title: Systematic review of instruments for assessing culinary skills in adults: What is the quality of their psychometric properties?

abstract:
BackgroundCulinary skills are important objects of study in the field of Public Health. Studies that propose to develop instruments for assessing such construct show lack of methodological uniformity to report validity and reliability of their instruments.

ObjectiveTo identify studies that have developed instruments to measure culinary skills in adult population, and critically assess their psychometric properties.

DesignWe conducted a systematic review according to the PRISMA statement. We searched literature PubMed/Medline, Scopus, LILACS, and Web of Science databases until January 2021, and consulted Google Scholar for relevant grey literature. Two reviewers independently selected the studies, conducted data extraction, and assessed the psychometric quality of the instruments. A third reviewer resolved any doubts or disagreements in all steps of the systematic review.

ResultsThe search identified 1148 potentially relevant studies, out of which 9 met the inclusion criteria. In addition, we included 3 studies by searching the related articles and the reference lists of these studies, totaling 12 included studies in this review. Ten studies reported the development of tools measuring culinary skills in adults and 2 studies performed cross-cultural adaptations of original instruments. We considered adequate quality of internal consistency reliability in four studies. One study received adequate rating for test-retest reliability. No studies presented adequate rating for content validity and four studies showed satisfactory results for at least one type of construct validity. One study reported criterion validity and the quality of this psychometric property was inadequate.

ConclusionsWe identified many studies that surveyed culinary skills. Although the isolated measures appraised in this review show good promise in terms of quality of psychometric properties, no studies presented adequate measures for each aspect of reliability and validity. A more consistent and consensual definition of culinary skills is recommended. The flaws observed in these studies show that there is a need for ongoing research in the area of the psychometric properties of instruments assessing culinary skills.


title: Mathematical Modeling of Coronavirus Reproduction Rate with Policy and Behavioral Effects

abstract: In this paper a modified mathematical model based on the SIR model used which can predict the spreading of the corona virus disease (COVID-19) and its effects on people in the days ahead. This model considers all the death, infected and recovered characteristics of this disease. To determine the extent of the risk posed by this novel coronavirus; the transmission rate (R0) is utilized for a time period from the beginning of spreading virus. Particularly it includes a novel policy to capture the Ro response in the virus spreading over time. The model estimates the vulnerability of the pandemic according to John H. Cochranes method with a prediction of new cases by estimating a time-varying R0 to capture changes in the behavior of SIR model implies to new policy taken at different times and different locations of the world. This modified SIR model with the different values of R0 can be applied to different country scenario using the real time data report provided by the authorities during this pandemic. The effective evaluation of R0 can forecast the necessity of lockdown as well as reopening the economy.

category: health policy


title: Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: results of a Bayesian evidence synthesis model

abstract: Reported COVID-19 cases and deaths provide a delayed and incomplete picture of SARS-CoV-2 infections in the United States (US). Accurate estimates of both the timing and magnitude of infections are needed to characterize viral transmission dynamics and better understand COVID- 19 disease burden. We estimated time trends in SARS-CoV-2 transmission and other COVID-19 outcomes for every county in the US, from the first reported COVID-19 case in January 13, 2020 through January 1, 2021. To do so we employed a Bayesian modeling approach that explicitly accounts for reporting delays and variation in case ascertainment, and generates daily estimates of incident SARS-CoV-2 infections on the basis of reported COVID-19 cases and deaths. The model is freely available as the covidestim R package. Nationally, we estimated there had been 49 million symptomatic COVID-19 cases and 400,718 COVID-19 deaths by the end of 2020, and that 27% of the US population had been infected. The results also demonstrate wide county-level variability in the timing and magnitude of incidence, with local epidemiological trends differing substantially from state or regional averages, leading to large differences in the estimated proportion of the population infected by the end of 2020. Our estimates of true COVID-19 related deaths are consistent with independent estimates of excess mortality, and our estimated trends in cumulative incidence of SARS-CoV-2 infection are consistent with trends in seroprevalence estimates from available antibody testing studies. Reconstructing the underlying incidence of SARS-CoV-2 infections across US counties allows for a more granular understanding of disease trends and the potential impact of epidemiological drivers.

category: epidemiology


title: Descriptive Epidemiological Assessment of the Relationship between the Global Burden of Influenza from 2017-2019 and COVID-19

abstract:
BackgroundSARS-CoV-2 and influenza are lipid-enveloped viruses with differential morbidity and mortality but shared modes of transmission. With a descriptive epidemiological framing, we assessed whether historical patterns of regional influenza burden are reflected in the observed heterogeneity in COVID-19 cases across regions of the world.

MethodsWeekly surveillance data reported in FluNet from January 2017-December 2019 for influenza and World Health Organization for COVID-19 (to May 31, 2020) across the seven World Bank regions were used to assess the total and annual number of influenza and COVID-19 cases per country, within and across all regions, to generate comparative descending ranks from highest to lowest burden of disease.

ResultsAcross regions, rankings of influenza and COVID-19 were relatively consistent. Europe and Central Asia and North America ranked first and second for COVID-19 and second and first for influenza, respectively. East Asia and the Pacific traditionally ranked higher for influenza with recent increases in COVID-19 consistent with influenza season. Across regions, Sub-Saharan Africa ranked amongst the least affected by both influenza and COVID-19.

ConclusionConsistency in the regional distribution of the burden of COVID-19 and influenza suggest shared individual, structural, and environmental determinants of transmission. Using a descriptive epidemiological framework to assess shared regional trends for rapidly emerging respiratory pathogens with better studied respiratory infections may provide further insights into the differential impacts of non-pharmacologic interventions and intersections with environmental conditions. Ultimately, forecasting trends and informing interventions for novel respiratory pathogens like COVID-19 should leverage epidemiologic patterns in the relative burden of past respiratory pathogens as prior information.


title: IL-13 is a driver of COVID-19 severity

abstract:
Immune dysregulation is characteristic of the more severe stages of SARS-CoV-2 infection. Understanding the mechanisms by which the immune system contributes to COVID-19 severity may open new avenues to treatment. Here we report that elevated interleukin-13 (IL-13) was associated with the need for mechanical ventilation in two independent patient cohorts. In addition, patients who acquired COVID-19 while prescribed Dupilumab had less severe disease. In SARS-CoV-2 infected mice, IL-13 neutralization reduced death and disease severity without affecting viral load, demonstrating an immunopathogenic role for this cytokine. Following anti-IL-13 treatment in infected mice, in the lung, hyaluronan synthase 1 (Has1) was the most downregulated gene and hyaluronan accumulation was decreased. Blockade of the hyaluronan receptor, CD44, reduced mortality in infected mice, supporting the importance of hyaluronan as a pathogenic mediator, and indicating a new role for IL-13 in lung disease. Understanding the role of IL-13 and hyaluronan has important implications for therapy of COVID-19 and potentially other pulmonary diseases.

SummaryL-13 levels are elevated in patients with severe COVID-19. In a mouse model of disease, IL-13 neutralization results in reduced disease and lung hyaluronan deposition. Similarly, blockade of hyaluronans receptor, CD44, reduces disease, highlighting a novel mechanism for IL-13-mediated pathology.

category: infectious diseases


title: Recovery-associated resting-state activity and connectivity alterations in Anorexia nervosa

abstract:
BackgroundPrevious studies provided controversial insight on the impact of starvation, disease status and underlying grey matter volume (GMV) changes on resting-state functional magnetic resonance imaging (rsfMRI) alterations in Anorexia nervosa (AN). Here we adapt a combined longitudinal and cross-sectional approach to disentangle the effects of these factors on resting-state alterations in AN.

MethodsOverall, 87 female subjects were included in the study: adolescent patients with acute AN scanned at inpatient admission (N = 22, mean age 15.3 years) and at discharge (N = 21), 21 patients recovered from AN (22.3 years) and two groups of healthy age-matched controls (both N = 22, 16.0 and 22.5 years). Whole-brain measures of resting-state activity and functional connectivity were computed (Network Based Statistics, Global Correlation, Integrated Local Correlation, fractional Amplitude of Low Frequency Fluctuations) to assess rsfMRI alterations over the course of AN treatment before and after controlling for underlying GMV.

ResultsPatients with acute AN displayed strong and widespread prefrontal, sensorimotor, parietal, temporal, precuneal and insular reductions of resting-state connectivity and activity. All alterations were independent of GMV and were largely normalized in short- and absent in long-term recovered AN.

ConclusionsResting-state fMRI alterations in AN constitute acute and GMV independent presumably starvation-related phenomena. The majority of alterations found here normalized over the course of recovery without evidence for possible preexisting trait- or remaining "scar"-effects.

category: psychiatry and clinical psychology


title: Comparison of Care Utilization and Medical Institutional Death among Older Adults by Home Care Facility Type: A Retrospective Cohort Study in Fukuoka, Japan

abstract:
ObjectivesWe compared the care services use and medical institutional deaths among older adults across four home care facility types.

DesignThis was a retrospective cohort study.

SettingWe used administrative claims data from April 2014 to March 2017.

ParticipantsWe included 18,347 residents of Fukuoka Prefecture, Japan, who received home care during the period, and aged [≥]75 years with certified care needs of at least level 3. Participants were categorized based on home care facility use (i.e., general clinics, Home Care Support Clinics/Hospitals (HCSCs), enhanced HCSCs with beds, and enhanced HCSCs without beds).

Primary and secondary outcome measuresWe used generalized linear regression models to estimate care utilization and the incidence of medical institutional death, as well as the potential influence of sex, age, care needs level, and Charlson comorbidity index as risk factors.

