title: Modeling of COVID-19 Transmission Dynamics on US Population: Inter-transfer Infection in Age Groups, Mutant Variants, and Vaccination Strategies

abstract:
The in-depth understanding of the dynamics of COVID-19 transmission among different age groups is of great interest for governments and health authorities so that strategies can be devised to reduce the pandemics detrimental effects. We developed the SIRDV-Virulence epidemiological model based on a population balance equation to study the effect of mutants of the virus and the effect of vaccination strategies on mitigating the transmission among the population in the United States. Based on the available data from the Centers for Disease Control and Prevention (CDC), we obtain the key parameters governing the dynamic evolution of the spread of the COVID-19 pandemic. In the context studied, the results show that a large fraction of infected cases comes from the adult and children populations in the presence of a mutant variant of COVID-19 with high infection rates. We further investigate the optimum vaccine distribution strategy among different age groups. Given the current situation in the United States, the results show that prioritizing children and adult vaccinations over that of seniors can contain the spread of the active cases, thereby preventing the healthcare system from being overwhelmed and minimizing subsequent deaths. The model suggests that the only option to curb the effects of this pandemic is to reduce the population of unvaccinated individuals. A higher fraction of  Anti/Non-vaxxers can lead to the resurgence of the pandemic.

Author summaryThe changing dynamics of the COVID-19 pandemic are primarily due to the mutations of the SARS-CoV-2 virus. It is often seen that these mutants not only have a higher infection rate but also evade the presently administered vaccines. To consider the fact that different age population groups are affected to varied extent by these mutants, we build a mathematical model to account for the inter-transfer infection among age groups, which can predict the overall COVID-19 transmission in the United States. The parameter quantification of our mathematical model is based on the public data for infected cases, deaths and vaccinated from the Centers for Disease Control and Prevention (CDC). Additionally, our study shows that the vaccine distribution strategies should be developed with a priority given to the most infected age groups in order to curb the total infected and death cases. We also show how the  Anti/Non-vaxxers can be a potential reason for resurgence of the pandemic. These results are of immediate practical application in determining future vaccine distribution regarding to the pandemic and ensuring the health care system is ready to deal with the worst-case scenario with a very high infection rate.


title: SARS-CoV-2 Transmission Potential and Policy Changes in South Carolina, February 2020 - January 2021

abstract:
IntroductionWe aimed to examine how public health policies influenced the dynamics of COVID-19 time-varying reproductive number (Rt) in South Carolina from February 26, 2020 to January 1, 2021.

MethodsCOVID-19 case series (March 6, 2020 - January 10, 2021) were shifted by 9 days to approximate the infection date. We analyzed the effects of state and county policies on Rt using EpiEstim. We performed linear regression to evaluate if per-capita cumulative case count varies across counties with different population size.

ResultsRt shifted from 2-3 in March to <1 during April and May. Rt rose over the summer and stayed between 1.4 and 0.7. The introduction of statewide mask mandates was associated with a decline in Rt (-15.3%; 95% CrI, -13.6%, -16.8%), and school re-opening, an increase by 12.3% (95% CrI, 10.1%, 14.4%). Less densely populated counties had higher attack rate (p<0.0001).

ConclusionThe Rt dynamics over time indicated that public health interventions substantially slowed COVID-19 transmission in South Carolina, while their relaxation may have promoted further transmission. Policies encouraging people to stay home, such as closing non-essential businesses, were associated with Rt reduction, while policies that encouraged more movement, such as re-opening schools, were associated with Rt increase.

category: epidemiology


title: A nighttime telemedicine and medication delivery service to avert pediatric emergencies: An exploratory cost-effectiveness analysis

abstract:
ObjectiveWe sought to compare the costs of a nighttime pre-emergency pediatric telemedicine and medication delivery service (TMDS) per disability-adjusted life year (DALY) averted to the costs of hospital emergency medicine (HEM) per DALY averted from a societal perspective.

MethodsWe studied a nighttime pediatric TMDS and HEM in a semi-urban and rural region of Haiti. Costs of the 2 services were enumerated to represent the financial investments of both providers and patients. DALYs averted were calculated to represent the  years lives lost (YLL) and  years lost to disability (YLD) from diarrheal, respiratory, and skin (bacterial and scabies etiologies) disease among children from zero to 9 years old. The incremental cost-effectiveness ratio (ICER) was estimated and compared to the per-capita gross domestic product (GDP) of Haiti ($1,177). Cost-effectiveness was defined as an ICER less than 3 times the per-capita GDP of Haiti ($3,531). Univariate sensitivity analysis was performed to evaluate how uncertainty of individual parameter estimates (utilization rates, costs, lost wages, discounting factor) affected the ICER.

ResultsThe total costs of the nighttime TMDS and HEM to society were $285,931.72 per year and $89,335.41 per year, respectively. The DALYs averted by the TMDS and HEM were 199.76 and 22.37, respectively. Through sensitivity analyses, the ICER of the TMDS ranged from $791.43 to $1,593.35.

ConclusionA nighttime pediatric TMDS is a cost-effective alternative to HEM for pre-emergency pediatric care in semi-urban and rural regions in Haiti, and possibly in similar lower-middle income countries.

category: public and global health


title: Non-Pharmaceutical Interventions and COVID-19 Burden in the United States

abstract:
BackgroundNon-pharmaceutical interventions (NPIs) are mitigation strategies used to reduce the spread of transmissible diseases. The relative effectiveness of specific NPIs remains uncertain.

MethodsWe used state-level Coronavirus disease 2019 (COVID-19) case and mortality data between January 19, 2020 and March 7, 2021 to model NPI policy effectiveness. Empirically derived breakpoints in case and mortality velocities were used to identify periods of stable, decreasing, or increasing COVID-19 burden. The associations between NPI adoption and subsequent decreases in case or death velocities were estimated using generalized linear models accounting for weekly variability shared across states. State-level NPI policies included: stay at home order, indoor public gathering ban (mild >10 or severe [≤]10), indoor restaurant dining ban, and public mask mandate.

Results28,602,830 cases and 511,899 deaths were recorded. The odds of a decrease in COVID-19 case velocity were significantly elevated for stay at home (OR 2.02, 95% CI 1.63-2.52), indoor dining ban (OR 1.62, 95% CI 1.25-2.10), public mask mandate (OR 2.18, 95% CI 1.47-3.23), and severe gathering ban (OR 1.68, 95% CI 1.31-2.16). In mutually adjusted models, odds remained elevated for stay at home (AOR 1.47, 95% CI 1.04-2.07) and public mask mandate (AOR = 2.27, 95% CI 1.51-3.41). Stay at home (OR 2.00, 95% CI 1.53-2.62; AOR 1.89, 95% CI 1.25-2.87) was also associated with greater likelihood of decrease in death velocity in unadjusted and adjusted models.

ConclusionsNPIs employed in the U.S. during the COVID-19 pandemic, most significantly stay at home orders, were associated with decreased COVID-19 burden.


title: Clinical application of interactive monitoring of indicators of health in professional dancers

abstract:
ObjectivesThe purpose of this study was to assess the effectiveness of interactive monitoring of professional dancer health with a variety of subjective and objective monitoring methods and delivering swift personalised clinical advice.

MethodsDancers from a ballet company completed a published, online dance-specific health questionnaire. Over the study period, dancers recorded wellbeing and training metrics, with menstrual cycle tracking and capillary blood testing for the recognised indicators of low energy availability. At regular, virtual clinical discussions with each dancer, findings were discussed and personalised advice given.

ResultsTwenty dancers participated in the study (mean age 26.2 years, SD 3.7), comprising 14 females (mean age 25.5 years, SD 3.7) and 6 males (mean age 27.7 years, SD 2.4). Ten of the female and all the male dancers recorded positive scores on the dance health questionnaire, suggesting a low risk of relative energy deficiency in sport (RED-S). Two female dancers were taking hormonal contraception. Apart from one, all female dancers not on hormonal contraception reported current eumenorrhoeic status. Blood testing confirmed the low risk of insufficient energy availability across the group, apart from female dancers with negative questionnaire scores. The initiative of monitoring menstrual cycles and on demand virtual clinical support was well received by dancers, healthcare and artistic staff.

ConclusionsMultimodal monitoring facilitated delivery of prompt personalised clinical medical feedback specific for dance. This interactive strategy permitted the early identification and swift management of emergent clinical issues. Dancers highly rated the new monitoring modalities and opportunity to discuss health and well-being, in confidence, with a doctor conversant in dance.

Summary boxesO_ST_ABSWhat are the new findings?C_ST_ABSO_LIMonitoring professional dancers with a variety of interactive methods: dance specific questionnaire; online tracking of menstrual cycle for female dancers; wellbeing and training load; blood testing and personal online meetings - facilitates comprehensive, personalised support for dancer health.
C_LIO_LIOverall, the dancer participants were healthy both physically and mentally. This was demonstrated by the positive scores derived from the dancer health questionnaire. The healthy status of the majority of the dancers was confirmed with online health tracking and objective blood test results.
C_LIO_LIAll results were discussed individually with dancers remotely and where any issues were found from questionnaires, online health tracking or blood tests, timely appropriate tailored recommendations were made.
C_LIO_LIAlthough not the original design, the timing of the study during the COVID-19 pandemic provided insights into the impact of this unprecedented time on dancers. The study showed that easy virtual access to clinical medical support was helpful.
C_LIO_LIDancers and healthcare staff highly rated this initiative of multimodal, personalised monitoring and access to rapid virtual clinical discussion.
C_LI

How might this study impact on clinical practice in the future?O_LIProactive, interactive monitoring of dancer health and wellbeing facilitates personalised, preventative support. It is far better to be proactive in preventing future illness or injury than to deal with issues after they have happened.
C_LIO_LIPersonalised medical input is important for optimising health and performance and prevention, not just for outcomes injury or illness.
C_LIO_LIThe dancer health questionnaire could be used for all new dancers entering a dance school or company, to identify any areas where individual dancers might benefit more specific input. For example, to identify any early warning signs of low energy availability in both male and female dancers. In all cases, the objective would be to offer prompt targeted support. The health questionnaire could then be completed annually to act as a monitoring system.
C_LIO_LIComprehensive online monitoring of wellbeing, training load and menstrual cycle for female dancers, is a valuable clinical tool for dancers. Combined with access to individual virtual discussion, this provision is highly rated by dancers and healthcare staff.
C_LIO_LIRegular blood testing for dancers provides objective measures of health. This allows early identification of any deficiencies or dysfunction and facilitates prompt advice on appropriate practical measures. This testing can also act as an objective monitoring tool for individual dancers which could be combined with artificial intelligence techniques further personalisation.
C_LIO_LIOpen access for all dancers to discuss clinical issues with virtual discussions to facilitate ease of access at short notice and on return to performing and touring, which is highly valued by dancers.
C_LIO_LIProvision of educational information about relative energy deficiency in sport (RED-S) such as British Association Sport and Exercise Medicine website www.health4performance.co.uk can help the dance community be aware of low energy availability
C_LI

category: sports medicine


title: Prenatal phenotype of PNKP-related primary microcephaly associated with variants in the FHA and Phosphatase domain

abstract:
Biallelic PNKP variants cause heterogeneous disorders ranging from neurodevelopmental disorder with microcephaly/seizures to adult-onset Charcot-Marie-Tooth disease. To date, only postnatal descriptions exist.

