title: Prolonged SARS-CoV-2 RNA virus shedding and lymphopenia are hallmarks of COVID-19 in cancer patients with poor prognosis

abstract: Patients with cancer are at higher risk of severe coronavirus infectious disease 2019 (COVID-19), but the mechanisms underlying virus-host interactions during cancer therapies remain elusive. When comparing nasopharyngeal swabs from cancer and non-cancer patients for RT-qPCR cycle thresholds measuring acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in 1063 patients (58% with cancer, 89% COVID-19+), we found that malignant disease favors the magnitude and duration of viral RNA shedding concomitant with prolonged serum elevations of type 1 IFN that anticorrelated with anti-RBD IgG antibodies. Chronic viral RNA carriers exhibited the typical immunopathology of severe COVID-19 at the early phase of infection including circulation of immature neutrophils, depletion of non-conventional monocytes and a general lymphopenia that, however, was accompanied by a rise in plasmablasts, activated follicular T helper cells, and non-naive Granzyme B+ FasL+, EomehighTCF-1high, PD-1+CD8+ Tc1 cells. Virus-induced lymphopenia worsened cancer-associated lymphocyte loss, and low lymphocyte counts correlated with chronic SARS-CoV-2 RNA shedding, COVID-19 severity and a higher risk of cancer-related death in the first and second surge of the pandemic. Lymphocyte loss correlated with significant changes in metabolites from the polyamine and biliary salt pathways as well as increased blood DNA from Enterobacteriaceae and Micrococcaceae gut family members in long term viral carriers. We surmise that cancer therapies may exacerbate the paradoxical association between lymphopenia and COVID-19-related immunopathology, and that the prevention of COVID-19-induced lymphocyte loss may reduce cancer-associated death.


title: Impact of Dutasteride on PSA Kinetics and Time to Progression in Men with PSA-only Recurrent Prostate Cancer

abstract:
BackgroundAVODART After Radical Therapy For Prostate Cancer Study (ARTS) reported dutasteride reduced PSA doubling (PSADT) at two years by 66% and disease progression by 59%. The durability of the cancer control is unknown.

ObjectiveExplore the impact of dutasteride on PSADT and time to progression in men with PSA-only recurrent disease.

Design, Setting and ParticipantsRetrospective examination of the impact of dutasteride on PSA kinetics and time to progression with PSA-only recurrent prostate cancer.

InterventionDutasteride daily.

Outcome, Measurement and Statistical AnalysisChange in PSA over time was determined by linear regression of natural log of PSA versus time. The slope of that curve was used as a measure of exponential PSA progression. Impact of dutasteride on slope was analyzed using Wilcoxon signed-rank two-sided test. Time to progression was analyzed using Kaplan-Meier, univariant and multivariant Cox regression.

Results and LimitationCompared to men with BPH, patients showed little change in PSA during the first 3 months. Thereafter, the PSA resumed an exponential increase. PSADT was 10.3 months pre dutasteride and 24.8 months post dutasteride. Multivariant analysis showed a strong correlation between post dutasteride PSA kinetics and time to progression, with close to 50% relapse free at 10 years. Post-dutasteride, patients with PSADT >9 months had significantly better survival.

ConclusionsDutasteride slows PSADT in PSA-only recurrent prostate cancer. This decline correlated with time to disease progression with close to 50% progression free at 10 years.

Patient SummaryMen with PSA-only recurrent prostate cancer on dutasteride experience a significant drop in the rate at which the PSA increases. If the PSA does not double between months 3-12, they are likely to remain free of metastases for many years.

category: oncology


title: Automated vision screening of children using a mobile graphic device

abstract:
Background/ObjectiveCan measures of interocular brightness disparity, acuity, and colour vision identify children with amblyopia?

Subjects/Methods208 subjects from 3 to 14 years were recruited for a prospective, observational protocol to measure interocular brightness disparity, acuities with and without a pinhole, and colour vision using an iPad. Interocular brightness disparity was assessed as the subject looked through a system of polarizing filters and chose the brighter of two spaceships. The differential brightness of image pairs was varied according to a staircase algorithm until equal brightness was perceived. Acuities were tested with tumbling Es. Colour vision was tested with AO-HRR colour plates. 2 subjects (1%) were later confirmed to have unilateral amblyopia.

ResultsBinocular brightness balance on the iPad detected both amblyopes and excluded all 202 non-amblyopes, in this study with sensitivity and specificity of 100%. By using 20/30 as cutoff for normal acuity, 1 of the 2 amblyopes was detected and all non-amblyopes were excluded by visual acuity testing with pinhole. The mean difference between iPad and E-Chart visual acuities with pinhole was 0.02 logMAR with limits of agreement from -0.08 to +0.11 logMAR. Colour vision testing with iPad and printed plates gave identical results. Testing times were brief and exit pleasure poll responses were positive.

ConclusionsInterocular brightness disparity, acuity, and colour vision can be measured in children as young as 3 years playing a fun game on a mobile graphic device. Interocular brightness disparity may be a sensitive and specific method to detect unilateral amblyopia.

category: ophthalmology


title: ATLAS: An automated association test using probabilistically linked health records with application to genetic studies

abstract:
ObjectiveLarge amounts of health data are becoming available for biomedical research. Synthesizing information across databases with no gold standard mappings between records may provide a more complete picture of patient health and enable novel research studies. To do so, researchers may probabilistically link databases and conduct inference using the linked data. However, previous inference methods for linked data are constrained to specific linkage settings and exhibit low power. Here, we present ATLAS, an automated, flexible, and robust association testing algorithm for probabilistically linked data.

Materials and MethodsMissing variables are imputed at various thresholds using a weighted average method that propagates uncertainty from the linkage process. Next, an estimated effect size is obtained using a generalized linear model. ATLAS then conducts the threshold combination test by optimally combining p-values obtained from data imputed at varying thresholds using Fishers method and perturbation resampling.

ResultsIn simulations, ATLAS controls for type I error and exhibits high power compared to previous methods. In a real-world application study, incorporation of linked data-enabled analyses using ATLAS yielded two additional signifigant associations between rheumatoid arthritis genetic risk score and biomarkers.

DiscussionThe ATLAS weighted average imputation weathers false matches and increases contribution of true matches to mitigate linkage error induced bias. ATLAS threshold combination test avoids arbitrarily choosing a threshold to rule a match, thus automating linked data-enabled analyses and preserving power.

ConclusionATLAS promises to enable novel and powerful research studies using linked data to capitalize on all available data sources.

category: health informatics


title: Comprehensive mapping of neutralizing antibodies against SARS-CoV-2 variants induced by natural infection or vaccination

abstract:
BackgroundImmunity after SARS-CoV-2 infection or vaccination has been threatened by recently emerged SARS-CoV-2 variants. A systematic summary of the landscape of neutralizing antibodies against emerging variants is needed.

MethodsWe systematically searched PubMed, Embase, Web of Science, and 3 pre-print servers for studies that evaluated neutralizing antibodies titers induced by previous infection or vaccination against SARS-CoV-2 variants and comprehensively collected individual data. We calculated lineage-specific GMTs across different study participants and types of neutralization assays.

FindingsWe identified 56 studies, including 2,483 individuals and 8,590 neutralization tests, meeting the eligibility criteria. Compared with lineage B, we estimate a 1.5-fold (95% CI: 1.0-2.2) reduction in neutralization against the B.1.1.7, 8.7-fold (95% CI: 6.5-11.7) reduction against B.1.351 and 5.0-fold (95% CI: 4.0-6.2) reduction against P.1. The estimated neutralization reductions for B.1.351 compared to lineage B were 240.2-fold (95% CI: 124.0-465.6) reduction for non-replicating vector platform, 4.6-fold (95% CI: 4.0-5.2) reduction for RNA platform, and 1.6-fold (95% CI: 1.2-2.1) reduction for protein subunit platform. The neutralizing antibodies induced by administration of inactivated vaccines and mRNA vaccines against lineage P.1 were also remarkably reduced by an average of 5.9-fold (95% CI: 3.7-9.3) and 1.5-fold (95% CI: 1.2-1.9).

InterpretationOur findings indicate that the antibody response established by natural infection or vaccination might be able to effectively neutralize B.1.1.7, but neutralizing titers against B.1.351 and P.1 suffered large reductions. Standardized protocols for neutralization assays, as well as updating immune-based prevention and treatment, are needed.

FundingChinese National Science Fund for Distinguished Young Scholars

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSeveral newly emerged SARS-CoV-2 variants have raised significant concerns globally, and there is concern that SARS-CoV-2 variants can evade immune responses that are based on the prototype strain. It is not known to what extent do emerging SARS-CoV-2 variants escape the immune response induced by previous infection or vaccination. However, existing studies of neutralizing potency against SARS-CoV-2 variants are based on limited numbers of samples and lack comparability between different laboratory methods. Furthermore, there are no studies providing whole picture of neutralizing antibodies induced by prior infections or vaccination against emerging variants. Therefore, we systematically reviewed and quantitively synthesized evidence on the degree to which antibodies from previous SARS-CoV-2 infection or vaccination effectively neutralize variants.

Added value of this studyIn this study, 56 studies, including 2,483 individuals and 8,590 neutralization tests, were identified. Antibodies from natural infection or vaccination are likely to effectively neutralize B.1.1.7, but neutralizing titers against B.1.351 and P.1 suffered large reductions. Lineage B.1.351 escaped natural-infection-mediated neutralization the most, with GMT of 79.2 (95% CI: 68.5-91.6), while neutralizing antibody titers against the B.1.1.7 variant were largely preserved (254.6, 95% CI: 214.1-302.8). Compared with lineage B, we estimate a 1.5-fold (95% CI: 1.0-2.2) reduction in neutralization against the B.1.1.7, 8.7-fold (95% CI: 6.5-11.7) reduction against B.1.351 and 5.0-fold (95% CI: 4.0-6.2) reduction against P.1. The neutralizing antibody response after vaccinating with non-replicating vector vaccines against lineage B.1.351 was worse than responses elicited by vaccines on other platforms, with levels lower than that of individuals who were previously infected. The neutralizing antibodies induced by administration of inactivated vaccines and mRNA vaccines against lineage P.1 were also remarkably reduced by an average of 5.9-fold (95% CI: 3.7-9.3) and 1.5-fold (95% CI: 1.2-1.9).