ResultsThe results of generalized linear models showed the inpatient days were 53.3, 67.4, 63.9, and 72.6 for users of enhanced HCSCs with beds, enhanced HCSCs without beds, HCSCs, and general clinics, respectively. Correspondingly, the numbers of home care days were 64.0, 51.6, 57.9, and 28.4. Our multivariable logistic regression model estimated medical institutional death rate among participants who died during the study period (n = 9919) was 2.32 times higher (P<0.001) for general clinic users than enhanced HCSCs with beds users (relative risks=1.69, P<0.001).

ConclusionsParticipants who used enhanced HCSCs with beds had a relatively low inpatient utilization, medical institutional deaths, and a high utilization of home care and home-based end-of-life care. Findings suggest enhanced HCSCs with beds could reduce hospitalization days and medical institutional deaths. Our study warrants further investigations of home care as part of community-based integrated care.

Trial registrationThis study was approved by the Kyushu University Institutional Review Board for Clinical Research (Approval No. 20209).

Strengths and limitations of this studyO_LIThis was a retrospective cohort study including data on 18,347 individuals.
C_LIO_LIThis study was designed to suggest the kind of healthcare system that will be needed in the future in aging societies by examining the associations of the type of home care provision system with end-of-life care and place of death for older adults.
C_LIO_LIWe calculated the number of years that participants lived during the study period and estimated the annual utilization rates per person-year of observation.
C_LIO_LIThis study was conducted using data only on residents of Fukuoka Prefecture in Japan, which limits the generalizability of our findings
C_LIO_LIThere were no clinical data for individual participants because this study focused on the types of healthcare facilities that provide home care.
C_LI


title: Face masks, old age, and obesity explain country's COVID-19 death rates

abstract:
Identifying biomedical and socioeconomic predictors of the number of deaths caused by COVID-19 can help the development of effective interventions. In this study, we used the hypothesis-driven regression approach to test the hypothesis that the mask wearing rate, along with age and obesity, can largely predict the cumulative number of deaths across countries. Our regression models explained 69% of the variation in the cumulative number of deaths per million (March to June 2020) among 22 countries, identifying the face mask wearing rate in March as an important predictor. The number of deaths per million predicted by our elastic net regression model showed high correlation (r = 0.86) with observed numbers. These findings emphasize the importance of face masks in preventing the ongoing pandemic of COVID-19.

One Sentence SummaryFace mask wearing rate in March is a strong predictor of the cumulative number of deaths per million caused by COVID-19 among 22 countries.


title: Forecasting COVID-19 and Analyzing the Effect of Government Interventions

abstract: One key question in the ongoing COVID-19 pandemic is understanding the impact of government interventions, and when society can return to normal. To this end, we develop DELPHI, a novel epidemiological model that captures the effect of under-detection and government intervention. We applied DELPHI across 167 geographical areas since early April, and recorded 6% and 11% two-week out-of-sample Median Absolute Percentage Error on cases and deaths respectively. Furthermore, DELPHI successfully predicted the large-scale epidemics in many areas months before, including US, UK and Russia. Using our flexible formulation of government intervention in DELPHI, we are able to understand how government interventions impacted the pandemics spread. In particular, DELPHI predicts that in absence of any interventions, over 14 million individuals would have perished by May 17th, while 280,000 current deaths could have been avoided if interventions around the world started one week earlier. Furthermore, we find mass gathering restrictions and school closings on average reduced infection rates the most, at 29.9 {+/-} 6.9% and 17.3 {+/-} 6.7%, respectively. The most stringent policy, stay-at-home, on average reduced the infection rate by 74.4 {+/-} 3.7% from baseline across countries that implemented it. We also illustrate how DELPHI can be extended to provide insights on reopening societies under different policies.


title: Retrospective Methodology to Estimate Daily Infections from Deaths (REMEDID) in COVID-19: the Spain case study

abstract: The number of new daily infections is one of the main parameters to understand the dynamics of an epidemic. During the COVID-19 pandemic in 2020, however, such information has been underestimated. Here, we propose a retrospective methodology to estimate daily infections from daily deaths, because those are usually more accurately documented. This methodology is applied to Spain and its 19 administrative regions. Our results showed that probable infections during the first wave were between 35 and 42 times more than those officially documented on 14 March, when the national government decreed a national lockdown and 9 times more than those documented by the updated version of the official data. The national lockdown had a strong effect on the growth rate of virus transmission, which began to decrease immediately. Finally, the first inferred infection in Spain is about 43 days before it was officially reported during the first wave. The current official data show delays of 15-30 days in the first infection relative to the inferred infections in 63% of the regions. In summary, we propose a methodology that allows reinterpretation of official daily infections, improving data accuracy in infection magnitude and dates because it assimilates valuable information from the National Seroprevalence Studies.


title: Psychological distress across adulthood: test-equating in three British birth cohorts

abstract: Valid and reliable life-course and cross-cohort comparisons of psychological distress are limited by differences in measures used. We aimed to examine adulthood distribution of symptoms and cross-cohort trends by scale-equating psychological distress measures administered in the 1946, 1958 and 1970 British birth cohorts. We used data from these three birth cohorts (N=32,242) and an independently recruited calibration sample (n=5,800) to inform the scale-equating. We used two approaches to scale-equating (equipercentile linking and multiple imputation) and two index-measures (General Health Questionnaire [GHQ]-12 and Malaise-9) to compare means, distributions and prevalence of distress across adulthood. While we consistently observed an inverse U-shape of distress across adulthood, we also observed measure and method differences in point estimates, particularly for cross-cohort comparisons. Sensitivity analysis suggested that multiple imputation yielded more accurate estimates than equipercentile linking. Though we observed an inverse-U shaped trajectory of psychological distress across adulthood, differences in point estimates between measures and methods did not allow for clear conclusions regarding between-cohort trends.


title: Behavioral dynamics of COVID-19: estimating under-reporting, multiple waves, and adherence fatigue across 92 nations

abstract:
COVID-19 prevalence and mortality remain uncertain. For all 86 countries with reliable testing data we estimate how asymptomatic transmission, disease acuity, hospitalization, and behavioral responses to risk shape pandemic dynamics. Estimated cumulative cases and deaths through 10 July 2020 are 10.5 and 1.47 times official reports, yielding an infection fatality rate (IFR) of 0.65%, with wide variation across nations. Despite underestimation, herd immunity remains distant. Sufficient early testing could have averted 39.7 (35.3-45.3) million cases and 218 (191-257) thousand deaths. Responses to perceived risk cause the reproduction number to settle near 1, but with very different steady-state incidence, while some nations experience endogenous rebounds. Scenarios through March 2021 show modest enhancements in responsiveness could reduce cumulative cases {approx}80%, to 271 (254-412) million across these nations.

One Sentence SummaryCOVID-19 under-reporting is large, varies widely across nations, and strongly conditions projected outbreak dynamics.


title: Weeding Through the Haze: A Survey on Cannabis Use Among People Living with Parkinson's Disease in the US

abstract: Symptomatic management of Parkinsons disease (PD) is complex and many symptoms, especially non-motor symptoms, are not effectively addressed with current medications. In the US, cannabis has become more widely available for medical and recreational use, permitting those in the PD community to try alternative means of symptom control. However, little is known about the attitudes towards, and experiences with, cannabis use among those living with PD. To address this shortcoming, we distributed an anonymous survey to 7,607 people with PD in January 2020 and received 1,339 responses (17.6%). 1,064 complete responses were available for analysis. Respondents represented 49 states with a mean age of 71.2 years ({+/-} 8.3) and mean PD duration of 7.4 years ({+/-} 6.2). About a quarter of respondents (24.5%) reported cannabis use within the previous six months. Age and gender were found to be predictors of cannabis use in this sample (Age OR = 0.95, 95% CI 0.93 to 0.97; Male OR = 1.44, 95% CI 1.03 to 2.03). Users reported learning about cannabis use from the internet/news (30.5%) and friends or other people with PD (26.0%). Cannabis users were more likely to report insufficient control of their non-motor symptoms with prescription medications than non-users (p = 0.03). Cannabis was primarily used for PD (63.6%) and was most often used to treat nonmotor symptoms of anxiety (45.5%), pain (44.0%), and sleep disorders (44.0%). However, nearly a quarter of users (23.0%) also reported they had stopped cannabis use in the previous six months, primarily due to a lack of symptom improvement (35.5%). Three quarters of respondents (75.5%) did not use cannabis, primarily because there was a lack of scientific evidence supporting efficacy (59.9%). Our results suggest that the lack of formal guidance or research evidence about cannabis for PD may in part underlie inconsistencies in both use and reported effectiveness.

category: neurology


title: Shut and re-open: the role of schools in the spread of COVID-19 in Europe

abstract: We investigate the effect of school closure and subsequent reopening on the transmission of COVID-19, by considering Denmark, Norway, Sweden, and German states as case studies. By comparing the growth rates in daily hospitalisations or confirmed cases under different interventions, we provide evidence that school closures contribute to a reduction in the growth rate approximately 7 days after implementation. Limited school attendance, such as older students sitting exams or the partial return of younger year groups, does not appear to significantly affect community transmission. In countries where community transmission is generally low, such as Denmark or Norway, a large-scale reopening of schools while controlling or suppressing the epidemic appears feasible. However, school reopening can contribute to statistically significant increases in the growth rate in countries like Germany, where community transmission is relatively high. In all regions, a combination of low classroom occupancy and robust test-and-trace measures were in place. Our findings underscore the need for a cautious evaluation of reopening strategies.


title: Genome-Wide Association Studies of retinal vessel tortuosity identify 173 novel loci, capturing genes and pathways associated with disease and vascular tissue pathomechanics

abstract:
BackgroundFundus images allow for non-invasive assessment of the retinal vasculature whose features provide important information on health. Blood vessel tortuosity is a morphological feature associated with many diseases including hypertension.