We present the first prenatal diagnosis of PNKP-related primary microcephaly. Detailed pathological examination of a male fetus revealed micrencephaly with extracerebral malformations and thus presumed syndromic microcephaly. A recessive disorder was suspected because of previous pregnancy termination for similar abnormalities in a sibling fetus. Prenatal trio exome sequencing identified compound-heterozygosity for the PNKP variants c.498G>A, p.[(=),0?] and c.302C>T, p.(Pro101Leu). Segregation confirmed both variants in the sibling fetus. Through RNA analyses, we characterized skipping of exon 4 affecting the PNKP Forkhead-associated (FHA) and Phosphatase domains (p.Leu67_Lys166del) as the predominant effect of the c.498G>A variant. We retrospectively investigated two unrelated individuals diagnosed with biallelic PNKP-variants to compare prenatal/postnatal phenotypes. Both carry the same splice-donor variant c.1029+2T>C in trans with a variant in the FHA domain (c.311T>C, p.(Leu104Pro) and c.151G>C, p.(Val51Leu), respectively). RNA-seq showed complex splicing events for c.1029+2T>C and c.151G>C. Computational modelling and structural analysis revealed significant clustering of missense variants in the FHA domain, with some variants potentially generating structural damage.

Our detailed clinical description extends the PNKP-continuum to the prenatal stage. Investigating possible PNKP-variant effects using RNA and structural modelling, we highlight the mutational complexity and exemplify a framework for variant characterization in this multi-domain protein.

category: genetic and genomic medicine


title: Systems Leadership: how Chief Executives manage tension between organisation and system pressures

abstract:
AimSystem leadership is the requirement for a leader of a single organisation to operate on behalf of a wider system, rather than their individual organisation. It is not clear to what extent the current policy landscape supports leaders in managing misalignment between the needs of their organisation and the wider system, as many national structures still emphasise a focus on individual organisations. This study aims to understand how Chief Executives implement system leadership in practice when faced with decisions that benefit the system to the detriment of their own trust.

MethodologySemi-structured interviews were conducted with ten Chief Executives from a range of trust types to understand their perceptions and decision-making process in practice. Semantic thematic analysis was used to draw out themes in relation to how Chief Executives approach decisions which weigh up the system and organisation.

ResultsThemes raised by interviewees included both advantages (such as support in managing demand) and disadvantages (such as increased bureaucracy) of system leadership and practical considerations in operationalisation (such as the importance of interpersonal relationships). Interviewees endorsed system leadership in principle, but did not feel that the organisational incentives as currently structured support the implementation of system leadership in practice. This was not seen as a major challenge or impediment to effective leadership.

ConclusionAs a specific policy area, a direct focus on systems leadership is not necessarily helpful. Chief Executives should be supported to make decisions in a complex environment, without a specific focus on healthcare systems as a unit of operation.

category: health policy


title: Pre-pandemic SARS-CoV-2 serological reactivity in rural malaria-experienced Cambodians

abstract:
Greater Mekong inhabitants are exposed to pathogens, zoonotic and otherwise, that may influence SARS-CoV-2 seroreactivity. A pre-pandemic (2005 to 2011) serosurvey of from 528 malaria-experienced Cambodians demonstrated higher-than-expected (up to 13.8 %) positivity of non-neutralizing IgG to SARS-CoV-2 spike and RBD antigens. These findings have implications for interpreting large-scale serosurveys.

Article Summary LineIn the pre-COVID19 pandemic years of 2005 to 2011, malaria experienced Cambodians from rural settings had higher-than-expected seroreactivity to SARS-CoV-2 spike and receptor binding domain proteins.

category: infectious diseases


title: Changes in dispensing of medicines proposed for re-purposing in the first year of the COVID-19 pandemic in Australia

abstract:
ObjectiveWe quantified changes in dispensing of common medicines proposed for "re-purposing" due to their perceived benefits as therapeutic or preventive for COVID-19 in Australia, a country with relatively low COVID-19 incidence in the first year of the pandemic.

MethodsWe performed an interrupted time series analysis and cross-sectional study using nationwide dispensing claims data (January 2017-November 2020). We focused on six subsidised medicines proposed for re-purposing: hydroxychloroquine, azithromycin, ivermectin, colchicine, corticosteroids, and calcitriol (Vitamin D analogue). We quantified changes in monthly dispensing and initiation trends during COVID-19 (March-November 2020) using autoregressive integrated moving average models (ARIMA) and compared characteristics of initiators in 2020 and 2019.

ResultsIn March 2020, we observed a 99% (95%CI 96%-103%) increase in hydroxychloroquine dispensing (of which approximately 22% attributable to new use), and a 199% increase (95%CI 184%-213%) in initiation, with a shift towards prescribing by general practitioners (42% in 2020 vs 25% in 2019) rather than specialists. These increases subsided following regulatory restrictions on prescribing to relevant specialties. There was a small but sustained increase in ivermectin dispensing over multiple months, with a 80% (95%CI 42%-118%) increase in initiation in May 2020 following its first identification as potentially disease-modifying in April. Other than increases in March related to stockpiling, we observed no increases in initiation of calcitriol or colchicine during COVID-19. Dispensing of corticosteroids and azithromycin remained lower than expected in April through November 2020.

ConclusionsWhile most increases in dispensing observed early on during COVID-19 were temporary and appear to be related to stockpiling among existing users, we did observed increases in initiation of hydroxychloroquine and ivermectin and a shift in prescribing patterns which may be related to media hype around these medicines. A quick response by regulators can help limit inappropriate repurposing to lessen the impact on medicine supply and patient harms.


title: In COVID-19, NLRP3 inflammasome genetic variants are associated with critical disease and these effects are partly mediated by the sickness symptom complex: a nomothetic network approach.

abstract:
BackgroundIn COVID-19, the NLRP3 inflammasome is activated in response to SARS-CoV-2 infection. Acute infections are accompanied by a sickness symptom complex (SSC) which is a highly conserved symptom complex that protects against infections and hyperinflammation. Aims: To examine the associations of COVID-19, SSC and the NLPR3 rs10157379 T>C and NLPR3 rs10754558 C>G SNV variants; and the protective role of SSC in severe acute respiratory syndrome (SARS)-CoV-2 infection.

MethodsWe recruited COVID-19 patients, 308 with critical, 63 with moderate and 157 with mild disease.

ResultsIncreased SSC protects against SARS, critical disease, and death due to COVID-19. Increasing age, male sex and rs10754558 CG significantly predict reduced SSC protection. The rs10157379 CT and rs10754558 GG genotypes are positively associated with SARS. Partial Least Squares analysis shows a) that 41.8% of the variance in critical COVID-19 symptoms could be explained by SSC and oxygen saturation (inversely associated), and inflammation, chest computed tomography abnormalities, increased body mass index, SARS and age (positively associated); and b) the effects of the NLRP3 rs10157379 and rs10754558 variants on critical COVID-19 are mediated via SSC (protective) and SARS (detrimental). SSC includes anosmia, dysgeusia and gastrointestinal symptoms.

ConclusionsIntersections among the rs10754558 variant, age, and sex increase risk towards critical COVID-19 by attenuating SSC. NLRP3 variants play an important role in SARS, and severe and critical COVID-19 especially in individuals with reduced SSC, elderly people, and those with increased BMI, hypertension, and diabetes type 2. SSC is a new drug target to combat acute COVID-19.

category: allergy and immunology


title: Depression, anxiety, and chronic fatigue symptoms in acute rheumatoid arthritis are associated with immune-inflammatory, autoimmune, endogenous opioid system and lactosylceramide signaling pathways: a nomothetic network approach.

abstract:
BackgroundRheumatoid arthritis (RA) is a chronic inflammatory and autoimmune disorder which affects the joints in the wrists, fingers, and knees. RA is often associated with depressive and anxiety symptoms as well as chronic fatigue syndrome (CFS)-like symptoms.

AimTo examine the association between depressive symptoms (measured with the Beck Depression Inventory, BDI), anxiety (Hamilton Anxiety Rating Scale, HAMA), and CFS-like (Fibro-fatigue Scale) symptoms and immune-inflammatory, autoimmune, and endogenous opioid system (EOS) markers, and lactosylceramide in RA.

MethodsSerum biomarkers were assayed in RA patients with (n=59) and without (n=59) increased psychopathology (PP) and 50 healthy controls.

ResultsThere were highly significant correlations between the BDI, FF, and HAMA scores and severity of RA, as assessed with the DAS28-4, clinical and disease activity indices, the number of tenders and swollen joints, and patient and evaluator global assessment scores. A common latent vector (reflective model) could be extracted from the PP and RA-severity scales, which showed excellent psychometric properties. Partial least squares analysis showed that 69.7% of the variance in this common core underpinning PP and RA symptoms could be explained by the regression on immune-inflammatory pathways, rheumatoid factor and anti-citrullinated protein antibodies, CD17, and mu-opioid receptor levels.

ConclusionsDepression, anxiety, and CFS-like symptoms due to RA are reflective manifestations of the phenome of RA and are mediated via the effects of the same immune-inflammatory, autoimmune, and EOS pathways and lactosylceramide that underpin the pathophysiology of RA. These PP symptoms are clinical manifestations of the pathophysiology of RA.

category: rheumatology


title: AnFiSA: An open-source computational platform for the analysis of sequencing data for rare genetic disease

abstract:
Despite genomic sequencing rapidly transforming from being a bench-side tool to a routine procedure in a hospital, there is a noticeable lack of genomic analysis software that supports both clinical and research workflows as well as crowdsourcing. Furthermore, most existing software packages are not forward-compatible in regards to supporting ever-changing diagnostic rules adopted by the genetics community. Regular updates of genomics databases pose challenges for reproducible and traceable automated genetic diagnostics tools. Lastly, most of the software tools score low on explainability amongst clinicians.

We have created a fully open-source variant curation tool, AnFiSA, with the intention to invite and accept contributions from clinicians, researchers and professional software developers. The design of AnFiSA addresses the aforementioned issues via the following architectural principles: using a multidimensional database management system (DBMS) for genomic data to address reproducibility, curated decision trees adaptable to changing clinical rules, and a crowdsourcing-friendly interface to address difficult-to-diagnose cases. We discuss how we have chosen our technology stack and describe the design and implementation of the software. Finally, we show in detail how selected workflows can be implemented using the current version of AnFiSA by a medical geneticist.

All software is available at https://github.com/ForomePlatform under the Apache 2.0 license.

The public demo instance with the public data sets can be accessed via https://github.com/ForomePlatform/AnFiSA#public-demo


title: Implementation, interrupted: Identifying and leveraging factors that sustain after a program interruption

abstract:
BackgroundMany implementation efforts experience interruptions, especially in settings with developing health systems. Approaches for evaluating interruptions are needed to inform targeted re-implementation strategies.

MethodsThis study took place in two public health centers with tuberculosis (TB) units in Uganda that previously implemented diabetes mellitus (DM) screening in 2017. In 2019, we conducted interviews with clinic staff to determine current DM practices. We mapped themes identified in the interviews to a Social Ecological Model with three levels: outer setting, inner setting, and individuals.

ResultsWe conducted nine interviews with clinic staff. Respondents explained that DM screening ceased due to disruptions in the supply chain for glucose test strips. This outer setting interruption had cascading effects on the inner setting and individuals. The lack of screening supplies limited the staffs opportunities to perform DM screening within the inner setting level, which was associated with diminished self-efficacy within the individual level. However, culture, compatibility and individual beliefs about DM screening sustained throughout the interruption.

ConclusionsWe identified factors that diminished and sustained within and between ecological levels during a program interruption. Using this approach, other programs facing interruptions can identify factors and cascading effects of the interruption to target them for re-implementation.


title: Expansion of 5' UTR CGG repeat in RILPL1 is associated with oculopharyngodistal myopathy

abstract: Oculopharyngodistal myopathy is an adult-onset degenerative muscle disorder characterized by ptosis, ophthalmoplegia and weakness of the facial, pharyngeal and limb muscles. Trinucleotide repeat expansions in non-coding regions of LRP12, G1PC1and NOTCH2NLC were recently reported to be the etiologies for OPDM. However, a significant portion of OPDM patients still have unknown genetic causes. In this study, we performed long-read whole-genome sequencing in a large five-generation family of 156 individuals, including 22 patients diagnosed with typical OPDM and identified CGG repeat expansions in RILPL1 gene in all patients we tested while not in unaffected family members. Methylation analysis indicated that methylation levels of the RILPL1 gene were unaltered in OPDM patients, which was in consistent with previous reports. Our findings first provided evidences that RILPL1 were associated OPDM which we suggested as OPDM type 4.

category: neurology


title: Detecting a History of Repetitive Head Impacts from a Short Voice Recording

abstract: Repetitive head impacts (RHI) are associated with an increased risk of developing various neurodegenerative disorders, such as Alzheimers disease (AD), Parkinsons disease (PD), and most notably, chronic traumatic encephalopathy (CTE). While the clinical presentation of AD and PD is well established, CTE can only be diagnosed post-mortem. Therefore, a distinction can be made between the pathologically defined CTE and RHI-related functional or structural brain changes (RHI-BC) which may result in CTE. Unfortunately, there are currently no accepted biomarkers of CTE nor RHI-BC, a major hurdle to achieving clinical diagnoses. Interestingly, speech has shown promise as a potential biomarker of both AD and PD, being used to accurately classify individuals with AD and PD from those without. Given the overlapping symptoms between CTE, RHI-BC, PD and AD, we aimed to determine if speech could be used to identify individuals with a history of RHI from those without. We therefore created the Verus dataset, consisting of 13 second voice recordings from 605 professional fighters (RHI group) and 605 professional athletes in non-contact sports (control group) for a total of 1210 recordings. Using a deep learning approach, we achieved 85% accuracy in detecting individuals with a history of RHI from those without. We then used our model trained on the Verus dataset to fine-tune on publicly available AD and PD speech datasets and achieved new state-of-the-art accuracies of 84.99% on the AD dataset and 89% on the PD dataset. Finding a biomarker of CTE and RHI-BC that presents early in disease progression is critical to improve risk management and patient outcome. Our study is the first we are aware of to investigate speech as such a candidate biomarker of RHI-BC.


title: Methods for Estimation of SARS-CoV-2 Seroprevalence and Reported COVID-19 Cases in U.S. Children, August 2020 - May 2021

abstract:
Background and ObjectivesCase-based surveillance of pediatric COVID-19 cases underestimates the prevalence of SARS-CoV-2 infections among children and adolescents. Our objectives were to: 1) estimate monthly SARS-CoV-2 antibody seroprevalence among children aged 0-17 years and 2) calculate ratios of SARS-CoV-2 infections to reported COVID-19 cases among children and adolescents in 14 U.S. states.

MethodsUsing data from commercial laboratory seroprevalence surveys, we estimated monthly SARS-CoV-2 antibody seroprevalence among children aged 0-17 years from August 2020 through May 2021. Seroprevalence estimates were based on SARS-CoV-2 anti-nucleocapsid immunoassays from February to May 2021. We compared estimated numbers of children infected with SARS-CoV-2 by May 2021 to cumulative incidence of confirmed and probable COVID-19 cases from case-based surveillance, and calculated infection: case ratios by state and type of anti-SARS-CoV-2 nucleocapsid immunoassay used for seroprevalence testing.

ResultsAnalyses included 67,321 serum specimens tested for SARS-CoV-2 antibodies among children in 14 U.S. states. Estimated ratios of SARS-CoV-2 infections to reported confirmed and probable COVID-19 cases among children and adolescents varied by state and type of immunoassay, ranging from 0.8-13.3 in May 2021.

ConclusionsThrough May 2021, the majority of children in selected states did not have detectable SARS-CoV-2 nucleocapsid antibodies. Case-based surveillance underestimated the number of children infected with SARS-CoV-2, however the predicted extent of the underestimate varied by state, immunoassay, and over time. Continued monitoring of pediatric SARS-CoV-2 antibody seroprevalence should inform prevention and vaccination strategies.

category: pediatrics


title: Usual Source of Primary Care and Preventive Care Measures in a Pandemic: A Nationwide Study in Japan

abstract:
ObjectivesIn a pandemic when there are many barriers to providing preventive care by health care workers, it is unclear whether primary care contributes to the quality of preventive care and what type of preventive care delivery is a challenge for primary care providers. This study aimed to assess multiple preventive care measures and to examine their associations with having a usual source of primary care and primary care performance during the COVID-19 pandemic in Japan.

DesignNationwide cross-sectional study.

SettingJapanese general adult population.

Participants1,757 adult residents.

Primary outcome measuresFourteen preventive care measures aggregated the overall, screening, immunization, and counseling composites.

ResultsDepression screening, zoster vaccination, and tetanus vaccination had low implementation rates even among participants with a usual source of primary care. After adjustment for possible confounders, having a usual source of primary care was positively associated with all preventive care composites. Primary care performance assessed by the Japanese version of Primary Care Assessment Tool Short Form was also dose-dependently associated with an increase in all composites. Results of the sensitivity analyses using a different calculation of preventive care composite were similar to those of the primary analyses.

ConclusionsReceipt of primary care, particularly high-quality primary care, contributed to increased preventive care utilization even during the COVID-19 pandemic. However, the rate of mental health screening in primary care was at a very low level. Therefore, addressing mental health issues should be a major challenge for primary care providers during and after the pandemic.

category: primary care research


title: Combination between Mifepristone and Methotrexate to Treat Ectopic Pregnancy: A Systematic Review Protocol

abstract:
AimThe increase in ectopic pregnancies (EP) in recent years and their impact on female fertility forces physicians to find an effective medical treatment that can avoid surgery as soon as possible. Methotrexate and mifepristone are widely used in conservative treatments, but the effectiveness of this combination is not completely clear. Therefore, the aims in this meta-analysis are to systematically analyze the efficacy of mifepristone combined with methotrexate in the treatment of EP through existing studies and draw a conclusion, to evaluate the advantages and disadvantages of inclusion trials and propose improvement measures and scientific designing schemes.

MethodsSix databases will be searched, including PubMed, Embase, Cochrane Library, the China National Knowledge Infrastructure(CNKI), Chinese Science and Technology Periodical Database (VIP), and Wanfang Database (WF). Randomized controlled trials published up to October 2020 will be selected. Search terms include mifepristone, methotrexate, EP, and random (free word/synonym expansion). We will include trials in which the experimental group was treated with combination of mifepristone and methotrexate, and the control group was treated with mifepristone alone. Revman 5.4 will be used to evaluate the quality of the trials, and the effect model will be selected to analyze the results. Cure rate will be the main outcome index.