Implications of all the available evidenceOur findings indicate that antibodies from natural infection of the parent lineage of SARS-CoV-2 or vaccination may be less able to neutralize some emerging variants, and antibody-based therapies may need to be updated. Furthermore, standardized protocols for neutralizing antibody testing against SARS-CoV-2 are needed to reduce lab-to-lab variations, thus facilitating comparability and interpretability across studies.

category: infectious diseases


title: Tool to assess risk of bias due to missing evidence in network meta-analysis (ROB-MEN): elaboration and examples

abstract:
Selective outcome reporting and publication bias threaten the validity of systematic reviews and meta-analysis and ultimately can affect clinical decision-making. A rigorous methodology to evaluate the impact of this bias on the meta-analysis results of a network of interventions is still lacking. We present a tool to assess the Risk Of Bias due to Missing Evidence in Network meta-analysis (ROB-MEN) by expanding the methods previously developed for pairwise meta-analysis (ROB-ME, http://www.riskofbias.info).

ROB-MEN first evaluates the risk of bias due to missing evidence for each pairwise comparison separately. This step considers possible bias due to the presence of studies with unavailable results (known unknowns) and the potential for unpublished studies (unknown unknowns). The second step combines the overall judgements about the risk of bias due to missing evidence in pairwise comparisons with the percentage contribution of direct comparisons on the NMA estimates, the presence or absence of small-study effects, as evaluated by network meta-regression, and any bias from unobserved comparisons. Then, a level of "low risk", "some concerns" or "high risk" for the bias due to missing evidence is assigned to each NMA estimate, which is our tools final output.

We describe the methodology of ROB-MEN step-by-step using an illustrative example from a published NMA of non-diagnostic modalities for the detection of coronary artery disease in patients with low risk acute coronary syndrome. We also report a full application of the tool on a larger and more complex published network of 18 drugs from head-to-head studies for the acute treatment of adults with major depressive disorder. The ROB-MEN tool is the first tool for evaluating the risk of bias due to missing evidence in NMA and it is applicable to networks of all sizes and geometry.

category: epidemiology


title: Male-Female Disparities in Years of Potential Life Lost Attributable to COVID-19 in the United States: A State-by-State Analysis

abstract: Males are at higher risk relative to females of severe outcomes following COVID-19 infection. Focusing on COVID-19-attributable mortality in the United States (U.S.), we quantify and contrast years of potential life lost (YPLL) attributable to COVID-19 by sex based on data from the U.S. National Center for Health Statistics as of 31 March 2021, specifically by contrasting male and female percentages of total YPLL with their respective percent population shares and calculating age-adjusted male-to-female YPLL rate ratios both nationally and for each of the 50 states and the District of Columbia. Using YPLL before age 75 to anchor comparisons between males and females and a novel Monte Carlo simulation procedure to perform estimation and uncertainty quantification, our results reveal a near-universal pattern across states of higher COVID-19-attributable YPLL among males compared to females. Furthermore, the disproportionately high COVID-19 mortality burden among males is generally more pronounced when measuring mortality in terms of YPLL compared to age-irrespective death counts, reflecting dual phenomena of males dying from COVID-19 at higher rates and at systematically younger ages relative to females. The U.S. COVID-19 epidemic also offers lessons underscoring the importance of a public health environment that recognizes sex-specific needs as well as different patterns in risk factors, health behaviors, and responses to interventions between men and women. Public health strategies incorporating focused efforts to increase COVID-19 vaccinations among men are particularly urged.

category: public and global health


title: ROCCA study protocol and interim analysis on safety of Sputnik V vaccine (Gam-COVID-Vac) in the Republic of San Marino: an observational study using active surveillance

abstract:
OBJECTIVETo assess the safety of the Sputnik V (Gam-COVID-Vac) COVID-19 vaccine through participant-based active surveillance from the Republic of San Marino vaccination campaign.

DESIGN AND SETTINGThis is a nation-wide cohort study in the Republic of San Marino to monitor any Adverse Events Following Immunisation (AEFI) with the Sputnik V.

PARTICIPANTSAdults aged 18-89 years who had at least one dose of Sputnik V administered and who responded or accessed to an e-questionnaire sent via email, QR-code or were live/phone interviewed about the 7 days after the first vaccine dose (n=2,558) and 7 days after the second dose (n=1,288). Exclusion criteria were inability to understand nor to answer the questionnaire properly.

MAIN OUTCOME MEASURESRates of overall AEFI short-term and long-term (3 months). Secondary outcomes focus on subgroups of the population presenting specific comorbidities. Being this an interim analysis, long-term data (3 months) is still being collected, especially for vulnerable populations, including subjects with comorbidities and the youngest age groups.

RESULTThe median age of participants was 68 years. 56% were females. After the first dose, vaccine recipients described both local and systemic reactions in 16.4% of cases, 25.8% reported systemic reactions only, and 10.2% reported local symptoms only. After the second dose, both local and systemic reactions were reported in 31.9% of cases, 18.5% reported systemic reactions only, and 16.1% reported local symptoms only. Main symptoms were local pain (24.8% for first dose and 43.8% for the second), asthenia (23.8% and 31.9%), headache (18.5% and 21.0%), and joint pain (16.5% and 21.9%). In the population over 60, recipients having reported AEFI after the first dose could be a predictor of AEFI recurrence after the second dose (p<0.001). 81.8% of those reporting second-dose AEFI, reported AEFI after the first dose, while amongst those not having reported any AEFI after the first dose, 18.2% reported AEFI after the second dose.

CONCLUSIONThe ROCCA interim analysis confirmed a good tolerability profile in the over 60 years age group after both doses regarding short-term solicited AEFI to Sputnik V (Gam-COVID-Vac).


title: Protocol of the COVID-19 Health Adherence Research in Scotland Vaccination (CHARIS-V) study: Understanding the influence of vaccination decisions on adherence to transmission-reducing behaviours in a prospective longitudinal study of the Scottish Population.

abstract:
IntroductionThe global population has been asked to live under tight restrictions to slow the spread of SARS-CoV-2. Transmission-reducing behaviours (TRBs), (physical distancing, hand washing, wearing a face covering) were introduced by governments in 2020 prior to vaccine availability. People should maintain TRBs throughout the vaccination programme, because there is much uncertainty about the vaccine efficacy, immunity duration, whether there will be the requirement for booster vaccines, and whether vaccinated individuals can be carriers of the virus. This study will explore the effect of the vaccination programme in Scotland on adherence to TRBs.

Methods and analysisTelephone interviews will be conducted with participants from the nationally representative CHARIS project that agreed to be contacted for further research. Approximately 200, ten-minute telephone interviews will be conducted. Data will be collected on vaccine uptake or intention and adherence to TRBs. Univariate and multivariate logistic regression analyses and moderation analyses will be used to analyse the data collected. Ethical approval was granted by the Life Sciences and Medicine School Ethics Review Board (SERB) at the University of Aberdeen.

DiscussionCHARIS-V will provide an understanding of the effect of the vaccination programme on adherence to TRBs in Scotland. Findings should be useful to governments and public health agencies for the current COVID-19 pandemic and vaccination programme and assist in the management of any future outbreaks.


title: Investigating the relationship between serum ACE 2 level and COVID-19 patients' prognosis: a cross-sectional study

abstract:
BackgroundThe only known receptor for this virus in the human body is ACE2, the same known receptor for the SARS virus.

Material and MethodIn this single-center cross-sectional study, 38 hospitalized adult ([≥]18 years) patients with laboratory-confirmed COVID-19 were identified in the infectious disease ward in Imam Khomeini hospital complex. The study also has been approved in ethics committee of Tehran University of medical sciences with ethic code: 99/11/101/16529. Data were analyzed using SPSS 25. p < 0.05 was considered statistically significant when a two-tailed test was performed.

ResultAmong the 38 patients, the mean age was 64.13 years, 52.6% were male, 42% were PCR test positive and 39.5% was expired. The most common presenting symptoms were cough (80%), fever (75.5%), dyspnea (60.5%), myalgias (35.8%), diarrhea (20%), and nausea and vomiting (15%). There were not any significant differences between expired and discharged group in terms of serum ACE2 level. Results were similar between discharged and expired patients in the subgroup analysis of 38 patients.

ConclusionIt seems that serum ACE 2 level is not correlated with COVID-19 patients prognosis. However, it seems that more researches are required to confirm supposed association between serum ACE2 level and inflammatory biomarkers, clinical outcome, and patients survival.

category: respiratory medicine


title: Declining Opioid Distribution to US Hospitals

abstract: The United States is enduring a preventable opioid crisis, particularly involving a population specifically being treated in a hospital setting. This project analyzed trends in distribution of opioids by hospitals in the United States from 2000 to 2019. Opioids monitored included buprenorphine, codeine, fentanyl, hydrocodone, hydromorphone, meperidine, methadone, morphine, oxycodone, oxymorphone, powdered opium, remifentanil, and tapentadol. The Automation of Reports and Consolidated Orders System (ARCOS) reports controlled substances via the Drug Enforcement Administration (DEA). Data from ARCOS reports 5 and 7 from 2000 to 2019 were utilized for an observational study on hospital opioid distribution in the US. Morphine milligram equivalents (MME) were calculated using oral conversion factors for each opioid. The MME per person per state was calculated to compare data from the peak year, 2012, to data from 2019. Opioid use in the United States peaked in 2012 with a 46.6% decline from 2012 to 2019. Within the US, 25 of 50 states have seen a decrease of 50% or greater. Of the opioid compounds observed, buprenorphine has seen increased (123%) hospital use from 2000 to 2019. All other opioids have been experiencing a slow decline (>40%) in hospital use since that time. This study demonstrated the progress made thus far by hospitals in curbing the US opioid epidemic.

category: pain medicine


title: COVID-19 infection and hospitalization according to the burden of chronic noncommunicable diseases in Brazil

abstract: Chronic diseases, worse socioeconomic conditions and old age can increase infection and hospitalization rate due to Coronavirus disease (COVID-19). We assessed the association between the burden of NCDs and the occurrence of infections and hospitalizations of COVID-19 in Brazil in a large COVID-19 national survey data. We analyzed only data collected between July and November 2020 (n = 1,071,782). The frequencies of positive COVID-19 diagnosis and NCD burden were estimated according to age, sex, socioeconomic strata and skin color categories. We estimated hazard ratios and 95% confidence intervals using Cox regression models. There is a non-linear dose-response inverse association between per capita income and the rates of infection and hospitalization due to COVID-19. The presence of NCDs was associated with a higher incidence of COVID-19 infection (HR1NCD = 1.34; 95% CI: 1.26; 1.43; HR2 or more NCD= 1.54 95% CI: 1.39; 1.71) and incidence of hospitalization (HR1NCD = 3.08 95% CI: 2.26; 4.19; HR 2or more NCD= 6.81 95% CI: 4.88; 9.49).The difference between the risks of infection or hospitalization of COVID-19 attributable to the burden of NCDs is non-linearly associated with the income.


title: Cesarean section prevalence at a baby-friendly hospital in southern Brazil: current context in the face of COVID-19

abstract:
ObjectiveTo analyze cesarean prevalence at a baby-friendly hospital in Southern Brazil between 2017 and 2020 and possible annual and monthly changes due to the novel coronavirus (COVID-19) pandemic.