MethodsWe analyzed 116 639 fundus images of suitable quality from 63 662 participants from three cohorts, namely the UK Biobank (n = 62 751), SKIPOGH (n = 397), and OphtalmoLaus (n = 512). We used a fully automated image processing pipeline to annotate vessels and a deep learning algorithm to determine the vessel type, characterizing these subjects in terms of their median retinal vessel tortuosity specific to arteries and to veins. Tortuosity was measured by the distance factor (the length of a vessel segment over its chord length), as well as measures that integrate over vessel curvature. Using these measures as traits, we performed the largest genome-wide association study (GWAS) of vessel tortuosity to date. We assessed gene set enrichment using the novel high-precision statistical method PascalX.

ResultsHigher tortuosity was significantly associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis, and hypertension. We identified 175 significantly associated genetic loci in the UK Biobank; 173 of these were novel and 4 replicated in our second, much smaller, meta-cohort. We estimated heritability at [~]25% using linkage disequilibrium score regression. Vessel type specific GWAS revealed 114 loci for arteries and 63 for veins. Genes with significant association signals included COL4A2, ACTN4, LGALS4, LGALS7, LGALS7B, TNS1, MAP4K1, EIF3K, CAPN12, ECH1, and SYNPO2. These tortuosity genes were overexpressed in arteries and heart muscle and linked to pathways related to the structural properties of the vasculature. We demonstrated that tortuosity loci served pleiotropic functions as cardiometabolic disease variants and risk factors. Concordantly, Mendelian randomization revealed causal effects between tortuosity, BMI and LDL.

ConclusionsSeveral alleles associated with retinal vessel tortuosity point to a common genetic architecture of this trait with cardiovascular diseases and metabolic syndrome. Our results shed new light on the genetics of vascular diseases and their pathomechanisms and highlight how GWASs and heritability can be used to improve phenotype extraction from high-dimensional data, such as images.

Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABSO_LIWe automatically estimated arterial and venous tortuosity in over 100k retinal fundus images using image analysis and deep learning.
C_LIO_LIGWAS revealed 173 novel loci.
C_LIO_LIMendelian randomization showed that increased venous tortuosity reduces BMI whereas elevated LDL levels reduce the tortuosity of both arteries and veins.
C_LIO_LIMeasuring tortuosity in terms of the distance factor, which is sensitive to total vessel elongation, had higher heritability and more associated loci than other tortuosity measures that are sensitive to local vessel bending.
C_LI

What are the clinical implications?O_LITortuosity genes were overexpressed in the aorta, tibial artery, coronary artery, and in two heart tissues.
C_LIO_LIHigher tortuosity was associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis and hypertension.
C_LIO_LIWe demonstrated a shared genetic architecture between retinal tortuosity and certain diseases related to the vasculature, and the associations included several cardiometabolic disease variants and risk factors. Further research is needed to investigate the potential of the retinal vessel tortuosity as a clinically relevant biomarker for cardiovascular disease and metabolic syndrome.
C_LIO_LIEnriched pathways include a well-known therapeutic target for ocular diseases (VEGFA-VEGFR2) affecting tissue remodeling. We highlight several transcription factors as interesting targets for further experimentation.
C_LI

category: genetic and genomic medicine


title: GWAS of Retinal Vessel Tortuosity Identifies 173 Novel Loci Revealing Genes and Pathways Associated with Vascular Pathomechanics and Diseases


title: GWAS of Retinal Vessel Tortuosity Identifies 173 Novel Loci Revealing Genes and Pathways Associated with Vascular Pathomechanics and Cardiometabolic Diseases


title: A Metapopulation Network Model for the Spreading of SARS-CoV-2: Case Study for Ireland

abstract: We present preliminary results on an all-Ireland network modelling approach to simulate the spreading the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), commonly known as the coronavirus. In the model, nodes correspond to locations or communities that are connected by links indicating travel and commuting between different locations. While this proposed modelling framework can be applied on all levels of spatial granularity and different countries, we consider Ireland as a case study. The network comprises 3440 electoral divisions (EDs) of the Republic of Ireland and 890 superoutput areas (SOAs) for Northern Ireland, which corresponds to local administrative units below the NUTS 3 regions. The local dynamics within each node follows a phenomenological SIRX compartmental model including classes of Susceptibles, Infected, Recovered and Quarantined (X) inspired from Science 368, 742 (2020). For better comparison to empirical data, we extended that model by a class of Deaths. We consider various scenarios including the 5-phase roadmap for Ireland. In addition, as proof of concept, we investigate the effect of dynamic interventions that aim to keep the number of infected below a given threshold. This is achieved by dynamically adjusting containment measures on a national scale, which could also be implemented at a regional (county) or local (ED/SOA) level. We find that - in principle - dynamic interventions are capable to limit the impact of future waves of outbreaks, but on the downside, in the absence of a vaccine, such a strategy can last several years until herd immunity is reached.


title: Sex influences the effects of APOE genotype and Alzheimer's diagnosis on neuropathology and memory

abstract: Alzheimers disease (AD) is characterised by severe cognitive decline and pathological changes in the brain (brain atrophy, hyperphosphorylation of tau, and deposition of toxic amyloid-beta protein). Females have greater neuropathology (AD biomarkers and brain atrophy rates) and cognitive decline than males, however these effects can depend on diagnosis (amnestic mild cognitive impairment (aMCI) or AD) and APOE genotype (presence of {varepsilon}4 alleles). Using the ADNI database (N=630 females, N=830 males), we analysed the effect of sex, APOE genotype (non-carriers or carriers of APOE{varepsilon}4 alleles), and diagnosis (cognitively normal (CN), early aMCI (EMCI), late aMCI (LMCI), probable AD) on cognition (memory and executive function), hippocampal volume, and AD biomarkers (CSF levels of amyloid beta, tau and ptau). Regardless of APOE genotype, memory scores were higher in CN, EMCI, and LMCI females compared to males but this sex difference was absent in probable AD, which may suggest a delay in the onset of cognitive decline or diagnosis and/or a faster trajectory of cognitive decline in females. We found that, regardless of diagnosis, CSF tau-pathology was disproportionately elevated in female carriers of APOE{varepsilon}4 alleles compared to males. In contrast, male carriers of APOE{varepsilon}4 alleles had reduced levels of CSF amyloid beta compared to females, irrespective of diagnosis. We also detected sex differences in hippocampal volume but the direction was dependent on the method of correction. Altogether results suggest that across diagnosis females show greater memory decline compared to males and APOE genotype affects AD neuropathology differently in males and females which may influence sex differences in incidence and progression of aMCI and AD.


title: Maternal obesity and metabolic disorders associate with congenital heart defects in the offspring: a systematic review

abstract: Congenital heart defects (CHDs) are the most common congenital malformations and affect neonatal mortality and morbidity. The aetiology of CHDs is complex. Large cohort studies have reported an association between higher risk of CHDs in the offspring and individual maternal metabolic disorders such as obesity, diabetes, hypertension, and preeclampsia, all conditions that can be related to insulin resistance or hyperglycaemia and possibly metabolic syndrome (MetS). The aim of this review is to evaluate the existing evidence on the association between maternal metabolic disorders, defined as obesity, diabetes, hypertension, preeclampsia, dyslipidaemia, and MetS, or combinations thereof and CHDs overall as well as by subtype in the offspring. A literature search of PubMed and Embase databases identified 2,076 studies, 30 qualified for inclusion. All but one study investigated the individual metabolic disorders and their association with CHDs. Some disorders (obesity, gestational diabetes, and hypertension) increased risk of CHDs marginally whereas pre-gestational diabetes and early-onset preeclampsia were strongly associated with CHDs, without consistent differences between CHD subtypes. Future studies of the role of aberrations of the glucose-insulin homeostasis in the common aetiology and mechanisms of metabolic disorders, present during pregnancy, and their association with CHDs as well as subtypes of CHDs are needed.

category: obstetrics and gynecology


title: Assessing the nationwide impact of COVID-19 mitigation policies on the transmission rate of SARS-CoV-2 in Brazil

abstract: COVID-19 is now identified in almost all countries in the world, with poorer regions being particularly more disadvantaged to efficiently mitigate the impacts of the pandemic. In the absence of efficient therapeutics or vaccines, control strategies are currently based on non-pharmaceutical interventions, comprising changes in population behavior and governmental interventions, among which the prohibition of mass gatherings, closure of non-essential establishments, quarantine and movement restrictions. In this work we analyzed the effects of 707 published governmental interventions, and population adherence thereof, on the dynamics of COVID-19 cases across all 27 Brazilian states, with emphasis on state capitals and remaining inland cities. A generalized SEIR (Susceptible, Exposed, Infected and Removed) model with a time-varying transmission rate (TR), that considers transmission by asymptomatic individuals, is presented. We analyze the effect of both the extent of enforced measures across Brazilian states and population movement on the changes in the TR and effective reproduction number. The social mobility reduction index, a measure of population movement, together with the stringency index, adapted to incorporate the degree of restrictions imposed by governmental regulations, were used in conjunction to quantify and compare the effects of varying degrees of policy strictness across Brazilian states. Our results show that population adherence to social distance recommendations plays an important role for the effectiveness of interventions and represents a major challenge to the control of COVID-19 in low- and middle-income countries.


title: Group testing: revisiting the ideas

abstract: The task of identification of randomly scattered  bad items in a fixed set of objects is a frequent one, and there are many ways to deal with it.  Group testing (GT) refers to the testing strategy aiming to effectively replace the inspection of single objects by the inspection of groups spanning more than one object. First announced by Dorfman in 1943, the methodology has underwent vigorous development, and though many related research still takes place, the ground ideas remain the same. In the present paper, we revisit two classical GT algorithms: the Dorfmans algorithm and the halving algorithm. Our fresh treatment of the latter and expository comparison of the two is devoted to dissemination of GT ideas which are so important in the current COVID-19 induced pandemic situation.


title: Health care seeking behaviour and financial protection of patients with hypertension: a cross-sectional study in rural West Bengal, India

abstract:
BackgroundElevated blood pressure or hypertension is responsible for around 10 million annual deaths globally, and people residing in low and middle-income countries are disproportionately affected by it. India is no exception, where low rate of treatment seeking for hypertension coupled with widespread out-of-pocket payments (OOPs) have been a challenge. This study assessed the pattern of health care seeking and financial protection along with the associated factors among hypertensive individuals in a rural district of West Bengal, India.

Method and findingsA cross-sectional study was conducted in Birbhum district of the state of West Bengal, India during 2017-2018, where 300 individuals with hypertension were recruited randomly from a pre-defined list of individuals with hypertension in the district. Healthcare seeking along with two instance of financial protection -OOPs and relative expense, were analysed. Findings indicated that, of all hypertensives, 47% were not on treatment, 80% preferred private healthcare, and 91% of them had wide-spread OOPs. Cost of medication being a major share of expenses followed by significant transport cost to access public health care facility. Multivariable logistic regression analysis indicated longer duration of disease and private health care seeking were associated with more incident of OOPs. Results from linear regression modelling (generalized linear model) demonstrated association of co-morbidities with higher relative expenditure. Individuals belonging to poor economic group suffered from a high relative expense, compared to the richest.

ConclusionThis study suggested that individuals with hypertension had poor health care seeking, preferred private health care and had suboptimal financial protection. Hypertensives from economically poorer section had higher burden of health expenditure for treatment of hypertension, which indicated gaps in equitable health care for the control of hypertension.

category: health economics


title: A new estimation method for COVID-19 time-varying reproduction number using active cases

abstract: We propose a new method to estimate the time-varying effective (or instantaneous) reproduction number of the novel coronavirus disease (COVID-19). The method is based on a discrete-time stochastic augmented compartmental model that describes the virus transmission. A two-stage estimation method, which combines the Extended Kalman Filter (EKF) to estimate the reported state variables (active and removed cases) and a low pass filter based on a rational transfer function to remove short term fluctuations of the reported cases, is used with case uncertainties that are assumed to follow a Gaussian distribution. Our method does not require information regarding serial intervals, which makes the estimation procedure simpler without reducing the quality of the estimate. We show that the proposed method is comparable to common approaches, e.g., age-structured and new cases based sequential Bayesian models. We also apply it to COVID-19 cases in the Scandinavian countries: Denmark, Sweden, and Norway, where we see a delay of about four days in predicting the epidemic peak.


title: Inexpensive multi-patient respiratory monitoring system for helmet ventilation during COVID-19 pandemic

abstract:
BackgroundHelmet continuous positive applied pressure is a form of non-invasive ventilation (NIV) that has been used to provide respiratory support to COVID-19 patients. Helmet NIV is low-cost, readily available, provides viral filters between the patient and clinician, and may reduce the need for invasive ventilation. Its widespread adoption has been limited, however, by the lack of a respiratory monitoring system needed to address known safety vulnerabilities and to monitor patients. To address these safety and clinical needs, we developed an inexpensive respiratory monitoring system based on readily available components suitable for local manufacture. Open-source design and manufacturing documents are provided. The monitoring system comprises flow, pressure and CO2 sensors on the expiratory path of the helmet circuit and a central remote station to monitor up to 20 patients.

MethodsThe system is validated in bench tests, in human-subject tests on healthy volunteers, and in experiments that compare respiratory features obtained at the expiratory path to simultaneous ground-truth measurements from proximal sensors.

FindingsMeasurements of flow and pressure at the expiratory path are shown to deviate at high flow rates, and the tidal volumes reported via the expiratory path are systematically underestimated.

InterpretationHelmet monitoring systems exhibit high-flow rate, non-linear effects from flow and helmet dynamics. These deviations are found to be within a reasonable margin and should, in principle, allow for calibration, correction and deployment of clinically accurate derived quantities.

FundingThis project is supported by Princeton University, and by National Science Foundation grants OAC-1836650, PHY-2031509 and IOS-1845137. The funding sources provided no role in the design or execution of the the work or in the preparation of the manuscript.

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSRespiratory monitoring is standard when treating intubated patients undergoing invasive mechanical ventilation. In contrast, respiratory monitoring systems have not been developed for helmet non-invasive ventilation (NIV). Previous measurements of CO2 concentration in the helmet versus flow rate have been published and serve as the primary guide for setting the minimum flow rate for patient treatment of helmet NIV. Similar studies have explored optimal PEEP settings for clinical treatment. However, in practice, respiratory profiles are not measured during helmet treatment and more evidence is needed to evaluate whether clinically useful quantities, such as tidal volume, can be accurately measured during helmet NIV, to provide the same level of clincially relevant monitoring that is standard with invasive ventliation.

Added value of this studyDue to the widespread need for inexpensive multi-patient respiratory monitoring systems to cope with the COVID-19 pandemic, a helmet NIV monitoring system was developed and validated with bench tests, human-subject tests on healthy volunteers, and in experiments that compare respiratory features obtained at the expiratory path to simultaneous ground-truth measurements from proximal sensors. At high flow rate, the non-linear effects from the flow and helmet dynamics are observed and have a measurable effect on the estimation of tidal volumes and derived quantities.

Implications of all the available evidenceHelmet monitoring systems for NIV are in wide-spread use for the treatment of the coronavirus disease 2019. The introduction of respiratory monitoring systems for helmet NIV addresses important safety concerns and opens up the possibility of providing clinically relevant derived quantities to track disease progression. A systematic study of deviations between expiratory path measurements and ground-truth proximal sensors was conducted in bench tests and human-subject tests of health volunteers. The non-linear flow and helmet dynamics effects the accuracy of derived quantities at high flow rates. These deviations are found to be within a reasonable margin and should, in principle, allow for calibration, correction and deployment of clinically accurate derived quantities. An inexpensive implementation of the respiratory monitoring system was achieved to cope with the immense scale of the COVID-19 pandemic. Further steps to improve the quality of care for COVID-19 helmet NIV treatment can be achieved through the additional of respiratory monitoring systems that adjust for high flow-rate deviations in the estimation of tidal volumes and derived quantities.

category: intensive care and critical care medicine


title: Modeling impact and cost-effectiveness of gene drives for malaria elimination in the Democratic Republic of the Congo

abstract:
BackgroundThe tremendous burden of malaria has led to renewed efforts focusing on malaria elimination in high burden countries and has spurred the development of novel tools such as the use of transgenic mosquitoes to modify or suppress vector populations to interrupt transmission. Gene drives offer a pathway to propagate transgenes and their associated phenotypes to future generations more efficiently than the natural 50% probability and could potentially be applied as a vector control method. This study evaluates the role of suppression gene drives within broader intervention strategies, using the sex-ratio distorting driving-Y gene drive as an example.

MethodWe parameterize a spatially explicit, agent-based, mathematical model to capture malaria transmission in eight representative provinces of the Democratic Republic of the Congo, an operationally complex high-burden setting. We explore the potential impact of integrating driving-Y gene drive mosquitoes in malaria elimination strategies that include existing interventions such as insecticide-treated nets and treatment of clinical cases. An economic evaluation was performed to estimate the cost-effectiveness of gene drives, other interventions, and combinations.

FindingsReleases of gene drive mosquitoes were capable of eliminating malaria and were the most cost-effective intervention overall, as long as the drive component was highly effective with at least 95% X-shredding, and associated cost of deployment was below 7.17 $int per person per year.

InterpretationGenetically-based vector control via suppression gene drive could be a cost-effective supplement to traditional malaria interventions for malaria elimination, but tight constraints on drive effectiveness and cost ceilings may prove to limit its operational feasibility.

FundingFederal Ministry for Economic Cooperation and Development via German Academic Exchange Service (DAAD) and the Wellcome Trust.


title: Modeling the early phase of the Belgian COVID-19 epidemic using a stochastic compartmental model and studying its implied future trajectories

abstract: Following the onset of the ongoing COVID-19 pandemic throughout the world, a large fraction of the global population is or has been under strict measures of physical distancing and quarantine, with many countries being in partial or full lockdown. These measures are imposed in order to reduce the spread of the disease and to lift the pressure on healthcare systems. Estimating the impact of such interventions as well as monitoring the gradual relaxing of these stringent measures is quintessential to understand how resurgence of the COVID-19 epidemic can be controlled for in the future. In this paper we use a stochastic age-structured discrete time compartmental model to describe the transmission of COVID-19 in Belgium. Our model explicitly accounts for age-structure by integrating data on social contacts to (i) assess the impact of the lockdown as implemented on March 13, 2020 on the number of new hospitalizations in Belgium; (ii) conduct a scenario analysis estimating the impact of possible exit strategies on potential future COVID-19 waves. More specifically, the aforementioned model is fitted to hospital admission data, data on the daily number of COVID-19 deaths and serial serological survey data informing the (sero)prevalence of the disease in the population while relying on a Bayesian MCMC approach. Our age-structured stochastic model describes the observed outbreak data well, both in terms of hospitalizations as well as COVID-19 related deaths in the Belgian population. Despite an extensive exploration of various projections for the future course of the epidemic, based on the impact of adherence to measures of physical distancing and a potential increase in contacts as a result of the relaxation of the stringent lockdown measures, a lot of uncertainty remains about the evolution of the epidemic in the next months.


title: A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine

abstract:
BackgroundWe perform a phenome-wide scan to identify pre-existing conditions related to COVID-19 susceptibility and prognosis across the medical phenome and how they vary by race.

MethodsThe study is comprised of 53,853 patients who were tested/positive for COVID-19 between March 10 and September 2, 2020 at a large academic medical center.

ResultsPre-existing conditions strongly associated with hospitalization were renal failure, pulmonary heart disease, and respiratory failure. Hematopoietic conditions were associated with ICU admission/mortality and mental disorders were associated with mortality in non-Hispanic Whites. Circulatory system and genitourinary conditions were associated with ICU admission/mortality in non-Hispanic Blacks.

