Are HIV services in England accessible and acceptable to adults diagnosed with HIV at age 50 years and over? A mixed-methods study

In the UK, new HIV diagnoses are increasing in adults aged 50 years and over, a group that also has a higher likelihood of testing at an advanced stage of disease than younger people. Despite this, limited research has examined the pathway to HIV diagnosis and treatment experienced by this age group, or looked more broadly at the impact of living with HIV after diagnosis at this age. Using a mixed-methods approach, this thesis explores the acceptability and accessibility of HIV services in England to adults diagnosed at age 50+ years, from the perspective of these service users and healthcare professionals (HCPs) working in sexual health/HIV services and involved in caring for this age group. This thesis draws on semi-structured interviews with service users; an online survey and semi-structured interviews with HCPs; as well as national data on sexual health/GUM clinic attendance, HIV test coverage, and new HIV diagnoses by age. Adults aged 50+ years are found to experience often complex and non-linear journeys to HIV testing, particularly if they do not belong to a ‘risk group’ targeted in HIV prevention and testing efforts. Barriers to prompt HIV diagnosis include (i) the non-specific nature of HIV symptoms and their misattribution as being age-related, (ii) an age-associated decline in risk perception, and (iii) the decreased likelihood of HIV test offer in advancing age. Both service users and HCPs perceive HIV treatment services to provide exceptional care, which is associated with the benefits of closer health monitoring, clinician expertise in HIV, and consistency in care. General practitioners (GPs) by contrast appear to be underutilised in the management of older people with HIV, which may be particularly detrimental as these service users often develop additional, age-related morbidities, which extend beyond the remit of HIV clinician knowledge. The thesis concludes by highlighting a need to reconsider the model of HIV care in England, especially with respect to the role of GPs in HIV service provision. It is likely that increased GP involvement would optimise care and encourage the normalisation of HIV, which would promote testing and reduce stigma

Parents' and guardians' views on the acceptability of a future COVID-19 vaccine: A multi-methods study in England.

BACKGROUND: The availability of a COVID-19 vaccine has been heralded as key to controlling the COVID-19 pandemic. COVID-19 vaccination programme success will rely on public willingness to be vaccinated. METHODS: We used a multi-methods approach - involving an online cross-sectional survey and semi-structured interviews - to investigate parents' and guardians' views on the acceptability of a future COVID-19 vaccine. 1252 parents and guardians (aged 16 + years) who reported living in England with a child aged 18 months or under completed the survey. Nineteen survey participants were interviewed. FINDINGS: Most survey participants reported they would likely accept a COVID-19 vaccine for themselves (Definitely 55.8%; Unsure but leaning towards yes 34.3%) and their child/children (Definitely 48.2%; Unsure but leaning towards yes 40.9%). Less than 4% of survey participants reported that they would definitely not accept a COVID-19 vaccine. Survey participants were more likely to accept a COVID-19 vaccine for themselves than their child/children. Participants that self-reported as Black, Asian, Chinese, Mixed or Other ethnicity were almost 3 times more likely to reject a COVID-19 vaccine for themselves and their children than White British, White Irish and White Other participants. Survey participants from lower-income households were also more likely to reject a COVID-19 vaccine. In open-text survey responses and interviews, self-protection from COVID-19 was reported as the main reason for vaccine acceptance. Common concerns identified in open-text responses and interviews were around COVID-19 vaccine safety and effectiveness, mostly prompted by the newness and rapid development of the vaccine. CONCLUSION: Information on how COVID-19 vaccines are developed and tested, including their safety and efficacy, must be communicated clearly to the public. To prevent inequalities in uptake, it is crucial to understand and address factors that may affect COVID-19 vaccine acceptability in ethnic minority and lower-income groups who are disproportionately affected by COVID-19

Forensic Technologies in Music Copyright

The essay explores some recent controversies in British music copyright through the evolving technologies used to perform or play music in the courtroom. While the conceptual tension between cases has caused doctrinal anxiety about the effect of popular music in copyright, the essay contends that the recent stream of music copyright cases can be considered from a historical perspective, taking into account the tools, materials and experts as they featured in court. In doing so, the essay connects a history of legal expertise to the emergence of new technologies while arguing that legal knowledge about music copyright was, in fact, stabilised in the courtroom

Correction for Johansson et al., An open challenge to advance probabilistic forecasting for dengue epidemics.

