Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe.

Following the detection of the new coronavirus1 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics of coronavirus disease 2019 (COVID-19). In response, many European countries have implemented non-pharmaceutical interventions, such as the closure of schools and national lockdowns. Here we study the effect of major interventions across 11 European countries for the period from the start of the COVID-19 epidemics in February 2020 until 4 May 2020, when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks previously, allowing for the time lag between infection and death. We use partial pooling of information between countries, with both individual and shared effects on the time-varying reproduction number (Rt). Pooling allows for more information to be used, helps to overcome idiosyncrasies in the data and enables more-timely estimates. Our model relies on fixed estimates of some epidemiological parameters (such as the infection fatality rate), does not include importation or subnational variation and assumes that changes in Rt are an immediate response to interventions rather than gradual changes in behaviour. Amidst the ongoing pandemic, we rely on death data that are incomplete, show systematic biases in reporting and are subject to future consolidation. We estimate that-for all of the countries we consider here-current interventions have been sufficient to drive Rt below 1 (probability Rt < 1.0 is greater than 99%) and achieve control of the epidemic. We estimate that across all 11 countries combined, between 12 and 15 million individuals were infected with SARS-CoV-2 up to 4 May 2020, representing between 3.2% and 4.0% of the population. Our results show that major non-pharmaceutical interventions-and lockdowns in particular-have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.

Immunopathogenic Insights on Preferential Human Herpesvirus-6 Reactivation in Drug Rash With Eosinophilia and Systemic Symptoms: A Scoping Review.

INTRODUCTION: Human herpesvirus-6 (HHV-6) is a ubiquitous lymphotropic betaherpesvirus that can reactivate in drug rash with eosinophilia and systemic symptoms (DRESS). Despite recent publications advancing our understanding of HHV-6 in DRESS, the exact role of HHV-6 in disease pathogenesis remains unclear. METHODS: A scoping review with the PubMed query "(HHV 6 AND (drug OR DRESS OR DIHS)) OR (HHV6 AND (drug OR DRESS OR DIHS))" was conducted in accordance with PRISMA guidelines. Articles containing original data on at least one DRESS patient with HHV-6 testing were included. RESULTS: Our search returned a total of 373 publications, of which 89 met eligibility criteria. HHV-6 reactivation occurred in 63% of DRESS patients (n = 748), which was significantly more often than other herpesviruses. HHV-6 reactivation was associated with worse outcomes and greater severity in controlled studies. Case reports have demonstrated sometimes fatal HHV-6-related multi-organ involvement. Temporally, HHV-6 reactivation typically occurs 2 to 4 weeks after DRESS onset and has been linked to markers of immunologic signaling, such as OX40 (CD134), an HHV-6 entry receptor. Efficacy of antiviral or immunoglobulin treatment has only been demonstrated anecdotally, and steroid use may affect HHV-6 reactivation. CONCLUSION: HHV-6 is implicated in DRESS more than in any other dermatologic condition. It is still unclear whether HHV-6 reactivation is cause or consequence of DRESS dysregulation. Similar pathogenic mechanisms precipitated by HHV-6 in other contexts may be relevant in DRESS. Future randomized controlled studies to assess effects of viral suppression on clinical outcomes is needed.

Two years of a pilot virtual melanoma education program for adolescents in Texas: Assessing knowledge gaps and demographic disparities.

A formal melanoma primary prevention program was developed for a target audience of grade-school adolescents near Houston, Texas, focusing on skin cancer education and promoting long-term sun safety habits. Upon application of a multivariable regression model, adolescents of Black, non-Hispanic race, male gender, and lower grade levels were independent predictors of lower baseline skin cancer prevention knowledge. These findings reveal potential areas to prioritize when addressing knowledge gaps in the adolescent community.

Altmetric Analysis of Dermatology Manuscript Dissemination During the COVID-19 Era: Cross-Sectional Study.

BACKGROUND: Alternative bibliometrics or altmetrics, is a measure of an academic article's impact on social media outlets, which is quantified by the Altmetric Attention score (AAS). Given a lack of data for altmetric trends during the COVID-19 pandemic, we conducted a comprehensive, multivariable analysis of top dermatology manuscripts published during this time period. OBJECTIVE: We aim to assess (1) the relationship between traditional bibiliometrics and Altmetrics and (2) factors associated with high AAS. METHODS: All abstracted articles published in the top-5 (ranked by SCImago Journal Rankings) peer-reviewed dermatology journals published in 2021 were included in our study. We collected AAS as the dependent variable and categorical predictor variables included journal title, whether a conflict of interest existed, open access status, whether the article was related to COVID-19 or skin-of-color research, and the type of research (eg, clinical, basic science, review, etc). Numerical predictor variables consisted of the impact factor of journal, total citations, and number of authors. Multivariable linear or logistic regression models were used. RESULTS: The relationship between AAS and citation number was significant by multivariable analysis during the COVID-19 pandemic (P<.001). Numerous factors, including studies related to COVID-19, whether the article was open access, title of the journal, and journal impact factor were also independently related to higher AAS (P<.002). CONCLUSIONS: Our results validate the use of altmetrics as a complement to traditional bibliometrics, especially in times of widespread scientific interest. Despite existing in a complex realm of bibliometrics, there are also discernable patterns associated with higher AAS. This is especially relevant in the era of growing technologic importance and utility to assess the impact of scientific works within the general public.

Demographic and applicant-specific predictors of medical school research productivity in a national cohort of dermatology residents.

Research is a crucial aspect of medical advancement, and applicants applying to dermatology often have high research outputs. With United States Medical Licensing Examination (USMLE) Step 1 becoming pass/fail, research productivity may be more emphasized. We primarily sought to assess predictors of medical school research productivity. Class of 2023 dermatology residents publicly listed on Accreditation Council for Graduate Medical Education-accredited programs were included. Their medical school bibliography and demographics were assessed using PubMed and other platforms (eg, Doximity, LinkedIn). By multivariable analysis, students who attended a top 25 medical school (ranked by US News and World Report) or were PhD graduates had significantly higher H-indices, average impact factors, and total years of research activity (P < .01). Top 25 medical school graduates also had significantly higher total peer-reviewed publications, first authorships, and clinical research papers (P < .01). PhD graduates had significantly more clinical research and fewer dermatology-related papers (P < .03). Graduates of osteopathic medical schools had significantly fewer review papers (P = .02). Gender and graduation from an international medical school had no relationship with research productivity. Our study demonstrates a correlation between applicant-specific factors and research productivity. Because the emphasis on research productivity may increase, understanding the mechanisms behind these relationships may guide future dermatology applicants or their mentors.

Topical hedgehog inhibitors for basal cell carcinoma: how far away are we?

INTRODUCTION: The standard treatment of basal cell carcinoma (BCC) consists of conventional excision or Mohs micrographic surgery. However, surgical excision is not feasible in specific cases, particularly in patients with several BCCs such as those with Gorlin syndrome or individuals receiving immunosuppression after solid-organ transplantation. Additionally, the geriatric population may not be appropriate candidates for surgery. Thus, alternative therapies are needed for these populations. AREAS COVERED: Hedgehog (Hh) inhibitors are approved and effective but are currently available only in oral formulations. These agents such as vismodegib and sonidegib are associated with short-lived responses as well as significant adverse effects including myalgias, dysgeusia, and alopecia. Patidegib and itraconazole are two topical Hh inhibitors agents emerging as alternatives to oral Hh inhibiton for difficult-to-treat BCCs. These agents exhibit limited systemic absorption, leading to improved tolerability; however, an optimal formulation is needed to maximize efficacy and is currently being investigated. EXPERT OPINION: Ongoing and recent clinical studies on topical Hedgehog inhibitors show great promise for the development of an agent with a high therapeutic index and limited adverse effects. If patidegib continues to show clinical efficacy in randomized controlled trials, it may become a universal therapy for all subtypes of difficult-to-treat BCC.

π VAE: a stochastic process prior for Bayesian deep learning with MCMC.

Stochastic processes provide a mathematically elegant way to model complex data. In theory, they provide flexible priors over function classes that can encode a wide range of interesting assumptions. However, in practice efficient inference by optimisation or marginalisation is difficult, a problem further exacerbated with big data and high dimensional input spaces. We propose a novel variational autoencoder (VAE) called the prior encoding variational autoencoder ( π VAE). π VAE is a new continuous stochastic process. We use π VAE to learn low dimensional embeddings of function classes by combining a trainable feature mapping with generative model using a VAE. We show that our framework can accurately learn expressive function classes such as Gaussian processes, but also properties of functions such as their integrals. For popular tasks, such as spatial interpolation, π VAE achieves state-of-the-art performance both in terms of accuracy and computational efficiency. Perhaps most usefully, we demonstrate an elegant and scalable means of performing fully Bayesian inference for stochastic processes within probabilistic programming languages such as Stan.

Unique Challenges to Diagnosing Human Herpesvirus-6 (HHV-6) Encephalitis Following Post-Hematopoietic Stem Cell Transplant: A Case and Brief Review.

