title: Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic strength of methods review

abstract:
IntroductionAssessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.

MethodsWe included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating.

ResultsAfter 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.

DiscussionThe reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policy-makers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible.


title: Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of evidence strength

category: health policy


title: Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of study design and evidence strength


title: Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: an agent-based modeling approach

abstract:
Intervention strategies for minimizing indoor SARS-CoV-2 transmission are often based on anecdotal evidence because there is little evidence-based research to support them. We developed a spatially-explicit agent-based model for simulating indoor respiratory pathogen transmission, and used it to compare effects of four interventions on reducing individual-level SARS-CoV-2 transmission risk by simulating a well-known case study. We found that imposing movement restrictions and efficacious mask usage appear to have the greatest effects on reducing infection risk, but multiple concurrent interventions are required to minimize the proportion of susceptible individuals infected. Social distancing had little effect on reducing transmission if individuals move during the gathering. Furthermore, our results suggest that there is potential for ventilation airflow to expose susceptible people to aerosolized pathogens even if they are relatively far from infectious individuals. Maximizing rates of aerosol removal is the key to successful transmission-risk reduction when using ventilation systems as intervention tools.

Article Summary LineImposing mask usage requirements, group size restrictions, duration limits, and social distancing policies can have additive, and in some cases multiplicative protective effects on SARS-CoV-2 infection risk during indoor events.

category: infectious diseases


title: Do Pandemics Obey the Elliott Wave Principle of Financial Markets?

abstract: The Elliott Wave principle is a time-honored, oft-used method for predicting variations in the financial markets. It is based on the notion that human emotions drive financial decisions. In the fight against COVID-19, human emotions are similarly decisive, for instance in that they determine ones willingness to be vaccinated, and/or to follow preventive measures including the wearing of masks, the application of social distancing protocols, and frequent handwashing. On this basis, we postulated that the Elliott Wave Principle may similarly be used to predict the future evolution of the COVID-19 pandemic. We demonstrated that this method reproduces the data pattern especially well for USA (daily new cases). Potential scenarios were then extrapolated, from the best-case corresponding to a rapid, full vaccination of the population, to the utterly disastrous case of slow vaccination, and poor adherence to preventive protocols.


title: Personalized Virus Load Curves of SARS-CoV-2 Infection

abstract: We introduce an explicit function that describes virus-load curves on a patient-specific level. This function is based on simple and intuitive model parameters. It allows virus load analysis without solving a full virus load dynamic model. We validate our model on data from influenza A as well as SARS-CoV-2 infection data for Macaque monkeys and humans. Further, we compare the virus load function to an established target model of virus dynamics, which shows an excellent fit. Our virus-load function offers a new way to analyse patient virus load data, and it can be used as input to higher level models for the physiological effects of a virus infection, for models of tissue damage, and to estimate patient risks.


title: Development and validation of a predictive model for critical illness in adult patients requiring hospitalization for COVID-19

abstract:
BackgroundIdentifying factors that can predict severe disease in patients needing hospitalization for COVID-19 is crucial for early recognition of patients at greatest risk.

Objective1) Identify factors predicting intensive care unit (ICU) transfer and (2) develop a simple calculator for clinicians managing patients hospitalized with COVID-19.

MethodsA total of 2,685 patients with laboratory-confirmed COVID-19 admitted to a large metropolitan health system in Georgia, USA between March and July 2020 were included in the study. Seventy-five percent of patients were included in the training dataset (admitted March 1 to July 10). Through multivariable logistic regression, we developed a prediction model (probability score) for ICU transfer. Then, we validated the model by estimating its performance accuracy (area under the curve [AUC]) using data from the remaining 25% of patients (admitted July 11 to July 31).

ResultsWe included 2,014 and 671 patients in the training and validation datasets, respectively. Diabetes mellitus, coronary artery disease, chronic kidney disease, serum C-reactive protein, and serum lactate dehydrogenase were identified as significant risk factors for ICU transfer, and a prediction model was developed. The AUC was 0.752 for the training dataset and 0.769 for the validation dataset. We developed a free, web-based calculator to facilitate use of the prediction model (https://icucovid19.shinyapps.io/ICUCOVID19/).

ConclusionOur validated, simple, and accessible prediction model and web-based calculator for ICU transfer may be useful in assisting healthcare providers in identifying hospitalized patients with COVID-19, who are at high risk for clinical deterioration.

Triage of such patients for early aggressive treatment can impact clinical outcomes for this potentially deadly disease.

category: intensive care and critical care medicine


title: The Generalizability of Clinical Prediction Models for Patients with Acute Coronary Syndromes: Results from Independent External Validations

abstract:
PurposeIt is increasingly recognized that clinical prediction models (CPMs) often do not perform as expected when they are tested on new databases. Independent external validations of CPMs are recommended but often not performed. Here we conduct independent external validations of acute coronary syndrome (ACS) CPMs.

MethodsA systematic review identified CPMs predicting outcomes for patients with ACS. Independent external validations were performed by evaluating model performance using individual patient data from 5 large clinical trials. CPM performance with and without various recalibration techniques was evaluated with a focus on CPM discrimination (c-statistic, % relative change in c-statistic) as well as calibration (Harrells Eavg, E90, Net Benefit).

ResultsOf 269 ACS CPMs screened, 23 (8.5%) were compatible with at least one of the trials and 28 clinically appropriate external validations were performed. The median c statistic of the CPMs in the derivation cohorts was 0.76 (IQR, 0.74 to 0.78). The median c-statistic in these external validations was 0.70 (IQR, 0.66 to 0.71) reflecting a 24% decrement in discrimination. However, this decrement in discrimination was due mostly to narrower case-mix in the validation cohorts compared to derivation cohorts, as reflected in the median model based c-statistic [0.71 (IQR 0.66 to 0.75). The median calibration slope in external validations was 0.84 (IQR, 0.72 to 0.98) and the median Eavg (standardized by the outcome rate) was 0.4 (IQR, 0.3 to 0.8). Net benefit indicates that most CPMs had a high risk of causing net harm when not recalibrated, particularly for decision thresholds not near the overall outcome rate.

ConclusionIndependent external validations of published ACS CPMs demonstrate that models tested in our sample had relatively well-preserved discrimination but poor calibration when externally validated. Applying  off-the-shelf CPMs often risks net harm unless models are recalibrated to the populations on which they are used.

category: cardiovascular medicine


title: Detection and removal of pacing artifacts prior to automated analysis of 12-lead ECG

abstract:
BackgroundPacing artifacts must be excluded from the analysis of paced ECG waveform. This study aimed to develop and validate an algorithm to identify and remove the pacing artifacts on ECG.