ResultOnly when we finish this meta analysis can we get the result.

DiscussionThe results of this study will provide evidence for the efficacy of mifepristone combined with methotrexate therapy in the treatment of EP. The site of onset of pregnancy should be taken into account.

PROSPERO registration numberCRD42021246757

category: obstetrics and gynecology


title: Combination of Mifepristone and Methotrexate for the Treatment of Ectopic Pregnancy: A Systematic Review Protocol


title: Population-scale analysis of common and rare genetic variation associated with hearing loss in adults

abstract: Understanding the genetic underpinnings of disabling hearing loss, which affects [~]466 million people worldwide, can provide avenues for new therapeutic target development. We performed a genome-wide association meta-analysis of hearing loss with 125,749 cases and 469,497 controls across five cohorts, including UK Biobank, Geisinger DiscovEHR, the Malmo Diet and Cancer Study, Mount Sinais BioMe Personalized Medicine Cohort, and FinnGen. We identified 53 loci affecting hearing loss risk, 15 of which are novel, including common coding variants in COL9A3 and TMPRSS3. Through exome-sequencing of 108,415 cases and 329,581 controls from the same cohorts, we identified hearing loss associations with burden of rare coding variants in FSCN2 (odds ratio [OR] = 1.14, P = 1.9 x 10-15) and burden of predicted loss-of-function variants in KLHDC7B (OR = 2.14, P = 5.2 x 10-30). We also observed single-variant and gene-burden associations with 11 genes known to cause Mendelian forms of hearing loss, including an increased risk in heterozygous carriers of mutations in the autosomal recessive hearing loss genes GJB2 (Gly12fs; OR = 1.21, P = 4.2 x 10-11) and SLC26A5 (gene burden; OR = 1.96, P = 2.8 x 10-17). Our results suggest that loss of KLHDC7B function increases risk for hearing loss, and show that Mendelian hearing loss genes contribute to the burden of hearing loss in the adult population, suggesting a shared etiology between common and rare forms of hearing loss. This work illustrates the potential of large-scale exome sequencing to elucidate the genetic architecture of common traits in which risk is modulated by both common and rare variation.


title: Metric selection and promotional language in health artificial intelligence

abstract:
BackgroundRecent advances in Artificial intelligence (AI) have the potential to substantially improve healthcare across clinical areas. However, there are concerns health AI research may overstate the utility of newly developed systems and that certain metrics for measuring AI system performance may lead to an overly optimistic interpretation of research results. The current study aims to evaluate the relationship between researcher choice of AI performance metric and promotional language use in published abstracts.

Methods and findingsThis cross-sectional study evaluated the relationship between promotional language and use of composite performance metrics (AUC or F1). A total of 1200 randomly sampled health AI abstracts drawn from PubMed were evaluated for metric selection and promotional language rates. Promotional language evaluation was accomplished through the development of a customized machine learning system that identifies promotional claims in abstracts describing the results of health AI system development. The language classification system was trained with an annotated dataset of 922 sentences. Collected sentences were annotated by two raters for evidence of promotional language. The annotators achieved 94.5% agreement ({kappa} = 0.825). Several candidate models were evaluated and, the bagged classification and regression tree (CART) achieved the highest performance at Precision = 0.92 and Recall = 0.89. The final model was used to classify individual sentences in a sample of 1200 abstracts, and a quasi-Poisson framework was used to assess the relationship between metric selection and promotional language rates. The results indicate that use of AUC predicts a 12% increase (95% CI: 5-19%, p = 0.00104) in abstract promotional language rates and that use of F1 predicts a 16% increase (95% CI: 4% to 30%, p = 0. 00996).

ConclusionsClinical trials evaluating spin, hype, or overstatement have found that the observed magnitude of increase is sufficient to induce misinterpretation of findings in researchers and clinicians. These results suggest that efforts to address hype in health AI need to attend to both underlying research methods and language choice.

category: health informatics


title: Overall vertical transmission of hepatitis C, transmission net of clearance, and timing of transmission.

abstract:
BackgroundIt is widely accepted that the risk of HCV vertical transmission (VT) is 5-6% in mono-infected women, and that 25-40% of HCV infection clears spontaneously within 5 years. However, VT and clearance rates have not been estimated from the same datasets, and there is a lack of information on VT rates "net" of clearance.

MethodsWe re-analysed data on 1749 children in 3 prospective cohorts to obtain coherent estimates of overall VT rate and VT rates "net" of clearance at different ages. Clearance rates were used to impute the proportion of uninfected children who had been infected and then cleared before testing negative. The proportion of transmission early in utero, late in utero and at delivery was estimated from data on the proportion of RNA positives in samples tested within three days of birth, and differences between elective caesarean and non-elective caesarean deliveries.

FindingsOverall VT rates were 7.2% (95% credible interval 5.6-8.9) in mothers who were HIV negative and 12.1% (8.6-16.8) in HIV-co-infected women. The corresponding rates net of clearance at 5 years were 2.4% (1.1-4.1) and 4.1% (1.7-7.3). We estimated that 24.8% (12.1-40.8) of infections occur early in utero, 66.0% (42.5-83.3) later in utero, and 9.3% (0.5-30.6) during delivery.

ConclusionOverall VT rates are about 24% higher than previously assumed, but the risk of infection persisting beyond age 5 years is about 38% lower. The results can inform design of trials of to prevent or treat pediatric HCV infection, and strategies to manage children exposed in utero.

Key pointsTaking account of infections that would have cleared spontaneously before detection, the rate of HCV vertical transmission is 7.2% (95%CrI 5.6-8.9) in mono-infected women, but transmission "net" of clearance is 3.1% (1.8-4.4) at 3 years, and 2.4% (1.1-4.1) at 5.


title: Secondary infections modify the overall course of hospitalized COVID-19 patients: A retrospective study from a network of hospitals across North India

abstract:
IntroductionSARS-CoV-2 infection increases the risk of secondary bacterial and fungal infections and contributes to adverse outcomes. The present study was undertaken to get better insights into the extent of secondary bacterial and fungal infections in Indian hospitalized patients and to assess how these alter the course of COVID-19 so that the control measures can be suggested.

MethodsThis is a retrospective, multicentre study where data of all RT-PCR positive COVID-19 patients was accessed from Electronic Health Records (EHR) of a network of 10 hospitals across 5 North Indian states, admitted during the period from March 2020 to July 2021.The data included demographic profile of patients, clinical characteristics, laboratory parameters, treatment modalities, and outcome in those with secondary infections (SIs) and those without SIs. Spectrum of SIS was also studied in detail.

ResultsOf 19852 RT-PCR positive SARS-CO2 patients admitted during the study period, 1940 (9.8%) patients developed SIs. Patients with SIs were 8 years older on average (median age 62.6 years versus 54.3 years; P<0.001) than those without SIs. The risk of SIs was significantly (p < 0.001) associated with age, severity of disease at admission, diabetes, ICU admission, and ventilator use.

The most common site of infection was urinary tract infection (UTI) (41.7%), followed by blood stream infection (BSI) (30.8%), sputum/BAL/ET fluid (24.8%), and the least was pus/wound discharge (2.6%). As many as 13.4% had infections with more than organism and 34.1% patients had positive cultures from more than one site. Gram negative bacilli (GNB) were the commonest organisms (63.2%), followed by Gram positive cocci (GPC) (19.6%) and fungus (17.3%). Most of the patients with SIs were on multiple antimicrobials - the most commonly used were the BL-BLI for GNBs (76.9%) followed by carbapenems (57.7%), cephalosporins (53.9%) and antibiotics carbapenem resistant entreobacteriace (47.1%). The usage of emperical antibiotics for GPCs was in 58.9% and of antifungals in 56.9% of cases, and substantially more than the results obtained by culture.

The average stay in hospital for patients with SIs was twice than those without SIs (median 13 days versus 7 days). The overall mortality in the group with SIs (40.3%) was more than 8 times of that in those without SIs (4.6%). Only 1.2% of SI patients with mild COVID-19 at presentation died, while 17.5% of those with moderate disease and 58.5% of those with severe COVID-19 died (P< 0.001). The mortality was highest in those with BSI (49.8%), closely followed by those with HAP (47.9%), and then UTI and SSTI (29.4% each). The mortality rate where only one microorganism was identified was 37.8% and rose to 56.3% in those with more than one microorganism. The mortality in cases with only one site of infection was 28.8%, which steeply rose to 62.5% in cases with multiple sites of infection. The mortality in diabetic patients with SIs was 45.2% while in non-diabetics it was 34.3% (p < 0.001).

ConclusionsSecondary bacterial and fungal infections can complicate the course of almost 10% of COVID-19 hospitalised patients. These patients tend to not only have a much longer stay in hospital, but also a higher requirement for oxygen and ICU care. The mortality in this group rises steeply by as much as 8 times. The group most vulnerable to this complication are those with more severe COVID-19 illness, elderly, and diabetic patients. Varying results in different studies suggest that a region or country specific guideline be developed for appropriate use of antibiotics and antifungals to prevent their overuse in such cases. Judicious empiric use of combination antimicrobials in this set of vulnerable COVID-19 patients can save lives.


title: A Machine Learning Approach to Predict 5-year Risk for Complications in Type 1 Diabetes

abstract:
BackgroundIndividuals with long standing diabetes duration can experience damage to small microvascular blood vessels leading to diabetes complications (DCs) and increased mortality. Precision diagnostic tailors a diagnosis to an individual by using biomedical information. Blood small molecule profiling coupled with machine learning (ML) can facilitate the goals of precision diagnostics, including earlier diagnosis and individualized risk scoring.

MethodsUsing data in a cohort of 537 adults with type 1 diabetes (T1D) we predicted five-year progression to DCs. Prediction models were computed first with clinical risk factors at baseline and then with clinical risk factors and blood-derived molecular data at baseline. Progression of diabetic kidney disease and diabetic retinopathy were predicted in two complication-specific models.