MethodsDescriptive cross-sectional study using secondary data retrieved from the electronic information system of a Baby-Friendly Hospital in the municipality of Rio Grande, RS, Brazil. Data was retrieved for all hospitalizations at the obstetric center between January 1st 2017 and December 31st 2020. Data on COVID-19 deaths were obtained from the municipal government website. Annual and monthly cesarean prevalence rates were calculated in comparison to the same periods in 2017, 2018 and 2019. Differences in prevalence rates were tested using a chi-square test, taking a significance level of less than 5%. Prevalence ratios were estimated for 2018/2017, 2019/2018, and 2020/2019.

Results7,294 childbirths were included. Cesarean prevalence was 42.6% in 2017, 44.3% in 2018, 40.2% in 2019, and 51.0% in 2020. In 2018/2017, there was no statistically significant difference in cesarean prevalence (95%CI: 0.90-1.20). Between 2019/2018, there was a reduction of approximately 20% in prevalence (95%CI: 0.69-0.93). The scenario changes between 2020/2019 with a 40% increase in cesareans (95%CI: 1.20-1.62). The period comprising July to December 2020 was the only period in which over half the deliveries were done by cesarean section, exceeding 60% in July.

ConclusionCesarean prevalence rates increased in 2020 in relation to the three preceding years. The data highlight the need to reinforce compliance with childbirth protocols to reduce cesarean sections in baby-friendly hospitals.


title: Roles of generation-interval distributions in shaping relative epidemic strength, speed, and control of new SARS-CoV-2 variants

abstract: Inferring the relative strength (i.e., the ratio of reproduction numbers, [R]var/[R]wt) and relative speed (i.e., the difference between growth rates, rvar -rwt) of new SARS-CoV-2 variants compared to their wild types is critical to predicting and controlling the course of the current pandemic. Multiple studies have estimated the relative strength of new variants from the observed relative speed, but they typically neglect the possibility that the new variants have different generation intervals (i.e., time between infection and transmission), which determines the relationship between relative strength and speed. Notably, the increasingly predominant B.1.1.7 variant may have a longer infectious period (and therefore, a longer generation interval) than prior dominant lineages. Here, we explore how differences in generation intervals between a new variant and the wild type affect the relationship between relative strength and speed. We use simulations to show how neglecting these differences can lead to biases in estimates of relative strength in practice and to illustrate how such biases can be assessed. Finally, we discuss implications for control: if new variants have longer generation intervals then speed-like interventions such as contact tracing become more effective, whereas strength-like interventions such as social distancing become less effective.


title: Premature adult mortality in India: What is the size of the matter?

abstract:
BackgroundReducing adult mortality by 2030 is a key component of the United Nations Sustainable Development Goals (UNSDGs). Monitoring progress towards these goals requires timely and reliable information on deaths by age, sex, and cause. To estimate baseline measures for UNSDGs, this study aimed to use several different data sources to estimate subnational measures of premature adult mortality (between 30 and 70 years) for India in 2017.

MethodsAge-specific population and mortality data were accessed for India and its 21 larger states from the Civil Registration System and Sample Registration System for 2017, and the most recent National Family and Health Survey. Similar data on population and deaths were also procured from the Global Burden of Disease Study 2016 and the National Burden of Disease Estimates Study for 2017. Life table methods were used to estimate life expectancy and age-specific mortality at national and state level from each source. An additional set of life tables were estimated using an international two-parameter model life table system. Three indicators of premature adult mortality were derived by sex for each location and from each data source, for comparative analysis

ResultsMarked variations in mortality estimates from different sources were noted for each state. Assuming the highest mortality level from all sources as the potentially true value, premature adult mortality was estimated to cause a national total of 2.6 million male and 1.8 million female deaths in 2017, with Bihar, Maharashtra, Tamil Nadu, Uttar Pradesh, and West Bengal accounting for half of these deaths. There was marked heterogeneity in risk of premature adult mortality, ranging from 351 per 1000 in Kerala to 558 per 1000 in Chhattisgarh among men, and from 198 per 1000 in Himachal Pradesh to 409 per 1000 in Assam among women.

ConclusionsAvailable data and estimates for mortality measurement in India are riddled with uncertainty. While the findings from this analysis may be useful for initial subnational health policy to address UNSDGs, more reliable empirical data is required for monitoring and evaluation. For this, strengthening death registration, improving methods for cause of death ascertainment, and establishment of robust mortality statistics programs are a priority.

KEY MESSAGESO_ST_ABSWhat is already known?C_ST_ABSO_LIReliable measures of mortality at adult ages are required for evidence-based health policy, monitoring and evaluation of progress towards health-related UN SDGs.
C_LIO_LIIn the absence of reliable data from CRVS systems in many countries including India, these measures are largely derived from alternate data sources, data synthesis, or modelling methods.
C_LI

What are the new findings?O_LIThis article presents a comparative analysis of measures of premature adult mortality from several data sources for India and its 21 larger states, examining their reliability and correspondence
C_LIO_LIFollowing a conservative approach, the article proposes the maximum estimate of mortality between the ages of 30 and 70 years by sex for each location from any source as the potential baseline level of premature adult mortality around 2016-2017
C_LI

What do the new findings imply?O_LIAlthough each of the six data sources or estimation methods demonstrated some weaknesses, the adequate quality of data from the Civil Registration System (CRS) in several states suggests that through the implementation of strategic interventions, the CRS could be developed into a reliable data source for tracking progress towards the UNSDGs
C_LI


title: Analysis and visualization of epidemics on the timescale of burden: derivation and application of Epidemic Resistance Lines (ERLs) to COVID-19 outbreaks in the US

abstract:
The 2020 COVID-19 pandemic produced thousands of well-quantified epidemics in counties, states, and countries around the world. Comparing the dynamics and outcomes of these nested epidemics could improve our understanding of the efficacy of non-pharmaceutical interventions (NPIs) and help managers with risk assessment across multiple geographic levels. However, cross-outbreak comparisons are challenging due to their variable dates of introduction of the SARS-CoV-2 virus, rates of transmission, case detection rates, and asynchronous and diverse management interventions.

Here, we present a graphical method for comparing ongoing COVID-19 epidemics by using disease burden as a natural timescale for comparison. Trajectories of growth rates of cases over the timescale of lagged deaths per-capita produces coherent visual comparisons of epidemics that are otherwise incoherent and asynchronous in the timescale of calendar dates or incomparable using non-stationary measures of burden such as cases. Applied to US COVID-19 outbreaks at the county and state level, this approach reveals lockdowns reducing transmission at fewer deaths per-capita early in the epidemic, reopenings causing resurgent summer epidemics, and peaks that while separated in time and place actually occur at points of similar per-capita deaths.

Our method uses early and minimally mitigated epidemics, like that in NYC in March-April 2020 and Sweden in later 2020, to define what we call "epidemic resistance lines" (ERLs) or hypothesized upper bounds of epidemic speed and burden. ERLs from less-mitigated epidemics allow benchmarking of resurgent summer epidemics in the US. In particular, the unmitigated NYC epidemic resistance line appears to bound the growth rates of 3,000 US counties and funnel growth rates across counties to their peaks where growth rates equal zero in the fall and winter of 2020. Corroboration of upper-bounds on epidemic trajectories allowed early predictions of mortality burden for unmitigated COVID-19 epidemics in these populations, predictions that were more accurate for counties in states without mask-wearing mandates. We discuss how this method could be used for future epidemics, including seasonal epidemics caused by influenza or ongoing epidemics caused by new SARS-CoV-2 variants.

Press SummaryWhy, despite no statewide mask-wearing mandates or other restrictions like restaurant closures, did South Dakotas COVID-19 epidemic peak not in January, when seasonal forcing wanes, but in early November? Why are we not seeing a resurgent epidemic in Florida or Texas, where non-pharmaceutical interventions have been relaxed for months? How can we compare the current outbreak in India with other countries epidemics to contextualize the speed of the Indian outbreak and estimate the potential loss of life?

We have developed a new method of visualizing epidemics in progress that can help to compare distinct COVID-19 outbreaks to understand, in specific cases like South Dakota, why they peaked when they did. The "when" in this case does not refer to prediction of a calendar date, but rather a point in the accumulation of deaths in a given locale due to the disease in question. The method presented in this paper therefore essentially uses population-based burden of disease as a timescale for measuring epidemics. Just as the age of a car can be measured in years or miles, the age of a COVID-19 epidemic can be measured in days or deaths per-capita. Plotting growth rates of cases as a function of per-capita deaths 11 days later produces a real-time visual comparison of epidemics that are otherwise asynchronous in time.

This approach permits both direct comparison across local outbreaks that may be disparate in time and/or place, as well as benchmarking of any outbreak against known exemplars of archetypal response strategies, such as New York Citys unmitigated urban outbreak in Spring 2020 and Swedens uncontained summer 2020 epidemic. Whether comparing the speed of resurgent outbreaks following relaxation in US states like Florida or the peak mortality burden in fall outbreaks across thousands of US counties with and without statewide mask-wearing mandates, this method offers a simple, intuitive tool for real-time monitoring and prediction capability connecting epidemic speed, burden, and management interventions. While our findings point to compelling epidemiological hypotheses for peaks in less-regulated states, future work is needed to confirm and extend our results predicting mortality burden at the peak of confirmed cases in the ongoing and evolving COVID-19 pandemic.


title: Population behavioural dynamics can mediate the persistence of emerging infectious diseases

abstract: The critical community size (CCS) is the minimum closed population size in which a pathogen can persist indefinitely. Below this threshold, stochastic extinction eventually causes pathogen extinction. Here we use a simulation model to explore behaviour-mediated persistence: a novel mechanism by which the population response to the pathogen determines the CCS. We model severe coronavirus 2 (SARS-CoV-2) transmission and non-pharmaceutical interventions (NPIs) in a population where both individuals and government authorities restrict transmission more strongly when SARS-CoV-2 case numbers are higher. This results in a coupled human-environment feedback between disease dynamics and population behaviour. In a parameter regime corresponding to a moderate population response, this feedback allows SARS-CoV-2 to avoid extinction in the trough of pandemic waves. The result is a very low CCS that allows long term pathogen persistence. Hence, an incomplete pandemic response represents a "sour spot" that not only ensures relatively high case incidence and unnecessarily long lockdown, but also promotes long-term persistence of the pathogen by reducing the CCS. Given the worldwide prevalence of small, isolated populations in which a pathogen with low CCS can persist, these results emphasize the need for a global approach to coronavirus disease 2019 (COVID-19) vaccination.


title: Implementation of SARS-CoV2 Screening in K-12 Schools using In-School Pooled Molecular Testing and Deconvolution by Rapid Antigen Test

abstract:
What is already known about this topic?SARS-CoV2 testing is a key component of a multi-layered mitigation strategy to enable safe return to in-person school for the K-12 population. However, costs, logistics, and uncertainty about effectiveness are potential barriers to implementation.

What is added by this report?Over three months, 259,726 individual swabs were tested across 50,636 pools from 582 schools. Pool positivity rate was 0.8%; 98.1% of pools tested negative and 0.3% inconclusive, and 0.8% of pools submitted could not be tested. In reflex testing, 92.5% of fully deconvoluted pools with N1 or N2 target Ct [≤]30 yielded a positive individual using the BinaxNOW antigen rapid diagnostic test (Ag RDT) performed 1-3 days later. With sufficient staffing support and low pool positivity rates, pooled sample collection and reflex testing were feasible for schools.

What are the implications for public health practice?Screening testing for K-12 students and staff is achievable at scale and at low cost with a scheme that incorporates in-school pooling, RT-PCR primary testing, and Ag RDT reflex/deconvolution testing. Staffing support is a key factor for program success.


title: Almond Consumption for 8 Weeks Altered Host and Microbial Metabolism in Comparison to a Control Snack in Young Adults

abstract: Almond consumption can improve cardiometabolic (CM) health. However, the mechanisms underlying those benefits are not well characterized. This study explored the effects of consuming a snack of almonds vs. crackers for 8 weeks on changes in metabolomic profiles in young adults (clinicaltrials.gov ID: NCT03084003). Participants (n=73, age: 18-19 years, BMI: 18-41 kg/m2) were randomly assigned to consume either almonds (2 oz/d, n=38) or an isocaloric control snack of graham crackers (325 kcal/d, n=35) daily for 8 weeks. Blood samples were collected at baseline prior to and at 4 and 8 weeks after the intervention. Metabolite abundances in the serum were quantified by hydrophilic interaction chromatography quadrupole (Q) time-of-flight (TOF) mass spectrometry (MS/MS), gas chromatography (GC) TOF MS, CSH-ESI (electrospray) QTOF MS/MS, and targeted analyses for free PUFAs, total fatty acids, oxylipins and endocannabinoids. Linear mixed model analyses with baseline-adjustment were conducted, and those results were used for enrichment and network analyses. Microbial community pathway predictions from 16S rRNA sequencing of fecal samples was done using PICRUST2. Almond consumption enriched unsaturated triglycerides, unsaturated phosphatidylcholines, saturated and unsaturated lysophosphatidylcholines, tricarboxylic acids, and tocopherol clusters (p<0.05). Targeted analyses reveal lower levels of omega-3 total fatty acids (TFAs) overall in the almond group compared to the cracker group (p<0.05). Microbial amino acid biosynthesis, and amino sugar and nucleotide sugar metabolism pathways were also differentially enriched at the end of the intervention (p<0.05). The study demonstrates the differential effects of almonds on host tocopherol, lipid, and TCA cycle metabolism with potential changes in microbial metabolism, which may interact with host metabolism to facilitate the CM benefits.

category: nutrition


title: Outbreaks of Covid-19 Variants in Prisons: A Mathematical Modeling Analysis of Vaccination and Re-Opening Policies

abstract:
BackgroundResidents of correctional facilities have experienced disproportionately higher rates of SARS-CoV-2 infection and Covid-19-related mortality. To protect against outbreaks, many prisons and jails imposed heavy restrictions on in-person activities, which are now beginning to lift. Uncertainty surrounds the safety of these moves.

Methods and FindingsWe obtained system-wide resident-day level data for the California state prison system, the nations third largest. We used the data to develop a transmission-dynamic stochastic microsimulation model that projects the impact of various policy scenarios on risks of SARS-CoV-2 infections and related hospitalization among residents after an initial infection is introduced to a prison. The policy scenarios vary according to levels of vaccine coverage, baseline immunity, resumption of activities, and use of non-pharmaceutical interventions (e.g., masking, physical distancing). The analyses were conducted across 5 types of prisons that differed in their residential layouts, security levels, and resident demographics.

If a viral variant is introduced into a prison that has resumed pre-2020 contact levels, has moderate vaccine coverage, and has no baseline immunity, 23-74% of residents are expected to be infected over 200 days. High vaccination coverage coupled with use of non-pharmaceutical measures reduces cumulative infections to 2-54% of residents. In prisons consisting mostly of dormitory housing, even with high vaccine coverage and non-pharmaceutical interventions, resumption of in-person activities is associated with substantial risk, unless there is high baseline immunity (e.g., [≥]50%) from prior outbreaks. In prisons consisting mostly of cell housing, <10% of residents are expected to become infected, even with no baseline immunity. However, hospitalization risks are substantial in prisons that house medically vulnerable populations, even for prisons consisting mostly of cells. Risks of large outbreaks are substantially higher if there is continued introduction of infections into a prison. Some findings may not be transportable to other carceral settings, and our assumptions regarding viral variants will not be accurate for all variants.

ConclusionsBalancing the benefits of resuming normal in-person activities against the risks of Covid-19 outbreaks is a difficult challenge for correctional systems. The policy choices are not strictly binary. To protect against viral variants, prisons should focus on achieving both high vaccine coverage and maintaining widespread use of non-pharmaceutical interventions. With both in place, some prisons, especially those with lower room occupancy that have already had large outbreaks, could safely resume in-person activities, while continuing testing and measures to protect the medically-vulnerable.


title: A SARS-CoV-2 Nucleocapsid Variant that Affects Antigen Test Performance

abstract: More than one year into a global pandemic, SARS-CoV-2 is now defined by a variety of rapidly evolving variant lineages. Several FDA authorized molecular diagnostic tests have been impacted by viral variation, while no reports of viral variation affecting antigen test performance have occurred to date. While determining the analytical sensitivity of the Quidel Sofia SARS Antigen FIA test (Sofia 2), we uncovered a high viral load specimen that repeatedly tested negative by this antigen test. Whole genome sequencing of the specimen uncovered two mutations, T205I and D399N, present in the nucleocapsid protein of the isolate. All six SARS-CoV-2 positive clinical specimens available in our laboratory with a D399N nucleocapsid mutation and CT < 31 were not detected by the Sofia 2 but detected by the Abbott BinaxNOW COVID-19 Ag Card, while clinical specimens with the T205I mutation were detected by both assays. Testing of recombinant SARS-CoV-2 nucleocapsid with these variants demonstrated an approximate 1000-fold loss in sensitivity for the Quidel Sofia SARS Antigen FIA test associated with the D399N mutation, while the BinaxNOW and Quidel Quickvue SARS Antigen tests were unaffected by the mutation. The D399N nucleocapsid mutation has been relatively uncommon to date, appearing in only 0.02% of genomes worldwide at time of writing. Our results demonstrate how routine pathogen genomics can be integrated into the clinical microbiology laboratory to investigate diagnostic edge cases, as well as the importance of profiling antigenic diversity outside of the spike protein for SARS-CoV-2 diagnostics.


title: Infants are more susceptible to COVID-19 than children

abstract: Angiotensin-converting enzyme 2 (ACE2) has been found to mediate the host cell entry of SARS-CoV-2 that causes COVID-19. However, the link between ACE2 and the observed susceptibility of SARS-CoV-2 infection remains elusive. In contrast, observational studies can help identify the susceptibility biomarker of SARS-CoV-2 infection, those associated with age for example. Data of all PCR tests performed in the state of Sao Paulo of Brazil were gathered from the government database and were analyzed using multivariate logistic regression. Adjusted odds ratios for positive test results were calculated with the adjustment of age, gender, and comorbidities. Over 1.7 million test results were included in the study of which 38% were positive. Elderly was most vulnerable to SARS-CoV-2 infection. While underages were less susceptible than adults aged below 60 years, susceptibility was not equal among different pediatric groups. It is found that age and susceptibility to SARS-CoV-2 infection are not inversely related, but U-shaped, with infants more susceptible than children. Biomarkers that are linearly associated with age cannot explain the reduced susceptibility in children. These include lymphocyte count and cross-reactive antibodies against other coronaviruses that offers cross-protection. The expression level of ACE2 may still be able to explain but further investigations are needed.


title: A Call For Better Methodological Quality Of Reviews On Using Artificial Intelligence For COVID-19 Detection In Medical Imaging - An Umbrella Systematic Review

abstract:
ObjectiveIn this umbrella systematic review, we screen existing reviews on using artificial intelligence (AI) techniques to diagnose COVID-19 in patients of any age and sex (both hospitalised and ambulatory) using medical images and assess their methodological quality.

MethodsWe searched seven databases (MEDLINE, EMBASE, Web of Science, Scopus, dblp, Cochrane Library, IEEE Xplore) and two preprint services (arXiv, OSF Preprints) up to September 1, 2020. Eligible studies were identified as reviews or surveys where any metric of classification of detection of COVID-19 using AI was provided. Two independent reviewers did all steps of identification of records (titles and abstracts screening, full texts assessment, essential data extraction, and quality assessment). Any discrepancies were resolved by discussion. We qualitatively analyse methodological credibility of the reviews using AMSTAR 2 and evaluate reporting using PRISMA-DTA tools, leaving quantitative analysis for further publications.

ResultsWe included 22 reviews out of 725 records covering 165 primary studies. This review covers 416,254 participants in total, including 50,022 diagnosed with COVID-19. The methodological quality of all eligible studies was rated as critically low. 91% of papers had significant flaws in reporting quality. More than half of the reviews did not comment on the results of previously published reviews at all. Almost three fourth of the studies included less than 10% of available studies.

DiscussionIn this umbrella review, we focus on the descriptive summary of included papers. Much wasting time and resources could be avoided if referring to previous reviews and following methodological guidelines. Due to the low credibility of evidence and flawed reporting, any recommendation about automated COVID-19 clinical diagnosis from medical images using AI at this point cannot be provided.

FundingPO was supported by NIH grant AI116794 (the funding body had no role in the design, in any stage of the review, or in writing the manuscript); PJ and DS did not receive any funding.

RegistrationThe protocol of this review was registered on the OSF platform [1].


title: Genomic risk prediction for breast cancer in older women

abstract:
BackgroundGenomic risk prediction models for breast cancer (BC) have been predominantly developed with data from women aged less than 70 years. Prospective studies of women aged 70 years or older have been limited.

MethodsWe assessed the effect of a 313-variant polygenic risk score (PRS) for BC in 6,339 women of European ancestry aged [≥]70 years. We evaluated incident BC diagnoses over a median follow-up of 4.7 years. A multivariable Cox regression model including conventional risk factors was applied to prospective data, and re-evaluated after adding the PRS. We also assessed the association of rare pathogenic variants (PVs) with BC in susceptibility genes (BRCA1/BRCA2/PALB2/CHEK2/ATM).

ResultsThe PRS, as a continuous variable, was an independent predictor of incident BC (hazard ratio [HR] per standard deviation (SD)=1.4, 95% confidence interval [CI] 1.3-1.6, N=110 cases) and hormone receptor (ER/PR)-positive disease (HR=1.5 [CI 1.2-1.9], N=79 cases). Women in the top quintile of the PRS distribution had higher risk of BC than women in the lowest quintile (HR=2.2 [CI 1.2-3.9]). The concordance index of the model without the PRS was 0.62 (95% CI 0.56-0.68) which improved after addition of the PRS to 0.65 (95% CI 0.59-0.71). Among 41 (0.6%) carriers of PVs in BC susceptibility genes, we observed no incident BC diagnoses.

ConclusionThe 313-variant PRS predicts BC risk in women aged 70 years and older.

category: genetic and genomic medicine


title: dPQL: a lossless distributed algorithm for generalized linear mixed model with application to privacy-preserving hospital profiling

abstract: Hospital profiling provides a quantitative comparison of health care providers for their quality of care regarding certain clinical outcomes. To implement hospital profiling, the generalized linear mixed model (GLMM) is usually used to fit clinical or administrative claims data, adjusting for the effects of covariates. For better generalizability, data across multiple hospitals, databases or networks are desired. However, due to the privacy regulation and the computation complexity of GLMM, a convenient distributed algorithm for hospital profiling is needed. In this paper, we develop a novel distributed Penalized Quasi Likelihood algorithm (dPQL) to fit GLMM, when only aggregated data, rather than the individual patient data are available across hospitals. The dPQL algorithm is based on a newly-developed distributed linear mixed model (DLMM) algorithm. This proposed dPQL algorithm is lossless, i.e. it obtains identical results as if the individual patient data are pooled from all hospitals. We demonstrate the usage of the dPQL algorithms by ranking 929 hospitals for COVID-19 mortality or referral to hospice in Asch, et al. 2020.


title: Modelling upper respiratory viral load dynamics of SARS-CoV-2

abstract: Relationships between viral load, severity of illness, and transmissibility of virus, are fundamental to understanding pathogenesis and devising better therapeutic and prevention strategies for COVID-19. Here we present within-host modelling of viral load dynamics observed in the upper respiratory tract (URT), drawing upon 2172 serial measurements from 605 subjects, collected from 17 different studies. We developed a mechanistic model to describe viral load dynamics and host response, and contrast this with simpler mixed-effects regression analysis of peak viral load and its subsequent decline. We observed wide variation in URT viral load between individuals, over 5 orders of magnitude, at any given point in time since symptom onset. This variation was not explained by age, sex, or severity of illness, and these variables were not associated with the modelled early or late phases of immune-mediated control of viral load. We explored the application of the mechanistic model to identify measured immune responses associated with control of viral load. Neutralizing antibody correlated strongly with modelled immune-mediated control of viral load amongst subjects who produced neutralizing antibody. Our models can be used to identify host and viral factors which control URT viral load dynamics, informing future treatment and transmission blocking interventions.


title: The BNT162b2 mRNA vaccine against SARS-CoV-2 reprograms both adaptive and innate immune responses

abstract: The mRNA-based BNT162b2 vaccine from Pfizer/BioNTech was the first registered COVID-19 vaccine and has been shown to be up to 95% effective in preventing SARS-CoV-2 infections. Little is known about the broad effects of the new class of mRNA vaccines, especially whether they have combined effects on innate and adaptive immune responses. Here we confirmed that BNT162b2 vaccination of healthy individuals induced effective humoral and cellular immunity against several SARS-CoV-2 variants. Interestingly, however, the BNT162b2 vaccine also modulated the production of inflammatory cytokines by innate immune cells upon stimulation with both specific (SARS-CoV-2) and non-specific (viral, fungal and bacterial) stimuli. The response of innate immune cells to TLR4 and TLR7/8 ligands was lower after BNT162b2 vaccination, while fungi-induced cytokine responses were stronger. In conclusion, the mRNA BNT162b2 vaccine induces complex functional reprogramming of innate immune responses, which should be considered in the development and use of this new class of vaccines.


title: Estimating vaccine efficacy against transmission via effect on viral load

abstract: Determining policies to end the SARS-CoV-2 pandemic will require an understanding of the efficacy and effectiveness (hereafter, efficacy) of vaccines. Beyond the efficacy against severe disease and symptomatic and asymptomatic infection, understanding vaccine efficacy against transmission will help model epidemic trajectory and determine appropriate control measures. Recent studies have proposed using random virologic testing in individual randomized controlled trials to improve estimation of vaccine efficacy against infection. We propose to further use the viral load measures from these tests to estimate efficacy against transmission. This estimation requires a model of the relationship between viral load and transmissibility and assumptions about the vaccine effect on transmission and the progress of the epidemic. We describe these key assumptions, potential violations of them, and solutions that can be implemented to mitigate these violations. Assessing these assumptions and implementing this random sampling, with viral load measures, will enable better estimation of the crucial measure of vaccine efficacy against transmission.


title: Describing the burden of the COVID-19 pandemic in people with psoriasis: findings from a global cross-sectional study

abstract:
BackgroundIndirect excess morbidity has emerged as a major concern in the COVID-19 pandemic. People with psoriasis may be particularly vulnerable to this because of prevalent anxiety and depression, multimorbidity and therapeutic use of immunosuppression.

ObjectiveCharacterise the factors associated with worsening psoriasis in the COVID-19 pandemic, using mental health status (anxiety and depression) as the main exposure of interest.

MethodsGlobal cross-sectional study using a primary outcome of self-reported worsening of psoriasis. Individuals with psoriasis completed an online self-report questionnaire (PsoProtectMe; Psoriasis Patient Registry for Outcomes, Therapy and Epidemiology of COVID-19 Infection Me) between May 2020 and January 2021. Each individual completed a validated screen for anxiety (Generalized Anxiety Disorder-2) and depression (Patient Health Questionnaire-2). Odds ratios (OR) and 95% confidence intervals (CI) were estimated using multivariable logistic regression.

Results4,043 people with psoriasis (without COVID-19) from 86 countries self-reported to PsoProtectMe (mean age 47.2 years [SD 15.1]; mean BMI 27.6kg/m2 [SD 6.0], 2,684 [66.4%] female and 3,016 [74.6%] of white European ethnicity). 1,728 (42.7%) participants (1322 [77%] female) reported worsening of their psoriasis in the pandemic. A positive screen for anxiety or depression associated with worsening psoriasis in age and gender adjusted (OR 2.04, 95% CI 1.77-2.36), and fully adjusted (OR 2.01, 95% CI 1.72-2.34) logistic regression models. Female sex, obesity, shielding behaviour and systemic immunosuppressant non-adherence also associated with worsening psoriasis. The commonest reason for non-adherence was concern regarding complications related to COVID-19.

ConclusionsThese data indicate an association between poor mental health and worsening psoriasis in the pandemic. Access to holistic care including psychological support may mitigate potentially long-lasting effects of the pandemic on health outcomes in psoriasis. The study also highlights an urgent need to address patient concerns about immunosuppressant-related risks, which may be contributing to non-adherence.

category: dermatology


title: SARS-CoV-2 infections and hospitalizations among immigrants in Norway: significance of occupation, household crowding, education, household income and medical risk. A nationwide register study

abstract:
BackgroundAs in other countries, the coronavirus disease 2019 (COVID-19) pandemic has affected Norways immigrant population disproportionately with significantly higher infection rates and hospitalizations. The reasons for this are uncertain.

MethodsThrough the national emergency preparedness register, BeredtC19, we have studied laboratory-confirmed infections with SARS-CoV-2 and related hospitalizations in the entire Norwegian population, by birth-country background for the period 15 June 2020 - 31 March 2021, excluding the first-wave due to limited test capacity and restrictive test criteria. Straightforward linkage of individual-level data allowed adjustment for demographics, socioeconomic factors (occupation, household crowding, education, and household income), and underlying medical risk for severe COVID-19 in regression models.

ResultsThe sample comprised 5.49 million persons, of which 0.91 million born outside of Norway, 82 532 confirmed cases, and 3088 hospitalizations. Confirmed infections in this period (per 100 000): foreign-born 3140, Norwegian-born with foreign-born parents 4799, Norwegian-born with Norwegian-born parent(s) 1011. Hospitalizations (per 100 000): foreign-born 147, Norwegian-born with foreign-born parents 47, Norwegian-born with Norwegian-born parent(s) 37. The addition of socioeconomic and medical factors to the base-model (age, sex, municipality of residence) attenuated excess infection rates by 12.0% and hospitalizations by 3.8% among foreign-born, and 10.9% and 46.2% respectively among Norwegian-born with foreign parents, compared to Norwegian-born with Norwegian-born parent(s).

ConclusionThere were large differences in infection rates and hospitalizations by country background, and these do not appear to be fully explained by socioeconomic and medical factors. Our results may have implications for health policy, including the targeting of mitigation strategies.


title: Preliminary Analysis of Safety and Immunogenicity of a SARS-CoV-2 Variant Vaccine Booster

abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of a global pandemic of coronavirus disease 2019 (COVID-19) that has led to more than 3 million deaths worldwide. Safe and effective vaccines are now available, including the mRNA-1273 prototype vaccine, which encodes for the Wuhan SARS-CoV-2 spike (S) protein stabilized in the prefusion conformation by 2 proline substitutions. This vaccine showed 94% efficacy in prevention of symptomatic COVID-19 disease in a phase 3 clinical study. Recently, SARS-CoV-2 variants have emerged, some of which have shown decreased susceptibility to neutralization by vaccine-induced antibody, most notably the B.1.351 variant, although the overall impact on vaccine efficacy remains to be determined. In addition, recent evidence of waning antibody levels after infection or vaccination point to the need for periodic boosting of immunity. Here we present the preliminary evaluation of a clinical study on the use of the prototype mRNA-1273 or modified COVID-19 mRNA vaccines, designed to target emerging SARS-CoV-2 variants as booster vaccines in participants previously vaccinated approximately 6 months earlier with two doses of the prototype vaccine, mRNA-1273. The modified vaccines include a monovalent mRNA-1273.351 encoding for the S protein found in the B.1.351 variant and multivalent mRNA-1273.211 comprising a 1:1 mix of mRNA-1273 and mRNA-1273.351. As single 50 {micro}g booster vaccinations, both mRNA-1273 and mRNA-1273.351 had acceptable safety profiles and were immunogenic. Antibody neutralization titers against B.1.351 and P.1 variants measured by SARS-CoV-2 pseudovirus neutralization (PsVN) assays before the booster vaccinations, approximately 6 to 8 months after the primary series, were low or below the assay limit of quantification, although geometric mean titers versus the wild-type strain remained above levels likely to be protective. Two weeks after the booster vaccinations, titers against the wild-type original strain, B.1.351, and P.1 variants increased to levels similar to or higher than peak titers after the primary series vaccinations. Although both mRNA-1273 and mRNA-1273.351 boosted neutralization of the wild-type original strain, and B.1.351 and P.1 variants, mRNA-1273.351 appeared to be more effective at increasing neutralization of the B.1.351 virus versus a boost with mRNA-1273. The vaccine trial is ongoing and boosting of clinical trial participants with the multivalent mRNA-1273.211 is currently being evaluated.


title: Longitudinal SARS-CoV-2 infection study at Ulm University

abstract: In light of the COVID-19 pandemic, universities around the world were challenged by the difficult decision whether classes could be held face-to-face in the winter semester 20/21. The gross anatomy course is considered an essential practical element of medical school. In order to protect the participants and teaching staff and to gain more knowledge about SARS-CoV-2 infections among students during a semester with face-to-face teaching a longitudinal test study was conducted. Medical students from the first three years of medical school were also invited. Out of a total of almost 1,000 swabs, only two active asymptomatic infections were detected at the start of the semester, none during the semester. At semester start, approximately 6% of the students had antibodies. At the end of the semester, only nine seroconversions after infection in 671 individuals occurred. This was surprisingly low because a massive second wave of infections hit Germany during the same period. The conclusion therefore is that face-to-face teaching under these measures was not infection-promoting even with high incidence rates in the overall population with the SARS-CoV-2 variants present at that time period. Moreover, the results are indicative of a preventive effect of hygiene concepts together with repetitive testings before and during a semester.


title: Longitudinal SARS-CoV-2 infection study in a German medical school


title: Development and validation protocol for an instrument to measure women's empowerment in urban sanitation across countries: The Agency, Resources, and Institutional Structures for Sanitation-related Empowerment (ARISE) Scales

abstract:
IntroductionDespite an increasing emphasis on gender and empowerment in water, sanitation, and hygiene (WaSH) programs, no rigorously validated survey instruments exist for measuring empowerment within the WaSH sector. Our objective is to develop and validate quantitative survey instruments to measure womens empowerment in relation to sanitation in urban areas of low-and middle-income countries.

Methods and analysisWe are developing the Agency, Resources, and Institutional Structures for Sanitation-related Empowerment (ARISE) scales through a process that involves three phases: item development; scale development and initial validation; and scale evaluation and further validation. The first phase includes domain specification, item generation, face validity and content validity assessment, and item refinement. The second phase involves a second round of face validity and content validity assessment, followed by survey implementation in two cities (Tiruchirappalli, India and Kampala, Uganda) and data analysis involving factor analysis and item response theory approaches, as well as reliability and validity testing. The third phase involves a final round of face validity and content validity assessment, followed by survey implementation in three additional cities (Narsapur and Warangal, India; and Lusaka, Zambia) and statistical analysis using similar approaches as in Phase 2 for further validation.

Ethics and disseminationEthics approvals have been received from ethics boards in all study locations. The study team will share findings with key stakeholders to inform programming activities and will publish results in peer-reviewed journals.

Article SummaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIWe employ rigorous methods to develop survey instruments, including testing and validating 15 scales, to assess domains of womens empowerment related to sanitation.
C_LIO_LIPhased data collection is being carried out across five urban locations in South Asia and Africa to ensure that the survey instruments are valid and comparable across contexts.
C_LIO_LIOur survey instruments are specific to women in urban settings; adaptation and further validity testing is needed to develop instruments that can be administered in other settings (e.g. rural, peri-urban) and with men.
C_LIO_LIThe survey instruments are focused on empowerment at the individual, household, and community levels; they do not assess empowerment in markets (e.g. across the sanitation value chain) or in relation to policies and formal governance.
C_LI


title: Covid-19 and the South Asian Countries: factors ruling the pandemic

abstract: The novel corona virus causing Covid-19 was first detected in the city of Wuhan, China in December, 2019. In matter of months Covid-19 was declared a pandemic by the World Health Organization. The focus of this research includes the probable factors that might have played an important role in the spread of this infection causing a global threat. In this study we dealt with the South Asian countries namely Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan. Data on the demography of the countries, the climatic and geographical conditions, the socio-economic statuses, GDP being in the forefront, was collected and compared with Covid-19 related data such as total number of positive, recovered and death cases, etc. to determine if there was any significant correlation. The wide range of correlations observed can curve the path for the future research to understand the factors behind the spread of the communicable disease, analyzing the dynamics of the future biological threats to mankind and design the precautionary or preventive methods accordingly.


title: Obstructive sleep apnea is highly prevalent in COVID19 moderate to severe ARDS survivors: Findings of level I Polysomnography in a tertiary care hospital

abstract:
Study ObjectivesStudies have found Obstructive Sleep Apnea (OSA) as a risk factor for increased risk for COVID19 Acute respiratory Distress Syndrome (ARDS); but most of the studies were done in already known patients of OSA. This study was done to find prevalence of OSA in patients with COVID-19 related acute respiratory distress syndrome.

MethodologyA hospital based longitudinal study was conducted among COVID 19 Intensive Care Unit (ICU) survivors. All consecutive COVID19 with moderate to severe ARDS were evaluated for OSA by Level I Polysomnography (PSG) after 4-6 weeks of discharge. Prevalence of OSA and PSG variables {Total sleep time, Sleep efficiency, sleep stage percentage, Apnea Hypopnea Index (AHI), T90, nadir oxygen} was estimated.

ResultsOut of 103 patients discharged from ICU during study period (October 2020 to 15 December 2020), 67 underwent Level I PSG. Mean Age was 52.6{+/-}10.9 years and mean Body Mass Index was 27.5 {+/-} 6.2 Kg/m2. Total sleep time was 343.2 {+/-} 86 minutes, sleep efficiency was 75.9{+/-}14.2%. OSA (AHI [≥]5) was seen in 65/67 patients and 49 patients had moderate to severe OSA (i.e. AHI [≥] 15).

ConclusionModerate-severe OSA was highly prevalent (73%) in COVID19 moderate to severe ARDS survivors. Role of OSA in pathophysiology of COVID19 ARDS needs further evaluation.

HighlightsO_LIThis study was done to find prevalence of OSA in patients with COVID-19 related Acute respiratory distress syndrome
C_LIO_LIModerate-severe OSA is highly prevalent (73%) in COVID19 ARDS survivors.
C_LIO_LITo the best of our knowledge, it is first study in which level I PSG was done in COVID19 survivors.
C_LI


title: Prognostic value of the level of gut microbe-generated metabolite trimethylamine-N-oxide in patients with heart failure：a meta-analysis and systematic review

abstract:
AimsIntestinal microbial metabolite trimethylamine N-oxide (TMAO) is considered to be a key mediator between intestinal microbiota changes and heart failure (HF). Clinical evidences showed that patients with HF had relatively high level of plasma TMAO than those without. However, the relationship between plasma TMAO and the prognostics of patients with HF has not been investigated. This study aims to evaluate the relationship between plasma TMAO and the outcomes of patients with HF.

Methods and resultsPubMed, EMBASE, Cochrane Library databases were included for systematic literature search. The included studies were used for the extraction of overall hazard ratios of adverse events data (myocardial infarction, cardiovascular hospitalization, cardiovascular mortality, revascularization and stroke) as well as all-cause mortality data. Cochrans Q test and I2 statistical methods were applied to assess heterogeneity. Selection of random effects model or fixed effects model were according to heterogeneity. Sensitivity analysis and subgroup analysis were used to find the source of heterogeneity. Among the 7 included studies, all studies published all-cause mortality data and 6 provided adverse events. And the results demonstrated that higher level of plasma TMAO (defined according to original studies)was an indicator of risk of all-cause mortality (HR =0.26, 95% CI: 0.20-0.32, I2 = 96.1%,) and risk of adverse events (HR =1.79, 95% CI: 1.37-2.22, I2 = 78.6%). There was no significant publication bias among the included studies (Eggers,P = 0.130;Beggs tests P = 0.452). Further subgroup analysis did not show that study location, follow-up time, or year of publication had any effect on the results. The results of sensitivity analysis do not indicate that any of the included affected the robustness of the results.

ConclusionHeart failure patients with higher baseline plasma TMAO is a risk factor for all-cause mortality and adverse events.

category: cardiovascular medicine


title: Derivation and external validation of a simple risk score to predict in-hospital mortality in patients hospitalized for COVID-19

abstract:
BackgroundAs SARS-CoV-2 continues to spread, and hospitals are treating a large number of patients with COVID-19, easy-to-use risk models that predict hospital mortality can assist in clinical decision making and triage.

ObjectiveAs SARS-CoV-2 continues to spread, easy-to-use risk models that predict hospital mortality can assist in clinical decision making and triage. We aimed to develop a risk score model for in-hospital mortality in patients hospitalized with COVID-19 that was robust across hospitals and used clinical factors that are readily available and measured standardly across hospitals.

MethodsIn this observational study we developed a risk score model using data collected by trained abstractors for patients in 20 diverse hospitals across the state of Michigan (Mi-COVID19) who were discharged between March 5, 2020 and August 14, 2020. Patients who tested positive for SARS-CoV-2 during hospitalization or were discharged with an ICD-10 code for COVID-19 (U07.1) were included. We employed an iterative forward selection approach to consider the inclusion of 145 potential risk factors available at hospital presentation. Model performance was externally validated with patients from 19 hospitals in the Mi-COVID19 registry not used in model development. We shared the model in an easy-to-use online application that allows the user to predict in-hospital mortality risk for a patient if they have any subset of the variables in the final model.

ResultsOur final model includes the patients age, first recorded respiratory rate, first recorded pulse oximetry, highest creatinine level on day of presentation, and hospitals COVID-19 mortality rate. No other factors showed sufficient incremental model improvement to warrant inclusion. The AUC for the derivation and validation sets were .796 and .829 respectively.

ConclusionsRisk of in-hospital mortality in COVID-19 patients can be reliably estimated using a few factors, which are standardly measured and available to physicians very early in a hospital encounter.

category: emergency medicine


title: SARS-CoV-2 infection and reinfection in a seroepidemiological workplace cohort in the United States

abstract: Identifying the extent of SARS-CoV-2 reinfection is crucial for understanding possible long-term epidemic dynamics. We analysed longitudinal PCR and serological testing data from a prospective cohort of 4411 US employees in four states between April 2020 and February 2021. We conducted a multivariable logistic regression investigating the association between baseline serological status and subsequent PCR test result in order to calculate an odds ratio for reinfection. We estimated an adjusted odds ratio of 0.09 (95% CI: 0.005 - 0.48) for reinfection, implying that the presence of SARS-CoV-2 antibodies at baseline is associated with around 91% reduced odds of a subsequent PCR positive test. This suggests that primary infection with SARS-CoV-2 provides protection against reinfection in the majority of individuals, at least over a sixth month time period. We also highlight two major sources of bias and uncertainty to be considered when estimating reinfection risk, confounders and the choice of baseline time point, and show how to account for both in our analysis.


title: Pregnancy pharmacoepidemiology: How often are key methodological elements reported in publications?

abstract:
PurposePublications are an important information source for clinicians, researchers, and patients. Key methodological elements must be reported for maximum transparency. We identified key methodological elements necessary for fully understanding pharmacoepidemiological research in pregnancy and quantified the proportion of studies that report these elements in a sample of publications.

MethodsKey methodological elements were identified from guidelines from regulatory agencies, literature, and subject-matter knowledge: source of information to determine pregnancy start; mother- or father-infant linkages (process, success rate); unit of analysis; and whether non-live births and fetuses with various anomalies were included in the study population.

We conducted a literature review for recent observational studies on medical product utilization or safety during pregnancy and estimated the prevalence of reporting these elements.

ResultsData were extracted from a random sample of 100 publications; 8% were published in epidemiology/pharmacoepidemiology journals; 85% were medical product-safety studies.

Of included publications, 43% reported the source for determining pregnancy start; 57% reported whether the study population included multifetal pregnancies; 39%, whether it included more than 1 pregnancy per woman; 27%, whether it included fetuses with chromosomal abnormalities; 60%, fetuses with major congenital malformations; and 93%, non-live births. Of the 20 studies with mother-infant linkage, 35% described the process; 21% reported the linkage success rate. Among studies with more than one pregnancy/offspring per woman, 22% reported methods addressing sibling correlation.

ConclusionsIn this sample of pregnancy-related pharmacoepidemiology publications, completeness of reporting can be improved. A pregnancy-specific checklist would help to increase transparency in the dissemination of study results.

Key points{blacksquare} Publications on the utilization or safety of medical products in pregnancy (pregnancy pharmacoepidemiology) are fully understandable when all key methodological elements are presented to the reader.
{blacksquare}We identified 17 methodological elements from guidelines, literature, and subject-matter knowledge that we felt were crucial for understanding publications on pregnancy pharmacoepidemiology.
{blacksquare}In a random sample of 100 publications, completeness of reporting varied across elements, with almost perfect reporting on whether non-live births were included in the study population to a 21% completeness on mother-infant linkage success rate.
{blacksquare}A pregnancy-specific checklist would help to increase transparency in the dissemination of study results.


title: Quantifying the impact of UVC in reducing airborne pathogen transmission and improving energy efficiency for healthy buildings: Kahn-Mariita equivalent ventilation model

abstract: There is growing evidence that viruses responsible for pandemics, such as MERS and SARS, are mainly spread through aerosols. Recommendations have been introduced to reduce the transmission risk of virulent airborne viral particles by increasing ventilation rates, expressed in air-changes-per-hour (ACH), effectively improving the dilution of airborne pathogens via mechanical ventilation. However, the infrastructural and operational costs associated with upgrades of Heating, Ventilation, and Air Conditioning (HVAC) systems make these solutions expensive. It is well documented that UVC disinfection can help lower exposure risks by inactivating viruses in shared enclosed spaces, and the performances of such solutions be translated into equivalent ventilation (equivalent ACH or eACH). Here, we present the first framework to extract the optimum UVC output requirements for a target eACH, and improve facilities ability to comply with ventilation guidelines at lower energy costs. The Kahn-Mariita (KM) model considers the air quality of a shared enclosed space over time by supplementing existing mechanical ventilation with localized UVC air treatment, whether in recirculating units or upper-air systems, and extracts the systems requirements based on end-user needs by incorporating variables such as room size, occupancy, existing ventilation, and target eACH. An example of a conference room shows that a UVC chamber with an air recirculation rate of 160m3/h increases the ventilation from ACH=3 to eACH=7.9 and reduce down-time from 46 minutes to <10 minutes with as little 1W of UVC output. A recirculation rate of 30m3/h however offers no noticeable benefits above 200mW, with a maximum reachable eACH=3.9 and down-time of approximately 31 minutes. The KM model is unique in that it allows for the first time to find the optimum UVC output needs to ensure air quality is maintained and transmission risk minimized, while increasing energy savings. Recent studies suggest mechanically increasing fresh air supply will more than double the energy costs of HVAC systems, while the use of UVC reduces energy demand as much as by 50%. The KM model approaches air quality and energy efficiency in a unified way by incorporating UVC as a supplement to existing ventilation to increase eACH, reduce down-time, and increase the closed space occupancy.

category: health systems and quality improvement


title: SARS-CoV-2 seroprevalence in Germany - a population based sequential study in five regions

abstract:
Prevalence of SARS-CoV-2 antibodies is an essential indicator to guide measures. Few population-based estimates are available in Germany. We determine seroprevalence allowing comparison between regions, time points, socio-demographic and health-related factors.

MuSPAD is a sequential multi-local seroprevalence study. We randomly recruited adults in five counties with differing cumulative SARS-CoV-2 incidence July 2020 -February 2021. Serostatus was determined using Spike S1-specific IgG ELISA. We determined county-wise proportions of seropositivity. We assessed underestimation of infections, county and age specific infection fatality risks, and association of seropositivity with demographic, socioeconomic and health factors.

We found seroprevalence of 2.4 % (95%CI: 1.8-3.1%) for Reutlingen in June 2020 (stage 1) which increased to 2.9% (95%CI: 2.1-3.8%) in October (stage 2), Freiburg stage 1 1.5% (95% CI: 1.1-2.1%) vs. 2.5% (95%CI: 1.8-3.4%), Aachen stage 1 2.3% (95% CI: 1.7-3.1%) vs. 5.4% (95%CI: 4.4-6.6%), Osnabruck 1.3% (95% CI: 1.0-1.9%) and Magdeburg in Nov/Dec 2020. 2.4% (95%CI 1.9-3.1%). Number needed to quarantine to prevent one infection was 8.2. The surveillance detection ratio (SDR) between number of infections based on our results and number reported to health authorities ranged from 2.5-4.5. Participants aged 80+ had lower SDR. Infection fatality estimates ranged from 0.2-2.4%. Lower education was associated with higher, smoking with lower seropositivity.

Seroprevalence remained low until December 2020 with high underdetection. The second wave from November 2020 to February 2021 resulted in additional 2-5% of the population being infected. Detected age specific differences of SDR should be taken into account in modelling and forecasting COVID-19 morbidity.

FundingThe Helmholtz Association, European Unions Horizon 2020 research and innovation programme [grant number 101003480] and intramural funds of the Helmholtz Centre for infection (HZI).

HighlightsO_ST_ABSEvidence before this studyC_ST_ABSSeroepidemiological surveys on SARS-CoV-2 are a useful tool to track the transmission during the epidemic. We searched PubMed/the pre-print server medRxiv and included web-based reports from German health organizations using the keywords "seroprevalence", "SARS-CoV-2", "Germany" and similar other English and German terms in the period from January 1st, 2020 until March 2021. We identified 30 published studies in Germany which mostly report low SARS-CoV-2 seroprevalence (<5%). Most of these surveys were so-called hotspot studies which assessed seroprevalence after localized outbreaks or examined seroprevalence of specific population groups such as e.g. medical staff. Few studies are either population-based or blood donor-based, but do not allow comparisons between regions. To date, we only consider the Corona sub-study of the Rhineland study similar to MuSPAD. It reports a low SARS-CoV-2 seroprevalence (46/4755; 0.97%; 95% CI: 0.72-1.30). Based on this, almost the entire German population remained susceptible to a SARS-CoV-2 infection by the end of 2020.

Added value of this studyWe provide the first comprehensive, high-precision multi-region population-based SARS-CoV-2 seroprevalence study with representative sampling following the WHO protocol in Germany. By measuring SARS-CoV-2 IgG, we explore immunity at regional and national level over time. We also assess risk factors and sample each region twice, which permits to monitor seroprevalence progression throughout the epidemic in different exemplary German regions.

Implications of all the available evidenceOur results show low seroprevalence (<3%) until Mid-December 2020 in all regions. While estimates in Reutlingen, Aachen, Freiburg and Osnabruck reflect low seroprevalence mostly after the first wave, the survey in Magdeburg cumulatively already represents the beginning of the second wave. The number needed to quarantine to prevent one infection was 8.2 in our study. We also show that for the first wave reported infections reflected overall around 25% of those actually infected rising to 40-50% in the second wave. A slightly raised infection risk could be shown for persons with lower education.


title: Population Pharmacokinetic Analysis of Dexmedetomidine in Children using Real-World-Data Obtained from Electronic Health Records and Remnant Clinic Samples

abstract:
AimOur objectives were to perform a population pharmacokinetic analysis of dexmedetomidine in children using remnant specimens and data from electronic health records (EHRs) and explore the impact of patients characteristics and pharmacogenetics on dexmedetomidine clearance.

MethodsDexmedetomidine dosing and patient data were gathered from EHRs and combined with opportunistically sampled remnant specimens. Population pharmacokinetic models were developed using nonlinear mixed-effects modeling. The first stage developed a model without genotype variables; the second stage added pharmacogenetic effects.

ResultsOur final study population included 354 post-cardiac surgery patients age 0 to 22 years (median 16 months). The final two-compartment model included allometric weight scaling and age maturation. Population parameter estimates and 95% confidence intervals were 27.3 L/hr (24.0 - 31.1 L/hr) for total clearance (CL), 161 L (139 - 187 L) for central compartment volume of distribution (V1), 26.0 L/hr (22.5 - 30.0 L/hr) for intercompartmental clearance (Q), and 7903 L (5617 - 11119 L) for peripheral compartment volume of distribution (V2). The estimate for postmenstrual age when 50% of adult clearance is achieved was 42.0 weeks (41.5 - 42.5 weeks) and the Hill coefficient estimate was 7.04 (6.99 - 7.08). Genotype was not statistically or clinically significant.

ConclusionOur study demonstrates the use of real-world EHR data and remnant specimens to perform a population PK analysis and investigate covariate effects in a large pediatric population. Weight and age were important predictors of clearance. We did not find evidence for pharmacogenetic effects of UGT1A4 or UGT2B10 genotype or CYP2A6 risk score.

What is already known about this subject{circ} Previous dexmedetomidine pharmacokinetic (PK) studies in pediatric populations have limited sample size.
{circ}Smaller studies present a challenge for identifying covariates that may impact individual PK profiles.

What this study adds{circ} We performed a dexmedetomidine population PK study with a large pediatric cohort using data obtained from electronic health records and remnant plasma specimens to enable increased sample size.
{circ}xsDifferences in PK due to UGT1A4 or UGT2B10 variants or CYP2A6 risk score are not clinically impactful for this population.

category: pharmacology and therapeutics


title: Population Pharmacokinetic Analysis of Dexmedetomidine in Children using Real World Data from Electronic Health Records and Remnant Specimens


title: An Effective and Reliable Methodology for Deep Machine Learning Application in Caries Detection

abstract: Early detection of dental caries has been one of the most predominant topics studied over the last few decades. Conventional examination through visual-tactile inspection and radiography can be inaccurate and destructive to the tooth structure. The development of optical coherence tomography (OCT) has given dentistry an alternative diagnostic technique, which has been proven by numerous studies, that it has better sensitivity, specificity, and non-invasive characteristics. The growing popularity of artificial intelligence (AI) also contributes to a more efficient and effective way of image-based detection and decision-making. However, previous studies, which have attempted to employ AI for caries assessment, did not incorporate high-quality ground truth data. Therefore, this study aims to bypass this issue and highlights the importance of high-quality data. A two-phase study was carried out to explore different methods for caries detection. Initially, the comparison of caries detection based on OCT and apical radiography by 5 experienced clinicians was conducted. Then, five convolutional neural networks (CNNs), including AlexNet, VGG-16, ResNet-152, Xception, and ResNext-101, in the scope of AI were employed to detect caries and compared with the findings of the 5 clinicians. The data was preprocessed and labeled with the ground truth corresponding to microcomputed tomography (micro-CT) with rigorous definition. The weighted Kappa statistics suggested that OCT ({varkappa}= .699, SD = .090) showed a higher accuracy rate than radiography ({varkappa}= .407, SD = .049), and CNNs ({varkappa}= .860, SD = .049) were rated higher than clinicians ({varkappa}= .679, SD = .113), both at a .05 significance level. The best result was carried out by ResNet-152, which demonstrated a high accuracy rate of 95.21% and a sensitivity of 98.85%. These findings illustrate the importance of ground truth data for AI training and the potential of deep CNN algorithms combined with OCT for diagnosing dental caries.

category: dentistry and oral medicine


title: Deep learning for caries detection using optical coherence tomography


title: Computing a Lower Bound for the Total Size of the COVID-19 Infected Population Iceberg Using the General Age-Group Distribution

abstract:
Epidemics and Pandemics such as COVID-19 require estimating total infection prevalence. Accurate estimates support better monitoring, evaluation of proximity to herd immunity, estimation of infection fatality rates (IFRs), and assessment of risks due to infection by asymptomatic individuals, especially in developing countries, which lack population-wide serological testing.

We suggest a method for estimating the infection prevalence by finding the Pivot group, the population sub-group with the highest susceptibility for being confirmed as positively infected. We differentiate susceptibility to infection, assumed to be uniform across all population sub-groups (a key assumption), from susceptibility to developing symptoms and complications, which differs between sub-groups (e.g., by age). We compute the minimal infection-prevalence factor by which the number of positively confirmed patients should be multiplied that allows for a sufficient number of Pivot-group infections that explains the number of Pivot group confirmations.

We applied the method to the COVID-19 pandemic, using UK and Spain serological surveys. Our key assumption held, and actual infection-prevalence factors were consistent with our predictions. We computed minimal infection-prevalence factors, and when possible, assessed IFRs and serology-based IFRs, for the COVID-19 pandemic in eight countries.

Estimating a lower bound for an epidemics infection prevalence using our methodology is feasible, and the assumptions underlying it are valid. The use of our methodology is often necessary for developing countries, especially in the early phases of an epidemic when serological data are not yet available or when new mutations of a known virus appear.


title: Computing the Prevalence and Severity of an Epidemic Using only the Distribution of Simple Tests for Infection Confirmation


title: Unified real-time environmental-epidemiological data for multiscale modeling of the COVID-19 pandemic

abstract: An impressive number of COVID-19 data catalogs exist. None, however, are optimized for data science applications, e.g., inconsistent naming and data conventions, uneven quality control, and lack of alignment between disease data and potential predictors pose barriers to robust modeling and analysis. To address this gap, we generated a unified dataset that integrates and implements quality checks of the data from numerous leading sources of COVID-19 epidemiological and environmental data. We use a globally consistent hierarchy of administrative units to facilitate analysis within and across countries. The dataset applies this unified hierarchy to align COVID-19 case data with a number of other data types relevant to understanding and predicting COVID-19 risk, including hydrometeorological data, air quality, information on COVID-19 control policies, and key demographic characteristics.


title: Intentional and unintentional non-adherence to social distancing measures during COVID-19: A mixed-methods analysis.

abstract:
Social distancing measures implemented by governments worldwide during the COVID-19 pandemic have proven an effective intervention to control the transmission of SARS-CoV-2. There is a growing literature on predictors of adherence behaviours to social distancing measures, however, there are no comprehensive insights into the nature and types of non-adherence behaviours. To address this gap in the literature, we studied non-adherence in terms of counts of infringements and peoples accounts on their behaviours in a representative sample of North London residents. We focused on the following social distancing rules: keeping 2 mts. distancing, meeting family and friends, and going out for non-essential reasons.

A mixed-methods explanatory sequential design was used comprising an online survey (1st - 31st May 2020) followed by semi-structured in-depth interviews held with a purposive sample of survey respondents (5th August - 21st September 2020). A negative binomial regression model (quantitative) and Framework Analysis (qualitative) were undertaken.

681 individuals completed the survey, and 30 individuals were interviewed. We integrated survey and interview findings following three levels of the Social Ecological model: individual, interpersonal and community levels. We identified non-adherence behaviours as unintentional (barriers beyond individuals control) and intentional (deliberate decision). Unintentional adherence was associated with and reported as emotional inability to stay at home, lack of controllability in keeping 2 mts. distancing, social responsibility towards the community and feeling low risk. Intentional non-adherence included individual risk assessment and decision-making on the extent to following the rules, support from friends, and perceived lack of adherence in the local area. Our findings indicate that unintentional and intentional non-adherence should be improved by Government partnerships with local communities to build trust in social distancing measures; tailored messaging to young adults emphasising the need of protecting others whilst clarifying the risk of transmission; and ensuring COVID-secured environments by working with environmental health officers.


title: How can risk of COVID-19 transmission be minimised in domiciliary care for older people: development, parameterisation and initial results of a simple mathematical model

abstract: This paper proposes and analyses a stochastic model for the spread of an infectious disease that is transmitted between clients and care workers in the UK domiciliary care setting. Interactions between clients and care workers are modelled using specially generated networks, with network parameters reflecting realistic patterns of care needs and visit allocation. These networks are then used to simulate and SEIR-type epidemic dynamics with different numbers of infectious and recovery stages. The results indicate that with the same overall capacity provided by care workers, the minimum peak proportion of infection, and the smallest overall size of infection are achieved for the highest proportion of overlap between visit allocation, i.e. when care workers have the highest chances of being allocated a visit to the same client they have visited before. An intuitive explanation of this is that while providing the required care coverage, maximising overlap in visit allocation reduces the possibility of an infectious care worker inadvertently spreading the infection to other clients. The model is quite generic and can be adapted to any particular directly transmitted infectious disease, such as, more recently, COVID-19, provided accurate estimates of disease parameters can be obtained from real data.