptom onset to healthcare presentation when characterising the epidemic growth of mpox in the UK. The gradual reduction in the rate of epidemic spread, which pre-dated the vaccine roll-out, is consistent with gradual risk reduction or acquired immunity amongst the highest risk individuals. Our study highlights the need for public health agencies to record the delays from symptom onset to healthcare presentation early in an outbreak.

Abstract Background Understanding how the COVID-19 pandemic evolved under control measures is crucial to tackle the SARS-CoV-2 virus spread. Laos, a country bordering China but with late occurrence and low burden of COVID-19 compared to its neighbouring countries, was used for a case study. Methods A transmission model with disease reporting was proposed to investigate the impact of control measures on the SARS-CoV-2 virus spread in Laos from April 2021 to May 2022. It was assumed that the transmission rate changed with people’s behaviours, control measures and emerging variants; susceptibility decreased with vaccination and infection. Bayesian inference was used for model calibration to data of confirmed cases, deaths, and recoveries, and the deviance information criterion was used to select the best model variant. Results Our model including Non-pharmaceutical interventions (NPIs), behaviour change, vaccination, and changing variants well explained the three waves in Laos. The Alpha variant was estimated to have a basic reproduction number of 1.55 (95% CrI: 1.47–1.64) and was replaced by the Delta variant from September 2021 which was 1.88 (95% CrI: 1.77–2.01) times more transmissible; the Delta variant was replaced by Omicron variant from March 2022 which was 3.33 (95% CrI: 2.84–3.74) times more transmissible. The Delta variant was the most severe with a case fatality rate of 1.05% (95% CrI: 0.96–1.15%) while the Alpha variant and Omicron variant were much milder. The ascertainment rate was low and variable: first decreasing from 13.2 to 1.8% by 23 May 2021, and then increasing to 23.4% by 15 March 2022. Counterfactual simulations indicated that vaccination played strong roles in reducing infections even under the emergence of immune escape variants while behaviour change delayed but might not flatten the peak of outbreaks. Conclusions The three waves of Laos’ epidemics were due to the invasion of more transmissible and immune escape variants that affected the herd immunity built via vaccination and infection. Even with immunity waning and the escape of new variants, vaccination was still the major contributor to control COVID-19 and combining behaviour changes and vaccination would best suppress future outbreaks of COVID-19.

Mathematical modelling has played an important role in offering informed advice during the COVID-19 pandemic. In England, a cross government and academia collaboration generated medium-term projections (MTPs) of possible epidemic trajectories over the future 4–6 weeks from a collection of epidemiological models. In this article, we outline this collaborative modelling approach and evaluate the accuracy of the combined and individual model projections against the data over the period November 2021–December 2022 when various Omicron subvariants were spreading across England. Using a number of statistical methods, we quantify the predictive performance of the model projections for both the combined and individual MTPs, by evaluating the point and probabilistic accuracy. Our results illustrate that the combined MTPs, produced from an ensemble of heterogeneous epidemiological models, were a closer fit to the data than the individual models during the periods of epidemic growth or decline, with the 90% confidence intervals widest around the epidemic peaks. We also show that the combined MTPs increase the robustness and reduce the biases associated with a single model projection. Learning from our experience of ensemble modelling during the COVID-19 epidemic, our findings highlight the importance of developing cross-institutional multi-model infectious disease hubs for future outbreak control.

Earlier global detection of novel SARS-CoV-2 variants gives governments more time to respond. However, few countries can implement timely national surveillance, resulting in gaps in monitoring. The United Kingdom implemented large-scale community and hospital surveillance, but experience suggests it might be faster to detect new variants through testing England arrivals for surveillance. We developed simulations of emergence and importation of novel variants with a range of infection hospitalization rates to the United Kingdom. We compared time taken to detect the variant though testing arrivals at England borders, hospital admissions, and the general community. We found that sampling 10%–50% of arrivals at England borders could confer a speed advantage of 3.5–6 weeks over existing community surveillance and 1.5–5 weeks (depending on infection hospitalization rates) over hospital testing. Directing limited global capacity for surveillance to highly connected ports could speed up global detection of novel SARS-CoV-2 variants.

Abstract Background Near-real time surveillance of excess mortality has been an essential tool during the COVID-19 pandemic. It remains critical for monitoring mortality as the pandemic wanes, to detect fluctuations in the death rate associated both with the longer-term impact of the pandemic (e.g. infection, containment measures and reduced service provision by the health and other systems) and the responses that followed (e.g. curtailment of containment measures, vaccination and the response of health and other systems to backlogs). Following the relaxing of social distancing regimes and reduction in the availability of testing, across many countries, it becomes critical to measure the impact of COVID-19 infection. However, prolonged periods of mortality in excess of the expected across entire populations has raised doubts over the validity of using unadjusted historic estimates of mortality to calculate the expected numbers of deaths that form the baseline for computing numbers of excess deaths because many individuals died earlier than they would otherwise have done: i.e. their mortality was displaced earlier in time to occur during the pandemic rather than when historic rates predicted. This is also often termed “harvesting” in the literature. Methods We present a novel Cox-regression-based methodology using time-dependent covariates to estimate the profile of the increased risk of death across time in individuals who contracted COVID-19 among a population of hip fracture patients in England (N = 98,365). We use these hazards to simulate a distribution of survival times, in the presence of a COVID-19 positive test, and then calculate survival times based on hazard rates without a positive test and use the difference between the medians of these distributions to estimate the number of days a death has been displaced. This methodology is applied at the individual level, rather than the population level to provide a better understanding of the impact of a positive COVID-19 test on the mortality of groups with different vulnerabilities conferred by sociodemographic and health characteristics. Finally, we apply the mortality displacement estimates to adjust estimates of excess mortality using a “ball and urn” model. Results Among the exemplar population we present an end-to-end application of our methodology to estimate the extent of mortality displacement. A greater proportion of older, male and frailer individuals were subject to significant displacement while the magnitude of displacement was higher in younger females and in individuals with lower frailty: groups who, in the absence of COVID-19, should have had a substantial life expectancy. Conclusion Our results indicate that calculating the expected number of deaths following the first wave of the pandemic in England based solely on historical trends results in an overestimate, and excess mortality will therefore be underestimated. Our findings, using this exemplar dataset are conditional on having experienced a hip fracture, which is not generalisable to the general population. Fractures that impede mobility in the weeks that follow the accident/surgery considerably shorten life expectancy and are in themselves markers of significant frailty. It is therefore important to apply these novel methods to the general population, among whom we anticipate strong patterns in mortality displacement – both in its length and prevalence – by age, sex, frailty and types of comorbidities. This counterfactual method may also be used to investigate a wider range of disruptive population health events. This has important implications for public health monitoring and the interpretation of public health data in England and globally.

Summary: Background: The protection of fourth dose mRNA vaccination against SARS-CoV-2 is relevant to current global policy decisions regarding ongoing booster roll-out. We aimed to estimate the effect of fourth dose vaccination, prior infection, and duration of PCR positivity in a highly-vaccinated and largely prior-COVID-19 infected cohort of UK healthcare workers. Methods: Participants underwent fortnightly PCR and regular antibody testing for SARS-CoV-2 and completed symptoms questionnaires. A multi-state model was used to estimate vaccine effectiveness (VE) against infection from a fourth dose compared to a waned third dose, with protection from prior infection and duration of PCR positivity jointly estimated. Findings: 1298 infections were detected among 9560 individuals under active follow-up between September 2022 and March 2023. Compared to a waned third dose, fourth dose VE was 13.1% (95% CI 0.9 to 23.8) overall; 24.0% (95% CI 8.5 to 36.8) in the first 2 months post-vaccination, reducing to 10.3% (95% CI −11.4 to 27.8) and 1.7% (95% CI −17.0 to 17.4) at 2–4 and 4–6 months, respectively. Relative to an infection >2 years ago and controlling for vaccination, 63.6% (95% CI 46.9 to 75.0) and 29.1% (95% CI 3.8 to 43.1) greater protection against infection was estimated for an infection within the past 0–6, and 6–12 months, respectively. A fourth dose was associated with greater protection against asymptomatic infection than symptomatic infection, whilst prior infection independently provided more protection against symptomatic infection, particularly if the infection had occurred within the previous 6 months. Duration of PCR positivity was significantly lower for asymptomatic compared to symptomatic infection. Interpretation: Despite rapid waning of protection, vaccine boosters remain an important tool in responding to the dynamic COVID-19 landscape; boosting population immunity in advance of periods of anticipated pressure, such as surging infection rates or emerging variants of concern. Funding: UK Health Security Agency, Medical Research Council, NIHR HPRU Oxford, Bristol, and others.