Correction for “An open challenge to advance probabilistic forecasting for dengue epidemics,” by Michael A. Johansson, Karyn M. Apfeldorf, Scott Dobson, Jason Devita, Anna L. Buczak, Benjamin Baugher, Linda J. Moniz, Thomas Bagley, Steven M. Babin, Erhan Guven, Teresa K. Yamana, Jeffrey Shaman, Terry Moschou, Nick Lothian, Aaron Lane, Grant Osborne, Gao Jiang, Logan C. Brooks, David C. Farrow, Sangwon Hyun, Ryan J. Tibshirani, Roni Rosenfeld, Justin Lessler, Nicholas G. Reich, Derek A. T. Cummings, Stephen A. Lauer, Sean M. Moore, Hannah E. Clapham, Rachel Lowe, Trevor C. Bailey, Markel García-Díez, Marilia Sá Carvalho, Xavier Rodó, Tridip Sardar, Richard Paul, Evan L. Ray, Krzysztof Sakrejda, Alexandria C. Brown, Xi Meng, Osonde Osoba, Raffaele Vardavas, David Manheim, Melinda Moore, Dhananjai M. Rao, Travis C. Porco, Sarah Ackley, Fengchen Liu, Lee Worden, Matteo Convertino, Yang Liu, Abraham Reddy, Eloy Ortiz, Jorge Rivero, Humberto Brito, Alicia Juarrero, Leah R. Johnson, Robert B. Gramacy, Jeremy M. Cohen, Erin A. Mordecai, Courtney C. Murdock, Jason R. Rohr, Sadie J. Ryan, Anna M. Stewart-Ibarra, Daniel P. Weikel, Antarpreet Jutla, Rakibul Khan, Marissa Poultney, Rita R. Colwell, Brenda Rivera-García, Christopher M. Barker, Jesse E. Bell, Matthew Biggerstaff, David Swerdlow, Luis Mier-y-Teran-Romero, Brett M. Forshey, Juli Trtanj, Jason Asher, Matt Clay, Harold S. Margolis, Andrew M. Hebbeler, Dylan George, and Jean-Paul Chretien, which was first published November 11, 2019; 10.1073/pnas.1909865116. The authors note that the affiliation for Xavier Rodó should instead appear as Catalan Institution for Research and Advanced Studies (ICREA) and Climate and Health Program, Barcelona Institute for Global Health (ISGlobal). The corrected author and affiliation lines appear below. The online version has been corrected

An open challenge to advance probabilistic forecasting for dengue epidemics.

A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Distinct cellular pools of perilipin 5 point to roles in lipid trafficking

The PAT family of lipid storage droplet proteins comprised five members, each of which has become an established regulator of cellular neutral lipid metabolism. Perilipin 5 (also known as lsdp-5, MLDP, PAT-1, and OXPAT), the most recently discovered member of the family, has been shown to localize to two distinct intracellular pools: the lipid storage droplet (LD), and a poorly characterized cytosolic fraction. We have characterized the denser of these intracellular pools and find that a population of perilipin 5 not associated with large LDs resides in complexes with a discrete density (~1.15 g/ml) and size (~575 kDa). Using immunofluorescence, western blotting of isolated sucrose density fractions, native gradient gel electrophoresis, and co-immunoprecipitation, we have shown that these small (~15 nm), perilipin 5-encoated structures do not contain the PAT protein perilipin 2 (ADRP), but do contain perilipin 3 and several other as of yet uncharacterized proteins. The size and density of these particles as well as their susceptibility to degradation by lipases suggest that like larger LDs, they have a neutral lipid rich core. When treated with oleic acid to promote neutral lipid deposition, cells ectopically expressing perilipin 5 experienced a reorganization of LDs in the cell, resulting in fewer, larger droplets at the expense of smaller ones. Collectively, these data demonstrate that a portion of cytosolic perilipin 5 resides in high density lipid droplet complexes that participate in cellular neutral lipid accumulation

An open challenge to advance probabilistic forecasting for dengue epidemics.

A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue