title: Increase in SARS-CoV-2 seroprevalence in healthy blood donors after the second wave of COVID-19 pandemic in South-Eastern Italy: evidence for asymptomatic young individuals as potential virus spreaders

abstract:
BackgroundItaly has been the first among western countries to experience SARS-CoV-2 spread during which the southern regions were also heavily affected by the pandemic. To understand and monitor properly the evolution of COVID-19 pandemic, population based seroprevalence studies are a valid tool for the infection rates and effective prevalence of the SARS-CoV-2.

AimIn this prospective study, we assessed the changes in SARS-CoV-2 seroprevalence rates among non-vaccinated blood donors in South-Eastern Italy over May 2020 to March 2021.

Methods8,183 healthy blood donors referring to the Transfusion Center at the University Hospital "Riuniti" of Foggia (Italy) for blood donation in the period May 2020-March 2021 were tested for anti-SARS-CoV-2 antibodies by Ortho Clinical Diagnostics VITROS(R) 3600. None of the considered subjects had a diagnosed symptomatic COVID-19 infection.

ResultsOverall, 516 resulted positive for anti-SARS-CoV-2 IgG antibodies (6.3%, 95% CI, 0.03-0.15%), 387 (4.7%) were male and 129 (1.7%) female. A statistically significant increase in the seropositive population was found from May 2020 to March 2021 (Fishers p<0.001). The difference of the seroprevalence was significant in terms of age but not sex (2-sided p<0.05 for age; 2-sided p>0.05 for sex) in both groups.

ConclusionOur study shows a significant increase in the SARS-CoV-2 seroprevalence among blood donors and suggests a potential role of asymptomatic individuals in continuing the spread of the pandemic. These results may contribute to establishing containment measures and priorities in vaccine campaigns.


title: DNR order in SARS-CoV-2 patients: preliminary guidelines validation and quality of palliative care in a single Swiss COVID-19 Center.

abstract:
BackgroundThe worldwide pandemic situation forced many hospitals to adapt COVID-19 management strategies. In this scenario, the Swiss Academy of Medical Sciences (SAMW/ASSM) organized national guidelines based on expert opinion to identify Do-Not-Resuscitate (DNR) patients, to reduce futile ICU admission and resource misuse. However, the practical impact of this standardized national protocol has not been yet evaluated. In our specialized COVID-19 Center, we investigated characteristics and mortality of DNR patients identified according to national standardized protocol, comparing them to non-DNR patients.

MethodsThis was a pilot retrospective validation study, evaluating consecutive hospital admitted COVID-19 patients. Primary outcome was 30-days survival of DNR patients in comparison to the control group. Secondary outcomes reported quality of treatment of deceased patients, especially of agitation/sedation and dyspnea, using respectively the Richmond Agitation-Sedation Scale - Palliative care (RASS-PAL) for sedation and agitation (+4/-5) and the modified Borg Scale for dyspnea (1-10).

ResultsFrom March 16 to April 1, 2020, 213 consecutive patients were triaged; at 30-days follow-up, 9 patients (22.5%) died in the DNR group, 4 (2.2%) in the control group. The higher mortality rate in the DNR group was further confirmed by Log-Rank Mantel-Cox (23.104, p < 0.0001). In the DNR-group deceased patients, end-of-life support was performed with oxygen (100%), opioids (100%) and sedatives (89%); the mean RASS-PAL improved from 2.2 to -1.8 (p < 0.0001) and the Borg scale improved from 5.7 to 4.7 (p = 0.581).

ConclusionA national standardized protocol identified patients at higher risk of short-term death. Although the legal status of DNRs varies from country to country, the implementation of national standardized protocol could be the way to guarantee a better treatment of COVID-19 patients in a pandemic situation with limited resources.

category: emergency medicine


title: DNR orders in SARS-CoV-2 patients: a retrospective validation study in a Swiss COVID-19 Center


title: COVID-19 Pandemic Analysis

abstract:
The development of coronavirus disease (COVID-19) deaths in selected nations and states is compared to the result of calculations using a conventional SEIR model of pandemic development. The model is based on the infection multiplier, R0, defined as the number of people infected by each infectious person. The infection rate increases exponentially when R0 >1.0; it remains constant at R0 = 1.0 and decreases for R0 < 1.0. R0 is determined by population behavior (frequency and proximity of interactions) and the ease by which a victim is infected by an infectious person (virulence of the virus). It is reduced by herd immunity when a large fraction of the population acquires immunity by vaccination or by recovering from infection.

The daily death rates in the U.S. and northern Europe exhibited peaks in April/May 2020 and Dec. 2020/Jan. 2021 with more a modest rate during the summer of 2020 and a gradually decreasing rate since Jan. 2021. The model produces this type of oscillatory response if it assumes that the populations R0 responds to information reported about the pandemic, but with a delay between infections and resulting behavioral adjustments. Oscillatory behavior is typical of a control loop with delay in its feedback.

The analysis concludes thatO_QDGiven the history of R0 the model predicts the development of pandemic deaths. However, since R0 is determined by the populations behavior, control of the pandemic in democracies depends primarily on preparation and the persuasive power of political and scientific authorities. Data for S. Korea and New Zealand demonstrate the effectiveness of such methods.

For each death in the U.S. about 169 persons were infected, but fewer than half of them were identified as cases.

The pandemic was prolonged in the U.S. because the population chose to keep R0 near 1.0 by relaxing restrictions once the death rate subsided.

Initial values of R0 as high as 5.0 were observed, leading to infections doubling about every 2 days. If unabated, the resulting exponential growth increases the infected population by a factor of about 5000 before the death from the first infections is recorded.

Arrival from Italy probably initiated the pandemic in the eastern U.S., but, by the time the first death was recorded the number of domestic infections exceeded by far those that were imported. Import restrictions beyond this point are ineffective except in delaying the arrival of more virulent mutations.

If no social restrictions had been adopted, approximately 1.6 million deaths would have resulted in the U.S. The vaccine, although developed and deployed at record speed, was too late to ameliorate this result.

A third peak in death rate in Sept. 2021 may be prevented if more than 80% of the population is vaccinated.

C_QD

category: epidemiology


title: Quantifying social contact patterns in Minnesota during Stay-at-Home social distancing order

abstract:
SARS-CoV-2 is primarily transmitted through person-to-person contacts. It is important to collect information on age-specific contact patterns because SARS-CoV-2 susceptibility, transmission, and morbidity vary by age. To reduce risk of infection, social distancing measures have been implemented. Social contact data, which identify who has contact with whom especially by age and place are needed to identify high-risk groups and serve to inform the design of non-pharmaceutical interventions.

We estimated and used negative binomial regression to compare the number of daily contacts during the first wave (April-May 2020) of the Minnesota Social Contact Study, based on respondents age, gender, race/ethnicity, region, and other demographic characteristics. We used information on age and location of contacts to generate age-structured contact matrices. Finally, we compared the age-structured contact matrices during the stay-at-home order to pre-pandemic matrices.

During the state-wide stay-home order, the mean daily number of contacts was 5.6. We found significant variation in contacts by age, gender, race, and region. Adults between 40 and 50 years had the highest number of contacts. Respondents in Black households had 2.1 more contacts than respondent in White households, while respondents in Asian or Pacific Islander households had approximately the same number of contacts as respondent in White households. Respondents in Hispanic households had approximately two fewer contacts compared to White households. Most contacts were with other individuals in the same age group. Compared to the pre-pandemic period, the biggest declines occurred in contacts between children, and contacts between those over 60 with those below 60.


title: Ethnic and sexual identities: inequalities in adolescent health and wellbeing in a national population-based study

abstract:
AimsTo examine inequalities related to dual sexual- and ethnic-identities in risk for health, wellbeing, and health-related behaviours in a nationally representative sample of adolescents.

Methods9,789 adolescents (51% female) aged 17 years from the UK-wide Millennium Cohort Study, with data on self-identified sexual- and ethnic-identities. Adolescents were grouped into White-Heterosexual, White sexual minority (White-SM), ethnic minority (EM)-heterosexual, and ethnic- and sexual minority (EM-SM).

Mental health (e.g., self-reported psychological distress, doctor-diagnosed depression, attempted suicide, victimisation), general health (self-rated health, chronic illness, BMI) and a range of health-related behaviours (e.g., smoking, substance use) were assessed by questionnaires. Associations between dual identities and outcomes were analysed using logistic and linear regression (adjusted for sex and parental income).

ResultsSexual minorities (White:18% and ethnic minority:3%) had increased odds for mental ill-health and attempted suicide, with higher odds in White-SM than EM-SM. Compared to White-heterosexuals, White-SM and EM-SM had higher odds for psychological distress (OR 3.47/2.24 for White-SM/EM-SM respectively), and emotional problems (OR 3.17/1.65). White-SM and EM-SM had higher odds for attempted suicide (OR 2.78/2.02), self-harm (OR 3.06/1.52), and poor sleep quality (OR 1.88/1.67). In contrast, White-Heterosexual and White-SM groups had similarly high proportions reporting risky behaviours except for drug use (OR 1.34) and risky sex (OR 1.40) more common in White-SM individuals. EM-Heterosexuals and EM-SM individuals had decreased odds for health-related behaviours.

ConclusionsSexual minorities (White and EM) had substantially worse mental health compared to their heterosexual peers. Adverse health-related behaviours were more common in White sexual minority individuals. Further investigation into potentially different mechanisms leading to adverse health in White-SM and EM-SM individuals is needed.


title: Absence of SARS-CoV-2 antibodies in pre-pandemic plasma from children and adults in Vietnam

abstract: We tested pre-pandemic (2015-2019) plasma samples from 148 Vietnamese children, and 100 Vietnamese adults at high risk of zoonotic infections, for antibodies against SARS-CoV-2 nucleocapsid and spike proteins. None was positive, indicating no prior serological cross-reactivity with SARS-CoV-2 that might explain the low numbers of COVID-19 in Vietnam.


title: Modeling COVID-19 vaccine efficacy and coverage towards herd-immunity in the Basque Country, Spain

abstract: Vaccines have measurable efficacies, obtained first from vaccine trials. However, vaccine efficacy is not a static measure upon licensing, and the long term population studies are very important to evaluate vaccine performance and impact. COVID-19 vaccines were developed in record time and although the extent of sterilizing immunity is still under evaluation, the currently licensed vaccines are extremely effective against severe disease, with vaccine efficacy significantly higher after the full immunization schedule. We investigate the impact of vaccines which have different efficacies after first dose and after the second dose administration schedule, eventually considering different efficacies against severe disease as opposed to overall infection. As a proof of concept, we model the vaccine performance of hospitalization reduction at the momentary scenario of the Basque Country, Spain, with population in a mixed vaccination setting, giving insights into the population coverage needed to achieve herd immunity in the current vaccination context.


title: Birth during the COVID-19 pandemic, but not maternal SARS-CoV-2 infection during pregnancy, is associated with lower neurodevelopmental scores at 6-months

abstract: The intrauterine environment strongly influences development. Neurodevelopmental effects of in utero exposure to maternal SARS-CoV-2 infection are widely speculated but currently unknown. The COVID-19 Mother Baby Outcomes (COMBO) initiative was established at Columbia University Irving Medical Center (CUIMC) in New York City to prospectively study the health and wellbeing of infants with and without in utero exposure to maternal SARS-CoV-2 infection. We report findings on 6-month neurodevelopmental outcomes using the parental-report Ages & Stages Questionnaire, 3rd Edition (ASQ-3), from 107 in utero exposed and 131 unexposed full-term infants born between March and December, 2020. We compare these infants to a historical cohort comprised of 62 infants born at CUIMC at least two months prior to the onset of the pandemic. In utero exposure to maternal SARS-CoV-2 infection was not associated with differences on any ASQ-3 subdomain regardless of infection timing or severity, however, infants born during the pandemic had significantly lower scores on gross motor, fine motor, and personal-social subdomains when compared to the historical cohort. Infants born to women who were in the first trimester of pregnancy during the peak of the pandemic in NYC had the lowest personal-social scores. Birth during the pandemic, but not maternal SARS-CoV-2 infection, was associated with differences in neurodevelopmental outcomes at 6-months. These early findings suggest significantly higher public health impact for the generation born during the COVID-19 pandemic than previously anticipated.

category: pediatrics


title: When time-dependence in disease outcome risk is not captured by impact evaluation modeling studies: a measles vaccination case study

abstract:
BackgroundIn modeling studies that evaluate the effects of health programs, the risk of secondary outcomes attributable to infection can vary with underlying disease incidence. Consequently, the impact of interventions on secondary outcomes would not be proportional to incidence reduction. Here we use a case study on measles vaccine program to demonstrate how failure to capture this non-linear relationship can lead to over- or under-estimation.

MethodsWe used a published model of measles CFR that depends on incidence and vaccine coverage to illustrate the effects of: (1) assuming higher CFR in "no-vaccination" scenarios; (2) time-varying CFRs over the past; and (3) time-varying CFRs in future projections on measles impact estimation. We evaluated how different assumptions on vaccine coverage, measles incidence, and CFR levels in "no-vaccination" scenarios affect estimation of future deaths averted by measles vaccination.

ResultsCompared to constant CFRs, aligning both "vaccination" and "no-vaccination" scenarios with time variant measles CFR estimates led to larger differences in mortality in historical years and lower in future years.

ConclusionsTo assess consequences of interventions, impact estimates should consider the effect of "no-intervention" scenario assumptions on model parameters to project estimated impact for alternative scenarios according to intervention strategies and investment decisions.

category: public and global health


title: Making an equal system equitable: Proposing a sex-adjusted MELDNa score for liver transplantation allocation

abstract:
Background & AimsLiver allocation is determined by the model for end-stage liver disease (MELD), a scoring system based on four laboratory measurements. During the MELD era, sex disparities in liver transplant have increased and there are no modifications to MELD based on sex. We use data from electronic health records (EHRs) to describe sex differences in MELD labs and propose a sex adjustment.

MethodsWe extracted lab values for creatinine, International Normalized Ratio of prothrombin rate, bilirubin, and sodium from EHRs at Vanderbilt University Medical Center (VUMC) and the All of Us Research Project to determine sex differences in lab traits. We calculated MELDNa scores within liver transplant recipients, non-transplanted liver disease cases, and non-liver disease controls separately. To account for sex differences in lab traits in MELDNa scoring, we created a sex-adjusted MELDNa map which outputs adjusted female scores mapped to male scores of equal liver disease severity. Using waitlist data from the Liver Simulated Allocation Modeling, we conducted simulations to determine if the sex-adjusted scores reduced sex disparities.

ResultsAll component MELDNa lab values and calculated MELDNa scores yielded significant sex differences within VUMC (n=623,931) and All of Us (n=56,715) resulting in MELDNa scoring that disadvantaged females who, despite greater decompensation traits, had lower MELDNa scores. In simulations, the sex-adjusted MELDNa score modestly increased female transplantation rate and decreased overall death.

ConclusionsOur results demonstrate pervasive sex differences in all labs used in MELDNa scoring and highlight the need and utility of a sex-adjustment to the MELDNa protocol.

Lay SummaryLiver transplant waitlist position is determined by a score called MELDNa, which is calculated using four laboratory values. Once on the waitlist, males are more likely to receive a transplant, while females are more likely to die or be removed due to illness. We demonstrate that all four laboratory values in the MELDNa score show significant sex differences that disadvantage females in liver transplant. We created a sex-adjusted score that increases female transplantation rate and decreases death among both sexes in simulations.

category: transplantation


title: The impact of hypoxia on B cells in COVID-19

abstract: Prominent early features of COVID-19 include severe, often clinically silent, hypoxia and a pronounced reduction in B cells, the latter important in defence against SARS-CoV-2. This brought to mind the phenotype of mice with VHL-deficient B cells, in which Hypoxia-Inducible Factors are constitutively active, suggesting hypoxia might drive B cell abnormalities in COVID-19. We demonstrated the breadth of early and persistent defects in B cell subsets in moderate/severe COVID-19, including reduced marginal zone-like, memory and transitional B cells, changes we also observed in B cell VHL-deficient mice. This was corroborated by hypoxia-related transcriptional changes in COVID-19 patients, and by similar B cell abnormalities in mice kept in hypoxic conditions, including reduced marginal zone and germinal center B cells. Thus hypoxia might contribute to B cell pathology in COVID-19, and in other hypoxic states. Through this mechanism it may impact on COVID-19 outcome, and be remediable through early oxygen therapy.

category: infectious diseases


title: Genome Alert!: a standardized procedure for genomic variant reinterpretation and automated genotype-phenotype reassessment in clinical routine

abstract:
Numerous countries have set up population genomics plans, allowing an unprecedented growth in the ability of interpreting variants in human diseases. Retrospective interpretation of sequenced data in the light of the current literature is a major concern of the field. Moreover, such reinterpretation is manual and both the human resources and the variable operating procedures are main bottlenecks.

This work describes the Genome Alert! standardized procedure. This open-source method automatically reports changes with potential clinical significance in variant classification between releases of the ClinVar database. Using ClinVar submissions across time, this method assigns gene-disease associations validity category. Genome Alert! was assessed on a retrospective 29 months multicentric series of 5,959 consecutive individuals screened by targeted or exome sequencing.

Between July 2017 and December 2019, the retrospective analysis of ClinVar submissions revealed a monthly median of 1,247 changes in variant classification with potential clinical significance and 23 new gene-disease associations. Reexamination of 4,929 targeted sequencing files highlighted 45 changes, which 89% classifications were expert validated, leading to four additional diagnoses. Genome Alert! gene-disease association catalog provided 75 high-confidence associations not available in the OMIM morbid list, where 20% became OMIM morbid 8 months later. Over 356 negative exome sequencing data that were reannotated for variants in these 75 genes, this elective approach led to a new diagnosis.

Genome Alert! (https://genomealert.univ-grenoble-alpes.fr/) enables the systematic and reproducible reinterpretation of acquired sequencing data in a clinical routine with a limited human resource impact.

Graphical abstract

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category: genetic and genomic medicine


title: Automated Detection Model in Classification B-Lymphoblast Cell from Normal B-Lymphoid Precursors in Blood Smear Microscopic Images Based on the Majority Voting Technique

abstract:
IntroductionAcute Lymphoblastic Leukemia (ALL) is a deadly white blood cell disease that affects the human bone marrow. Detection of ALL, the most common type of leukemia, has been always riddled with complexity and difficulty in its early stages. Peripheral blood examination as a common method at the beginning of the ALL diagnosis process is a time-consuming, tedious process and greatly depends on the experts experience, keeping up with the advances in artificial intelligence in the diagnosis process. Keeping up with the growth and development of artificial intelligence algorithms a model was developed to classify B-ALL lymphoblast cells from lymphocytes.

Materials and MethodsA Fast, efficient and comprehensive model based on Deep Learning (DL) was proposed by implementing eight well-known Convolutional Neural Network (CNN) models for feature extraction on all images and evaluating in classifying B-ALL lymphoblast and Normal. After evaluating their performance, four best-performing CNN models were selected to compose an ensemble classifier, by combining the model performance of each classifier.

ResultsDue to the close similarity of the nuclei of cancerous and normal blood B-ALL cells, the state-of-the-art CNN models alone did not achieve acceptable performance in diagnosing these two classes and their sensitivity was low. The proposed classification model Based on the majority voting technique was adopted to combine the CNN models. The sensitivity of 99.4, the specificity of 96.7, AUC of 98.3, and accuracy of 98.5 were obtained for the proposed model.

ConclusionTo classify blood cancerous cells from normal cells, the proposed method can achieve high accuracy without the intervention of the operator in cell feature determination. Thus, the DL-based model can be recommended as an extraordinary tool for the analysis of blood samples in digital laboratory equipment to assist laboratory specialists.

category: health informatics


title: Generalizability Challenges of Mortality Risk Prediction Models: A Retrospective Analysis on a Multi-center Database

abstract:
Modern predictive models require large amounts of data for training and evaluation, absence of which may result in models that are specific to certain locations, populations in them and clinical practices. Yet, best practices for clinical risk prediction models have not yet considered such challenges to generalizability. Here we ask whether population- and group-level performance of mortality prediction models vary significantly when applied to hospitals or geographies different from the ones in which they are developed. Further, what characteristics of the datasets explain the performance variation? In this multi-center cross-sectional study, we analyzed electronic health records from 179 hospitals across the US with 70,126 hospitalizations from 2014 to 2015. Generalization gap, defined as difference between model performance metrics across hospitals, is computed for area under the receiver operating characteristic curve (AUC) and calibration slope. To assess model performance by the race variable, we report differences in false negative rates across groups. Data were also analyzed using a causal discovery algorithm "Fast Causal Inference" that infers paths of causal influence while identifying potential influences associated with unmeasured variables. When transferring models across hospitals, AUC at the test hospital ranged from 0.777 to 0.832 (1st-3rd quartile or IQR; median 0.801); calibration slope from 0.725 to 0.983 (IQR; median 0.853); and disparity in false negative rates from 0.046 to 0.168 (IQR; median 0.092). Distribution of all variable types (demography, vitals, and labs) differed significantly across hospitals and regions. The race variable also mediated differences in the relationship between clinical variables and mortality, by hospital/region. In conclusion, group-level performance should be assessed during generalizability checks to identify potential harms to the groups. Moreover, for developing methods to improve model performance in new environments, a better understanding and documentation of provenance of data and health processes are needed to identify and mitigate sources of variation.

Author SummaryWith the growing use of predictive models in clinical care, it is imperative to assess failure modes of predictive models across regions and different populations. In this retrospective cross-sectional study based on a multi-center critical care database, we find that mortality risk prediction models developed in one hospital or geographic region exhibited lack of generalizability to different hospitals or regions. Moreover, distribution of clinical (vitals, labs and surgery) variables significantly varied across hospitals and regions. Based on a causal discovery analysis, we postulate that lack of generalizability results from dataset shifts in race and clinical variables across hospitals or regions. Further, we find that the race variable commonly mediated changes in clinical variable shifts. Findings demonstrate evidence that predictive models can exhibit disparities in performance across racial groups even while performing well in terms of average population-wide metrics. Therefore, assessment of sub-group-level performance should be recommended as part of model evaluation guidelines. Beyond algorithmic fairness metrics, an understanding of data generating processes for sub-groups is needed to identify and mitigate sources of variation, and to decide whether to use a risk prediction model in new environments.


title: Within and between classroom transmission patterns of seasonal influenza among primary school students in Matsumoto city, Japan

abstract:
Schools play a central role in the transmission of many respiratory infections. Heterogeneous social contact patterns associated with the social structures of schools (i.e. classes/grades) are likely to influence the within-school transmission dynamics, but data-driven evidence on fine-scale transmission patterns between students has been limited. Using a mathematical model, we analysed a large-scale dataset of seasonal influenza outbreaks in Matsumoto city, Japan to infer social interactions within and between classes/grades from observed transmission patterns. While the relative contribution of within-class and within-grade transmissions to the reproduction number varied with the number of classes per grade, the overall within-school reproduction number, which determines the initial growth of cases and the risk of sustained transmission, was only minimally associated with class sizes and the number of classes per grade. This finding suggests that interventions that change the size and number of classes, e.g. splitting classes and staggered attendance, may have limited effect on the control of school outbreaks. We also found that vaccination and mask-wearing of students were associated with reduced susceptibility (vaccination and mask-wearing) and infectiousness (mask-wearing) and hand washing with increased susceptibility. Our results show how analysis of fine-grained transmission patterns between students can improve understanding of within-school disease dynamics and provide insights into the relative impact of different approaches to outbreak control.

SignificanceEmpirical evidence on detailed transmission patterns of influenza among students within and between classes and grades and how they are shaped by school population structure (e.g. class and school sizes) has been limited to date. We analysed a detailed dataset of seasonal influenza incidence in 29 primary schools in Japan and found that the reproduction number at school did not show any clear association with the size or the number of classes. Our findings suggest that the interventions that only focus on reducing the number of students in class at any moment in time (e.g. reduced class sizes and staggered attendance) may not be as effective as measures that aim to reduce within-class risk (e.g. mask-wearing and vaccines).


title: The minor allele of the CREBRF rs373863828 p.R457Q coding variant is associated with reduced levels of myostatin in males: Implications for body composition

abstract: The minor allele (A) of the rs373863828 variant (p.Arg457Gln) in CREBRF is restricted to indigenous peoples of the Pacific islands (including New Zealand M[a]ori and peoples of Polynesia), with a frequency up to 25% in these populations. This allele associates with a large increase in body mass index (BMI) but with significantly lower risk of type-2 diabetes (T2D). It is unclear whether the increased BMI is driven by increased adiposity or by increased lean mass. Hence, we undertook body composition analysis using DXA in 189 young men of M[a]ori and Pacific descent living in Aotearoa New Zealand. The rs373863828 A allele was associated with a trend toward increased relative lean mass although this was not statistically significant (p=0.06). Notably though this allele was associated with significantly lower circulating levels of the muscle inhibitory hormone myostatin (p<0.05). This was further investigated in two Arg458Gln knockin mouse models on FVB/Nj and C57Bl/6j backgrounds. Supporting the human data, significant increases in relative lean mass were observed in male knockin mice. This was more significant in older mice (p<0.01) where it was associated with increased grip strength (p<0.01) and lower levels of myostatin (p <0.05). Overall these results provide new evidence that the rs373863828 A-allele is associated with a reduction of myostatin levels which likely contributes to increased lean muscle mass component of BMI, at least in males.

category: endocrinology


title: Vitamin D status is associated with iron status, but not anemia, in African children

abstract: Vitamin D regulates the master iron hormone hepcidin, and iron in turn alters vitamin D metabolism. Although vitamin D and iron deficiency are highly prevalent globally little is known about their interactions in Africa. To evaluate associations between vitamin D and iron status we measured markers of iron status, inflammation, malaria parasitemia and 25-hydroxyvitamin D (25(OH)D) concentrations in 4509 children aged 0.3 months to 8 years living in Kenya, Uganda, Burkina Faso, The Gambia and South Africa. Prevalence of iron deficiency was 35.1%, and preva- lence of vitamin D deficiency was 0.6% and 7.8% as defined by 25(OH)D concentrations of <30 nmol/L and <50 nmol/L respectively. Children with 25(OH)D concentrations of <50 nmol/L had a 98% increased risk of iron deficiency (OR 1.98 [95% CI 1.52, 2.58]) compared to those with 25(OH)D concentrations >75 nmol/L. 25(OH)D concentrations variably influenced individual markers of iron status. Inflammation interacted with 25(OH)D concentrations to predict ferritin levels. The link between vitamin D and iron status should be considered in strategies to manage these nutrient deficiencies in African children.


title: Vitamin D deficiency and its association with iron deficiency in African children


title: Estimating the basic reproduction number at the beginning of an outbreak under incomplete data

abstract: We compare different methods of estimating the basic reproduction number, R0, focusing on the early stages of an epidemic, and considering weekly reports of new infecteds. We study three standard epidemiological models: SIR, SEIR, and SEAIR and examine the sensitivity of the estimators to the model structure. As some methods are developed assuming specific epidemiological models, our work adds a study of their performance in both the well- and miss-specified settings. We focus on parameters matching various types of respiratory viruses, although the general approach is easily extendable to other scenarios.


title: The age-stratified analytical model for the spread of the COVID-19 epidemic

abstract:
The previously developed ASILV model for calculating epidemic spread under conditions of lockdown and mass vaccination was modified to analyse the intensity of COVID-19 infection growth in the allocated age groups.

Comparison of the results of calculations of the epidemic spread, as well as the values of the seven-day incidence values with the corresponding observation data, shows their good correspondence for each of the selected age groups.

The greatest influence on the overall spread of the epidemic is in the 20-40 age groups. The relatively low level of vaccination and the high intensity of contact in these age groups contributes to the emergence of new waves of the epidemic, which is especially active when the virus mutates and the lockdown conditions are relaxed.

The intensity of the epidemic in the 90+ age group has some peculiarities compared to other groups, which may be explained by differences in contact patterns among individuals in this age group compared to others.

Approximate ratios for estimating mortality as a function of the intensity of infection for individual age groups are provided.

The proposed stratified ASILV model by age group will allow more detailed and accurate prediction of the spread of the COVID-19 epidemic, including when new, more transmissible versions of the virus mutate and emerge.


title: Variation in COVID-19 excess mortality by age, sex, and province within Italy

abstract: 1Although previous evidence suggests that the infection fatality rate from COVID-19 varies by age and sex, and that transmission intensity varies geographically within countries, no study has yet explored the age-sex-space distribution of excess mortality associated with the COVID pandemic. By applying the principles of small-area estimation to existing models formulations for excess mortality, this study develops a method for assessing excess mortality across small populations and assesses the pattern of COVID excess mortality by province, year, week, age group, and sex in Italy from March through May 2020. We estimate that 53,200 excess deaths occurred across Italy during this time period, compared to just 35,500 deaths where COVID-19 was registered as the underlying cause of death. Out of the total excess mortality burden, 97% of excess deaths occurred among adults over age 60, and 68% of excess deaths were concentrated among adults over age 80. The burden of excess mortality was unevenly distributed across the country, with just three of Italys 107 provinces accounting for 32% of all excess mortality. This method for estimating excess mortality can be adapted to other countries where COVID-19 diagnostic capacity is still insufficient, and could be incorporated into public health rapid response systems.


title: Adding a reaction-restoration type transmission rate dynamic law to the basic SEIR COVID-19 model

abstract: The classical SEIR model, being an autonomous system of differential equations, has important limitations when representing a pandemic situation. Particularly, the geometric unimodal shape of the epidemic curve is not what is generally observed. This work introduces the {beta}SEIR model, which adds to the classical SEIR model a differential law to model the variation in the transmission rate. It considers two opposite thrives generally found in a population: first, reaction to disease presence that may be linked to mitigation strategies, which tends to decrease transmission, and second, the urge to return to normal conditions that pulls to restore the initial value of the transmission rate. Our results open a wide spectrum of dynamic variabilities in the curve of new infected, which are justified by reaction and restoration thrives that affect disease transmission over time. Some of these dynamics have been observed in the existing COVID-19 disease data. In particular and to further exemplify the potential the model proposed in this article, we show its capability of capturing the evolution of the number of new confirmed cases of Chile and Italy for several months after epidemic onset, while incorporating a reaction to disease presence with decreasing adherence to mitigation strategies, as well as a seasonal effect on the restoration of the initial transmissibility conditions.


title: Optimising Early Management of Acute Severe Ulcerative Colitis in the Biologics Era: Admission Model for Intensification of Therapy in Acute Severe Colitis (ADMIT-ASC)

abstract:
Background & aimsWe aimed to determine whether changes in ulcerative colitis management have translated to improved outcomes, in order to develop a simple model to predict steroid non-response on admission.

MethodsOutcomes of 131 adult ASC admissions (117 patients) in Oxford, UK between 2015-19 were compared with prospectively collected data from 1992-3. All patients received standard treatment with intravenous corticosteroids and endoscopic disease activity scoring (UCEIS). Steroid non-response was defined as receiving rescue medical therapy or surgery. A predictive model created in the Oxford cohort was validated in Australia and India (110 hospitalised patients Gold Coast University Hospital 2015-20; 62 hospitalised patients AIIMS, New Delhi 2018-20).

ResultsIn the 2015-19 Oxford cohort, 71 (54%) patients received medical rescue therapy (27% ciclosporin, 27% anti-TNF), compared to 27% ciclosporin in 1992-3, p=0.0015. Only 15% required colectomy during admission vs 29% in 1992-3 (p=0.033). Admission CRP, albumin, and UCEIS scores predicted steroid non-response (FDR p=0.00066, 0.0066 and 0.015). A four-point model was developed involving CRP [≥]100mg/L (1 point), albumin [≤]25g/L (1 point), UCEIS [≥]4 (1 point) or [≥]7 (2 points). Scoring 0 or 4 was 100% predictive of steroid response and non-response, respectively, in all three cohorts. Patients scoring 3-4 had 83% risk of steroid non-response in Oxford and 84% (0.70-0.98) in the validation cohorts - OR 11.9 (10.8-13).

ConclusionColectomy rates for ASC have halved in 25 years, while use of rescue medical therapy has doubled. Patients who are highly unlikely to respond to parenteral steroid treatment alone may be readily identified on admission, to be prioritised for early intensification of therapy.

WHAT YOU NEED TO KNOWO_ST_ABSBackground and contextC_ST_ABSAcute severe colitis (ASC) requires hospitalisation and, frequently, colectomy. The accepted management of ASC is three-five days of intravenous steroids followed by protocolised response assessment.

New findingsMedical rescue therapy has doubled and the colectomy rate halved in 25 years. A predictive index identifying steroid non-response was derived and validated in three independent centres in three countries.

LimitationsA need remains to demonstrate that earlier rescue medical therapy for patients predicted to be steroid non-responders will further improve outcomes.

ImpactThe outcome of ASC has substantially improved in the past 25 years, with the potential for further improvement by identifying patients on admission for early escalation of therapy.

category: gastroenterology


title: Child Suicide Rates During the COVID-19 pandemic in England

abstract:
BackgroundThere is concern about the impact of COVID-19, and the control measures to prevent the spread, on childrens mental health. The aim of this work was to identify if there had been a rise of childhood suicide during the COVID pandemic; using data from Englands National Child Mortality Database (NCMD).

MethodChild suicide rates between April to December 2020 were compared with those in 2019 using negative binomial regression models, and characteristics compared. In a subset (1st January to 17th May 2020) further characteristics and possible contributing factors were obtained.

ResultsA total of 193 likely childhood deaths by suicide were reported. There was no evidence overall suicide deaths were higher in 2020 than 2019 (RR 1.09 (0.80-1.48), p=0.584) but weak evidence that the rate in the first lockdown period (April to May 2020) was higher than the corresponding period in 2019 (RR 1.56 (0.86-2.81), p=0.144). Characteristics of individuals were similar between periods. Restriction to education and other activities, disruption to care and support services, tensions at home and isolation appeared to be contributing factors.

LimitationsAs child suicides are fortunately rare, the analysis is based on small numbers of deaths with limited statistical power to detect anything but major increases in incidence.

ConclusionWe found no consistent evidence that child suicide deaths increased during the COVID-19 pandemic although there was a concerning signal they may have increased during the first UK lockdown. A similar peak was not seen during the following months, or the second lockdown.

category: psychiatry and clinical psychology


title: Comorbid-phenome prediction and phenotype risk scores enhance gene discovery for generalized anxiety disorder and posttraumatic stress disorder

abstract: UK Biobank (UKB) is a key contributor in mental health genome-wide association studies (GWAS) but only ~31% of participants completed the Mental Health Questionnaire ("MHQ responders"). We predicted generalized anxiety disorder (GAD), posttraumatic stress disorder (PTSD), and major depression symptoms using elastic net regression in the ~69% of UKB participants lacking MHQ data ("MHQ non-responders"; NTraining=50%; NTest=50%), maximizing the informative sample for these traits. MHQ responders were more likely to be female, from higher socioeconomic positions, and less anxious than non-responders. Genetic correlation of GAD and PTSD between MHQ responders and non-responders ranged from 0.636-1.08; both were predicted by polygenic scores generated from independent cohorts. In meta-analyses of GAD (N=489,579) and PTSD (N=497,803), we discovered many novel genomic risk loci (13 for GAD and 40 for PTSD). Transcriptomic analyses converged on altered regulation of prenatal dorsolateral prefrontal cortex in these disorders.


title: Polygenic profiles define aspects of clinical heterogeneity in ADHD

abstract: Attention deficit hyperactivity disorder (ADHD) is a complex disorder with heterogeneous clinical presentations that manifest variability in long-term outcomes. The genetic contributions to this clinical heterogeneity, however, are not well understood. Here, we study 14 084 individuals diagnosed with ADHD to identify several genetic factors underlying clinical heterogeneity. One genome-wide significant locus was specifically associated with an autism spectrum disorder (ASD) diagnosis among individuals diagnosed with ADHD and it was not previously associated with ASD nor ADHD, individually. We used a novel approach to compare profiles of polygenic scores for groups of individuals diagnosed with ADHD and uncovered robust evidence that biology is an important factor in on-going clinical debates. Specifically, individuals diagnosed with ASD and ADHD, substance use disorder (SUD) and ADHD, or first diagnosed with ADHD in adulthood had different profiles of polygenic scores for ADHD and multiple other psychiatric, cognitive, and socio-behavioral traits. A polygene overlap between an ASD diagnosis in ADHD and cognitive performance was replicated in an independent, typically developing cohort. Our unique approach uncovered evidence of genetic heterogeneity in a widely studied complex disorder, allowing for timely contributions to the understanding of ADHD etiology and providing a model for similar studies of other disorders.


title: Global research priorities for COVID-19 in maternal, reproductive and child health: results of an international survey

abstract:
BackgroundThe World Health Organizations "Coordinated Global Research Roadmap: 2019 Novel Coronavirus" outlined the need for research that focuses on the impact of COVID-19 on pregnant women and children. More than one year after the first reported case, significant knowledge gaps remain, highlighting the need for a coordinated approach. To address this need, the Maternal, Newborn and Child Health Working Group (MNCH WG) of the COVID-19 Clinical Research Coalition conducted an international survey to identify global research priorities for COVID-19 in maternal, reproductive and child health.

MethodThis project was undertaken using a modified Delphi method. An electronic questionnaire was disseminated to clinicians and researchers in three different languages (English, French and Spanish) via MNCH WG affiliated networks. Respondents were asked to select the five most urgent research priorities among a list of 17 identified by the MNCH WG. Analysis of questionnaire data was undertaken to identify key similarities and differences among respondents according to questionnaire language, location and specialty. Following elimination of the seven lowest ranking priorities, the questionnaire was recirculated to the original pool of respondents. Thematic analysis of final questionnaire data was undertaken by the MNCH WG from which four priority research themes emerged.

ResultsQuestionnaire 1 was completed by 225 respondents from 29 countries. Questionnaire 2 was returned by 49 respondents. The four priority research themes were 1) access to healthcare during the COVID-19 pandemic, 2) the direct and 3) indirect effects of COVID-19 on pregnant and breastfeeding women and children and 4) the transmission of COVID-19 and protection from infection.

ConclusionThe results of these questionnaires indicated a high level of concordance among continents and specialties regarding priority research themes. This prioritized list of research uncertainties, developed to specifically highlight the most urgent clinical needs as perceived by healthcare professionals and researchers, could help funding organizations and researchers to answer the most pressing questions for clinicians and public health professionals during the pandemic. It is hoped that these identified priority research themes can help focus the discussion regarding the allocation of limited resources to enhance COVID-19 research in MNCH globally.


title: Genomic surveillance of SARS-CoV-2 in the state of Parana, Southern Brazil, reveals the cocirculation of the VOC P.1, P.1-like-II lineage and a P.1 cluster harboring the S:E661D mutation

abstract: We report a genomic surveillance of SARS-CoV-2 lineages circulating in Parana, Southern Brazil, from March 2020 to April 2021. Our analysis, based on 333 genomes, revealed that the first variants detected in the state of Parana in March 2020 were the B.1.1.33 and B.1.1.28 variants. The variants B.1.1.28 and B.1.1.33 were predominant throughout 2020 until the introduction of the variant P.2 in August 2020 and a variant of concern (VOC), P.1, in January 2021. Phylogenetic analyses of the SARS-CoV-2 genomes that were previously classified as the VOC P.1 lineage by PANGO showed that some genomes from February to April 2021 branched in a monophyletic clade and that these samples grouped together with genomes recently described with the lineage P.1-like-II. An extended phylogenetic analysis, including SARS-CoV-2 genomes from all over Brazil, showed that the P.1-like-II lineage appears at a high frequency in the southern region of the country. The P.1-like-II lineage genomes share some, but not all, defining mutations of the VOC P.1. For instance, it has the previously described ORF1a:D2980H and N:P383 L unique mutations and the newly detected ORF1a:P1213 L and ORF1b:K2340N mutations. Additionally, a new mutation (E661D) in the spike (S) protein has been identified in nearly 10% of the genomes classified as the VOC P.1 from Parana in March and April 2021. We also report the identification of the S:W152C mutation in one genome from Parana, classified as the N.10 variant. Finally, we analyzed the correlation between the lineage and the P.1 variant frequency, age group (patients younger or older than 60 years old) and the clinical data of 86 cases from the state of Parana. This analysis does not support an association between the P.1 variant prevalence and COVID-19 severity or age strata. Our results provided a reliable picture of the evolution of the SARS-CoV-2 pandemic in the state of Parana characterized by the dominance of the P.1 strain, as well as a high frequencies of the P.1-like-II lineage and the S:E661D mutations. Epidemiological and genomic surveillance efforts should be continued to unveil the biological relevance of the novel mutations detected in the VOC P.1 in Parana.


title: EVALUATION OF THE PANBIO SARS-COV-2 RAPID ANTIGEN DETECTION TEST IN THE BAHAMAS

abstract: Identification and isolation of persons infected with SARS-COV-2 are key mitigation strategies in the current pandemic, and rapid antigen detection tests (RADTs) offer the promise of decreased turnaround time to diagnosis when compared with gold standard RT-PCR testing. We evaluated the analytical performance of the Abbott(R) Panbio RADT on nasopharyngeal samples stored at the Ministry of Health National Reference Lab in Nassau, Bahamas. The Panbio demonstrated a test sensitivity of 94% and a specificity of 100% on 50 PCR negative samples and 50 samples presumed to be infectious based on having PCR cycle threshold values below 30. Additionally, in our examination of operator results there was low interpersonal variation (1%) among three blind operators and significant correlation between sample Ct value and perceived signal strength on the RADT device. However, three PCR positive samples below Ct 30 were misdiagnosed by RADT, including one sample with Ct value less than 20. These results support the use of the Panbio in symptomatic persons to detect active SARS-COV-2 infections, with the caveat that RADT-negative samples should be confirmed by RT-PCR.


title: Gut bacterial tyrosine decarboxylase gene abundance associates with disease duration, medication exposure, and gastrointestinal symptoms in a longitudinal cohort of Parkinson's disease patients.

abstract: Gut microbiota influences the clinical response of a wide variety of orally administered drugs. However, the underlying mechanisms by which drug-microbiota interactions occur are still obscure. Previously, we reported that tyrosine decarboxylating (TDC) bacteria may restrict the levels of levodopa reaching the circulation in patients with Parkinsons disease (PD). We observed a significant positive association between disease duration and the abundance of the bacterial tdc-gene. The question arises whether increased exposure to anti-PD medication could affect the abundance of bacterial TDC, to ultimately impact drug efficacy. To this end, we investigated the potential association between anti-PD drug exposure and bacterial tdc-gene abundance over a time period of two years in a longitudinal cohort of PD patients and healthy controls. Our data reveal significant associations between tdc-gene abundance, anti-PD medication, and gastrointestinal symptoms and warrants further research on the effect of anti-PD medication on microbial changes and gastrointestinal-function.

category: neurology


title: PRISMA2020: an R package and Shiny app for producing PRISMA 2020-compliant flow diagrams, with interactivity for optimised digital transparency and Open Synthesis

abstract:
BackgroundReporting standards, such as PRISMA aim to ensure that the methods and results of systematic reviews are described in sufficient detail to allow full transparency. Flow diagrams in evidence syntheses allow the reader to rapidly understand the core procedures used in a review and examine the attrition of irrelevant records throughout the review process. Recent research suggests that use of flow diagrams in systematic reviews is poor and of low quality and called for standardised templates to facilitate better reporting in flow diagrams. The increasing options for interactivity provided by the Internet gives us an opportunity to support easy-to-use evidence synthesis tools, and here we report on the development of tools for the production of PRISMA 2020-compliant systematic review flow diagrams.

Methods and FindingsWe developed a free-to-use, Open Source R package and web-based Shiny app to allow users to design PRISMA flow diagrams for their own systematic reviews. Our tools allow users to produce standardised visualisations that transparently document the methods and results of a systematic review process in a variety of formats. In addition, we provide the opportunity to produce interactive, web-based flow diagrams (exported as HTML files), that allow readers to click on boxes of the diagram and navigate to further details on methods, results or data files. We provide an interactive example here; https://driscoll.ntu.ac.uk/prisma/.

ConclusionsWe have developed a user-friendly suite of tools for producing PRISMA 2020-compliant flow diagrams for users with coding experience and, importantly, for users without prior experience in coding by making use of Shiny. These free-to-use tools will make it easier to produce clear and PRISMA 2020-compliant systematic review flow diagrams. Significantly, users can also produce interactive flow diagrams for the first time, allowing readers of their reviews to smoothly and swiftly explore and navigate to further details of the methods and results of a review. We believe these tools will increase use of PRISMA flow diagrams, improve the compliance and quality of flow diagrams, and facilitate strong science communication of the methods and results of systematic reviews by making use of interactivity. We encourage the systematic review community to make use of these tools, and provide feedback to streamline and improve their usability and efficiency.

category: health policy


title: ANALYSIS OF FOUR DIFFERENT TRANSPORT AND PRESERVATION MEDIUM KITS FOR SARS-COV-2 DIAGNOSIS FROM NASOPHARYNGEAL SWAB BY REAL-TIME PCR: ADAPTING TO THE CONSTANTLY INCREASING DEMAND OF SAMPLING PROCESSING AND STOCK-OUTS DURING THE PANDEMIC

abstract: The high demand for supplies during the COVID19-pandemic has generated several stock-out of material and essential reagents needed to meet the current high demand for diagnosis in the worldwide population. In this way, there is limited information regarding the performance of different virus transport medium (VTM) for nasopharyngeal swab sampling (NPS) aimed for SARS-CoV-2 detection. We compared the RT-qPCR amplification profile of four different commercial transport medium kits, including DNA/RNA Shield, NAT, VTM, and Phosphate-buffered saline (PBS) transport medium, for NPSs samples from Central Metropolitan Health Service, Santiago, Chile. The RT-qPCR showed a slight lower RNase P Cq value of the samples preserved and transported in DNA/RNA Shield compared to NAT medium. By contrast, a marked increase in the RNase P Cq value was registered in the samples transported with VTM compared to DNA/RNA Shield medium. For PBS-preserved NPS, the performance of two strategies were assessed due to the potential presence of any remaining active virus in the sample: (1) thermal inactivation; and (2) thermal inactivation treatment followed by RNA extraction. The heat inactivation showed a significantly lower Cq value for RNase P and viral ORF1ab Cq compared to the followed by RNA extraction. This study indicates that new medium alternatives could be used if supplies run out to diagnose COVID19.


title: Clinical characterization and Genomic analysis of COVID-19 breakthrough infections during second wave in different states of India

abstract: During March to June 2021 India has experienced a deadly second wave of COVID-19 with an increased number of post-vaccination breakthrough infections reported across the country. To understand the possible reason of these breakthroughs we collected 677 clinical samples (throat swab/ nasal swabs) of individuals who had received two doses (n=592) and one dose (n=85) of vaccines (Covishield and Covaxin,) and tested positive for COVID-19, from 17 states/Union Territories of country. These cases were telephonically interviewed and clinical data was analyzed. A total of 511 SARS-CoV-2 genomes were recovered with genome coverage of higher than 98% from both the cases. Analysis of both the cases determined that 86.69% (n=443) of them belonged to the Delta variant along with Alpha, Kappa, Delta AY.1 and Delta AY.2. The Delta variant clustered into 4 distinct sub-lineages. Sub-lineage-I had mutations: ORF1ab-A1306S, P2046L, P2287S, V2930L, T3255I, T3446A, G5063S, P5401L, A6319V and N-G215C; Sub-lineage -II : ORF1ab- P309L, A3209V, V3718A, G5063S, P5401L and ORF7a-L116F; Sub-lineage -III : ORF1ab- A3209V, V3718A, T3750I, G5063S, P5401L and Spike-A222V; Sub-lineage -IV ORF1ab- P309L, D2980N, F3138S and spike - K77T. This study indicated that majority of the clinical cases in the breakthrough were infected with the Delta variant and only 9.8% cases required hospitalization while fatality was observed in only 0.4% cases. This clearly suggests that the vaccination does provide reduction in hospital admission and mortality.


title: Prospective, Randomized, Parallel-Group, Open-Label Study to Evaluate the Efficacy and Safety of IMU-838, in Combination with Oseltamivir, in Adults with Coronavirus Disease 19 The IONIC Trial

abstract:
BackgroundGlobally there is a scarcity of effective treatments for SARS-CoV-2 infections (causing COVID 19). Repurposing existing medications may offer the best hope for treating COVID 19 patients to curb the pandemic. IMU-838 is a dihydroorotate dehydrogenase (DHODH) inhibitor, which is an effective mechanism for antiviral effects against respiratory viruses. When used synergistically with Oseltamivir, therapeutic effects have been observed against influenza and SARS-CoV-2 in rodents.(13) The IONIC trial is a randomized control trial that will investigate whether time to clinical improvement in COVID 19 patients is improved following a 14 day course of IMU-838 + Oseltamivir versus Oseltamivir alone.

MethodsIONIC trial is an open label study in which participants will be randomised 1:1 in two parallel arms; the intervention arm (IMU-838 + Oseltamivir) and control arm (Oseltamivir only). The primary outcome is time-to-clinical improvement; defined as the time from randomisation to: a 2-point improvement on WHO ordinal scale; discharge from hospital, or death (whichever occurs first). The study is sponsored by UHCW NHS Trust and funded by LifeArc.

DiscussionThe IONIC Protocol describes an overarching trial design to provide reliable evidence on the efficacy of IMU-838 (vidofludimus calcium) when delivered in combination with an antiviral therapy (Oseltamivir) [IONIC Intervention] for confirmed or suspected COVID-19 infection in adult patients receiving usual standard of care.

Trial RegistrationThe trial was registered with EudraCT (2020-001805-21) on 09.04.2020 and ISRCTN on 23.09.2020 (ISRCTN53038326) and Clinicaltrials.gov on 17.08.2020 (NCT04516915)

Strengths and LimitationsThis study is the first to recruit participants in the trial exploring the effectiveness of IMU-838 in COVID-19. In addition, we believe it is the only trial exploring the effectiveness of IMU-838 in combination with Oseltamivir (Tamiflu) in patients with moderate to severe COVID-19. However, to make the trial design flexible due to the on-going pandemic the trial is un-blinded.


title: Detection and whole-genome sequencing of SARS-CoV-2 B.1.617.2 and B.1.351 variants of concern from Pakistan during the COVID-19 third wave

abstract: The viral lineages reflecting variants of concern have emerged worldwide and among them B.1.1.7 (Alpha), B.1351 (Beta) and B.1.617.2 (Delta) variants are the most significant ones and merit close monitoring. In Pakistan, very limited information is available on the circulation of these variants and only the alpha variant has been reported as the main circulating lineage. The objective of this study was to detect and explore the genomic diversity of B.1.351 and B.1.617.2 during the third wave in the indigenous population. During the current study, a total of 2274 samples were tested on real-time PCR for the presence of SARS-CoV-2 from May 14 to May 31, 2021, and among these, 17% were spike positive, whereas 83% of samples had the spike gene target failure (SGTF). From these spike positive samples, 22 samples were processed for whole-genome sequencing. Among VOCs, 45.5% (n=10) belonged to B.1.351 followed by B.1.617.2, 36% (n=8). The delta variant cases were reported mostly from Islamabad (n = 5; 63%) followed by Peshawar and Azad Kashmir (n = 1; 13% each). Beta variant cases originated from Islamabad (n=5; 56%), Peshawar (n=2; 22%), Azad Kashmir and Rawalpindi (n=1; 11% each). The mutation profile of delta variant isolates reported significant mutations, L452R, T478K, P681R, and D950N. The beta variant isolates reported characteristic mutations, D215G, K417N, E484K, N501Y, and A701V. Notably, a characteristic mutation, E484Q was also found in delta variant, B.1.617.2. Our current findings suggest detection of these VOCs from the local population and warrants large-scale genomic surveillance in the country. In addition, it provides timely information to the health authorities to take appropriate actions.


title: Antibody persistence and neutralising activity in primary school students and staff: prospective active surveillance, June to December 2020, England

abstract:
IntroductionSARS-CoV-2 serological studies have so far focused mainly on adults. Public Health England initiated prospective, longitudinal SARS-CoV-2 sero-surveillance in schools across England after the first national lockdown, which allowed comparison of child and adult responses to SARS-CoV-2 infection over time.

MethodsStaff and students had venepuncture for SARS-CoV-2 antibodies in school during June, July and December 2020. Blood samples were tested for nucleocapsid (Abbott) and receptor binding domain (RBD) antibodies (in-house assay), and student samples were additionally assessed for live virus neutralising activity.

ResultsIn June 2020, 1,344 staff and 835 students were tested. Overall, 11.5% (95% CI: 9.4-13.9) and 11.3% (95% CI: 9.2-13.6; p=0.88) of students had nucleoprotein and RBD antibodies, compared to 15.6% (95% CI: 13.7-17.6) and 15.3% (95% CI: 13.4-17.3; p=0.83) of staff. Live virus neutralising activity was detected in 79.8% (n=71/89) of nucleocapsid and 85.5% (71/83) of RBD antibody positive children. RBD antibodies correlated more strongly with neutralising antibodies (rs=0.7527; p<0.0001) than nucleocapsid antibodies (rs=0.3698; p<0.0001). A median of 24.4 weeks later, 58.2% (107/184) participants had nucleocapsid antibody seroreversion, compared to 20.9% (33/158) for RBD (p<0.001). Similar seroreversion rates were observed between staff and students for nucleocapsid (p=0.26) and RBD-antibodies (p=0.43). Nucleocapsid and RBD antibody quantitative results were significantly lower in staff compared to students (p=0.028 and <0.0001 respectively) at baseline, but not at 24 weeks (p=0.16 and p=0.37, respectively).

ConclusionRBD antibodies correlated more strongly with live virus neutralising activity. Most seropositive students and staff retained RBD antibodies for >6 months after SARS-CoV-2 infection.


title: Pre-existing antibodies targeting a dominant linear antibody epitope on SARS-CoV-2 S2 cross-reacted with commensal gut bacteria and shaped immune responses elicited by a candidate vaccine

abstract: The origins of pre-existing SARS-CoV-2 cross-reactive antibodies and their potential impacts on vaccine efficacy have not been fully clarified. In this study, we demonstrated that S2 was the prevailing target of the pre-existing S protein cross-reactive antibodies in both healthy human and SPF mice. A dominant antibody epitope was identified on the connector domain of S2 (1147-SFKEELDKYFKNHT-1160, P144), which could be recognized by pre-existing antibodies in both human and mouse. Through metagenomic sequencing and fecal bacteria transplant, we proved that the generation of S2 cross-reactive antibodies was associated with commensal gut bacteria. Furthermore, six P144 specific monoclonal antibodies were isolated from naive SPF mice and proved to cross-react with commensal gut bacteria collected from both human and mouse. Mice with high levels of pre-existing S2 cross-reactive antibodies mounted higher S protein specific binding antibodies, especially against S2, after being immunized with a SARS-CoV-2 S DNA vaccine. Similarly, we found that levels of pre-existing S2 and P144 reactive antibodies correlated positively with RBD specific binding antibody titers after two doses of inactivated SARS-CoV-2 vaccination in human. Finally, we provided data demonstrating that immunization of a SARS-CoV-2 S DNA vaccine could alter the gut microbiota compositions of mice.


title: Pre-existing antibodies targeting a linear epitope on SARS-CoV-2 S2 cross-reacted with commensal gut bacteria and shaped vaccine induced immunity


title: Characterization of long-term patient-reported symptoms of COVID-19: an analysis of social media data

abstract: As the SARS-CoV-2 virus (COVID-19) continues to affect people across the globe, there is limited understanding of the long term implications for infected patients1-3. While some of these patients have documented follow-ups on clinical records, or participate in longitudinal surveys, these datasets are usually designed by clinicians, and not granular enough to understand the natural history or patient experiences of  long COVID. In order to get a complete picture, there is a need to use patient generated data to track the long-term impact of COVID-19 on recovered patients in real time. There is a growing need to meticulously characterize these patients experiences, from infection to months post-infection, and with highly granular patient generated data rather than clinician narratives. In this work, we present a longitudinal characterization of post-COVID-19 symptoms using social media data from Twitter. Using a combination of machine learning, natural language processing techniques, and clinician reviews, we mined 296,154 tweets to characterize the post-acute infection course of the disease, creating detailed timelines of symptoms and conditions, and analyzing their symptomatology during a period of over 150 days.


title: The temporal correlation between positive testing and death in Italy: from the first phase to the later evolution of the COVID-19 pandemic

abstract: After the global spread of the novel coronavirus disease 2019 (COVID-19), research has concentrated its efforts on several aspects of the epidemiological burden of pandemic. In this frame, the presented study follows a previous analysis of the temporal link between cases and deaths during the first epidemic wave (Phase 1) in Italy (March-June 2020). We here analyze the COVID-19 epidemic in the time span from March 2020 to June 2021. The elaboration of the curves of cases and deaths allows identifying the temporal shift between the positive testing and the fatal event, which corresponds to one week from W2 to W33, two weeks from W34 to W41, and three weeks from W42 to W67. Based on this finding, we calculate the Weekly Lethality Rate (WLR). The WLR was grossly overestimated (~13.5%) in Phase 1, while a mean value of 2.6% was observed in most of Phase 2 (starting from October 2020), with a drop to 1.4% in the last investigated weeks. Overall, these findings offer an interesting insight into the magnitude and time evolution of the lethality burden attributable to COVID-19 during the entire pandemic period in Italy. In particular, the analysis highlighted the impact of the effectiveness of public health and social measures, of changes in disease management, and of preventive strategies over time.


title: Contamination of personal protective equipment during COVID-19 autopsies

abstract: Confronted with an emerging infectious disease, the medical community faced relevant concerns regarding the performance of autopsies of COVID-19 deceased at the beginning of the pandemic. This attitude has changed, and autopsies are now recognized as indispensable tools for elucidating COVID-19; despite this, the true risk of infection for autopsy staff is still debated. To elucidate the rate of SARS-CoV-2 contamination in personal protective equipment (PPE), swabs were taken at nine locations of the PPE of one physician and an assistant each from 11 full autopsies performed at four different centers. Further samples were obtained for three minimally invasive autopsies (MIA) conducted at a fifth center. Lung/bronchus swabs of the deceased served as positive controls. SARS-CoV-2 RNA was detected by RT-qPCR. In 9/11 full autopsies PPE samples were tested RNA positive with PCR, in total 21% of all PPE samples taken. The main contaminated parts of the PPE were the gloves (64% positive), the aprons (50% positive), and the upper sides of shoes (36% positive) while for example the fronts of safety goggles were only positive in 4.5% of the samples and all face masks were negative. In MIA, viral RNA was observed in one sample from a glove, but not in other swabs. Infectious virus isolation in cell culture was performed in RNA positive swabs from full autopsies. Of all RNA positive PPE samples, 21% of the glove samples were positive for infectious virus taken in 3/11 full autopsies. In conclusion, in >80% of autopsies, PPE was contaminated with viral RNA. In >25% of autopsies, PPE was found to be even contaminated with infectious virus, signifying a potential risk of infection among autopsy staff. Adequate PPE and hygiene measures, including appropriate waste deposition, are therefore mandatory to enable safe work environment.

category: pathology


title: Predicting cause of death from free-text health summaries: development of an interpretable machine learning tool

abstract:
Structured AbstractO_ST_ABSPurposeC_ST_ABSAccurately assigning cause of death is vital to understanding health outcomes in the population and improving health care provision. Cancer-specific cause of death is a key outcome in clinical trials, but assignment of cause of death from death certification is prone to misattribution, therefore can have an impact on cancer-specific trial mortality outcome measures.

MethodsWe developed an interpretable machine learning classifier to predict prostate cancer death from free-text summaries of medical history for prostate cancer patients (CAP). We developed visualisations to highlight the predictive elements of the free-text summaries. These were used by the project analysts to gain an insight of how the predictions were made.

ResultsCompared to independent human expert assignment, the classifier showed >90% accuracy in predicting prostate cancer death in test subset of the CAP dataset. Informal feedback suggested that these visualisations would require adaptation to be useful to clinical experts when assessing the appropriateness of these ML predictions in a clinical setting. Notably, key features used by the classifier to predict prostate cancer death and emphasised in the visualisations, were considered to be clinically important signs of progressing prostate cancer based on prior knowledge of the dataset.