Scots pine (Pinus sylvestris L.) is the most widely distributed pine species in the world. In Germany, as in many other European countries, it is a very important species both culturally and economically. Few studies have focused on bark volumes being delivered to the wood industry together with the roundwood, being potentially a valuable resource for material or energetic utilization. Therefore, logs from six different forest sites were collected and bark variables including double bark thickness (DBT) in three different categories, diameter, and bark damage (as a degree of miss-DBT) in three different categories, diameter, and bark damage (as a degree of missing bark) were measured and analyzed in order to model bark volume (Vbark) and bark mass (Mbark). The correlation analysis using Pearson’s method showed that the highest correlation coefficients were observed from the correlation between DBT and Vbark, as well as between DBT and Mbark. Also, results demonstrated that with DBT greater than 20 mm, the percentage of Vbark exceeded 20%. Finally, different linear regression models were recommended to predict Vbark and Mbark based on the other variables. The results of this study can be used in different wood industries in order to predict bark volume and bark mass of e.g. truckloads or roundwood stacks.

Objective In September 2020, 15 861 SARS-CoV-2 case records failed to upload from the Second Generation Surveillance System (SGSS) to the Contact Tracing Advisory Service (CTAS) tool, delaying the contact tracing of these cases. This study used CTAS data to determine the impact of this delay on population health outcomes: transmission events, hospitalisations and mortality. Previously, a modelling study suggested a substantial impact.Design Observational study.Setting England.Population Individuals testing positive for SARS-CoV-2 and their reported contacts.Main outcome measures Secondary attack rates (SARs), hospitalisations and deaths among primary and secondary contacts were calculated, compared with all other concurrent, unaffected cases. Affected SGSS records were matched to CTAS records. Successive contacts and cases were identified and matched to hospital episode and mortality outcomes.Results Initiation of contact tracing was delayed by 3 days on average in the primary cases in the delay group (6 days) compared with the control group (3 days). This was associated with lower completion of contact tracing: 80% (95% CI: 79% to 81%) in delay group and 83% (95% CI: 83% to 84%) in control group. There was some evidence to suggest increased transmission to non-household contacts among those affected by the delay. The SAR for non-household contacts was higher among secondary contacts in the delay group than the control group (delay group: 7.9%, 95% CI: 6.5% to 9.2%; control group: 5.9%, 95% CI: 5.3% to 6.6%). There did not appear to be a significant difference between the delay and control groups in the odds of hospitalisation (crude OR: 1.1 (95% CI: 0.9 to 1.2)) or death (crude OR: 0.7 (95% CI: 0.1 to 4.0)) among secondary contacts.Conclusions Our analysis suggests that the delay in contact tracing had a limited impact on population health outcomes; however, contact tracing was not completed for all individuals, so some transmission events might not be captured.

Relaxing social distancing measures and reduced level of influenza over the last two seasons may lead to a winter 2022 influenza wave in England. We used an established model for influenza transmission and vaccination to evaluate the rolled out influenza immunisation programme over October to December 2022. Specifically, we explored how the interplay between pre-season population susceptibility and influenza vaccine efficacy control the timing and the size of a possible winter influenza wave. Our findings suggest that susceptibility affects the timing and the height of a potential influenza wave, with higher susceptibility leading to an earlier and larger influenza wave while vaccine efficacy controls the size of the peak of the influenza wave. With pre-season susceptibility higher than pre-COVID-19 levels, under the planned vaccine programme an early influenza epidemic wave is possible, its size dependent on vaccine effectiveness against the circulating strain. If pre-season susceptibility is low and similar to pre-COVID levels, the planned influenza vaccine programme with an effective vaccine could largely suppress a winter 2022 influenza outbreak in England.

The term metagenomics refers to the use of sequencing methods to simultaneously identify genomic material from all organisms present in a sample, with the advantage of greater taxonomic resolution than culture or other methods. Applications include pathogen detection and discovery, species characterisation, antimicrobial resistance detection, virulence profiling, and study of the microbiome and microecological factors affecting health. However, metagenomics involves complex and multistep processes and there are important technical and methodological challenges that require careful consideration to support valid inference. We co-ordinated a multidisciplinary, international expert group to establish reporting guidelines that address specimen processing, nucleic acid extraction, sequencing platforms, bioinformatics considerations, quality assurance, limits of detection, power and sample size, confirmatory testing, causality criteria, cost, and ethical issues. The guidance recognises that metagenomics research requires pragmatism and caution in interpretation, and that this field is rapidly evolving.

The process of macroautophagy plays a pivotal role in the degradation of long-lived, superfluous, and damaged proteins and organelles, which are later recycled for cellular use. Normal cells rely on autophagy to combat various stressors and insults to ensure survival. However, autophagy is often upregulated in cancer cells, promoting a more aggressive phenotype that allows mutated cells to evade death after exposure to therapeutic treatments. As a result, autophagy has emerged as a significant factor in therapeutic resistance across many cancer types, with underlying mechanisms such as DNA damage, cell cycle arrest, and immune evasion. This review provides a comprehensive summary of the role of autophagy in therapeutic resistance and the limitations of available autophagic inhibitors in cancer treatment. It also highlights the urgent need to explore new inhibitors that can synergize with existing therapies to achieve better patient treatment outcomes. Advancing research in this field is crucial for developing more effective treatments that can help improve the lives of cancer patients.

This study investigates trends in mortality and length of stay for people hospitalised with COVID-19 in England until September 2021. It shows that risks were higher for unvaccinated people and those with multiple comorbidities, and that busier hospitals had higher mortality rates at the start of the pandemic but this effect lessened over time.

The proportion of bark in tree trunks is in the range of ~ 10-20%. This large amount of material is currently mainly considered as a by- or even waste-product by the timber processing industry. Recently, efforts towards the use of bark have been made, e.g. as a raw material to harvest different chemical compounds or as an additive for wood particle boards. Our motivation for this work was to keep the bark in an almost natural state and explore alternative processes and applications for use. The traditional method of de-barking tree trunks by peeling was used to harvest large bark pieces. Two pieces of peeled bark were placed crosswise, with the rhytidom side (outer bark) facing each other. After different conditioning steps, bark pieces were hot pressed to panels without adding adhesives. These experiments on bark samples of different Central European tree species suggest that production of panels with species dependent properties is possible and feasible. This is a step towards producing sustainable panels by using a natural waste material, while retaining its beneficial structure and its natural chemical composition.

ABSTRACT Background Gut‐brain axis is widely implicated in the pathophysiology of Parkinson's disease (PD). We take an integrated approach to considering the gut as a target for disease‐modifying intervention, using continuous measurements of disease facets irrespective of diagnostic divide. Methods We characterised 77 participants with diagnosed‐PD, 113 without, by dietary/exogenous substance intake, faecal metabolome, intestinal inflammation, serum cytokines/chemokines, clinical phenotype including colonic transit time. Complete‐linkage hierarchical cluster analysis of metabolites discriminant for PD‐status was performed. Results Longer colonic transit was linked to deficits in faecal short‐chain‐fatty acids outside PD, to a ‘tryptophan‐containing metabolite cluster’ overall. Phenotypic cluster analysis aggregated colonic transit with brady/hypokinesia, tremor, sleep disorder and dysosmia, each individually associated with tryptophan‐cluster deficit. Overall, a faster pulse was associated with deficits in a metabolite cluster including benzoic acid and an imidazole‐ring compound (anti‐fungals) and vitamin B3 (anti‐inflammatory) and with higher serum CCL20 (chemotactic for lymphocytes/dendritic cells towards mucosal epithelium). The faster pulse in PD was irrespective of postural hypotension. The benzoic acid‐cluster deficit was linked to (well‐recognised) lower caffeine and alcohol intakes, tryptophan‐cluster deficit to higher maltose intake. Free‐sugar intake was increased in PD, maltose intake being 63% higher (p = .001). Faecal calprotectin was 44% (95% CI 5%, 98%) greater in PD [p = .001, adjusted for proton‐pump inhibitors (p = .001)], with 16% of PD‐probands exceeding a cut‐point for clinically significant inflammation compatible with inflammatory bowel disease. Higher maltose intake was associated with exceeding this calprotectin cut‐point. Conclusions Emerging picture is of (i) clinical phenotype being described by deficits in microbial metabolites essential to gut health; (ii) intestinal inflammation; (iii) a systemic inflammatory response syndrome.

Objectives Problem drug use (PDU) prevalence is an essential part of evidence base to formulate policy, inform service provision, and assess interventions. Opiate and crack use, particularly injecting, is associated with infectious diseases. Multiple data sources, where PDU are observed, are linked to estimate the hidden population of PDU using capture-recapture. Approach Datasets consisted of (1) community treatment, (2) prison treatment, (3) probation (Ministry of Justice), and (4) drug-related deaths, for financial year 2018/19. The following offenders’ attributes and geography are used: first and second initials, date of birth, gender, multiple areas of residence and area of prison release. Geography information consists of local authority code and region name. Probabilistic linkage approach of Fellegi–Sunter is applied through FastLink package in R, where pairs of records are classified as match, possible match, or non-match at 85% threshold. Estimates of error rates, sensitivity and specificity are used to test the results. Results There were 138,341 records in community treatment, 41,700 records in prison, 18,849 in probation and 2,368 deaths from opiate or cocaine. The total number of individuals observed in at least one linked dataset is estimated at 170,307 records at 85% threshold. The number of exact and possible matches overlapping between community treatment and prison is estimated at 17,544 records, from which 13,731 (78.3%) are exact matches, and 3,813 (21.7%) are possible matches at 85% threshold. The number of exact and possible matches overlapping between linked community treatment/prison and probation is estimated at 12,586 records, from which 9,872 (78.4%) are exact and 2,714 (21.6%) are possible matches at 85% threshold. False discovery rate was estimated at 0.3%, sensitivity and specificity were 99.8%. Conclusions Information on PDUs attending community treatment is poor and relying on exact matches underestimate the overlap between data sources. This tend to bias hidden population estimates derived from capture-recapture. Probabilistic approaches, and use of multiple candidate geographic areas for matching, maximise linkages between individuals and thus likely to improve estimates.