MethodsWe developed a semi-automatic algorithm that identifies the onset and offset of a pacing artifact based on the ECG signal slope steepness and designed a graphical user interface that permits quality control and fine-tuning the constraining threshold values. We used 1,054 ECGs from the retrospective, multicenter cohort study "Global Electrical Heterogeneity and Clinical Outcomes," including 3,825 atrial and 10,031 ventricular pacing artifacts for the algorithm development and 22 ECGs including 108 atrial and 241 ventricular pacing artifacts for validation. Validation was performed per digital sample. We used the kappa-statistic of interrater agreement between manually labeled sample (ground-truth) and automated detection.

ResultsThe constraining parameter values were for onset threshold 13.06{+/-}6.21 V/ms, offset threshold 34.77{+/-}17.80 V/ms, and maximum window size 27.23 {+/-} 3.53 ms. The automated algorithm detected a digital sample belonging to pacing artifact with a sensitivity of 74.5% and specificity of 99.6% and classified correctly 98.8% of digital samples (ROC AUC 0.871; 95%CI 0.853-0.878). The kappa-statistic was 0.785, indicating substantial agreement. The agreement was on 98.81% digital samples, significantly (P<0.00001) larger than the random agreement on 94.43% of digital samples.

ConclusionsThe semi-automated algorithm can detect and remove ECG pacing artifacts with high accuracy and provide a user-friendly interface for quality control.

HighlightsO_LIWe developed and validated a semi-automated algorithm to detect and remove pacing spike artifacts from a digital ECG signal.
C_LIO_LIThe semi-automated algorithm can detect and remove pacing spike artifacts with high accuracy and provide a user-friendly interface for quality control.
C_LI


title: Comparative Effects of E-cigarette Aerosol on Periodontium

abstract:
IntroductionTobacco use is one of the main causes of periodontitis. E-cigarettes are gaining in popularity, and studies are needed to better understand the impact of e-cigarettes on oral health. Objective: To perform a longitudinal study to evaluate the adverse effects of e-cigarettes on periodontal health.

MethodsNaive e-cigarette users, cigarette smokers, and non-smokers were recruited using newspaper and social media. Demographics, age, gender, and ethnicity, were recorded. Participants were scheduled for two visits 6 months apart. At each visit, we collected data on the daily frequency puffs of an e-cigarette, the number of cigarettes smokes, and other parameters, such as alcohol consumption. Carbon monoxide levels, cotinine levels, salivary flow rate, probing depth, and bleeding on probing were determined at both baseline and follow-up visits. P-values less than 0.05 were considered statistically significant.

ResultsWe screened 159 subjects and recruited 140 subjects. One-hundred-one subjects (31 cigarette smokers, 32 e-cigarette smokers, and 38 non-smokers) completed every assessment in both visits. The retention and compliance rate of subjects was 84.1%. The use of social media and craigslist was significant in recruiting e-cigarette subjects. Ethnicity and race differed between cohorts, as did average age in the male subjects. Carbon monoxide and salivary cotinine levels were highest among cigarette smokers. Bleeding on probing and average probing depths similarly increased over time in all three cohorts. Increase in the rates of severe periodontal disease were significantly higher in cigarette smokers and e-cigarette users than non-smokers. Confounding factors were subjects age as most of the e-cigarette group were much younger than cigarette smokers.

ConclusionAmong the recruited participants, periodontal severity status after 6 month was significantly worse in cigarette smokers and e-cigarette smokers than non-smokers. This study design and protocol will assist in future larger studies on e-cigarette and oral health.

category: dentistry and oral medicine


title: Using body temperature and variables commonly available in the EHR to predict acute infection: A proof-of-concept study showing improved pretest probability estimates for acute COVID-19 infection among discharged emergency department patients

abstract:
ObjectivesObtaining body temperature is a quick and easy method to screen for acute infection such as COVID-19. Currently, the predictive value of body temperature for acute infection is inhibited by failure to account for other readily available variables that affect temperature values. In this proof-of-concept study, we sought to improve COVID-19 pretest probability estimation by incorporating covariates known to be associated with body temperature, including patient age, sex, comorbidities, month, time of day.

MethodsFor patients discharged from an academic hospital emergency department after testing for COVID-19 in March and April of 2020, we abstracted clinical data. We reviewed physician documentation to retrospectively generate estimates of pretest probability for COVID-19. Using patients COVID-19 PCR test results as a gold standard, we compared AUCs of logistic regression models predicting COVID-19 positivity that used: 1) body temperature alone; 2) body temperature and pretest probability; 3) body temperature, pretest probability, and body temperature-relevant covariates. Calibration plots and bootstrap validation were used to assess predictive performance for model #3.

ResultsData from 117 patients were included. The models AUCs were: 1) 0.69 2) 0.72, and 3) 0.76, respectively. The absolute difference in AUC was 0.029 (95%CI -0.057 to 0.114, p=0.25) between model 2 and 1 and 0.038 (95%CI -0.021 to 0.097, p=0.10) between model 3 and 2.

ConclusionsBy incorporating covariates known to affect body temperature, we demonstrated improved pretest probability estimates of acute COVID-19 infection. Future work should be undertaken to further develop and validate our model in a larger, multi-institutional sample.

category: emergency medicine


title: Abrupt increase in the UK coronavirus death-case ratio in December 2020

abstract:
1Objectiveto determine the statistical relationship between reported deaths and infections in the UK coronavirus outbreak

DesignPublicly available UK government data is used to determine a relationship between reported cases and deaths, taking into account various UK regions, age profiles and prevalence of the variant of concern (VOC) B.1.1.7.

Main Outcome MeasuresEstablishing a simple statistical relationship between detected cases and subsequent mortality.

ResultsThroughout October and November 2020, deaths in England are well described as 1/55th of detected cases from 12 days previously. After that, the relationship no longer holds and deaths are significantly higher. This is especially true in regions affected by the VOC B.1.1.7

ConclusionsIn early December, some new factor emerged to increase the case-fatality rate in the UK.

Summary BoxO_ST_ABSWhat is already known on this topicC_ST_ABSThe infection-mortality ratio enables one to predict future deaths based on current infections. Incomplete monitoring of infection may be sufficient to predict future trends.