FindingsThe model predicts the progression to diabetic kidney disease with accuracy: 0.96{+/-}0.25 and 0.96{+/-}0.06 area under curve, AUC, with clinical measurements and with small molecule predictors respectively and highlighted main predictors to be albuminuria, glomerular filtration rate, retinopathy status at baseline, sugar derivatives and ketones. For diabetic retinopathy, AUC 0.75{+/-}0.14 and 0.79{+/-}0.16 with clinical measurements and with small molecule predictors respectively and highlighted key predictors, albuminuria, glomerular filtration rate and retinopathy status at baseline. Individual risk scores were built to visualize results.

InterpretationWith further validation ML tools could facilitate the implementation of precision diagnosis in the clinic. It is envisaged that patients could be screened for complications, before these occur, thus preserving healthy life-years for persons with diabetes.

FundingThis study has been financially supported by Novo Nordisk Foundation grant NNF14OC0013659.

Research in context

Evidence before this studyMicrovascular diabetes complications (DCs), such as diabetic kidney disease (DKD) and diabetic retinopathy (DR), lead to increased mortality, blindness, kidney failure and overall decreased quality of life in individuals with diabetes.

Added value of this studyWe have developed four algorithms based on traditional risk factors alone and risk factors with metabolomic and lipidomic data. Two accurately predicted the future progression in individuals with type 1 diabetes. The top predictors chosen by the algorithm were hemoglobin A1c, albuminuria and retinopathy status at baseline for diabetic retinopathy. The most promising models predicted future diabetic kidney disease in which albuminuria, eGFR, retinopathy status at baseline were complemented with a number of ketones and sugar derivatives.

Implications of all the available evidenceWith further validation in several cohorts, the prediction models presented here have the potential for early diagnosis of CKD in persons with diabetes, thus enabling appropriate decisions on the available therapies. It is envisaged that these algorithms will be trialed and support clinicians with precision diagnosis and treatments.

category: endocrinology


title: Precision Diagnostic Approach to Predict 5-Year Risk for Microvascular Complications in Type 1 Diabetes


title: Nucleobindin-2 (NUCB2) gene transcription activity and nesfatin-1 levels in correlation with anthropometric and biochemical parameters in type 2 diabetes mellitus patient groups in Vietnam

abstract:
IntroductionNucleobindin-2 (NUCB2) was identified as a DNA/Ca2+ binding protein with multiple functions in humans. Prohormone convertase-mediated NUCB2 processing produced nesfatin-1 - a biologically active. Nesfatin-1, an 82-amino acid peptide, was extracted from the N-terminus of nucleobindin-2. Recently, it was described as an anorexia peptide related to weight loss, malnutrition, and appetite regulation in type 2 diabetes mellitus patients.

Research design and methodsIn this study, we collected samples and divided them into groups of patients with long-term type 2 diabetes and newly diagnosed type 2 diabetes group. Serum nesfatin-1 level and mRNA NUCB2 gene expression level of the groups were analyzed and compared with those of the healthy group.Biometric parameters and biochemical indices were also analyzed to determine the correlation with nesfatin-1 level.

ResultsLevels of nesfatin-1 were found to be higher in the newly diagnosed group than in the other groups. Similar results were also reported in the analysis of mRNA NUCB2 gene expression by Realtime-PCR. Meanwhile, no significant difference was found in both analyzes of nesfatin-1 levels and NUCB2 mRNA expression in subjects with long-term type 2 diabetes compared with the control group. This result can be explained by the effects of long-term treatment. In the correlation of anthropometric parameters and biochemical indices, nesfatin-1 exhibited a significant correlation with BMI (r=0.569), HbA1c (r=-0.468), HDL-C (r=0.731), LDL-C (r=-0.482), Creatinine serum (r=0.525), and Creatinine urine (r=0.592), with p<0.001, in regression analysis.

ConclusionsThese results indicate that the serum nesfatin-1 level and the NUCB2 mRNA gene expression level may be associated with newly diagnosed type 2 diabetes in Vietnamese patients. However, more specific studies with larger sample sizes were still needed in future studies.


title: Is there an association between daytime napping and cognitive function? A Mendelian randomisation study in the UK Biobank

abstract:
Daytime napping has been associated with cognitive function and brain health in observational studies. However, it remains elusive whether these associations are causal. Using Mendelian randomisation (MR), we studied the relationship between habitual daytime napping and cognitive/structural brain outcomes. Data were from UK Biobank (UKB) (maximum n= 378 932; mean age= 57 years). Our exposure (daytime napping) was instrumented using 92 previously identified genome-wide, independent genetic variants (single-nucleotide polymorphisms, SNPs). Our cognitive outcomes were reaction time and visual memory; our neuroimaging outcomes were total brain volume and hippocampal volume (cm3). Inverse-variance weighted (IVW) MR was implemented, with sensitivity analyses including MR-Egger and the Weighted Median Estimator for horizontal pleiotropy. We also tested different daytime napping instruments (47 SNPs, 86 SNPs and 17 SNPs) to ensure the robustness of our results. Our main MR analysis (IVW) showed an association between genetic liability to habitual daytime napping and larger total brain volume (unstandardised {beta}=15.80 cm3, 95% confidence interval (CI)=0.25; 31.34), but not hippocampal volume ({beta}=-0.03 cm3, 95%CI=-0.13; 0.06). No associations were found between daytime napping and reaction time (exp{beta}=1.01, 95%CI=1.00; 1.03), or visual memory (exp{beta}=0.99, 95%CI=0.94; 1.05). Additional analyses with 47 SNPs (adjusted for excessive daytime sleepiness), 86 SNPs (excluding sleep apnoea) and 17 SNPs (no sample overlap with UKB) were largely consistent with our main findings. MR-Egger and Weighted Median Estimator approaches showed no evidence of horizontal pleiotropy. Overall, we observed evidence of an association between genetically-instrumented daytime napping and larger total brain volume, but no evidence of an association between habitual daytime napping and hippocampal volume, reaction time or visual memory. Future studies could focus on the associations between napping and other cognitive/brain outcomes, as well as replication of these findings using other datasets and methods.

Key MessagesO_LIDaytime napping has been linked with cognitive function and brain health in observational studies, but whether these links are causal remains elusive.
C_LIO_LIUsing Mendelian randomisation, we investigated the potential causal role of habitual daytime napping on cognitive and neuroimaging outcomes.
C_LIO_LIWe observed evidence of a modest causal association between habitual daytime napping and larger total brain volume, but not enough evidence to support associations with hippocampal volume, reaction time or visual memory.
C_LI


title: Is there an association between daytime napping, cognitive function and brain volume? A Mendelian randomisation study in the UK Biobank


title: Transmission clusters, predominantly associated with men who have sex with men, play a main role in the propagation of HIV-1 in Northern Spain (2013-2018)

abstract: Viruses of HIV-1-infected individuals whose transmission is related group phylogenetically in transmission clusters (TCs). The study of the phylogenetic relations of these viruses and the factors associated with these individuals is essential to analyze the HIV-1 epidemic. In this study, we examine the role of TCs in the epidemiology of HIV-1 infection in Galicia and the Basque County, two regions of Northern Spain. A total of 1158 newly HIV-1-diagnosed patients (NDs) from both regions diagnosed in 2013-2018 were included in the study. Partial HIV-1 pol sequences were analyzed phylogenetically by approximately-maximum-likelihood with FastTree 2. In this analysis, 10,687 additional sequences from samples from HIV-1-infected individuals collected in Spain in 1999-2019 were also included to assign and determine the TCs sizes. TCs were defined as those which included viruses from [≥]4 individuals, at least 50% of them Spaniards, and with [≥]0.95 Shimodaira-Hasegawa-like node support in the phylogenetic tree. Factors associated to TCs were evaluated using odds ratios (OR) and their 95% confidence intervals (CI). Fifty one percent of NDs grouped in 162 TCs. Male patients (OR: 2.6; 95% CI: 1.5-4.7) and men having sex with men (MSM) (OR: 2.1; 95% CI: 1.4-3.2) had higher odds of belonging to a TC compared to female and heterosexual patients, respectively. Individuals from Latin America (OR: 0.3; 95% CI: 0.2-0.4), North Africa (OR: 0.4; 95% CI: 0.2-1.0), and especially Sub-Saharan Africa (OR: 0.02; 95% CI: 0.003-0.2) were inversely associated to belonging to TCs compared to native Spaniards. Differences in distribution and sizes of local TCs were observed in both regions reflecting a different epidemic pattern. Our results show that TCs play an important role in the spread of HIV-1 infection in the two Spanish regions studied, where transmission between MSM is predominant. The majority of migrants were infected with viruses not belonging to TCs that expand in Spain. Molecular epidemiology is essential to identify local peculiarities of HIV-1 propagation. The early detection of TCs and prevention of their expansion, implementing effective control measures, could reduce HIV-1 infections.


title: Pre-referral rectal artesunate and referral completion among children with suspected severe malaria in the Democratic Republic of the Congo, Nigeria and Uganda

abstract:
BackgroundChildren who receive pre-referral rectal artesunate (RAS) require urgent referral to a health facility where appropriate treatment for severe malaria can be provided. However, the rapid improvement of a childs condition after RAS administration may influence a caregivers decision to follow this recommendation. Currently, the evidence on the effect of RAS on referral completion is limited. In this study, we investigated the relationship between RAS implementation and administration and referral completion.

Methods and FindingsAn observational study accompanied the roll-out of RAS in three malaria endemic settings in the Democratic Republic of the Congo (DRC), Nigeria and Uganda. Community health workers and primary health centres enrolled children under five years with suspected severe malaria before and after the roll-out of RAS. All children were followed up 28 days after enrolment to assess their treatment seeking pathways, treatments received, and their health outcome. In total, 8,365 children were enrolled, 77% of whom fulfilled all inclusion criteria and had a known referral completion status. Referral completion was 67% (1,408/2,104) in DRC, 48% (287/600) in Nigeria and 58% (2,170/3,745) in Uganda. In DRC and Uganda, RAS users were less likely to complete referral than RAS non-users in the pre-roll-out phase (adjusted odds ratio [aOR] = 0.48, 95% CI 0.30-0.77 and aOR = 0.72, 95% CI 0.58-0.88, respectively). Among children seeking care from a primary health centre in Nigeria, RAS users were less likely to complete referral compared to RAS non-users in the post-roll-out phase (aOR = 0.18, 95% CI 0.05-0.71). In Uganda, among children who completed referral, RAS users were significantly more likely to complete referral on time than RAS non-users enrolled in the pre-roll-out phase (aOR = 1.81, 95% CI 1.17-2.79).

ConclusionsThe findings of this study raise legitimate concerns that the roll-out of RAS may lead to lower referral completion in children who were administered pre-referral RAS. To ensure that community-based programmes are effectively implemented, barriers to referral completion need to be addressed at all levels. Alternative effective treatment options should be provided to children unable to complete referral.


title: Calibrating an SIR model for South Korea COVID-19 infections and predicting vaccination impact

abstract: In the span of 1.5 years, COVID-19 has caused more than 4 million deaths worldwide. To prevent such a catastrophe from reoccurring, it is necessary to test and refine current epidemiological models that impact policy decisions. Thus, we developed a deterministic SIR model to examine the long-term transmission dynamics of COVID-19 in South Korea. Using this model, we analyzed how vaccines would affect the number of cases. We found that a 70% vaccination coverage with a 100% effective vaccine would effectively eliminate the number of cases and herd immunity would have been obtained approximately 85 days after February 15 had there not been a reintroduction of cases.


title: A multivariable Mendelian randomization analysis disentangling the causal relations between abdominal obesity, non-alcoholic fatty liver disease and cardiometabolic diseases

abstract:
BackgroundObservational studies have linked obesity and especially abdominal obesity to non-alcoholic fatty liver disease (NAFLD). These traits are also associated with type 2 diabetes (T2D) and coronary artery disease (CAD) but the causal factor(s) underlying these associations remain unexplored.

MethodsWe used a multivariable Mendelian randomization (MVMR) study design to determine whether obesity (defined using body mass index [BMI]) and abdominal obesity (defined using waist circumference) were causally associated with NAFLD using publicly available genome-wide association study (GWAS) summary statistics of the UK Biobank (n>450,000) and a GWAS meta-analysis of NAFLD (8434 cases and 770,180 control). A MVMR study design was also used to determine the respective causal contributions of waist circumference and NAFLD to T2D and CAD using additional GWAS summary statistics of the DIAGRAM (74,124 cases and 824,006 controls) and CARDIoGRAMplusC4D (122,733 cases and 424,528 controls) consortia.

ResultsIn univariable Mendelian randomization analyses, both BMI and waist circumference were associated with NAFLD. NAFLD was not associated with obesity or abdominal obesity. In MVMR analyses, waist circumference was associated with NAFLD when accounting for BMI (OR per 1-standard deviation increase = 2.56 95% CI: 1.39-4.69, p=2.4e-03) and BMI was not associated with NAFLD when accounting for waist circumference (0.81 95% CI: 0.5-1.31, p =3.9e-01). In MVMR analyses accounting for NAFLD, waist circumference remained strongly associated with both T2D (3.25 95% CI: 2.87-3.68, p=5.1e-77) and CAD (1.62 95% CI: 1.48-1.76, p=6.5e-28).

ConclusionsThese results identified abdominal obesity as a strong, independent and causal contributor to NAFLD, T2D and CAD, suggesting that interventions targeting abdominal obesity rather than body weight per se should be prioritized for the prevention and management of cardiometabolic diseases.


title: Effect of long-term low dose glucocorticoid on children with bronchial asthma

abstract:
ObjectivesTo investigate the clinical efficacy of long-term of low-dose inhaled glucocorticoid (ICS) in the treatment on children with bronchial asthma, and to evaluate its effects on the height, weight and expression of serum insulin-like growth factor of children with bronchial asthma.

Methods91 children with bronchial asthma treated in our hospital from January 2017 to December 2017 were chosen, and 31 healthy children without asthma history in our hospital were selected as the control group (Group C); For the different treatment methods comparison, 91 children with bronchial asthma were divided into treatment group A (48 children) and treatment group B (43 children) randomly. In treatment group A, children were treated with low-dose ICS for more than 1 year; in treatment group B, children were treated with low-dose ICS for less than 1 year or received low-dose ICS for less than 2 months/year. For treatment evaluation, the asthma control test (C-ACT) were scored at 0 months, 12 months and 24 months in three groups, and the height and weight of children, the levels of insulin-like growth factor-1 (IGF-1) and insulin-like growth factor binding protein-3 (IGFBP-3) in serum in each group were also measured.

ResultsIn the control group, the C-ACT scores were increased with time (P<0.01); the C-ACT scores of treatment group A at 12 months and at 24 months was significantly higher than that of treatment group B (P<0.05); there was no significant difference in height and weight between the treatment group and the control group at months, 12 months and 24 months after treatment (P>0.05); there was no significant difference in the expression levels of IGF-1 and IGFBP-3 in serum between treatment group and control group (P>0.05).

Compared with the C-ACT scores in treatment group A and treatment group B at 0 month, the C-ACT scores were significantly higher at 12 months and at 24 months, and there was a statistical difference among 0 month, 12 months and at 24 months in treatment group A and treatment group B (P<0.01); The C-ACT score of treatment group A at the 12 month was significantly higher than that in treatment group B at the 12 months(P<0.05), and the C-ACT score in treatment group A at the 24 months was significantly higher than that of treatment group B (P<0.001).

ConclusionsTreatment for children with bronchial asthma by long-term use of low-dose ICS is safe and effective, it does not affect health and development of children with bronchial asthma; children with bronchial asthma were treated with low-dose ICS for more than 1 year had a better effective than children were treated with low-dose ICS for less than 1 year or received low-dose ICS for less than 2 months/year.


title: Understanding the evidence for climate concerns, negative emotions and climate-related mental ill-health in young people: a scoping review

abstract:
BackgroundHuman-induced climate change represents a serious threat to human health, including mental health, due to both the traumatising effects of extreme climate events and the psychological effect of worry about climate change. The present scoping review aims to systematically search and synthesise original research related to mental health and climate related concerns, negative emotions and mental ill-health in young people. Findings will help to understand the current landscape, gaps in the literature, and to provide recommendations for future youth mental health research and practice.

MethodsA systematic search and narrative synthesis of the literature published prior to October 2020 examining negative emotions associated with climate change in young people was undertaken. Studies were included if they examined mental ill-health (e.g. symptoms of depression or anxiety) or negative emotions (e.g. distress, worry, concern) associated with the threat of climate change.

FindingsOf the 3329 peer-reviewed articles screened, 12 met the inclusion criteria. Together, included studies show that young people are worried about climate change. Studies also explored the coping strategies young people use to manage their distress caused by climate change.

InterpretationsThe limited literature in this area indicates a key gap in youth mental health research. Available evidence suggests that young people are concerned about climate change, which may increase risk of mental ill-health. Thus, clinicians should assess for and address climate anxiety in young people. Mental health leaders are urged to advocate for urgent climate action to mitigate the effects of climate anxiety in young people.

Fundingthis project was not funded.

category: psychiatry and clinical psychology


title: Young adults vulnerability to COVID-19 in Brazil: an overview across the country

abstract: Brazil is a country of continental dimensions, where many smaller countries would fit. In addition to demographic, socioeconomic, and cultural differences, hospital infrastructure and healthcare varies across all 27 federative units. Therefore, the evolution of COVID-19 pandemic did not manifest itself in a homogeneous and predictable trend across the nation. In late 2020 and early 2021, new waves of the COVID-19 outbreak have caused an unprecedented sanitary collapse in Brazil. Unlike the first COVID-19 wave, in subsequent waves, preliminary evidence has pointed to an increase in the daily reported cases among younger people being hospitalized, overloading the healthcare system. In this comprehensive retrospective study, confirmed cases of hospitalization, ICU admission, IMV requirement and in-hospital death from Brazilian COVID-19 patients throughout 2020 until the beginning of 2021 were analyzed through a spatio-temporal study for patients aged 20-59 years. All Brazilian federative units had their data disaggregated in six periods of ten epidemiological weeks each. We found that there is a wide variation in the waves dynamic due to SARS-CoV-2 infection, both in the first and in subsequent outbreaks in different federative units over the analyzed periods. As a result, atypical waves can be seen in the Brazil data as a whole. The analysis showed that Brazil is experiencing a numerical explosion of hospitalizations and deaths for patients aged 20-59 years, especially in the state of Sao Paulo, with a similar proportion of hospitalizations for this age group but higher proportion of deaths compared to the first wave.


title: Availability and readiness of healthcare facilities and their effects on long-acting modern contraception use in Bangladesh: Analysis of linked data

abstract:
AimEvidence on the availability and accessibility of health facilities and their impacts on long-acting modern contraceptives (LAMC) use in low- and middle-Income countries are scarce. This study examined the influence of the availability and readiness of health facilities in determining the use of LAMC in Bangladesh.

MethodsWe linked data of the Bangladesh Demographic and Health Survey and the Health Facility Survey using the administrative-boundary linkage method. Mixed effect multilevel logistic regression was conducted. The sample comprised 10,938 married women of 15-49 years of age, who were fertile but did not desire a child within two years of the date of survey. The outcome variable was the current use of LAMC (yes, no) and the explanatory variables were health facility-, individual-, household- and community-level factors.

ResultsNearly 34% of participants used LAMC with significant variations across areas in Bangladesh. The average distance between the nearest LAMC-providing health facilities and womens homes was 6.36 km, higher in the Sylhet division (8.34 km) and lower in the Dhaka division (4.34 km). Increased scores for the management (adjusted odds ratio (AOR) 1.59; 95% CI, 1.21-2.42) and infrastructure (AOR, 1.44; 95% CI, 1.01-1.69) of health facilities were positively associated with the overall uptake of LAMC. AORs for women to report using LMAC were 2.16 (95% CI, 1.18-3.21) and 1.74 (95% CI, 1.15-3.20), respectively, for per unit increase in the availability and readiness scores to provide LAMC at the nearest health facilities. Nearly 27% decline in the likelihood of LAMC uptake was observed for every kilometer increase in the average regional-level distance between womens homes and the nearest health facilities.

ConclusionThe availability of health facilities close to residence and their improved management, infrastructure, and readiness to provide LAMC play a significant role in increasing LAMC uptake among women. Policies and programs should prioritize increasing the availability and accessibility of health facilities that provide LAMC services.


title: Clinical application of monitoring indicators of female dancer health, including application of artificial intelligence in female hormone networks

abstract:
ObjectivesThe purpose of this study was to assess the effectiveness of monitoring professional female dancer health with a variety of subjective and objective monitoring methods, including application of artificial intelligence (AI) techniques to modelling menstrual cycle hormones and delivering swift personalised clinical advice.

MethodsFemale dancers from a ballet company completed a published online dance-specific health questionnaire. Over the study period, dancers recorded wellbeing and training metrics, with menstrual cycle tracking and blood tests. For menstrual cycle hormones AI-based techniques modelled hormone variation over a cycle, based on capillary blood samples taken at two time points. At regular, virtual, clinical interviews with each dancer, findings were discussed, and personalised advice given.

Results14 female dancers (mean age 25.5 years, SD 3.7) participated in the study. 10 dancers recorded positive scores on the dance health questionnaire, suggesting a low risk of relative energy deficiency in sport (RED-S). 2 dancers were taking hormonal contraception. Apart from 1 dancer, those not on hormonal contraception reported current eumenorrhoeic status. The initiative of monitoring menstrual cycles and application of AI to model menstrual cycle hormones found that subclinical hormone disruption was occurring in 6 of the 10 dancers reporting regular cycles. 4 of the 6 dancers who received personalised advice, showed improved menstrual hormone function, including one dancer who had planned pregnancy.

ConclusionsMultimodal monitoring facilitated delivery of prompt personalised clinical medical feedback specific for dance. This strategy enabled the early identification and swift management of emergent clinical issues. These innovations received positive feedback from the dancers.

Summary boxesO_ST_ABSWhat are the new findings?C_ST_ABSO_LIMonitoring female dancers with a variety of interactive methods - dance specific questionnaire, online tracking and blood testing - together with individual clinical discussion, facilitates comprehensive, personalised support for dancer health.
C_LIO_LIThe clinical application of artificial intelligence (AI) techniques to endocrine function provides the finer detail of female hormone network function.
C_LIO_LIThis novel approach to monitoring dynamic hormone function enabled the detection of subtle female hormone dysfunction as a result of changes in training and nutrition patterns, which occurred before change in menstruation pattern from menstrual tracking.
C_LIO_LIThis multifaceted clinical approach was also effective and helpful in supporting dancers restore full hormone network function through personalised training and nutritional strategies.
C_LI

How might this study impact on clinical practice in the future?O_LIPersonalised, dance specific health advice based on subjective and objective measures can support sustainable individual dancer health.
C_LIO_LIClinical application of artificial intelligence (AI) to menstrual cycle hormones can provide a dynamic and complete picture of hormone network function, without the need to do daily blood tests to measure all four key menstrual cycle hormones.
C_LIO_LIThis AI approach to modelling hormones enables early detection of subtle, subclinical endocrine dysfunction due to low energy availability in female exercisers. This clinical tool can also facilitate the close clinical monitoring of the restoration of full hormone network function in recovery from low energy availability.
C_LIO_LIUsing AI to model female hormones can be an important clinical tool for female athletes, including those athletes where it is difficult to distinguish between perimenopause symptoms and those associated with low energy availability.
C_LI


title: Perfusate metabolomics content and tubular transporters expression during kidney graft preservation by hypothermic machine perfusion

abstract:
BackgroundIschemia-related injury during the pre-implantation period impacts kidney graft outcome. Evaluating these lesions by a non-invasive approach before transplantation could help to understand the mechanisms of graft injury and identify potential biomarkers predictive of graft outcomes. This study aims to determine metabolomic content of graft perfusion fluids and its dependence on preservation time and to explore whether tubular transporters are possibly involved in the metabolomics variations observed.

MethodsKidneys were stored on hypothermic perfusion machines. We evaluated the metabolomic profiles of perfusion fluids (n=35) using Liquid Chromatography coupled with tandem Mass Spectrometry and studied the transcriptional expression of tubular transporters on pre-implantation biopsies (n=26). We used univariate and multivariate analyses to assess the impact of perfusion time on these parameters and their relationship with graft outcome.

ResultsSeventy-two metabolites were found in preservation fluids at the end of perfusion, of which 40% were already present in the native conservation solution. We observed an increase of 23 metabolites with longer perfusion time and a decrease for 8. The predictive model for time-dependent variation of metabolomics content showed good performance (R2= 76%, Q2= 54%, accuracy= 41%, permutations test significant). Perfusion time had no effect on the mRNA expression of transporters. We found no correlation between metabolomics and transporters expression. Neither the metabolomics profile nor the transporters expression were predictive of graft outcome.

ConclusionOur results open the way for further studies, focusing on both intra- and extra-tissue metabolome, to investigate whether transporter alterations can explain the variations observed in pre-implantation period.

category: transplantation


title: Assessing inertial measurement unit locations for freezing of gait detection and patient preference

abstract:
BackgroundFreezing of gait, a common symptom of Parkinsons disease, presents as sporadic episodes in which an individuals feet suddenly feel stuck to the ground. Inertial measurement units (IMUs) promise to enable at-home monitoring and personalization of therapy, but there is a lack of consensus on the number and location of IMUs for detecting freezing of gait. The purpose of this study was to assess IMU sets in the context of both freezing of gait detection performance and patient preference.

MethodsSixteen people with Parkinsons disease were surveyed about sensor preferences. Raw IMU data from seven people with Parkinsons disease, wearing up to eleven sensors, were used to train convolutional neural networks to detect freezing of gait. Models trained with data from different sensor sets were assessed for technical performance; a best technical set and minimal IMU set were identified. Clinical utility was assessed by comparing model- and human-rater-determined percent time freezing and number of freezing events.

ResultsThe best technical set consisted of three IMUs (lumbar and both ankles, AUROC = 0.83), all of which were rated highly wearable. The minimal IMU set consisted of a single ankle IMU (AUROC = 0.80). Correlations between these models and human raters were good to excellent for percent time freezing (ICC = 0.93, 0.89) and number of freezing events (ICC = 0.95, 0.86) for the best technical set and minimal IMU set, respectively.

ConclusionsSeveral IMU sets consisting of three IMUs or fewer were highly rated for both technical performance and wearability, and more IMUs did not necessarily perform better in FOG detection. We openly share our data and software to further the development and adoption of a general, open-source model that uses raw signals and a standard sensor set for at-home monitoring of freezing of gait.


title: Lexical and acoustic features in speech relating to Alzheimer's disease pathology

abstract:
INTRODUCTIONIn this study, we compared digital speech features of AD and lvPPA patients in a biologically confirmed cohort and related them to specific neuropsychiatric test scores and CSF proteins.

METHODSWe extracted language variables with automated lexical and acoustic pipelines from oral picture descriptions of 44 AD and 21 lvPPA patients with autopsy or CSF confirmation of AD pathology. We correlated distinct speech features with MMSE and BNT test scores and CSF p-tau levels.

RESULTSLvPPA patients produced fewer verbs, adjectives, and more fillers with lower lexical diversity and higher pause rate than AD. Both groups showed some shared language impairments compared with normal speakers.

DISCUSSIONOur speech measures captured differences in speech between the two phenotypes. Also, shared speech markers were linked to the common underlying pathology. This work demonstrates the potential of natural speech analysis in detecting underlying AD pathology.


title: Lexical and acoustic speech features relating to Alzheimer's disease pathology


title: A Novel Retinal Vascular Feature and Machine Learning-based Brain White Matter Lesion Prediction Model

abstract:
White matter lesion (WML) is one of the common cerebral abnormalities, it indicates changes in the white matter of human brain and have shown significant association with stroke, dementia and deaths. Magnetic resonance imaging (MRI) of the brain is frequently used to diagnose white matter lesion (WML) volume. Regular screening can detect WML in early stage and save from severe consequences. Current option of MRI based diagnosis is impractical for regular screening because of its high expense and unavailability. Thus, earlier screening and prediction of the WML volume/load specially in the rural and remote areas becomes extremely difficult. Research has shown that changes in the retinal micro vascular system reflect changes in the cerebral micro vascular system. Using this information, we have proposed a retinal image based WML volume and severity prediction model which is very convenient and easy to operate.

Our proposed model can help the physicians to detect the patients who need immediate and further MRI based detail diagnosis of WML. Our model uses quantified measurement of retinal micro-vascular signs (such as arteriovenular nicking (AVN), Opacity (OP) and focal arteriolar narrowing (FAN)) as input and estimate the WML volume/load and classify its severity. We evaluate our proposed model on a dataset of 111 patients taken from the ENVISion study which have retinal and MRI images for each patient. Our model shows high accuracy in estimating the WML volume, mean square error (MSE) between our predicted WML load and manually annotated WML load is 0.15. The proposed model achieves an F1 score of 0.92 in classifying the patients having mild and severe WML load.