ConclusionThe results suggest that our interpretability approach improve analyst confidence in the tool, and reveal how the approach could be developed to produce a decision-support tool that would be useful to health care reviewers. As such, we have published the code on GitHub to allow others to apply our methodology to their data (https://zenodo.org/badge/latestdoi/294910364).


title: CAUSES AND CONSEQUENCES OF STIGMA LEADING TO MENTAL DISORDERS AMONG LEPROSY AFFECTED: KEY ELEMENTS IN THE PROCESS OF COUNSELLING TO IMPROVE MENTAL HEALTH CARE

abstract:
Despite counselling has been in practice for quite a long time not yet an essential ingredient in leprosy control programmes especially in India nor a standardised system is available for prevention of mental disorders. With the broad objective to fulfil this need an action research was carried out to explore the unfulfilled needs of leprosy affected that are creating crisis situations lead to mental health issues while experimenting a practicably affective process of counselling system and document the essential stages to be involved in carrying out inter-personal counselling on each ones unique problems. The study was conducted by the Psych-social counselling and Guidance Centre of Gandhi Memorial Leprosy Foundation on 146 leprosy affected. Counselling provided by trained counsellors in every monthly visit for MDT till declared RFT or afterwards.

ResultsSystematic process of counselling needs to be caried out in the following five essential stages viz Rapport Establishment, Identification of Crisis Situation, Psycho-Social Diagnosis, Prescription of Counselling Elements and Fulfilment of counselling elements

Majority or psychological problems initially develop due to cognitive issues of affected individuals, their family members, society members, work place, institutions and treatment centres etc. If not attended at initial stage result to treatment compliance issues leading to deformity which accelerates adjustment problems in the family, society, workplace, educational and other institutions thus in turn lead in to unemployment, stigmatization of the patient from family and all sorts of mental disorders.. prior to reaching the stage of needing treatment.

The study concludes that a systematic counselling addressing the issues at the cognitive level also including decision makers in the family, along with leprosy treatment can be a successful method to prevent the mental health problems and throw light towards zero stigma

category: health systems and quality improvement


title: Development and Validation of a Multivariable Risk Prediction Model for Sudden Cardiac Death after Myocardial Infarction (PROFID Risk Model): Study Rationale, Design and Protocol

abstract:
IntroductionSudden cardiac death (SCD) is the leading cause of death in patients with myocardial infarction (MI) and can be prevented by the implantable cardioverter defibrillator (ICD). Currently, risk stratification for SCD and decision on ICD implantation are based solely on impaired left ventricular ejection fraction (LVEF). However, this strategy leads to over- and under-treatment of patients because LVEF alone is insufficient for accurate assessment of prognosis. Thus, there is a need for better risk stratification. This is the study protocol for developing and validating a prediction model for risk of SCD in patients with prior MI.

Methods and AnalysisThe EU funded PROFID project will analyse 23 datasets from Europe, Israel and the US ([~]225,000 observations). The datasets include patients with prior MI or ischemic cardiomyopathy with reduced LVEF<50%, with and without a primary prevention ICD. Our primary outcome is SCD in patients without an ICD, or appropriate ICD therapy in patients carrying an ICD as a SCD surrogate. For analysis, we will stack 18 of the datasets into a single database (datastack), with the remaining analysed remotely for data governance reasons (remote data). We will apply 5 analytical approaches to develop the risk prediction model in the datastack and the remote datasets, all under a competing risk framework: 1) Weibull model, 2) flexible parametric survival model, 3) random forest, 4) likelihood boosting machine, and 5) neural network. These dataset-specific models will be combined into a single model (one per analysis method) using model aggregation methods, which will be externally validated using systematic leave-one-dataset-out cross-validation. Predictive performance will be pooled using random effects meta-analysis to select the model with best performance.

Ethics and disseminationLocal ethical approval was obtained. The final model will be disseminated through scientific publications and a web-calculator. Statistical code will be published through open-source repositories.

category: cardiovascular medicine


title: Relative Ratios of Human Seasonal Coronavirus Antibodies Predict the Efficiency of Cross-Neutralization of SARS-CoV-2 Spike Binding to ACE2

abstract:
BackgroundAntibodies raised against human seasonal coronaviruses (sCoVs), which are responsible for the common cold, are known to cross-react with SARS-CoV-2 antigens. This prompts questions about their protective role against SARS-CoV-2 infections and COVID-19 severity. However, the relationship between sCoV exposure and SARS-CoV-2 correlates of protection are not clearly identified.

MethodsWe performed a cross-sectional analysis of cross-reactivity and cross-neutralization to SARS-CoV-2 antigens (S-RBD, S-trimer, N) using pre-pandemic serum from four different groups: pediatrics and adolescents, persons 21 to 70 years of age, older than 70 years of age, and persons living with HCV or HIV.

FindingsAntibody cross-reactivity to SARS-CoV-2 antigens varied between 1.6% and 15.3% depending on the cohort and the isotype-antigen pair analyzed. We also show a range of neutralizing activity (0-45%) in serum that interferes with SARS-CoV-2 spike attachment to ACE2. While the abundance of sCoV antibodies did not directly correlate with neutralization, we show that neutralizing activity is rather dependent on relative ratios of IgGs in sera directed to all four sCoV spike proteins. More specifically, we identified antibodies to NL63 and OC43 as being the most important predictors of neutralization.

InterpretationOur data support that exposure to sCoVs triggers antibody responses that influence the efficiency of SARS-CoV-2 spike binding to ACE2, and may also impact COVID-19 disease severity through other latent variables.

Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSThere is a growing body of evidence showing that within the population there are varying levels of pre-existing immunity to SARS-CoV-2 infection and possibly COVID-19 disease severity. This immunity is believed to be attributable to prior infection by four prevalent seasonal coronaviruses (sCoVs) responsible for the common cold. Pre-existing immunity can be assessed in part by antibodies directed to sCoVs that also cross-react to SARS-CoV-2 antigens. The SARS-CoV-2 spike and, more specifically, the receptor binding domain are the primary targets for neutralizing antibodies. It is unclear if cross-reactive antibodies to SARS-CoV-2 are neutralizing and are also responsible for the broad spectrum of COVID-19 disease severity, from asymptomatic to critical, observed in the infected population.

Added-value of this studyHere we carried out a detailed analysis of sCoV prevalence in samples acquired before the pandemic from individuals of various age groups and in people living with HIV and HCV. We then analyzed the frequency of all the different types of antibodies that cross-react to three SARS-CoV-2 antigens. We found a high level of people with cross-reactive antibodies, surprisingly we also detected that some people have antibodies that block the SARS-CoV-2 spike from binding to its human receptor, ACE2. By using machine learning, we were able to accurate predict which individuals can neutralize SARS-CoV-2 spike-ACE2 interactions based on their relative ratios of antibodies against the four sCoVs.

Implications of all the available evidenceWe demonstrate that it not absolute levels of sCoVs antibodies that are predictive of neutralization but the relative ratios to all four sCoVs, with NL63 being the most weighted for this prediction. Machine learning also highlighted the existence of latent variables that contribute to the neutralization and that may be related to the type of cellular immune response triggered by the infection to certain sCoVs. This study is one of the first to identify a functional relationship between prior-exposure to sCoV and the establishment of a certain degree of immunity to SARS-CoV-2 by way of a cross-reactive antibody response.

Graphical Abstract

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title: Harnessing the power of polygenic risk scores to predict type 2 diabetes and its subtypes in a high-risk population of British Pakistanis and Bangladeshis in a routine healthcare setting

abstract:
BackgroundType 2 diabetes is highly prevalent in British Pakistanis and Bangladeshis (BPB). The Genes & Health (G&H) cohort offers means to explore genetic determinants of disease in BPBs.

MethodsWe assessed whether common genetic loci associated with type 2 diabetes in European-ancestry individuals (EUR) replicate in G&H. We constructed a type 2 diabetes polygenic risk score (PRS) and combined it with a clinical risk instrument (QDiabetes) to build a novel, integrated risk tool (IRT). We compared IRT performance using net reclassification index (NRI) versus QDiabetes alone.We compared PRS distribution between type 2 diabetes subgroups identified by clinical features at diagnosis.

FindingsWe replicated fewer loci in G&H (n = 76/338, 22%) than would be expected given power if all EUR-ascertained loci were transferable (n = 95, 28%) (p-value = 0.01). In 13,648 patients free from type 2 diabetes followed up for 10 years, NRI was 3.2% for IRT versus QDiabetes (95% confidence interval 2.0 - 4.4%). IRT performed best in reclassification of young adults deemed low risk by QDiabetes as high risk. PRS was independently associated with progression to type 2 diabetes after gestational diabetes (p = 0.028). Mean type 2 diabetes PRS differed between phenotypically-defined type 2 diabetes subgroups (p = 0.002).

InterpretationThe type 2 diabetes PRS has broad potential clinical application in BPB, improving identification of type 2 diabetes risk (especially in the young), and characterisation of subgroups at diagnosis.

FundingWellcome Trust, MRC, NIHR, and others.

Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSPeople of south Asian origin are disproportionately affected by type 2 diabetes, yet are underrepresented in genetic studies assessing its causation. To date, there have been no published studies that systematically assess how type 2 diabetes genetic risk loci identified in European individuals can be transferred into south Asians, taking into account power and differences in linkage disequilibrium, nor has the clinical utility of a type 2 diabetes polygenic risk score (PRS) been evaluated in this ethnic group. For coronary artery disease, integration of PRS with clinical risk tools has been shown to enhance the prediction of incident disease, in multiple ancestral groups. For type 2 diabetes, whilst it is known from multiple studies of Europeans that PRS can enhance prediction of incident disease, no study has examined PRS performance when integrated with an existing clinical risk tool, although it has potentially significant clinical impact. The identification of type 2 diabetes subgroups at disease presentation has now been studied extensively, but the influence of polygenic risk in characterising these subgroups has not been tested. We examined prior evidence using multiple updated searches across MEDLINE, CINAHL, EMBASE, MEDRXIV and BIORXIV on 29/6/2021 with terms including "type 2 diabetes" and "polygenic risk scor$," "genetic risk scor$", "subgroup", and "cluster" did not identify similar published work.

Added value of this studyIn the first study to systematically assess the transferability of genetic loci associated with type 2 diabetes in European ancestry individuals into a British Pakistanis and Bangladeshis (BPBs), we find fewer transferable loci than would be expected, accounting for power. We also construct a type 2 diabetes PRS for BPBs and show that its integration with QDiabetes enhances 10-year prediction of incident type 2 diabetes, especially in individuals aged less than 40 years deemed low risk by QDiabetes alone, who tended to be free from comorbidities, and relatively slim. Additionally, we find the PRS is independently associated with progression from gestational diabetes mellitus to type 2 diabetes in BPBs, replicating previous findings in European individuals. We replicate previously-reported subgroups of type 2 diabetes in BPBs, including Mild Age-Related Diabetes, Mild Obesity-Related Diabetes, and Insulin-Resistant Diabetes, and show that PRS distribution differs between clinically-defined clusters. In a novel clustering approach integrating PRS with clinical features, we identify a previously unreported subgroup we name "Clinically Undifferentiated High Polygenic Susceptibility Diabetes", and observe differences in rates of progression to micro- and macrovascular complications between subgroups.

Implications of all the available evidenceA single, low-cost genotyping array can now determine the polygenic risk of multiple diseases in parallel at any point in the life course. We build on existing genomic resources to build a type 2 diabetes PRS that can be used to predict incident disease in a specific ancestral group that is disproportionately affected by the condition. We show that a PRS, when integrated with an established and well-validated clinical risk algorithm, has significant potential clinical utility as both a means to better estimate individual disease risk, and to elucidate the influence of genetics on disease subgroups to aid future efforts to stratify care and treatment of the disease.


title: Polygenic Risk Prediction using Gradient Boosted Trees Captures Non-Linear Genetic Effects and Allele Interactions in Complex Phenotypes

abstract: Polygenic risk scores (PRS) are commonly used to quantify the inherited susceptibility for a given trait. However, the standard PRS fail to account for non-linear and interaction effects between single nucleotide polymorphisms (SNPs). Machine learning algorithms can be used to account for such non-linearities and interactions. We trained and validated polygenic prediction models for five complex phenotypes in a multi-ancestry population: total cholesterol, triglycerides, systolic blood pressure, sleep duration, and height. We used an ensemble method of LASSO for feature selection and gradient boosted trees (XGBoost) for non-linearities and interaction effects. In an independent test set, we found that combining a standard PRS as a feature in the XGBoost model increases the percentage variance explained (PVE) of the prediction model compared to the standard PRS by 25% for sleep duration, 26% for height, 44% for systolic blood pressure, 64% for triglycerides, and 85% for total cholesterol. Machine learning models trained in specific racial/ethnic groups performed similarly in multi-ancestry trained models, despite smaller sample sizes. The predictions of the machine learning models were superior to the standard PRS in each of the racial/ethnic groups in our study. However, among Blacks the PVE was substantially lower than for other groups. For example, the PVE for total cholesterol was 8.1%, 12.9%, and 17.4% for Blacks, Whites, and Hispanics/Latinos, respectively. This work demonstrates an effective method to account for non-linearities and interaction effects in genetics-based prediction models.


title: The cost of building an environmental surveillance system for typhoid

abstract:
IntroductionThe typhoid conjugate vaccine is a safe and effective method for preventing Salmonella enterica serovar Typhi (typhoid) and the WHOs guidance supports its use in locations with ongoing transmission. However, many countries lack a robust clinical surveillance system, making it challenging to determine where to use the vaccine. Environmental surveillance is an alternative approach to identify ongoing transmission, but the cost to implement such a strategy is previously unknown.

MethodsWe estimated the cost of an environmental surveillance program for thirteen potential protocols. Unit costs were obtained from research labs involved in protocol development and equipment information was obtained from manufacturers and expert opinion. The cost model includes thirteen components and twenty-seven pieces of equipment. We used Monte Carlo simulations to project total costs.

ResultsTotal costs per sample including setup, overhead, and operational costs, range from $357-794 at a scale of 25 sites to $116-532 at 125 sites. Operational costs (ongoing expenditures) range from $218-584 per sample (25 sites) to $74-421 (125 sites). Eleven of the thirteen protocols have operational costs below $200 at this higher scale. Protocols with high up-front equipment costs benefit more from scale efficiencies. Sensitivity analyses show that laboratory labor, process efficiency, and the cost of consumables are the primary drivers of cost.

ConclusionAt scale, environmental surveillance may be affordable, depending on the protocol chosen and the geographic context. Costs will need to be considered along with protocol sensitivity. Opportunities to leverage existing infrastructure and multi-disease platforms may be necessary to further reduce costs.

Summary BoxO_ST_ABSWhat is already known?C_ST_ABSEnvironmental surveillance has been used for polio transmission surveillance to target vaccination campaigns to prevent outbreaks. Similarly, methods for typhoid environmental surveillance are being developed, and could be used to support vaccine introduction decisions, if they are accurate and affordable.

What are the new findings?Across the scenarios examined, operational costs are between $74-584 per sample depending on the scale and protocol selected. Operational costs are 67-79% of total annualized costs across the same permutations.

What do the new findings imply?Policymakers can use these estimates and understanding of the efficiency of scale benefits in order to design a surveillance system that balances total cost with surveillance sensitivity and geographic coverage.

category: health economics


title: Global and regional prevalence and outcomes of COVID-19 in people living with HIV: A systematic review and meta-analysis

abstract:
BackgroundThe relationship between HIV infection and COVID-19 clinical outcome is uncertain, with conflicting data and hypotheses. We aimed to assess the prevalence and risk of severe COVID-19 and death in people living with HIV (PLWH) on the global and continental level.

MethodsElectronic databases were systematically searched in July 2021. Studies were screened and then extracted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Narratives were synthesised and data pooled for global and continental prevalence and relative risk of severity and mortality in HIV-infected COVID-19 patients using random-effect model. Risk of bias was assessed using the Newcastle-Ottawa score, Eggers test and presented as funnel plots.

ResultsA total of 46 studies were included involving 18,034,947 COVID-19 cases of which 31,269 were PLWH. The global prevalence of PLWH with SARS-CoV-2 infection was 1% (95% CI = 0.9% -1.1%) with the highest prevalence observed in sub-Saharan Africa. The relative risk (RR) of COVID-19 severity was significant only in Africa (RR, 95% CI = 1.14, 1.08 - 1.24) while risk of COVID-19 mortality was 1.53% (95% CI = 1.45 - 2.03) globally. The prevalence of PLWH in COVID-19 cases was significantly low, and the calculated global risk ratio show that HIV infection may be linked with increased COVID-19 death. The between-studies heterogeneity was significantly high while risk of publication bias was not significant.

ConclusionThere is low prevalence of HIV-SARS-CoV-2 co-infection. HIV infection was linked with severe COVID-19 in Africa and increased risk of death globally.

category: hiv aids


title: Impact of BNT162b2 vaccination and isolation on SARS-CoV-2 transmission in Israeli households: an observational study

abstract:
BackgroundMassive vaccination rollouts against SARS-CoV-2 infections have facilitated the easing of control measures in countries like Israel. While several studies have characterized the effectiveness of vaccines against severe forms of COVID-19 or SARS-CoV-2 infection, estimates of their impact on transmissibility remain limited. Here, we evaluated the role of vaccination and isolation on SARS-CoV-2 transmission within Israeli households.

MethodsFrom December 2020 to April 2021, confirmed cases were identified among healthcare workers of the Sheba Medical Centre and their family members. Households were recruited and followed up with repeated PCR for a minimum of ten days after case confirmation. Symptoms and vaccination information were collected at the end of follow-up. We developed a data augmentation Bayesian framework to ascertain how age, isolation and BNT162b2 vaccination with more than 7 days after the 2nd dose impacted household transmission of SARS-CoV-2.

Findings210 households with 215 index cases were enrolled. 269 out of 687 (39%) household contacts developed a SARS-CoV-2 infection. Of those, 170 (63%) developed symptoms. Children below 12 years old were less susceptible than adults/teenagers (Relative Risk RR=0{middle dot}50, 95% Credible Interval CI 0{middle dot}32-0{middle dot}79). Vaccination reduced the risk of infection among adults/teenagers (RR=0{middle dot}19, 95% CI 0{middle dot}07-0{middle dot}40). Isolation reduced the risk of infection of unvaccinated adult/teenager (RR=0{middle dot}11, 95% CI 0{middle dot}05-0{middle dot}19) and child contacts (RR=0{middle dot}16, 95% CI 0{middle dot}07-0{middle dot}31) compared to unvaccinated adults/teenagers that did not isolate. Infectivity was significantly reduced in vaccinated cases (RR=0{middle dot}22, 95% CI 0{middle dot}06-0{middle dot}70).

InterpretationWithin households, vaccination reduces both the risk of infection and of transmission if infected. When contacts were not vaccinated, isolation also led to important reductions in the risk of transmission. Vaccinated contacts might reduce their risk of infection if they isolate, although this requires confirmation with additional data.

FundingSheba Medical Center.

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSThe efficacy of vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmissions in households remains understudied. On June 28, 2021, we searched PubMed and medRxiv for articles published between December 1, 2020, and June 28, 2021, using the following combination of search terms: ("COVID-19" OR "SARS-CoV-2") AND ("household*" OR "famil*") AND "transmission" AND "vaccination". Our search yielded two articles that investigated the effect of vaccination on SARS-CoV-2 transmission in households. They showed a lower risk of infection in households with vaccinees. Vaccine efficacy on the risk of infection was estimated to 80% after the 2nd dose, and vaccine efficacy on the risk of transmission if infected was estimated to 49% 21 days after the 1st dose. However, these estimates are derived from surveillance data with no active follow-up of the households. In addition, the impact of isolation precautions has not been assessed.

Added value of this studyBased on the active follow-up of households of health care workers from the Sheba Medical Center in Israel, we estimated the effect of vaccination on household transmission. To our knowledge, our study is the first to conjointly investigate the effect of vaccination, age, and isolation precautions on the risk of infection and the risk of transmission in households while accounting for tertiary infections in the household, infections within the community, the reduced infectivity of asymptomatic cases, misidentification of index cases, and household size. Our study confirmed the high efficacy of BNT-162b2 vaccination to reduce infection risk and transmission risk. It also suggests that isolation might remain beneficial to vaccinated contacts.

Implications of all the available evidenceVaccination reduces susceptibility to infection and case infectivity in households. Isolation precautions also mitigate the risk of infection and should be implemented whenever a household member is infected. They might remain beneficial to vaccinated contacts.