ConclusionsUnderstanding pre-existing clinical diagnoses related to COVID-19 outcomes informs the need for targeted screening to support specific vulnerable populations to improve disease prevention and healthcare delivery.


title: Phenoflow: A Microservice Architecture for Portable Workflow-based Phenotype Definitions

abstract: Phenotyping is an effective way to identify cohorts of patients with particular characteristics within a population. In order to enhance the portability of a phenotype definition across institutions, it is often defined abstractly, with implementers expected to realise the phenotype computationally before executing it against a dataset. However, unclear definitions, with little information about how best to implement the definition in practice, hinder this process. To address this issue, we propose a new multi-layer, workflow-based model for defining phenotypes, and a novel authoring architecture, Phenoflow, that supports the development of these structured definitions and their realisation as computable phenotypes. To evaluate our model, we determine its impact on the portability of both code-based (COVID-19) and logic-based (diabetes) definitions, in the context of key datasets, including 26,406 patients at North-western University. Our approach is shown to ensure the portability of phenotype definitions and thus contributes to the transparency of resulting studies.

category: health informatics


title: Spatiotemporal Trends in Bed Bug Metrics, New York City

abstract: Bed bug outbreaks pose a major challenge in urban environments and cause significant strain on public resources. Few studies have systematically analyzed the epidemic or the potential effects of policies to combat bed bugs. Here we use three sources of administrative data to characterize the spatial-temporal trends of bed bug inquiries, complaints, and reports in New York City. From 2014-2020, Bed bug complaints have significantly decreased (p < 0.01), the absolute number of complaints per month dropping by half (875 average complaints per month to 440 average complaints per month); conversely cockroach-specific complaints increased over the same period. Despite the decrease of bed bug complaints, areas with reported high bed bug infestation tend to remain infested, highlighting the persistence of these pests. There are limitations to the datasets; still the evidence available suggests that interventions employed by New York City residents and lawmakers are stemming the bed bug epidemic and may serve as a model for other large cities.


title: Identifying target regions for enhanced control of gambiense human African trypanosomiasis in the Democratic Republic of Congo

abstract: Gambiense human African trypanosomiasis (sleeping sickness, gHAT) is a disease targeted for elimination of transmission (EOT) by 2030. Despite the number of new cases reported annually being at a historical minimum, the likelihood of achieving EOT is unknown. We utilised modelling to study the impact of four strategies comprised of currently-available intervention methods including active and passive screening and vector control (VC) on transmission across 168 health zones in the Democratic Republic of the Congo. By estimating the median year of EOT and the probability of EOT by 2030 under each strategy, the model predicts only 81 health zones are on track to achieve the EOT target using medical-only strategies and this number drops to 52 when uncertainty is considered (> 90% probability). Although all health zones are predicted to meet EOT by 2030 under strategies with VC, blanket coverage is impractical so this analysis provides a priority list of health zones for consideration for supplementary VC implementation in conjunction with medical interventions.


title: Convolutional neural networks on eye tracking trajectories classify patients with spatial neglect

abstract:
Background and ObjectiveEye-movement trajectories are rich behavioral data, providing a window on how the brain processes information. We address the challenge of characterizing signs of visuo-spatial neglect from saccadic eye trajectories recorded in brain-damaged patients with spatial neglect as well as in healthy controls during a visual search task.

MethodsWe establish a standardized preprocessing pipeline adaptable to other task-based eye-tracker measurements. We use a deep convolutional network, a very successful type of neural network architecture in many computer vision applications, including medical diagnosis systems, to automatically analyze eye trajectories.

ResultsOur algorithm can classify brain-damaged patients vs. healthy individuals with an accuracy of 86{+/-}5%. Moreover, the algorithm scores correlate with the degree of severity of neglect signs estimated with standardized paper-and-pencil test and with white matter tracts impairment via Diffusion Tensor Imaging (DTI). Interestingly, the latter showed a clear correlation with the third branch of the superior longitudinal fasciculus (SLF), especially damaged in neglect.

ConclusionsThe study introduces a new classification method to analyze eyes trajectories in patients with neglect syndrome. The method can likely be applied to other types of neurological diseases opening to the possibility of new computer-aided, precise, sensitive and non-invasive diagnosing tools.

HighlightsO_LIWe identify signs of visuo-spatial neglect through an automated analysis of saccadic eye trajectories using deep convolutional neural networks (CNNs).
C_LIO_LIWe provide a standardized pre-processing pipeline adaptable to other task-based eye-tracker measurements.
C_LIO_LIPatient-wise, we benchmark the algorithm prediction with standardized paper-and-pencil test results.
C_LIO_LIWe evaluate white matter tracts by using Diffusion Tensor Imaging (DTI) and find a clear correlation with the microstructure of the third branch of the superior longitudinal fasciculus.
C_LIO_LIDeep CNNs can efficiently and non-invasively characterize left spatial neglect.
C_LI


title: Impact of climate on COVID-19 transmission: A case study with Indian states

abstract: Coronavirus Disease 2019 (COVID-19) started in Wuhan province of China in November 2019 and within a short time, it was declared as a worldwide pandemic by the World Health Organisation due to the very fast worldwide spread of the virus. There were a few studies that look for the correlation with infected individuals and different environmental parameters using early data of COVID-19 but there was no study that deal with the variation of effective reproduction number and environmental factors. Effective reproduction number is the driving parameter of the spread of a pandemic and it is important to study the effect of various environmental factors on effective reproduction numbers to understand the effect of those factors on the spread of the virus. We have used time-dependent models to investigate the variation of different time-dependent driving parameters of COVID-19 like effective reproduction number and contact rate using data from India as a test case. India is a large population country that was highly affected due to the COVID-19 pandemic and has a wide span of different temperature and humidity regions and is ideal for such study. We have studied the impact of temperature and humidity on the spread of the virus of different Indian states using time-dependent epidemiological models SIRD, and SEIRD for a long time scale. We used a linear regression method to look for any dependency between the effective reproduction number with the relative humidity, absolute humidity, and temperature. The effective reproduction number showed a negative correlation with both relative and absolute humidity for most of the Indian states, which are statistically significant. This implies that relative and absolute humidity may have an important role in the variation of effective reproduction numbers. There was no conclusive evidence of a correlation between effective reproduction numbers and average air temperature.


title: Developing a deep learning system to drive the work of the critical care outreach team

abstract:
BackgroundCare of patients at risk of deterioration on acute medical and surgical wards requires timely identification, increased monitoring and robust escalation procedures. The critical care outreach role brings specialist-trained critical care nurses and physicians into acute wards to facilitate these processes. Performing this role is challenging, as the breadth of information synthesis required is both high and rapidly updating.

We propose a novel automated  watch-list to identify patients at high risk of deterioration, to help prioritise the work of the outreach team.

ResultsThis system takes data from the electronic medical record in real-time and creates a discrete tokenized trajectory, which is fed into a recurrent neural network model. These models achieve an AUROC of 0.928 for inpatient death and 0.778 for unplanned ICU admission (within 24 hours), which compares favourably with existing early warning scores and is comparable with proof of concept deep learning systems requiring significantly more input data.

ConclusionsBased on these results, we can conclude that it is technically feasible to build a set of predictive models that meet the needs of the critical care outreach role, based on a limited set of real-time clinical data.


title: Community factors associated with local epidemic timing of respiratory syncytial virus: a spatiotemporal modeling study

abstract:
BackgroundRespiratory syncytial virus (RSV) causes a large burden of morbidity in infants, young children, and the elderly. The timing of RSV seasonal epidemics exhibits strong spatial patterns within the United States. Spatial variability in the timing of RSV epidemics provides an opportunity to probe the factors driving transmission of the virus.

MethodsWe evaluated competing hypotheses about the associations between RSV epidemic timing at the ZIP-code level and household size, population density, school district boundaries, commuting patterns, and geographic proximity. We used hierarchical Bayesian models with monthly ZIP-code level hospitalization data from New York, New Jersey, and Connecticut between July 1997 and June 2014 to investigate these hypotheses.

ResultsEarly epidemic timing across ZIP codes was associated with large household sizes and high population density, and nearby ZIP codes shared similar epidemic timing. Variations in epidemic timing attributed to commuting patterns or school district boundaries are negligible.

ConclusionOur results suggest RSV epidemics take off faster in areas with more household crowding and higher population density, and that epidemic spread follows a spatial diffusion process based on geographic proximity. With several vaccines against RSV under development, it is important to understand the drivers of RSV transmission and disease in order to maximize population protection of a vaccine program. Our findings can inform more effective control measures against RSV, such as vaccine programs and household infection control, and guide future studies on the transmission dynamics of RSV.


title: Community factors associated with local RSV epidemic patterns: a spatiotemporal modeling study


title: Characterisation of alcohol polygenic risk scores in the context of mental health outcomes: Within-individual and intergenerational analyses in the Avon Longitudinal Study of Parents and Children

abstract:
BackgroundHeavy alcohol consumption often co-occurs with mental health problems; this could be due to confounding, shared biological mechanisms, or causal effects. Polygenic risk scores (PRS) for alcohol use can be used to explore this association at critical life stages.

DesignWe characterised a PRS reliably associated with patterns of adult alcohol consumption by 1) validating whether it predicts own alcohol use at different life-stages (pregnancy, adolescence) of interest for mental health impact. Additionally, we explored associations of alcohol PRS on mental health phenotypes 2) within-individuals (using own alcohol PRS on own phenotypes) and 3) intergenerationally (using maternal alcohol PRS on offspring phenotypes). We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (n=960 to 7841). Additional substance abuse behaviours and mental health/behavioural outcomes were investigated (alcohol phenotypes n=22; health phenotypes n=91). Findings: Maternal alcohol PRS was associated with consumption during pregnancy (strongest signal: alcohol frequency at 18 weeks gestation: {beta}=0.041, 95% CI=1.02 to 1.8), p=1.01x10-5, adjusted R2=1.16%), offspring alcohol PRS did not predict offspring alcohol consumption. We found evidence for an association of maternal alcohol PRS with own perinatal depression (OR=1.10, 95% CI=0.02 to 0.06, p=0.02) and decreased offspring intellectual ability ({beta}=-0.209, 95% CI -0.38 to 0.04, p=0.016). Conclusions: These alcohol PRS are a valid proxy for maternal alcohol use in pregnancy. Offspring alcohol PRS was not associated with drinking in adolescence.

Consistently with results from different study designs, we found evidence that maternal alcohol PRS are associated with both prenatal depression and decreased offspring intellectual ability.


title: APOE-stratified genome-wide association study suggests potential novel genes for late-onset Alzheimers disease in East-Asian descent

abstract: In this study, we report two new possible susceptible genes for late-onset Alzheimers disease identified through an APOE-stratified genome-wide association analysis (GWAS) using East Asian samples. In the discovery phase, we performed a GWAS of Alzheimers disease in 2,291 Korean seniors from the Gwangju Alzheimers and Related Dementias (GARD) cohort study. A successive replication analysis with a Japanese sample of size 1,956 suggested three novel susceptible SNPs in two genes: LRIG1 and CACNA1A. This study demonstrates that the discovery of AD-associated variants can be accomplished in non-European ethnic groups with a more homogeneous genetic background using samples comprising fewer subjects.


title: Ward-Level Factors Associated with Methicillin-Resistant Staphylococcus aureus Acquisition - an Electronic Medical Records study in Singapore

abstract:
BackgroundMethicillin-Resistant Staphylococcus aureus (MRSA) is endemic in hospitals worldwide. When patients are transferred between wards within a hospital, their risk of acquiring MRSA may change. In this study, we investigated how ward characteristics and connectivity are associated with MRSA acquisition.

MethodsWe analysed electronic medical records on patient transfers and MRSA screening of in-patients at an acute-care tertiary hospital in Singapore to investigate whether ward characteristics and connectivity within the hospital network were associated with MRSA acquisition rates over a period of four years.

ResultsMost patient transfers concentrated in a stable core network of wards. Factors associated with increased rate of MRSA acquisition were ward MRSA admission prevalence (rate ratio (RR): 1.50, 95% CI: 1.28, 1.71, per one percentage point increase), admission to a critical care ward (RR: 1.86, 95% CI: 1.14, 3.06) and average number of patients in the ward on a typical day (RR: 1.31, 95% CI: 1.02, 1.68, for every 10 patients quarterly). Admission to an oncology ward (RR: 0.61, 95% CI: 0.40, 0.93) (compared to medical ward), and median length of stay (RR: 0.71, 95% CI: 0.54, 0.93) were associated with lower acquisition rates. We did not find evidence that network measures of ward connectivity, including in-degree, weighted in-degree, influenced MRSA acquisition rate after adjusting for other ward characteristics.

ConclusionWard MRSA admission prevalence, critical care ward, ward patient capacity, ward specialty, and median length of stay, rather than relative connectivity of the ward in the hospital network were associated with MRSA acquisition.


title: Two Separate, Large Cohorts Reveal Potential Modifiers of Age-Associated Variation in Visual Reaction Time Performance

abstract: To identify individual differences and potential factors influencing age-related cognitive decline and disease, we created MindCrowd. MindCrowd is a cross-sectional web-based assessment of simple visual (sv) reaction time (RT, index of processing speed) and paired-associate learning (PAL, index of verbal episodic memory). svRT and PAL results were combined with 22 survey questions. Analysis of MindCrowds svRT data revealed education and reported stroke as potential modifiers of changes in processing speed and memory from younger to older ages (ntotal = 75,666, nwomen = 47,700, nmen = 27,966; ages 18-85 years old, mean (M)Age = 46.54, standard deviation (SD)Age = 18.40). To complement this work, we evaluated complex recognition reaction time (cvrRT) in the UK Biobank cohort (ntotal = 158,249 nwomen = 89,333 nmen = 68,916; ages 40-70 years old, MAge = 55.81, SDAge = 7.72). Similarities between the UK Biobank and MindCrowd were assessed using a subset of the MindCrowd cohort. Labeled UKBb MindCrowd (ntotal = 39,795, nwomen = 29,640, nmen = 10,155; ages 40-70 years old, MAge = 56.59, SDAge = 8.16), this subset was carefully selected to mirror the UK Biobank. An identical linear model (LM) was used to assess both cohorts. The LM revealed similarities between MindCrowd and the UK Biobank across most results, despite obvious cohort differences (e.g., US vs. the UK). Notable divergent findings from the UK Biobank included (1) a first-degree family history of Alzheimers disease (FHAD) was associated with longer RTs in only. (2) Compared to being a man with more education, being a woman was associated with longer cvrRT length differences observed from younger to older ages. Divergent results from UKBb MindCrowd include more education and reported smoking. More education was associated with shorter and smoking longer cvrRTs differences observed from younger to older ages. Collected with our prior work, MindCrowd is beginning to reveal the intricate network connecting processing speed, memory, and cognition to healthy and pathological brain aging.

category: geriatric medicine


title: Growth Differentiation Factor-15 as a candidate biomarker in gynecologic malignancies: a meta-analysis

abstract: Growth Differentiation Factor-15 (GDF-15), though emerged as a novel marker in gynecological cancers, is yet to be recognized in clinical diagnostics. Eligible studies were sorted from multiple online databases, namely PubMed, Cochrane, ClinicalTrials.gov, Google Scholar, Web of Science, Embase, Scopus, LILACS, OpenGrey. From six studies, histopathologically diagnosed cases without prior treatment, and with diagnostic accuracy data for GDF-15 in gynecological cancers, were included. Our meta-analysis shows that GDF-15 has pooled diagnostic odds ratio of 12.74 at 80.5% sensitivity and 74.1% specificity, and an AUC of 0.84. Hence, GDF-15 is a potential marker to differentiate gynecological malignancy from non-malignant tumors.


title: Using computable knowledge mined from the literature to elucidate confounders for EHR-based pharmacovigilance

abstract:
IntroductionConfounding bias threatens the reliability of observational studies and poses a significant scientific challenge. This paper introduces a framework for identifying confounding factors by exploiting literature-derived computable knowledge. In previous work, we have shown that semantic constraint search over computable knowledge extracted from the literature can be useful for reducing confounding bias in statistical models of EHR-derived observational clinical data. We hypothesize that adjustment sets of literature-derived confounders could also improve causal inference.

MethodsWe introduce two methods (semantic vectors and string-based confounder search) that query the literature for potential confounders and use this information to build models from EHR-derived data to more accurately estimate causal effects. These methods search SemMedDB for indications TREATED BY the drug that is also known to CAUSE the adverse event. For evaluation, we attempt to rediscover associations in a publicly available reference dataset containing expected pairwise relationships between drugs and adverse events from empirical data derived from a corpus of 2.2M EHR-derived clinical notes. For our knowledge-base, we use SemMedDB, a database of computable knowledge mined from the biomedical literature. Using standard adjustment and causal inference procedures on dichotomous drug exposures, confounders, and adverse event outcomes, varying numbers of literature-derived confounders are combined with EHR data to predict and estimate causal effects in light of the literature-derived confounders. We then compare the performance of the new methods with naive ({chi}2, reporting odds ratio) measures of association.

Results and ConclusionsLogistic regression with ten vector space-derived confounders achieved the most improvement with AUROC of 0.628 (95% CI: [0.556,0.720]), compared with baseline{chi} 20.507 (95% CI: [0.431,0.583]). Bias reduction was improved more often in modeling methods using more rather than less information, and using semantic vector rather than string-based search. We found computable knowledge useful for improving automated causal inference, and identified opportunities for further improvement, including a role for adjudicating literature-derived confounders by subject matter experts.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=86 SRC="FIGDIR/small/20113035v1_ufig1.gif" ALT="Figure 1">
View larger version (27K):
org.highwire.dtl.DTLVardef@77d8a9org.highwire.dtl.DTLVardef@317d09org.highwire.dtl.DTLVardef@107dc05org.highwire.dtl.DTLVardef@fdf3c5_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsO_LIAccess to causal background knowledge is required for causal learning to scale to large datasets.
C_LIO_LIWe introduce a framework for identifying confounders to enhance causal inference from EHR.
C_LIO_LIWe search computable knowledge for indications TREATED BY the drug that CAUSE the outcome.
C_LIO_LILiterature-derived confounders reduce confounding bias in EHR data.
C_LIO_LIStructured knowledge helps interpret and explain data captured in clinical narratives.
C_LI


title: Zika Virus Congenital Microcephaly Severity Classification and the Association of Severity with Neuropsychomotor Development

abstract:
BackgroundZika virus infection during pregnancy is linked to birth defects, most notably, microcephaly, which in its turn, is associated with neurodevelopmental delays.

ObjectiveThe goal of the study is to propose a method for severity classification of congenital microcephaly based on neuroradiological findings of MRI scans, and to investigate the association of severity with neuropsychomotor developmental scores. We also propose a semi-automated method for MRI-based severity classification of microcephaly.

MethodsCross-sectional investigation of 42 infants born with congenital Zika infection. Bayley-III developmental evaluations and MRI scans were carried out at ages 13-39 months (mean: 24.8, SD: 5.8). The severity score was generated based on neuroradiologist evaluations of brain malformations. Next, we established a distribution of Zika virus-microcephaly severity score into mild, moderate, and severe and investigated the association of severity with neuropsychomotor developmental scores. Finally, we propose a simplified semi-automated procedure for estimating the severity score, based only on volumetric measures.

ResultsResults showed a correlation of r = 0.89 (p < 0.001) between the Zika virus-microcephaly severity score and the semi-automated method. The trimester of infection did not correlate with the semi-automated method. Neuropsychomotor development correlated with the severity classification based on radiological readings and with the semi-automated method; the more severe the imaging scores, the lower neuropsychomotor developmental scores.

ConclusionThe severity classification methods may be used to evaluate severity of microcephaly and possible association with developmental consequences. The semi-automated methods thus may be an alternative for prediction of severity of microcephaly using only one MRI sequence.


title: What effect might border screening have on preventing importation of COVID-19 compared with other infections? A modelling study

abstract:
The effectiveness of screening travellers during times of international disease outbreak is contentious, especially as the reduction in the risk of disease importation can be very small. Border screening typically consists of travellers being thermally scanned for signs of fever and/or completing a survey declaring any possible symptoms prior to admission to their destination country; while more thorough testing typically exists, these would generally prove more disruptive to deploy. In this paper, we describe a simple Monte Carlo based model that incorporates the epidemiology of COVID-19 to investigate the potential benefit of requiring all travellers to undergo thorough screening upon arrival. This is a purely theoretical study to investigate whether a single test at point of entry might ever prove to be a way of significantly decreasing risk of importation. We therefore assume ideal conditions such as 100% compliance among travellers and the use of a "perfect" test. In addition to COVID-19, we also apply the presented model to simulated outbreaks of Influenza, SARS and Ebola for comparison. Our model only considers screening implemented at airports, being the predominant method of international travel. Primary results showed that in the best-case scenario, screening may expect to detect 8.8% of travellers infected with COVID-19, compared to 34.8.%, 9.7% and 3.0% for travellers infected with influenza, SARS and Ebola respectively. While results appear to indicate that screening is more effective at preventing disease ingress when the disease in question has a shorter average incubation period, our results indicate that screening alone does not represent a sufficient method to adequately protect a nation from the importation of COVID-19 cases.

Data availabilityAll results described in the work, in addition to technical descriptions of methods used, are made available in the supplementary material. The Python package used to implement these methods and obtain our results has been made accessible online[1].


title: Wastewater SARS-CoV-2 Concentration and Loading Variability from Grab and 24-Hour Composite Samples

abstract: The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires a significant, coordinated public health response. Assessing case density and spread of infection is critical and relies largely on clinical testing data. However, clinical testing suffers from known limitations, including test availability and a bias towards enumerating only symptomatic individuals. Wastewater-based epidemiology (WBE) has gained widespread support as a potential complement to clinical testing for assessing COVID-19 infections at the community scale. The efficacy of WBE hinges on the ability to accurately characterize SARS-CoV-2 RNA concentrations in wastewater. To date, a variety of sampling schemes have been used without consensus around the appropriateness of grab or composite sampling. Here we address a key WBE knowledge gap by examining the variability of SARS-CoV-2 RNA concentrations in wastewater grab samples collected every 2 hours for 72 hours compared with three corresponding 24-hour flow-weighted composite samples collected over the same period. Results show relatively low variability (respective means for N1, N2, N3 assays = 608, 847.9, 768.4 copies 100 mL-1, standard deviations = 501.4, 500.3, 505.8 copies 100 mL-1) for grab sample concentrations, and good agreement between most grab samples and their respective composite (mean deviation from composite = 159 copies 100 mL-1). When SARS-CoV-2 RNA concentrations are used to calculate viral load (RNA concentration * total influent flow the sample day), the discrepancy between grabs (log10 range for all grabs = 11.9) or a grab and its associated 24-hour composite (log10 difference = 11.6) are amplified. A similar effect is seen when estimating carrier prevalence in a catchment population with median estimates based on grabs ranging 63-1885 carriers. Findings suggest that grab samples may be sufficient to characterize SARS-CoV-2 RNA concentrations, but additional calculations using these data may be sensitive to grab sample variability and warrant the use of flow-weighted composite sampling. These data inform future WBE work by helping determine the most appropriate sampling scheme and facilitate sharing of datasets between studies via consistent methodology.


title: Excess Mortality probably due to COVID-19 in Tokyo, Japan in August, 2020

abstract:
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan.

ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model.

MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo.

ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected

Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.


title: Few Excess Mortality probably due to COVID-19 in Tokyo, Japan in August and October, 2020


title: Excess Mortality probably due to COVID-19 in Tokyo, Japan in August and September, 2020


title: Excess Mortality probably due to COVID-19 in Tokyo, Japan between August and October, 2020


title: Significant Excess Mortality probably due to COVID-19 in Tokyo, Japan until March, 2021


title: Significant Excess Mortality probably due to COVID-19 in Tokyo, Japan until April, 2021


title: Significant Excess Mortality probably due to COVID-19 in Tokyo, Japan until May, 2021


title: Huge Excess Mortality due to the delta strain of COVID-19 in Japan in August, 2021


title: Huge Excess Mortality due to the delta strain of COVID-19 in Japan in August and September, 2021


title: Associations of Loneliness and Social Isolation with Healthspan and Lifespan in the US Health and Retirement Study

abstract:
BackgroundLoneliness and social isolation are emerging public health challenges for aging populations.

MethodsWe followed N=11,302 US Health and Retirement Study (HRS) participants aged 50-95 from 2006-2014 to measure persistence of experiences of loneliness and exposure to social isolation. We tested associations of longitudinal loneliness and social isolation phenotypes with disability, morbidity, mortality, and biological aging through 2018.

ResultsDuring follow-up, 18% of older adults met criteria for loneliness, with 6% meeting criteria at two or more follow-up assessments. For social isolation, these fractions were 21% and 8%. HRS participants who experienced loneliness and were exposed to social isolation were at increased risk for disease, disability, and mortality. Those experiencing persistent loneliness were at a 57% increased hazard of mortality compared to those who never experienced loneliness. For social isolation, the increase was 28%. Effect-sizes were somewhat larger for counts of prevalent activity limitations and somewhat smaller for counts of prevalent chronic diseases. Covariate adjustment for socioeconomic and psychological risks attenuated but did not fully explain associations. Older adults who experienced loneliness and were exposed to social isolation also exhibited physiological indications of advanced biological aging (Cohens-d for persistent loneliness and social isolation=0.26 and 0.21, respectively). For loneliness, but not social isolation, persistence was associated with increased risk.

ConclusionDeficits in social connectedness prevalent in a national sample of US older adults were associated with morbidity, disability, and mortality and with more advanced biological aging. Bolstering social connectedness to interrupt experiences of loneliness may promote healthy aging.


title: Evolution of DNA methylome from precancerous lesions to invasive lung adenocarcinomas

abstract: The evolution of DNA methylome and methylation intra-tumor heterogeneity (ITH) during early carcinogenesis of lung adenocarcinoma has not been systematically studied. We perform reduced representation bisulfite sequencing of invasive lung adenocarcinoma and its precursors, atypical adenomatous hyperplasia, adenocarcinoma in situ and minimally invasive adenocarcinoma. We observe gradual increase of methylation aberrations and significantly higher level of methylation ITH in later-stage lesions. The phylogenetic patterns inferred from methylation aberrations resemble those based on somatic mutations suggesting parallel methylation and genetic evolution. De-convolution reveal higher ratio of T regulatory cells (Tregs) versus CD8+ T cells in later-stage diseases, implying progressive immunosuppression with neoplastic progression. Furthermore, increased global hypomethylation is associated with higher mutation burden, copy number variation burden and allelic imbalance burden as well as higher Treg/CD8 ratio, highlighting the potential impact of methylation on chromosomal instability, mutagenesis and tumor immune microenvironment during early carcinogenesis of lung adenocarcinomas.


title: Causal influence of dietary habits on the risk of major depressive disorder: A diet-wide Mendelian randomization analysis

abstract:
Background & aimsSome evidence suggests that diet may potentially increase or decrease the risk of major depressive disorder (MDD). However, the association between dietary habits and MDD remains controversial. The aim of this study is to systemically investigate the causal influence of dietary habits on the risk of MDD by Mendelian randomization (MR) using diet- and genome-wide summary data.

MethodsTo perform two-sample MR, we collected publicly available genome-wide association studies summary statistics for dietary habits from Benjamin Neales lab (n = 361,194) and MDD from the Psychiatric Genomics Consortium (n = 142,646). We used a weighted median approach to synthesize MR estimates across genetic instruments. For the robustness of our results, we compared weighted median results with results from the inverse-variance weighted method, the weighted mode method, and MR-PRESSO.

ResultsBeef intake showed a significant protective effect against MDD ({beta} = -1.25; p-value = 0.002; Bonferroni-corrected p-value = 0.034; 9 single nucleotide polymorphisms [SNPs]); and cereal intake was nominally significantly protective ({beta} = -0.52; p-value = 0.011; 21 SNPs). In contrast, non-oily fish intake showed a nominally significantly effect on the risk of MDD ({beta} = 0.84; p-value = 0.030; 6 SNPs). We obtained similar results by using an inverse-variance weighted method and weighted mode approach, although some results were non-significant. On the other hand, we did not observe any significant causal effect of MDD on dietary habits.

ConclusionsIn this two-sample MR analysis, we observed that higher beef and cereal intake may be protective factors for MDD, and that higher non-oily fish intake might increase the risk for MDD. However, MDD did not appear to affect dietary habits. Potential mechanisms need to be further investigated to support our novel findings.


title: The consequences of adjustment, correction and selection in genome-wide association studies used for two-sample Mendelian randomization

abstract:
IntroductionGenome-wide association studies (GWASs) often adjust for covariates, correct for medication use, or select on medication users. If these summary statistics are used in two-sample Mendelian randomization analyses, estimates may be biased. We used simulations to investigate how GWAS adjustment, correction and selection affects these estimates and performed an analysis in UK Biobank to provide an empirical example.