Objective To describe the clinical presentation, course of disease and health-care seeking behaviour of the first few hundred cases of coronavirus disease 2019 (COVID-19) in the United Kingdom of Great Britain and Northern Ireland. Methods We implemented the World Health Organization's First Few X cases and contacts investigation protocol for COVID-19. Trained public health professionals collected information on 381 virologically confirmed COVID-19 cases from 31 January 2020 to 9 April 2020. We actively followed up cases to identify exposure to infection, symptoms and outcomes. We also collected limited data on 752 symptomatic people testing negative for COVID-19, as a control group for analyses of the sensitivity, specificity and predictive value of symptoms. Findings Approximately half of the COVID-19 cases were imported (196 cases; 51.4%), of whom the majority had recent travel to Italy (140 cases; 71.4%). Of the 94 (24.7%) secondary cases, almost all reported close contact with a confirmed case (93 cases; 98.9%), many through household contact (37 cases; 39.8%). By age, a lower proportion of children had COVID-19. Most cases presented with cough, fever and fatigue. The sensitivity and specificity of symptoms varied by age, with nonlinear relationships with age. Although the proportion of COVID-19 cases with fever increased with age, for those with other respiratory infections the occurrence of fever decreased with age. The occurrence of shortness of breath also increased with age in a greater proportion of COVID-19 cases. Conclusion The study has provided useful evidence for generating case definitions and has informed modelling studies of the likely burden of COVID-19. Objectif Decrire la manifestation clinique, l'evolution de la maladie et la propension a recourir aux services de sante des premieres centaines de cas de maladie a coronavirus 2019 (COVID-19) au Royaume-Uni de Grande-Bretagne et d'Irlande du Nord. Methodes Nous avons applique le Protocole d'enquete sur la maladie a coronavirus 2019 (COVID-19)--les X premiers cas et contacts (FFX) publie par l'Organisation mondiale de la Sante. Des professionnels de la sante formes a cet effet ont collecte des informations sur 381 cas virologiquement confirmes de COVID-19 entre le 31 janvier 2020 et le 9 avril 2020. Nous avons etroitement surveille ces cas afin d'identifier la source d'exposition a l'infection, les symptomes observes et l'issue de la maladie. Nous avons egalement recolte des donnees sur 752 personnes symptomatiques testees negatives a la COVID-19 qui ont servi de groupe de controle pour analyser la sensibilite, la specificite et la valeur predictive des symptomes. Resultats Environ la moitie des cas de COVID-19 ont ete importes (196 cas; 51,4%), la majorite s'etant recemment rendue en Italie (140 cas; 71,4%). Sur les 94 (24,7%) cas secondaires, presque tous ont signale un contact rapproche avec un cas confirme (93 cas; 98,9%), generalement au sein de leur foyer (37 cas; 39,8%). Au niveau de l'age, la proportion d'enfants ayant contracte la COVID-19 etait moindre. La plupart des cas avaient de la toux, de la fievre et de la fatigue. La sensibilite et la specificite des symptomes variaient en fonction de l'age, presentant une relation non lineaire avec cet element. Plus l'age des cas de COVID-19 avancait, plus ils etaient susceptibles de developper de la fievre, a l'exception de ceux touches par d'autres infections respiratoires. Le risque d'essoufflement augmentait lui aussi avec l'age chez une grande partie des cas de COVID-19. Conclusion Cette etude a apporte un eclairage utile dans l'etablissement d'une definition des cas. Elle a egalement fourni, pour diverses modelisations, des indications sur la charge que pourrait faire peser la COVID-19. Objetivo Describir la presentacion clinica, el curso de la enfermedad y el comportamiento de busqueda de atencion sanitaria de los primeros cientos de casos de la enfermedad del coronavirus de 2019 (COVID-19) en Reino Unido e Irlanda del Norte. Metodos Implementamos el protocolo de investigacion de los primeros casos y contactos de la Organizacion Mundial de la Salud para la COVID-19. Profesionales expertos en el area de la salud publica recopilaron informacion sobre 381 casos virologicamente confirmados de COVID-19 entre el 31 de enero de 2020 y el 9 de abril de 2020. Realizamos un seguimiento activo de los casos para identificar la exposicion a la infeccion, los sintomas y los resultados. Tambien recogimos datos limitados sobre 752 personas sintomaticas que dieron negativo en los resultados de la COVID-19, como grupo de control para el analisis de la sensibilidad, la especificidad y el valor predictivo de los sintomas. Resultados Casi la mitad de los casos de COVID-19 fueron importados (196 casos; 51,4%), de los cuales la mayoria habia hecho un viaje reciente a Italia (140 casos; 71,4%). De los 94 (24,7%) casos secundarios, casi todos informaron de un contacto cercano con un caso confirmado (93 casos; 98,9%), muchos de ellos a traves del contacto con el hogar (37 casos; 39,8%). Por edad, una proporcion menor de ninos tenia COVID-19. La mayoria de los casos se presentaban con tos, fiebre y fatiga. La sensibilidad y especificidad de los sintomas variaba segun la edad, con relaciones no lineales con la edad. Aunque la proporcion de casos de COVID-19 con fiebre aumentaba con la edad, en el caso de los que tenian otras infecciones respiratorias la aparicion de fiebre disminuia con la edad. La incidencia de la falta de aliento tambien aumento con la edad en una mayor proporcion de casos de COVID-19. Conclusion El estudio ha aportado pruebas utiles para generar definiciones de casos y tambien ha servido de base a los estudios de modelizacion del probable coste de la COVID-19., Introduction The World Health Organization (WHO) recommended that Member States implement their established First Few X enhanced surveillance protocol (1) to investigate the clinical and epidemiological characteristics of at least [...]