A patient with an ultimate diagnosis of human herpesvirus-6 (HHV-6) encephalitis developed central nervous system (CNS) symptoms 13 days after undergoing myeloablative haploidentical allogeneic hematopoietic stem cell transplant (HSCT). Due to the patient's body habitus, magnetic resonance (MR) imaging was not obtained until the onset of retrograde amnesia on day +24. MR imaging and other clinical findings eliminated all skepticism of HHV-6 encephalitis and HHV-6 antivirals were initiated on day +28, leading to gradual recovery. This case demonstrates some of the factors that may complicate the diagnosis of post-alloHSCT HHV-6 encephalitis. Because HHV-6 encephalitis and viremia can occur without warning, a single negative study should not exclude future development, especially if CNS symptoms are present. Acute graft-versus-host disease and cord blood transplantation are both significant risk factors for HHV-6 encephalitis. Human leukocyte antigen (HLA) mismatch, engraftment complications, or certain HLA alleles have also been associated with HHV-6 encephalitis. Chromosomally integrated HHV-6 must also be ruled out to prevent inappropriate and potentially harmful administration of antivirals. Due to the severe short- and long-term sequelae of HHV-6 encephalitis, appropriate treatment should be administered as soon as possible.

3D Printed Skull Cap and Benchtop Fabricated Microwire-Based Microelectrode Array for Custom Rat Brain Recordings.

Microwire microelectrode arrays (MEAs) have been a popular low-cost tool for chronic electrophysiological recordings and are an inexpensive means to record the electrical dynamics crucial to brain function. However, both the fabrication and implantation procedures for multi-MEAs on a single rodent are time-consuming and the accuracy and quality are highly manual skill-dependent. To address the fabrication and implantation challenges for microwire MEAs, (1) a computer-aided designed and 3D printed skull cap for the pre-determined implantation locations of each MEA and (2) a benchtop fabrication approach for low-cost custom microwire MEAs were developed. A proof-of-concept design of a 32-channel 4-MEA (8-wire each) recording system was prototyped and tested through Sprague Dawley rat recordings. The skull cap design, based on the CT-scan of a single rat conforms well with multiple Sprague Dawley rats of various sizes, ages, and weight with a minimal bregma alignment error (A/P axis standard error of the mean = 0.25 mm, M/L axis standard error of the mean = 0.07 mm, n = 6). The prototyped 32-channel system was able to record the spiking activities over five months. The developed benchtop fabrication method and the 3D printed skull cap implantation platform would enable neuroscience groups to conduct in-house design, fabrication, and implantation of customizable microwire MEAs at a lower cost than the current commercial options and experience a shorter lead time for the design modifications and iterations.

A Bibliometric Analysis of Ophthalmology Resident Research Productivity in the United States.

Background The extent and impact of ophthalmology resident scholarly output is not well known. The authors aim to quantify scholarly activity of ophthalmology residents during residency and assess what factors may be associated with greater research productivity of these residents. Material and Methods Ophthalmology residents who graduated in 2021 were identified from their respective program Web sites. Bibliometric data published by these residents between the beginning of their postgraduate year 2 (July 1, 2018) until 3 months after graduation (September 30, 2021) were captured through searches via PubMed, Scopus, and Google Scholar. The association of the following factors with greater research productivity numbers was analyzed: residency tier, medical school rank, sex, doctorate degree, type of medical degree, and international medical graduate status. Results We found 418 ophthalmology residents from 98 residency programs. These residents published a mean (±standard deviation [SD]) number of 2.68 ± 3.81 peer-reviewed publications, 2.39 ± 3.40 ophthalmology-related publications, and 1.18 ± 1.96 first-author publications each. The mean (±SD) Hirsch index (h-index) for this cohort was 0.79 ± 1.17. Upon multivariate analysis, we discovered significant correlations between both residency tier and medical school rank and all bibliometric variables assessed. Pairwise comparisons revealed that residents from higher tier programs had greater research productivity numbers than those from lower tier programs. Conclusion We obtained bibliometric standards for ophthalmology residents on a national scale. Residents who graduated from higher-ranked residency programs and medical schools possessed higher h-indices and published more peer-reviewed publications, ophthalmology-related articles, and first-author publications.

Social Media Impact of Articles Published by Dermatology Residents During Medical School: Cross-sectional Study.