What the study addsFor the specific case of the second wave of coronavirus infection in the UK, we show a clear mathematical relationship between detected infections (positive tests) and subsequent deaths. This relationship begins to fail in December, with unexpectedly high death rates. This may be correlated in time and region with the emergence of the Variant of Concern B 1.1.7.

category: epidemiology


title: Theoretical framework for retrospective studies of the effectiveness of SARS-CoV-2 vaccines

abstract: Observational studies of the effectiveness of vaccines to prevent COVID-19 are needed to inform real-world use. These are now in planning amid the ongoing rollout of SARS-CoV-2 vaccines globally. While traditional case-control (TCC) and test-negative design (TND) studies feature prominently among strategies used to assess vaccine effectiveness, such studies may encounter important threats to validity. Here we review the theoretical basis for estimation of vaccine direct effects under TCC and TND frameworks, addressing specific natural history parameters of SARS-CoV-2 infection and COVID-19 relevant to these designs. Bias may be introduced by misclassification of cases and controls, particularly when clinical case criteria include common, non-specific indicators of COVID-19. When using diagnostic assays with high analytical sensitivity for SARS-CoV-2 detection, individuals testing positive may be counted as cases even if their symptoms are due to other causes. The TCC may be particularly prone to confounding due to associations of vaccination with healthcare-seeking behavior or risk of infection. The TND reduces but may not eliminate this confounding, for instance if individuals who receive vaccination seek care or testing for less-severe infection. These circumstances indicate the two study designs cannot be applied naively to datasets gathered through public health surveillance or administrative sources. We suggest practical strategies to reduce bias in vaccine effectiveness estimates at the study design and analysis stages.


title: Agent-Based Simulation of Covid-19 Vaccination Policies in CovidSIMVL

abstract:
An agent-based infectious disease modeling tool (CovidSIMVL) is employed in this paper to explore outcomes associated with MRNA two-dose vaccination regimens set out in Emergency Use Authorization (EUA) documents submitted by Pfizer and Moderna to the US Department of Health & Human Services. As well, the paper explores outcomes associated with a third "Hybrid" policy that reflects ranges of expected levels of protection according to Pfizer and Moderna EUAs, but entails a 35 day separation between first and second dose, which exceeds the 21 days set out in Pfizer documentation or the 28 days in Moderna documentation.

Four CovidSIMVL parameters are varied in the course of 75 simulated clinical trials. Two relate directly to the vaccines and their impacts (duration between doses; degree of expected protection conferred by different vaccines following first or second dose). Two relate to the simulation contexts to which the vaccines are applied (degree of infectivity; duration of infectivity). The simulated trials demonstrate expected effects for timing of second dose, and for degree of protection associated with first and second dose of Pfizer and Moderna vaccines, and the effects are consistent with an assumed value of 75% for degree of protection after first and second doses for the Hybrid vaccine. However, the simulated trials suggest a more complex interaction between expected level of protection following first dose, timing of second dose and degree of infectivity. These results suggest that policy options should not be considered independent of the transmission dynamics that are manifested in the contexts in which the policies could be applied.

CovidSIMVL embodies stochasticity in the mechanisms that govern viral transmission, and it treats the basic reproduction number (R0)as an emergent characteristic of transmission dynamics, not as a pre-set value that determines those dynamics. As such, results reported in this paper reflect outcomes that could happen, but do not necessarily reflect what is more or less likely to happen, given different configurations of parameters. The discussion section goes into some measure of detail regarding next steps that could be pursued to enhance the potential for agent-based models such as CovidSIMVL to inform exploration of possible vaccination policies, and to project outcomes that are possible or likely in local contexts, where stochasticity and heterogeneity of transmission must be featured in models that are intended to reflect local realism.


title: Ready-to-drink beverage (RTD) consumption in Thai population: trend and associated factors

abstract:
ObjectivesTo examine ready-to-drink beverage (RTD) consumption and to investigate the effects of gender and age on RTD consumption by using data 2011 and 2014 waves of a national alcohol survey.

DesignAnalysis of data from Smoking and Drinking Behavior Survey (SADBeS) 2011 and 2014, a nationally representative survey.

SettingThailand

Participants177,350 (2011 survey) and 25,758 (2014 survey) samples of Thais aged 15 years or older who were randomly selected using multistage-sampling technique.

Primary outcomeRTD consumption in past 12 months (yes/no) as stated by survey participants

ResultsThe prevalence of RTD drinkers increased from 0.5% (95% CI, 0.5-0.5%) in 2011 to 2.4% (95% CI, 2.1-2.6%) in 2014. Female drinkers were 5.1 (95% CI, 4.1-6.4) times more likely to consume RTDs than male drinkers. The likelihood of drinking RTDs decreased with age. Drinking initiation before the legal purchasing age (20 years old) was associated with 1.5 (95% CI, 1.1-1.9) times likelihood of RTDs consumption.

ConclusionsA substantial increase in RTD consumption was observed in Thailand, a middle-income country, during 2011-2014. The consumption was notable in youths and females. Given that RTDs have been introduced into the Thai market relatively recently, this may be a part of the alcohol industry strategies to boost their sales in middle-income countries. Growth in RTD consumption could pose a challenge for health authorities to control alcohol-related harms in the future especially among youths and females.

Article SummaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIA reliable estimate of prevalence of RTD consumption was obtained by using data from two waves of a large national representative survey.
C_LIO_LIThe lack of information about pattern of RTD consumption including quantity and drinking frequency limited further analysis.
C_LI

FundingThis work was supported by the Center for Alcohol Studies, Thailand, grant number 62-02029-0043.

Competing interests statementNone declared.

category: public and global health


title: Negative Excess Mortality in Pneumonia Death caused by COVID-19 in Japan

abstract:
BackgroundSince the emergence of COVID-19, cases of excess mortality from all causes have been very few in Japan.

ObjectTo evaluate COVID-19 effects precisely, we specifically examine deaths caused by pneumonia and examine excess mortality attributable to pneumonia in Japan.

MethodWe applied the NIID model to pneumonia deaths from 2005 up through November, 2020 for the whole of Japan. Introduction of routine pneumococcal vaccination for elderly people and revision in ICD10 were incorporated into the estimation model.

ResultsNo excess mortality was found for 2020. However, negative excess mortality was observed as 178 in May, 314 in June, and 75 in July. No negative excess mortality was not found between August and November.