The preliminary results of our study indicate that quantified measurement of retinal micro-vascular features (AVN, OP and FAN) can more accurately identify the patients who have high risk of cardio-vascular diseases and dementia.

category: ophthalmology


title: TSABL: Trait Specific Annotation Based Locus Predictor

abstract: The majority of GWAS loci fall in the non-coding genome, making causal variants difficult to identify and study. We hypothesized that the regulatory features underlying causal variants are biologically specific, identifiable from data, and that the regulatory architecture that influences one trait is distinct compared to biologically unrelated traits. To better characterize and identify these variants, we used publicly available GWAS loci and genomic annotations to build 17 Trait Specific Annotation Based Locus (TSABL) predictors to identify differences between GWAS loci associated with different phenotypic trait groups. We used a penalized binomial logistic regression model to select trait relevant annotations and tested all models on a holdout set of loci not used for training in any trait. We were able to successfully build models for autoimmune, electrocardiogram, lipid, platelet, red blood cell, and white blood cell trait groups. We used these models both to prioritize variants in existing loci and to identify new genomic regions of interest. We found that TSABL models identified biologically relevant regulatory features, and anticipate their future use to enhance the design and interpretation of genetic studies.


title: CovRNN - A recurrent neural network model for predicting outcomes of COVID-19 patients: model development and validation using EHR data

abstract:
BackgroundPredicting outcomes of COVID-19 patients at an early stage is critical for optimized clinical care and resource management, especially during a pandemic. Although multiple machine learning models have been proposed to address this issue, based on the need for extensive data pre-processing and feature engineering, these models have not been validated or implemented outside of the original study site.

MethodsIn this study, we propose CovRNN, recurrent neural network (RNN)-based models to predict COVID-19 patients outcomes, using their available electronic health record (EHR) data on admission, without the need for specific feature selection or missing data imputation. CovRNN is designed to predict three outcomes: in-hospital mortality, need for mechanical ventilation, and long length of stay (LOS >7 days). Predictions are made for time-to-event risk scores (survival prediction) and all-time risk scores (binary prediction). Our models were trained and validated using heterogeneous and de-identified data of 247,960 COVID-19 patients from 87 healthcare systems, derived from the Cerner(R) Real-World Dataset (CRWD). External validation was performed using three test sets (approximately 53,000 patients). Further, the transferability of CovRNN was validated using 36,140 de-identified patients data derived from the Optum(R) de-identified COVID-19 Electronic Health Record v. 1015 dataset (2007-2020).

FindingsCovRNN shows higher performance than do traditional models. It achieved an area under the receiving operating characteristic (AUROC) of 93% for mortality and mechanical ventilation predictions on the CRWD test set (vs. 91{middle dot}5% and 90% for light gradient boost machine (LGBM) and logistic regression (LR), respectively) and 86.5% for prediction of LOS > 7 days (vs. 81{middle dot}7% and 80% for LGBM and LR, respectively). For survival prediction, CovRNN achieved a C-index of 86% for mortality and 92{middle dot}6% for mechanical ventilation. External validation confirmed AUROCs in similar ranges.

InterpretationTrained on a large heterogeneous real-world dataset, our CovRNN model showed high prediction accuracy, good calibration, and transferability through consistently good performance on multiple external datasets. Our results demonstrate the feasibility of a COVID-19 predictive model that delivers high accuracy without the need for complex feature engineering.


title: Why promising drugs are shelved and barriers and facilitators to re-purposing them: A systematic literature review

abstract:
BackgroundDespite enthusiasm on the role of repurposing in drug development, enhanced by the Covid-19 pandemic with the FDA granting emergency use authorization of several repurposed drugs to treat Covid-19, there remain knowledge gaps on why pharmaceutical companies abandon the development of promising drug candidates as well as facilitators and barriers to moving them back into development, a process often referred to as drug repurposing.

MethodThis systematic literature review used a combination of controlled vocabulary and free text terms related to the de-prioritization, shelving, abandonment and repurposing of promising experimental drugs unapproved by the FDA for any indication, to search ABI/Informa, Academic Search Premier, Business Source Complete, Cochrane Library, EconLit, Google Scholar, Ovid Embase, Ovid Medline, Pubmed, Scopus, and Web of Science Core Collection databases. The main outcomes of interest were the characteristics and reasons for the phenomenon of companies deprioritizing or abandoning development of promising drugs, facilitators and successful examples of advancing development of promising abandoned or deprioritized drugs (often referred to as drug repositioning or re-purposing), and barriers to advancing development of promising abandoned or de-prioritized drugs. Study inclusion was not limited by publication date or type. Data extracted included article type, article title, journal title, first author, publication date, extraction and analysis of terminology used to describe abandoned investigational drugs and moving them back into research and development, reason(s) and methods for drug de-prioritization or abandonment, conditions treated, examples of deprioritized or repurposed drugs, as well as barriers and facilitators to drug repurposing. Risk of bias was not performed due to the varying study designs included in this study. Instead, Oxford Centre for Evidence-Based Medicine: Levels of Evidence was used to grade the level of evidence included in this study.

ResultsWe identified 11,814 articles, screening 5,976 for relevance, finding 437 eligible for full text review, 115 of which were included in full analysis. Most articles (66%, 76/115) provided reasons for why drug development may be abandoned, with lack of efficacy, or superiority to other therapies, for the studied indication (n=59), strategic business reasons (n=35), safety problems (n=28), research design decisions (n=12), the complex nature of a studied disease or drug (n=7) and regulatory bodies requiring more information (n=2) among the top. Inadequate resources (n=42) including expertise (n=11), intellectual property challenges (n=26), poor data access (n=20), and uncertainty about the value of repurposing (n=13) along with liability risks (n=5) are key barriers to repurposing. The most common facilitators of drug repurposing were multi-partner collaborations (n=38), access to comprehensive compound databases and corresponding screening tools (n=32), regulatory modifications (n=5) and tax incentives (n=2).

ConclusionMore research is needed on the current value of repurposing in drug development, as there remain uncertainties, as well as on how to better facilitate access to resources to support it, where valuable. Financial barriers, insufficient staffing focused on out-licensing shelved products, and challenges negotiating IP agreements in multi-partner collaborations were discussed as barriers to repurposing without clear solutions, suggesting more research is needed in this area.

RegistrationThe protocol was registered on Open Science Framework (https://osf.io/f634k/) as it was not eligible for registration on PROSPERO.


title: Risk scores for predicting HIV incidence among the general population in sub-Saharan Africa: a systematic review and meta-analysis

abstract:
IntroductionSeveral HIV risk scores have been developed to identify individuals for prioritised HIV prevention in sub-Saharan Africa. We systematically reviewed HIV risk scores to: (i) identify factors that consistently predicted incident HIV infection, (ii) review inclusion of community-level HIV risk in predictive models, and (iii) examine predictive performance.

MethodsWe searched nine databases from inception until February 15, 2021 for studies developing and/or validating HIV risk scores among the heterosexual adult population in sub-Saharan Africa. Studies not prospectively observing seroconversion or recruiting only key populations were excluded. Record screening, data extraction, and critical appraisal were conducted in duplicate. We used random-effects meta-analysis to summarise hazard ratios and the area under the receiver-operating characteristic curve (AUC-ROC).

ResultsFrom 1563 initial search records, we identified 14 risk scores in 13 studies. Seven studies were among sexually active women using contraceptives enrolled in randomised-controlled trials, three among adolescent girls and young women (AGYW), and three among cohorts enrolling both men and women. Consistently identified HIV prognostic factors among women were younger age (pooled adjusted hazard ratio: 1.62 [95% Confidence Interval: 1.17, 2.23], compared to above-25), single/not cohabiting with primary partners (2.33 [1.73, 3.13]) and having sexually transmitted infections (STIs) at baseline (HSV-2: 1.67 [1.34, 2.09]; curable STIs: 1.45 [1.17; 1.79]). Among AGYW only STIs were consistently associated with higher incidence, but studies were limited (n=3). Community-level HIV prevalence or unsuppressed viral load strongly predicted incidence but were only considered in three of 11 multi-site studies. The AUC-ROC ranged from 0.56 to 0.79 on the model development sets. Only the VOICE score was externally validated by multiple studies, with pooled AUC-ROC 0.626 [0.588, 0.663] (I2: 64.02%).

ConclusionsYounger age, non-cohabiting, and recent STIs were consistently identified as predicting future HIV infection. Both community HIV burden and individual factors should be considered to quantify HIV risk. However, HIV risk scores had only low-to-moderate discriminatory ability and uncertain generalisability, limiting their programmatic utility.

Further evidence on the relative value of specific risk factors, studies populations not restricted to  at-risk individuals, and data outside South Africa will improve the evidence base for risk differentiation in HIV prevention programmes.

PROSPERO NumberCRD42021236367

category: hiv aids


title: Risk scores for predicting HIV incidence among adult heterosexual populations in sub-Saharan Africa: a systematic review and meta-analysis


title: The impact of SARS-CoV-2 vaccination on Alpha and Delta variant transmission

abstract:
BackgroundPre-Delta, vaccination reduced SARS-CoV-2 transmission from individuals infected despite vaccination, potentially via reducing viral loads. While vaccination still lowers the risk of infection, similar viral loads in vaccinated and unvaccinated individuals infected with Delta question how much vaccination prevents transmission.

MethodsWe performed a retrospective observational cohort study of adult contacts of SARS-CoV-2-infected adult index cases using English contact testing data. We used multivariable Poisson regression to investigate associations between transmission and index case and contact vaccination, and how these vary with Alpha and Delta variants (classified using S-gene detection/calendar trends) and time since second vaccination.

Results54,667/146,243(37.4%) PCR-tested contacts of 108,498 index cases were PCR-positive. Two doses of BNT162b2 or ChAdOx1 vaccines in Alpha index cases were independently associated with reduced PCR-positivity in contacts (aRR, adjusted rate ratio vs. unvaccinated=0.32[95%CI 0.21-0.48] and 0.48[0.30-0.78] respectively). The Delta variant attenuated vaccine-associated reductions in transmission: two BNT162b2 doses reduced Delta transmission (aRR=0.50[0.39-0.65]), more than ChAdOx1 (aRR=0.76[0.70-0.82]). Variation in Ct values (indicative of viral load) explained 7-23% of vaccine-associated transmission reductions. Transmission reductions declined over time post-second vaccination, for Delta reaching similar levels to unvaccinated individuals by 12 weeks for ChAdOx1 and attenuating substantially for BNT162b2. Protection in contacts also declined in the 3 months post-second vaccination.

ConclusionsVaccination reduces transmission of Delta, but by less than the Alpha variant. The impact of vaccination decreased over time. Factors other than PCR Ct values at diagnosis are important in understanding vaccine-associated transmission reductions. Booster vaccinations may help control transmission together with preventing infections.