MethodsWe simulated six GWASs: no adjustment for a covariate, correction for medication use, or selection on medication users; adjustment only; selection only; correction only; both adjustment and selection; and both adjustment and correction. We then ran two-sample Mendelian randomization analyses using these GWASs to evaluate bias. We also performed equivalent GWASs using empirical data from 306,560 participants in UK Biobank with systolic blood pressure as the exposure and body mass index as the covariate and ran two-sample Mendelian randomization with coronary heart disease as the outcome.

ResultsThe simulation showed that estimates from GWASs with selection can produce biased two-sample Mendelian randomization estimates. Yet, we observed relatively little difference between empirical estimates of the effect of systolic blood pressure on coronary artery disease across the six scenarios.

ConclusionsGiven the potential for bias from using GWASs with selection on Mendelian randomization estimates demonstrated in our simulation, careful consideration before using this approach is warranted. However, based on our empirical results, using adjusted, corrected or selected GWASs is unlikely to make a large difference to two-sample Mendelian randomization estimates in practice.


title: Fluvastatin mitigates SARS-CoV-2 infection in human lung cells

abstract: The retrospective analysis of clinical data of patients suffering from COVID-19 has indicated that statin therapy, used to lower plasma cholesterol levels, is associated with a better clinical outcome. We therefore investigated the effect of statins on SARS-CoV-2 infection and found that selective statins reduced SARS-CoV-2 cell entry and inhibited high and low pathogenic coronavirus infection in human cells. A retrospective study on hospitalized patients with COVID-19 implies that reduced high density lipoprotein levels, which are typically counteracted by statin therapy, are associated with aggravated disease outcome. These results suggest that statin therapy poses no additional risk to individuals exposed to SARS-CoV-2 and that some statins may have a mild beneficial effect on COVID-19 outcome. Placebo controlled trials are required to clarify the role of statins in COVID-19 infected patients.


title: Power law behaviour in the saturation regime of fatality curves of the COVID-19 pandemic

abstract: ABSTRACWe apply a versatile growth model, whose growth rate is given by a generalised beta distribution, to describe the complex behaviour of the fatality curves of the COVID-19 disease for several countries in Europe and North America. We show that the COVID-19 epidemic curves not only may present a subexponential early growth but can also exhibit a similar subexponential (power-law) behaviour in the saturation regime. We argue that the power-law exponent of the latter regime, which measures how quickly the curve approaches the plateau, is directly related to control measures, in the sense that the less strict the control, the smaller the exponent and hence the slower the diseases progresses to its end. The power-law saturation uncovered here is an important result, because it signals to policymakers and health authorities that it is important to keep control measures for as long as possible, so as to avoid a slow, power-law ending of the disease. The slower the approach to the plateau, the longer the virus lingers on in the population, and the greater not only the final death toll but also the risk of a resurgence of infections.


title: Persistent intestinal abnormalities and symptoms in cystic fibrosis: The underpinning mechanisms impacting gut health and motility. Protocol for a systematic review.

abstract:
BackgroundPatients with cystic fibrosis (CF) are characterised by abnormalities of the intestinal tract relating to gut motility and physiological issues, with daily symptoms of disease including abdominal pain, flatulence, bloating, and constipation. With improvements in respiratory outcomes, a shift in disease manifestations has highlighted the prevalence of the gastrointestinal-related problems associated with CF, yet most therapies currently in clinical use for the gut symptoms of CF have been repurposed from other disease indications and have not been developed with a knowledge of the mechanisms underpinning gastrointestinal disease in CF. Increased attention towards the role of intestinal inflammation and microbial dysbiosis in the CF population warrants a comprehensive knowledge of these aspects alongside the increased luminal fat content, dysmotility, and small intestinal bacterial overgrowth (SIBO) resultant of the primary consequences of CFTR dysfunction (disrupted fluid secretion and pancreatic insufficiency), and how they contribute towards the intestinal complications of CF disease.

Methods and Study DesignWe will conduct a systematic review to comprehensively address our current understanding of the primary consequences of CFTR dysfunction, and their subsequent secondary effects that contribute towards the disruption of gut motility, health, and associated symptoms in the CF intestine. Databases searched will include PubMed, CINAHL, MEDLINE and the Cochrane library from 1939 until a specified date of last search, alongside clinical trial databases for ongoing studies. Search strategies will include various terminology that relates to the primary mechanistic defects of CF, postulated secondary effects of such defects, and symptoms experienced in patients. A full search strategy is outlined in appendix B. One reviewer will apply an inclusion criterion to obtained abstracts. Following agreement from a second reviewer, full-text articles will be sought, and data will be extracted from relevant articles. Disagreements will be resolved with a third reviewer. The quality of data will be assessed by the GRADE criteria. Data will be used to present a narrative, and where possible, quantitative synthesis.

DiscussionThis systematic review will discuss our current understanding of the underpinning mechanisms of the persisting abnormalities in gut health and motility within CF, addressing potential intricate relationships that further contribute to disease progression within the intestinal tract. Furthermore, we will identify current gaps in the literature to propose directions for future research. A comprehensive understanding of these aspects in relation to intestinal abnormalities will aid future clinical directions.

category: gastroenterology


title: Covid-19 infection and attributable mortality in UK Long Term Care Facilities: Cohort study using active surveillance and electronic records (March-June 2020)

abstract:
BackgroundEpidemiological data on COVID-19 infection in care homes are scarce. We analysed data from a large provider of long-term care for older people to investigate infection and mortality during the first wave of the pandemic.

MethodsCohort study of 179 UK care homes with 9,339 residents and 11,604 staff.We used manager-reported daily tallies to estimate the incidence of suspected and confirmed infection and mortality in staff and residents. Individual-level electronic health records from 8,713 residents were used to model risk factors for confirmed infection, mortality, and estimate attributable mortality.

Results2,075/9,339 residents developed COVID-19 symptoms (22.2% [95% confidence interval: 21.4%; 23.1%]), while 951 residents (10.2% [9.6%; 10.8%]) and 585 staff (5.0% [4.7%; 5.5%]) had laboratory-confirmed infections. The incidence of confirmed infection was 152.6 [143.1; 162.6] and 62.3 [57.3; 67.5] per 100,000 person-days in residents and staff respectively. 121/179 (67.6%) care homes had at least one COVID-19 infection or COVID-19-related death. Lower staffing ratios and higher occupancy rates were independent risk factors for infection.

217/607 residents with confirmed infection died (case-fatality rate: 35.7% [31.9%; 39.7%]). Mortality in residents with no direct evidence of infection was two-fold higher in care homes with outbreaks versus those without (adjusted HR 2.2 [1.8; 2.6]).

ConclusionsFindings suggest many deaths occurred in people who were infected with COVID-19, but not tested. Higher occupancy and lower staffing levels were independently associated with risks of infection. Protecting staff and residents from infection requires regular testing for COVID-19 and fundamental changes to staffing and care home occupancy.


title: Dynamics of B-cell repertoires and emergence of cross-reactive responses in COVID-19 patients with different disease severity

abstract: COVID-19 patients show varying severity of the disease ranging from asymptomatic to requiring intensive care. Although a number of SARS-CoV-2 specific monoclonal antibodies have been identified, we still lack an understanding of the overall landscape of B-cell receptor (BCR) repertoires in COVID-19 patients. Here, we used high-throughput sequencing of bulk and plasma B-cells collected over multiple time points during infection to characterize signatures of B-cell response to SARS-CoV-2 in 19 patients. Using principled statistical approaches, we determined differential features of BCRs associated with different disease severity. We identified 38 significantly expanded clonal lineages shared among patients as candidates for specific responses to SARS-CoV-2. Using single-cell sequencing, we verified reactivity of BCRs shared among individuals to SARS-CoV-2 epitopes. Moreover, we identified natural emergence of a BCR with cross-reactivity to SARS-CoV-1 and SARS-CoV-2 in a number of patients. Our results provide important insights for development of rational therapies and vaccines against COVID-19.


title: Development and large-scale validation of a highly accurate SARS-COV-2 serological test using regular test strips for autonomous and affordable finger-prick sample collection, transportation, and storage

abstract: Accurate serological tests are essential tools to allow adequate monitoring and control of COVID-19 spread. Production of a low-cost and high-quality recombinant viral antigen can enable the development of reliable and affordable serological assays, which are urgently needed to facilitate epidemiological surveillance studies in low-income economies. Trimeric SARS-COV-2 spike (S) protein was produced in serum-free, suspension-adapted HEK293 cells. Highly purified S protein was used to develop an ELISA, named S-UFRJ test. It was standardized to work with different types of samples: (i) plasma or serum from venous blood samples; (ii) eluates from dried blood spots (DBS) obtained by collecting blood drops from a finger prick. We developed a cost-effective, scalable technology to produce S protein based on its stable expression in HEK293 cells. Using this recombinant antigen, we presented a workflow for test development in the setting of a pandemic, starting from limited amounts of samples up to reaching final validation with hundreds of samples. Test specificity was determined to be 98.6%, whereas sensitivity was 95% for samples collected 11 or more days after symptoms onset. A ROC analysis allowed optimizing the cut-off and confirming the high accuracy of the test. Endpoint titers were shown to correlate with virus neutralization assessed as PRNT90. There was excellent agreement between plasma and DBS samples, significantly simplifying sample collection, storing, and shipping. An overall cost estimate revealed that the final retail price could be in the range of one US dollar. The S-UFRJ assay developed herein meets the quality requirements of high sensitivity and specificity. The low cost and the use of mailable DBS samples allow for serological surveillance and follow-up of SARS-CoV-2 vaccination of populations regardless of geographical and socio-economic aspects. We hope the detailed guidelines for the development of an affordable and accurate anti-spike SARS-COV-2 ELISA, such as S-UFRJ described here, will stimulate governmental and non-governmental health agencies in other countries to engage in much-needed large-scale studies monitoring the spread and immunity to SARS-COV-2 infection.