BACKGROUND: The Altmetric score (AS) is a novel measure of publication impact that is calculated by the number of mentions across various social media websites. This method may have advantages over traditional bibliometrics in the context of research by medical students. OBJECTIVE: This study aimed to determine whether dermatology matriculants who graduated from higher-ranked medical schools published more articles with greater impact (ie, a higher AS) than those from lower-ranked institutions. METHODS: A PubMed search for articles published by dermatology residents who started medical school in 2020 was conducted. Demographic information and Altmetric data were collected, and medical schools were sorted according to US News' top-25 and non-top-25 categories. RESULTS: Residents who completed their medical training at a top-25 institution published more papers (mean 4.93, SD 4.18 vs mean 3.11, SD 3.32; P<.001) and accrued a significantly higher total AS (mean 67.9, SD 160 vs mean 22.9, SD 75.9; P<.001) and average AS (mean 13.1, SD 23.7 vs mean 6.71, SD 32.3; P<.001) per article than those who graduated from non-top-25 schools. CONCLUSIONS: Our results indicate that students in top-25 schools may have greater access to research resources and opportunities. With a pass/fail United States Medical Licensing Examination Step 1 exam that may increasingly shift focus toward scholarly output from medical students, further discussion on how to create a more equitable dermatology match is essential.

A COVID-19 model for local authorities of the United Kingdom.

We propose a new framework to model the COVID-19 epidemic of the United Kingdom at the local authority level. The model fits within a general framework for semi-mechanistic Bayesian models of the epidemic based on renewal equations, with some important innovations, including a random walk modelling the reproduction number, incorporating information from different sources, including surveys to estimate the time-varying proportion of infections that lead to reported cases or deaths, and modelling the underlying infections as latent random variables. The model is designed to be updated daily using publicly available data. We envisage the model to be useful for now-casting and short-term projections of the epidemic as well as estimating historical trends. The model fits are available on a public website: https://imperialcollegelondon.github.io/covid19local. The model is currently being used by the Scottish government to inform their interventions.

Epstein-Barr Virus and Human Herpesvirus-6 Reactivation in Acute COVID-19 Patients.

Beyond their pulmonary disease, many COVID-19 patients experience a complex constellation of characteristics, including hyperinflammatory responses, autoimmune disorders, and coagulopathies. However, the pathogenesis of these aspects of COVID-19 is obscure. More than 90% of people are latently infected with the lymphotropic herpesviruses Epstein-Barr Virus (EBV) and/or Human Herpesvirus-6 (HHV-6). Some of the inflammatory features of COVID-19 resemble clinical syndromes seen during EBV and HHV-6 infection, and these latent viruses can be reactivated by inflammatory mediators. We hypothesized that EBV and HHV-6 reactivation might be a common feature of early COVID-19, particularly in patients with more inflammation. We tested for EBV and HHV-6 reactivation in 67 patients acutely hospitalized with COVID-19 using previously validated quantitative PCR assays on the plasma. In our cohort, we found that 15/67 (22.4%) patients had detectable EBV and 3/67 (4.5%) had detectable HHV-6. This frequency of activation is somewhat more than the frequency reported for some healthy cohorts, such as blood donors and other healthy control cohorts. There was no association between EBV or HHV-6 and markers indicative of more inflammatory disease. We conclude that EBV and HHV-6 activation at about day 7 of hospitalization occurred in a modest fraction of our cohort of COVID-19 patients and was not associated with high levels of inflammation. In the modest fraction of patients, EBV and HHV-6 reactivation could contribute to some features of acute disease and pre-disposition to post-acute sequelae in a subset of patients.

Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling.

The UK and Sweden have among the worst per-capita COVID-19 mortality in Europe. Sweden stands out for its greater reliance on voluntary, rather than mandatory, control measures. We explore how the timing and effectiveness of control measures in the UK, Sweden and Denmark shaped COVID-19 mortality in each country, using a counterfactual assessment: what would the impact have been, had each country adopted the others' policies? Using a Bayesian semi-mechanistic model without prior assumptions on the mechanism or effectiveness of interventions, we estimate the time-varying reproduction number for the UK, Sweden and Denmark from daily mortality data. We use two approaches to evaluate counterfactuals which transpose the transmission profile from one country onto another, in each country's first wave from 13th March (when stringent interventions began) until 1st July 2020. UK mortality would have approximately doubled had Swedish policy been adopted, while Swedish mortality would have more than halved had Sweden adopted UK or Danish strategies. Danish policies were most effective, although differences between the UK and Denmark were significant for one counterfactual approach only. Our analysis shows that small changes in the timing or effectiveness of interventions have disproportionately large effects on total mortality within a rapidly growing epidemic.