Discussion and ConclusionSignificantly negative excess mortality might reflect precautions taken by people including wearing masks, washing hands with alcohol, and maintaining social distance. They reduced the infection risk not only of for COVID-19 but also of other infectious diseases causing pneumonia.


title: Predicting Prognosis and IDH Mutation Status for Patients with Lower-Grade Gliomas Using Whole Slide Images

abstract: We developed end-to-end deep learning models using whole slide images of adults diagnosed with diffusely infiltrating, World Health Organization (WHO) grade 2 gliomas to predict prognosis and the mutation status of a somatic biomarker, isocitrate dehydrogenase (IDH) 1/2. The models, which utilize ResNet-18 as a backbone, were developed and validated on 296 patients from The Cancer Genome Atlas (TCGA) database. To account for the small sample size, repeated random train/test splits were performed for hyperparameter tuning, and the out-of-sample predictions were pooled for evaluation. Our models achieved a concordance- (C-) index of 0.715 (95% CI: 0.569, 0.830) for predicting prognosis and an area under the curve (AUC) of 0.667 (0.532, 0.784) for predicting IDH mutations. When combined with additional clinical information, the performance metrics increased to 0.784 (95% CI: 0.655, 0.880) and 0.739 (95% CI: 0.613, 0.856), respectively. When evaluated on the grade 3 gliomas TCGA dataset, which was not used for training, our models were able to predict survival with a C-index of 0.654 (95% CI: 0.537, 0.768) and IDH mutations with an AUC of 0.814 (95% CI: 0.721, 0.897). If validated in a prospective study, our method could potentially assist clinicians in managing and treating patients with diffusely infiltrating gliomas.

category: health informatics


title: Effects of Diabetes and Blood Glucose on COVID-19 Mortality: A Retrospective Observational Study

abstract:
OBJECTIVETo investigate the association of diabetes and blood glucose on mortality of patients with Coronavirus Disease 2019 (COVID-19).

RESEARCH DESIGN AND METHODSThis was a retrospective observational study of all patients with COVID-19 admitted to Huo-Shen-Shan Hospital, Wuhan, China. The hospital was built only for treating COVID-19 and opened on February 5, 2020. The primary endpoint was all-cause mortality during hospitalization.

RESULTSAmong 2877 hospitalized patients, 13.5% (387/2877) had a history of diabetes and 1.9% (56/2877) died in hospital. After adjustment for confounders, patients with diabetes had a 2-fold increase in the hazard of mortality as compared to patients without diabetes (adjusted HR 2.11, 95%CI: 1.16-3.83, P=0.014). The on-admission glucose (per mmol/L[≥]4mmol/L) was significantly associated with subsequent mortality on COVID-19 (adjusted HR 1.17, 95%CI: 1.10-1.24, P<0.001).

CONCLUSIONSDiabetes and on-admission glucose (per mmol/L[≥]4mmol/L) are associated with increased mortality in patients with COVID-19. These data support that blood glucose should be properly controlled for possibly better survival outcome in patients with COVID-19.


title: Two-sample Mendelian randomization analysis of associations between periodontal disease and risk of colorectal, lung, and pancreatic cancers

abstract: Observational studies indicate that periodontal disease may increase the risk of colorectal, lung, and pancreatic cancers. We tested these associations using two-sample Mendelian randomization to emulate a randomized study with observational data. We developed an instrument including single nucleotide polymorphisms with strong genome-wide association study evidence for associations with aggressive and/or advanced periodontal disease. We used this instrument to assess associations with summary-level genetic data for colorectal cancer (n=58,131 cases), lung cancer (n=18,082 cases), and pancreatic cancer (n=9254 cases). The genetic predisposition index for periodontitis was significantly associated with an increased risk of colorectal cancer (p=0.026), colon cancer (p=0.021), proximal colon cancer (p=0.013), and colorectal cancer among females (p=0.039); however, it was not significantly associated with the risk of lung cancer or pancreatic cancer, overall or within most subgroups. Further research should determine whether increased periodontitis prevention and increased cancer surveillance of patients with periodontitis is warranted.


title: Tool for estimating the probability of having COVID-19 with one or more negative RT-PCR results

abstract: Early case detection and isolation of infected individuals are critical to controlling COVID-19. RT-PCR is considered the diagnosis gold standard, but false-negatives occur. Based on previous work, we built a user-friendly online tool to estimate the probability of having COVID-19 with negative RT-PCR results and thus avoid preventable SARS-CoV-2 transmission.


title: New Role of Red Blood Cells in Absorption of DNA Bearing Tumorigenic Mutations from Lung Cancer Tissue

abstract: Red blood cells (RBC) are commonly assumed to be vehicles for oxygen, carbon dioxide, and cells metabolic byproducts. In this study, we investigated whether RBC may contain cancer-cell derived DNA and whether such cargo may be used as a biomarker for detecting cancer. Using an in vitro co-culture system, we showed that RBC could absorb DNA bearing tumorigenic mutations from cancer cell lines. Next, we demonstrated that we could detect common genetic mutations, including EGFR 19 deletion, L858R, and KRAS G12 in RBC collected from early-stage non-small cell lung cancer patients. We were able to repeat our finding using both next-generation sequencing and droplet digital PCR. Our study highlights a new biological phenomenon involving RBC and their translational potential as a novel liquid biopsy technology platform that can be used for early cancer screening.

category: oncology


title: Artificial Intelligence for Emotion-Semantic Trending and People Emotion Detection During COVID-19 Social Isolation

abstract: Taking advantage of social media platforms, such as Twitter, this paper provides an effective framework for emotion detection among those who are quarantined. Early detection of emotional feelings and their trends help implement timely intervention strategies. Given the limitations of medical diagnosis of early emotional change signs during the quarantine period, artificial intelligence models provide effective mechanisms in uncovering early signs, symptoms and escalating trends. Novelty of the approach presented herein is a multitask methodological framework of text data processing, implemented as a pipeline for meaningful emotion detection and analysis, based on the Plutchik/Ekman approach to emotion detection and trend detection. We present an evaluation of the framework and a pilot system. Results of confirm the effectiveness of the proposed framework for topic trends and emotion detection of COVID-19 tweets. Our findings revealed Stay-At-Home restrictions result in people expressing on twitter both negative and positive emotional semantics (feelings), where negatives are "Anger" (8.5% of tweets), followed by "Fear" (5.2%), "Anticipation" (53.6%) and positive emotional semantics are "Joy" (14.7%) and "Trust" (11.7%). Semantic trends of safety issues related to staying at home rapidly decreased within the 28 days and also negative feelings related to friends dying and quarantined life increased in some days. These findings have potential to impact public health policy decisions through monitoring trends of emotional feelings of those who are quarantined. The framework presented here has potential to assist in such monitoring by using as an online emotion detection tool kit.


title: Six-month Neurological and Psychiatric Outcomes in 236,379 Survivors of COVID-19

abstract:
BackgroundNeurological and psychiatric sequelae of COVID-19 have been reported, but there are limited data on incidence rates and relative risks.

MethodsUsing retrospective cohort studies and time-to-event analysis, we estimated the incidence of ICD-10 diagnoses in the 6 months after a confirmed diagnosis of COVID-19: intracranial haemorrhage; ischaemic stroke; Parkinsonism; Guillain-Barre syndrome; nerve/nerve root/plexus disorders; myoneural/muscle disease; encephalitis; dementia; mood, anxiety, and psychotic disorders; substance misuse; and insomnia. Data were obtained from the TriNetX electronic health records network (over 81 million patients). We compared incidences with those in propensity score-matched cohorts of patients with influenza or other respiratory infections using a Cox model. We investigated the effect on incidence estimates of COVID-19 severity, as proxied by hospitalization and encephalopathy (including delirium and related disorders).

Findings236,379 patients survived a confirmed diagnosis of COVID-19. Among them, the estimated incidence of neurological or psychiatric sequelae at 6 months was 33.6%, with 12.8% receiving their first such diagnosis. Most diagnostic categories were commoner after COVID-19 than after influenza or other respiratory infections (hazard ratios from 1.21 to 5.28), including stroke, intracranial haemorrhage, dementia, and psychotic disorders. Findings were equivocal for Parkinsonism and Guillain-Barre syndrome. Amongst COVID-19 cases, incidences and hazard ratios for most disorders were higher in patients who had been hospitalized, and markedly so in those who had experienced encephalopathy. Results were robust to sensitivity analyses, including comparisons against an additional four index health events.

InterpretationThe study provides evidence for substantial neurological and psychiatric morbidity following COVID-19 infection. Risks were greatest in, but not limited to, those who had severe COVID-19. The information can help in service planning and identification of research priorities.

FundingNational Institute for Health Research (NIHR) Oxford Health Biomedical Research Centre.

category: neurology


title: The "throwaways". Conflicts of interest in dermatology publications.

abstract:
ImportanceConflict of interest as it relates to medical education is a topic of concern. Dermatology journals, periodicals, editorials, and news magazines are influential resources that are not uniformly regulated and subject to influence from the pharmaceutical industry.

ObjectiveThis study evaluates industry payments to physician editorial board members of common dermatology publications, including "throwaway" publications.

DesignA list of editorial board members was compiled from a collection of clinical dermatology publications received over a 3-month period. To analyze the nature and extent of industry payments to this cohort, payments data from the Open Payments database from 2013 to 2019 were collected. Analysis of the total payments, number of transactions, categories of payments, payment sources, and physician specific characteristics was performed.

ResultsTen publications were evaluated, and payments data for 466 physicians were analyzed. The total compensation across all years was $75,622,369.64. Services other than consulting, consulting, and travel/lodging payments comprised most of the payments. A faction of dermatologists received the majority of payments. The top payers were manufacturers of biologic medications. Payment amounts were higher for throwaway publications compared to peer-reviewed journals.

ConclusionsEditorial board members of dermatology publications received substantial payments from the pharmaceutical industry. A minority of physicians receive the lions share of payments from industry. "Throwaway" publications have more financial conflict of interest than peer-reviewed journals. The impact of these conflicts of interest on patient care, physicians practice patterns, and patient perception of physicians is noteworthy.

category: dermatology


title: Genome-wide analysis of 102,084 migraine cases identifies 123 risk loci and subtype-specific risk alleles

abstract: Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. This genome-wide association study (GWAS) of 102,084 migraine cases and 771,257 controls identified 123 loci of which 86 are novel. The loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. A stratification of the risk loci using 29,679 cases with subtype information, of which approximately half have never been used in a GWAS before, indicated three risk variants that appear specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that appear specific for migraine without aura (near SPINK2 and near FECH), and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.

category: genetic and genomic medicine


title: Diagnosing pulmonary tuberculosis using sequence-specific purification of urine cell-free DNA

abstract: Transrenal urine cell-free DNA (cfDNA) is a promising tuberculosis (TB) biomarker, but is challenging to detect because of the short length (<100 bp) and low concentration of TB-specific fragments. We aimed to improve the diagnostic sensitivity of TB urine cfDNA by increasing recovery of short fragments during sample preparation. We developed a highly sensitive sequence-specific purification method that uses hybridization probes immobilized on magnetic beads to capture short TB cfDNA (50 bp) with 91.8% average efficiency. Combined with short-target PCR, the assay limit of detection was [≤]5 copies of cfDNA in 10 mL urine. In a clinical cohort study in South Africa, our urine cfDNA assay had 83.7% sensitivity (95% CI: 71.0- 91.5%) and 100% specificity (95% CI: 86.2-100%) for diagnosis of active pulmonary TB when using sputum Xpert MTB/RIF as the reference standard. The detected cfDNA concentration was 0.14-2804 copies/mL (median 14.6 copies/mL) and was inversely correlated with CD4 count and days to culture positivity. Sensitivity was non-significantly higher in HIV-positive (88.2%) compared to HIV-negative patients (73.3%), and was not dependent on CD4 count. Sensitivity remained high in sputum smear-negative (76.0%) and urine LAM-negative (76.5%) patients. With improved sample preparation, urine cfDNA is a viable biomarker for TB diagnosis. Our assay has the highest reported accuracy of any TB urine cfDNA test to date and has the potential to enable rapid non-sputum-based TB diagnosis across key underserved patient populations.


title: Survey of contaminated percutaneous injuries in anesthesiologists

abstract:
BackgroundAnesthesia practitioners are at inherent risk for percutaneous injuries by blood-contaminated needles and sharp objects. These exposures may result in transmission of HIV and hepatitis viruses. Data about this occupational hazard from contaminated needles and sharp devices is limited and decades old. We conducted a web-based survey to assess the occurrence, reporting, characteristics, and outcome of contaminated percutaneous injuries (CPI) in anesthesia residents, fellows, and attendings.

MethodsAfter institutional research board approval, an email was sent to 217 anesthesia practitioners requesting their participation in an online survey about contaminated percutaneous injuries. Responses were collected from February through March 2020. Results are reported as absolute numbers and proportions with 95% confidence interval (CI).

ResultsThe overall survey response rate was 51% (110/217). 59% (65/110) (95% CI, 50-68) of participants reported having one or more contaminated percutaneous injury during their years of anesthesia practice (42% (21/50) of residents, 50% (4/8) of fellows, 77% (40/52) of anesthesia attendings). Prevalence of injuries related to attendings years of anesthesia practice was 69% (95% CI, 44-94) for 5-10 years, 62.5% (95% CI, 29-96) for 10-15 years, and 79% (95% CI, 63- 95) for greater than 15 years of practice.

35% (95% CI, 26-44) of participants reported having one or more CPI within the last 5 years (40% of residents, 50% of fellows, 29% of attendings). Occurrence of CPI within the last 5 years based on attending anesthesiologist years of practice was 57% for less than 5 years, 37.5% for 10-15 years, and 20% for 15-20 years of practice. 75% (95% CI, 65-85) reported the incident at the time of injury. 59% (95% CI, 48-70) of injuries were due to hollow bore needles. 50% (95% CI, 39-61) of total injuries were high risk. 26% of injured anesthesia practitioners received post-exposure prophylaxis and there were zero seroconversions.

ConclusionMost anesthesiologists will sustain a contaminated percutaneous injury during their careers. Incidence of these injuries decreases with years of practice. Occurrence of these injuries is high among anesthesia residents, with the majority reporting their injuries. Half of the injuries are high risk with a quarter requiring postexposure prophylaxis. More education and interventions are needed to reduce percutaneous injuries and improve reporting.

category: anesthesia


title: Survey of Contaminated Percutaneous Injuries in Anesthesia Practitioners


title: Validation of the new pathology staging system for progressive supranuclear palsy

abstract: Progressive supranuclear palsy (PSP) is a neurodegenerative disorder associated with neuroglial accumulation of 4-repeat tau protein. Kovacs et al. have recently proposed a new semi-quantitative staging system to categorise the severity of PSP pathology, using the distribution of tau aggregates as it progresses from subcortical to cerebellar and cortical regions. Here, we test the new PSP pathology staging system in an independent series of PSP, and test the potential association between pathology stage and clinical severity at death. We include tissue from 35 people with a clinical diagnosis of PSP (including N=25 with Richardsons syndrome and N=10 with other phenotypes). Donors had attended longitudinal clinical studies at the Cambridge Centre Parkinson-plus including assessment of clinical severity by the PSP rating scale (PSPRS) and cognitive performance by the revised Addenbrookes Cognitive Examination (ACE-R). We rated tau pathology from none-to-severe in six regions. We focused on (I) astrocytic tau inclusions in striatum, frontal and occipital regions, and (II) neuronal and oligodendroglia tau inclusions in globus pallidus, subthalamic nucleus, and cerebellum. Thirty-two cases (91%) readily conformed to the new staging system, ranging from stage 2 to 6. Staging system applied to brains from people with different clinical phenotypes of PSP. Neuropathology stages correlated with clinical severity at death using both PSPRS and ACE-R, weighted for the interval between last assessment and donation. Our study supports the proposed sequential distribution of tau aggregates in PSP pathology, and the hypothesised relationship between clinical and neuropathological severity. For future studies, in order to standardise rating between centres, we propose a set of operational criteria for region-specific thresholds or tau burden, and a visual guide.

category: pathology


title: A phase IV, multi-centre, randomized clinical trial comparing two pertussis-containing vaccines in pregnant women in England and vaccine responses in their infants

abstract:
BackgroundPertussis vaccines containing three or five pertussis antigens are recommended in pregnancy in many countries, but no studies have compared the effect on infants antigen-specific immunoglobulin G (IgG) concentrations. The aim of this study was to compare anti-pertussis IgG responses following primary immunization in infants of mothers vaccinated with TdaP5-IPV (low dose diphtheria toxoid, tetanus toxoid, acellular pertussis [five antigens] and inactivated polio) or TdaP3-IPV in pregnancy (three pertussis antigens).

MethodsThis multi-centre phase IV randomized clinical trial was conducted in a tertiary referral centre and primary care sites in England from 2014-2016. Women were randomized to receive TdaP5-IPV (n=77) or TdaP3-IPV (n=77) at 28-32 gestational weeks. A non-randomized control group of 44 women who had not received a pertussis-containing vaccine in pregnancy and their 47 infants were enrolled postpartum.

ResultsFollowing infant primary immunization, there was no difference in the geometric mean concentrations (GMCs) of anti-pertussis toxin, filamentous haemagglutinin or pertactin IgG between infants born to women vaccinated with TdaP5-IPV (n=67) or TdaP3-IPV (n=63). However, the GMC of anti-pertussis toxin IgG was lower in infants born to TdaP5-IPV and TdaP3-IPV vaccinated mothers compared to infants born to unvaccinated mothers (n=45) (geometric mean ratio: 0.71 [0.56-0.90] and 0.78 [0.61-0.98], respectively); by 13 months of age, this difference was no longer observed.

ConclusionBlunting of anti-pertussis toxin IgG response following primary immunization occurs in infants born to women vaccinated with TdaP5-IPV and TdaP3-IPV, with no difference between maternal vaccines. The blunting effect had resolved by 13 months of age. These results may be helpful for countries considering which pertussis-containing vaccine to recommend for use in pregnancy.

Clinical Trials identifierClinicalTrials.gov: NCT02145624

category: pediatrics


title: Effect of a home-based health, nutrition, and responsive stimulation intervention and conditional cash transfers on child development and growth: a cluster-randomized controlled trial in Tanzania

abstract:
IntroductionEvidence on the effect of community health worker (CHW) interventions and conditional cash transfers (CCTs) on child growth and development in sub-Saharan Africa remains sparse.

MethodsWe conducted a single-blind, cluster-randomized controlled trial of an integrated home-visiting health, nutrition, and responsive stimulation intervention alone and in combination with CCTs to promote antenatal and child clinic attendance from 2017 to 2019 in rural Morogoro region, Tanzania. Pregnant women and caregivers with a child <1{square}year of age were enrolled. Twelve villages were randomized to either a (i) CHW (n=200 participants), (ii) CHW+CCT (n=200), or (iii) control arm (n=193). An intention-to-treat analysis was conducted for the primary trial outcomes of child cognitive, language and motor development assessed with the Bayley Scales of Infant and Toddler Development and child length/height-for-age z-scores (HAZ) at 18-months of follow-up.

ResultsThe CHW and CHW+CCT interventions had beneficial effects on child cognitive development as compared to control (standardized mean difference (SMD): 0.15; 95% confidence interval (CI): 0.05, 0.24) and SMD: 0.18; 95% CI: 0.07, 0.28, respectively). The CHW+CCT intervention also had positive effects on language (SMD: 0.08; 95% CI: 0.01, 0.15) and motor development (SMD: 0.16; 95% CI: 0.03, 0.28). Both CHW and CHW+CCT interventions had no effect on HAZ in the primary analysis; however, there were statistically significant positive effects in multivariable analyses. The CHW+CCT group (mean difference: 3.0 visits; 95% CI: 2.1-4.0) and the CHW group (mean difference: 1.5 visits; 95% CI: 0.6-2.5) attended greater number of child health and growth monitoring clinic visits as compared to the control group.

ConclusionIntegrated CHW home-visiting interventions can improve child cognitive development and may have positive effects on linear growth. Combining CHWs with CCTs may provide additional benefits on clinic visit attendance and selected child development outcomes.

Trial registration numberISRCTN10323949

Key Questions BoxO_ST_ABSWhat is already known?C_ST_ABSO_LICommunity health worker interventions that integrate health, nutrition and responsive stimulation components can improve child development but evidence from sub-Saharan Africa is limited.
C_LIO_LIConditional cash transfers can increase healthcare utilization but effects on child development and growth remain unclear.
C_LI

What are the new findings?O_LIAn integrated home-visiting community health worker intervention benefited child cognitive development and may have improved child linear growth in rural Tanzania.
C_LIO_LICombining conditional cash transfers with the community health worker intervention increased child clinic visit attendance as intended and improved child cognitive, motor, and language development and may have improved child linear growth as compared to control.
C_LI

What do the new findings imply?O_LICommunity health workers can improve child development and possibly child growth outcomes; however, additional research is needed to determine the intensity and frequency of visits to optimize impact as well as the direct and indirect mechanisms through which community health worker interventions work.
C_LIO_LIConditional cash transfers may provide additional benefits on clinic attendance and selected development domains as compared to community health workers alone; however, additional research is needed to directly compare integrated supply-side and demand-side strategies to promote child growth and development.
C_LI


title: An effect of the COVID-19 pandemic: significantly more complicated appendicitis due to delayed presentation of patients!

abstract:
AIMS OF THE STUDYThe novel coronavirus pandemic has affected emergency department consultations for surgical pathologies. The aim of our study was to compare the number of acute appendicitis cases and the proportion of complicated appendicitis before and during the COVID-19 pandemic.

METHODSWe retrospectively analyzed all data collected from a multi-center database of patients presenting to the emergency department for acute appendicitis during the COVID-19 pandemic from March 12 to June 6, 2020, and compared these data with those from the same periods in 2017, 2018, and 2019. The number of acute appendicitis cases, proportion of complicated appendicitis, and pre- and postoperative patient characteristics were evaluated.

RESULTSA total of 306 patients were included in this evaluation. Sixty-five patients presented during the 2020 COVID-19 pandemic lockdown (group A), and 241 patients in previous years (group B: 2017-2019). The number of consultations for acute appendicitis decreased by almost 20 percent during the pandemic compared with previous periods, with a significant increase in complicated appendicitis (52% in group A versus 20% in group B, p < 0,001.). Comparing the two groups, significant differences were also noted in the duration of symptoms (symptoms > 48h in 61% and 26%, p < 0,001), the intervention time (77 vs 61 minutes, p = 0,002), length of hospital stay (hospitalization of > 2 days in 63% and 32%, p < 0.001) and duration of antibiotic treatment (antibiotics > 3 days in 36% and 24% p = 0.001).

CONCLUSIONSThe COVID-19 pandemic resulted in a decreased number of consultations for acute appendicitis, with a higher proportion of complicated appendicitis, most likely due to patient delay in consulting the emergency department at symptom onset. Patients and general practitioners should be aware of this problem to avoid a time delay from initial symptoms to consultation.

category: surgery


title: Are probiotics and prebiotics safe for use during pregnancy and lactation? A systematic review and meta-analysis

abstract: Probiotic and prebiotic products have shown potential health benefits, including for the prevention of adverse pregnancy outcomes. The incidence of adverse effects in pregnant people and their infants associated with probiotic/prebiotic/synbiotic intake, however, remains unclear. The objectives of this study were to evaluate the evidence on adverse effects of maternal probiotic, prebiotic and/or synbiotic supplementation during pregnancy and lactation and interpret the findings to help inform clinical decision-making and care of this population. A systematic review was conducted following PRISMA guidelines. Scientific databases were searched using pre-determined terms, and risk of bias assessments were conducted to determine study quality. Inclusion criteria were English language studies, human studies, access to full-text, and probiotic/prebiotic/synbiotic supplementation to the mother and not the infant. 11/100 eligible studies reported adverse effects and were eligible for inclusion in quantitative analysis, and data were visualised in a GOfER diagram. Probiotic and prebiotic products are safe for use during pregnancy and lactation. One study reported increased risk of vaginal discharge and changes in stool consistency (Relative Risk [95% CI]: 3.67 [1.04, 13.0]) when administering Lactobacillus rhamnosus and L. reuteri. Adverse effects associated with probiotic and prebiotic use do not pose any serious health concerns to mother or infant. Our findings and knowledge translation visualisations provide healthcare professionals and consumers with information to make evidence-informed decisions about the use of pre- and probiotics.

category: obstetrics and gynecology


title: Functional Comparison of Different Exome Capture-based Methods for Transcriptomic Profiling of Formalin-Fixed Paraffin-Embedded Tumor Samples

abstract:
BackgroundThe need for fresh frozen (FF) tissue limits implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are processed in clinical laboratories and stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture has recently emerged as a promising approach for RNA-seq from FFPE samples. Multiple exome capture platforms are now available. However, their performances have not been systematically compared.

MethodsTranscriptomic analysis of 32 FFPE tumor samples from 11 patients was performed using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features, including the expression of key immune genes, expression outliers often associated with actionable genes, gene expression-based subtypes, and fusions using each of these capture methods.

ResultsThe Spearmans correlation coefficients between global expression profiles of the three capture-based methods and matched FF tumor samples, analyzed using TruSeq RNA-seq, were high (rho = 0.72-0.9, p < 0.05). There was a significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05). All three exome capture-based methods reliably detected the outlier expression of actionable genes, including ERBB2, MET, NTRK1, and PPARG, initially detected in FF-TruSeq. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtyping agreement with FF-TruSeq (Cohens k = 0.7, p < 0.01). Both Agilent and IDT detected all the clinically relevant fusions which were initially identified in FF-TruSeq.

ConclusionAll exome capture-based methods had comparable performance and concordance with FF-TruSeq. These findings provide a path for the transcriptomic profiling of vast numbers of FFPE currently stored in biobanks. For specific applications such as fusion detection and gene expression-based subtyping, some methods performed better. By enabling the interrogation of FFPE tumor samples, our findings open the door for implementing RNA-seq in the clinic to guide precision oncology approaches.


title: The ferroxidase HEPHaestin in Lung cancer: Pathological Significance and Prognostic Value

abstract:
Iron is a fundamental nutrient utilized by living cells to support several key cellular processes. Despite its paramount role to sustain cell survival, excess of labile iron availability can inflict severe cell damage via reactive oxygen species generation which, in turn, can promote neoplastic transformation. The lung is particularly sensitive to iron-induced oxidative stress, given the high oxygen tensions herein present. Moreover, cigarette smoke as well as air pollution particulate can function as vehicles of iron supply, leading to an iron dysregulation condition shown to be crucial in the pathogenesis of several respiratory diseases including lung cancer. Hephaestin (HEPH) belongs to a group of exocytoplasmic ferroxidases emerged to contribute to cellular iron homeostasis by favouring its export. Although HEPH can affect the concentration of intracellular iron labile pool, its expression in lung cancer and its influence on prognosis have not been investigated.