Assessing the impact of an intervention by using time-series observational data on multiple units and outcomes is a frequent problem in many fields of scientific research. Here, we propose a novel Bayesian multivariate factor analysis model for estimating intervention effects in such settings and develop an efficient Markov chain Monte Carlo algorithm to sample from the high-dimensional and nontractable posterior of interest. The proposed method is one of the few that can simultaneously deal with outcomes of mixed type (continuous, binomial, count), increase efficiency in the estimates of the causal effects by jointly modeling multiple outcomes affected by the intervention, and easily provide uncertainty quantification for all causal estimands of interest. Using the proposed approach, we evaluate the impact that Local Tracing Partnerships had on the effectiveness of England's Test and Trace programme for COVID-19. [ABSTRACT FROM AUTHOR]

Abstract Background Ending the global tuberculosis (TB) epidemic requires a focus on treating individuals with latent TB infection (LTBI) to prevent future cases. Promising trials of shorter regimens have shown them to be effective as preventative TB treatment, however there is a paucity of data on self-administered treatment completion rates. This pilot trial assessed treatment completion, adherence, safety and the feasibility of treating LTBI in the UK using a weekly rifapentine and isoniazid regimen versus daily rifampicin and isoniazid, both self-administered for 12 weeks. Methods An open label, randomised, multi-site pilot trial was conducted in London, UK, between March 2015 and January 2017. Adults between 16 and 65 years with LTBI at two TB clinics who were eligible for and agreed to preventative therapy were consented and randomised 1:1 to receive either a weekly combination of rifapentine/isoniazid (‘intervention’) or a daily combination of rifampicin/isoniazid (‘standard’), with both regimens taken for twelve weeks; treatment was self-administered in both arms. The primary outcome, completion of treatment, was self-reported, defined as taking more than 90% of prescribed doses and corroborated by pill counts and urine testing. Adverse events were recorded. Results Fifty-two patients were successfully enrolled. In the intervention arm 21 of 27 patients completed treatment (77.8, 95% confidence interval [CI] 57.7–91.4), compared with 19 of 25 (76.0%, CI 54.9–90.6) in the standard of care arm. There was a similar adverse effect profile between the two arms. Conclusion In this pilot trial, treatment completion was comparable between the weekly rifapentine/isoniazid and the daily rifampicin/isoniazid regimens. Additionally, the adverse event profile was similar between the two arms. We conclude that it is safe and feasible to undertake a fully powered trial to determine whether self-administered weekly treatment is superior/non-inferior compared to current treatment. Trial registration The trial was funded by the NIHR, UK and registered with ISRCTN ( 26/02/2013-No.04379941 ).

Abstract COVID-19 is reported to have been brought under control in China. To understand the COVID-19 outbreak in China and provide potential lessons for other parts of the world, in this study we apply a mathematical model with multiple datasets to estimate the transmissibility of the SARS-CoV-2 virus and the severity of the illness associated with the infection, and how both were affected by unprecedented control measures. Our analyses show that before 19th January 2020, 3.5% (95% CI 1.7–8.3%) of infected people were detected; this percentage increased to 36.6% (95% CI 26.1–55.4%) thereafter. The basic reproduction number (R 0) was 2.33 (95% CI 1.96–3.69) before 8th February 2020; then the effective reproduction number dropped to 0.04(95% CI 0.01–0.10). This estimation also indicates that control measures taken since 23rd January 2020 affected the transmissibility about 2 weeks after they were introduced. The confirmed case fatality rate is estimated at 9.6% (95% CI 8.1–11.4%) before 15 February 2020, and then it reduced to 0.7% (95% CI 0.4–1.0%). This shows that SARS-CoV-2 virus is highly transmissible but may be less severe than SARS-CoV-1 and MERS-CoV. We found that at the early stage, the majority of R 0 comes from undetected infectious people. This implies that successful control in China was achieved through reducing the contact rates among people in the general population and increasing the rate of detection and quarantine of the infectious cases.