In this study we explored the expression pattern and prognostic value of HEPH in the most prevalent histotypes of lung cancers including lung adenocarcinoma and lung squamous cell carcinoma across in silico analyses using UALCAN, Gepia and Kaplan-Meier plotter bioninformatics. We took advantage of TIMER to assess the correlation between HEPH and tumour infiltrating immune and non-immune cells. Then we performed immunohistochemical analysis to dissect the presence of HEPH either in "healthy" and tumor lung tissues. Overall, our data suggest a positive correlation between higher level of HEPH expression with a favorable prognosis in both cancer histotypes.


title: Gene-level analysis of rare variants in 363,977 whole exome sequences reveals an association of GIGYF1 loss of function with diabetes

abstract:
Sequencing of large cohorts offers an unprecedented opportunity to identify rare genetic variants and to find novel contributors to human disease. We used gene-based collapsing tests to identify genes associated with glucose, HbA1c and type 2 diabetes (T2D) diagnosis in 363,977 exome-sequenced participants in the UK Biobank. We identified associations for variants in GCK, HNF1A and PDX1, which are known to be involved in Mendelian forms of diabetes. Notably, we uncovered novel associations for GIGYF1, a gene not previously implicated by human genetics, in diabetes. GIGYF1 predicted loss of function (pLOF) variants associated with increased levels of glucose (0.77 mmol/L increase, p = 4.42 x 10-12) and HbA1c (4.33 mmol/mol, p = 1.28 x 10-14) as well as T2D diagnosis (OR = 4.15, p= 6.14 x10-11). Multiple rare variants contributed to these associations, including singleton variants. GIGYF1 pLOF also associated with decreased cholesterol levels as well as an increased risk of hypothyroidism. The association of GIGYF1 pLOF with T2D diagnosis replicated in an independent cohort from the Geisinger Health System. In addition, a common variant association for glucose and T2D was identified at the GIGYF1 locus. Our results highlight the role of GIGYF1 in regulating insulin signaling and protecting from diabetes.

Author SummaryGenetic studies focused on high impact variants in protein-coding regions of the genome can provide valuable insight into the biology of human disease. As these variants tend to be rare, studying them requires large cohort sizes and methods to aggregate variants that are likely to have a similar biological impact. We studied how rare genetic variants contribute to type 2 diabetes (T2D) using sequencing data from 363,977 participants in the UK Biobank, employing methods to aggregate variants at the level of individual genes. As well as identifying genes known to be involved in inherited forms of diabetes, we uncovered a novel association for GIGYF1. GIGYF1 loss of function associated with increased risk of T2D and increased levels of the diabetes biomarkers glucose and HbA1c. This association was also seen in an independent dataset. GIGYF1 encodes a protein that binds a negative regulator of the insulin receptor that has not been well-characterized in the literature. By highlighting the importance of GIGYF1 in modulating insulin signaling these results may lead to new therapeutic approaches for diabetes as well as a new appreciation for GIGYF1 loss of function as a genetic risk factor for T2D.


title: Gene-level analysis of rare variants in 363,977 whole exome sequences identifies an association of GIGYF1 loss of function with type 2 diabetes


title: Large-scale validation of the Prediction model Risk Of Bias ASsessment Tool (PROBAST) using a short form: high risk of bias models show poorer discrimination

abstract:
ObjectiveTo assess whether the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and a shorter version of this tool can identify clinical prediction models (CPMs) that perform poorly at external validation.

Study Design and SettingWe evaluated risk of bias (ROB) on 102 CPMs from the Tufts CPM Registry, comparing PROBAST to a short form consisting of six PROBAST items anticipated to best identify high ROB. We then applied the short form to all CPMs in the Registry with at least 1 validation and assessed the change in discrimination (dAUC) between the derivation and the validation cohorts (n=1,147).

ResultsPROBAST classified 98/102 CPMS as high ROB. The short form identified 96 of these 98 as high ROB (98% sensitivity), with perfect specificity. In the full CPM registry, 529/556 CPMs (95%) were classified as high ROB, 20 (4%) low ROB, and 7 (1%) unclear ROB. Median change in discrimination was significantly smaller in low ROB models (dAUC -0.9%, IQR -6.2%-4.2%) compared to high ROB models (dAUC -11.7%, IQR -33.3%-2.6%; p<0.001).

ConclusionHigh ROB is pervasive among published CPMs. It is associated with poor performance at validation, supporting the application of PROBAST or a shorter version in CPM reviews.

What is newO_LIHigh risk of bias is pervasive among published clinical prediction models
C_LIO_LIHigh risk of bias identified with PROBAST is associated with poorer model performance at validation
C_LIO_LIA subset of questions can distinguish between models with high and low risk of bias
C_LI


title: Mask adherence and rate of COVID-19 across the United States

abstract: Mask wearing has been advocated by public health officials as a way to reduce the spread of COVID-19. In the United States, policies on mask wearing have varied from state to state over the course of the pandemic. Even as more and more government leaders encourage or even mandate mask wearing, many citizens still resist the notion. Our research examines mask wearing policy and adherence in association with COVID-19 case rates. We used state-level data on mask wearing policy for the general public and on proportion of residents who stated they always wear masks in public. For all 50 states and the District of Columbia (DC), these data were abstracted by month for April  September 2020 to measure their impact on COVID-19 rates in the subsequent month (May  October 2020). Monthly COVID-19 case rates (number of cases per capita over two weeks) >200 per 100,000 residents were considered high. Fourteen of the 15 states with no mask wearing policy for the general public through September reported a high COVID-19 rate. Of the 8 states with at least 75% mask adherence, none reported a high COVID-19 rate. States with the lowest levels of mask adherence were most likely to have high COVID-19 rates in the subsequent month, independent of mask policy or demographic factors. Mean COVID-19 rates for states with at least 75% mask adherence in the preceding month was 109.26 per 100,000 compared to 249.99 per 100,000 for those with less adherence. Our analysis suggests high adherence to mask wearing could be a key factor in reducing the spread of COVID-19. This association between high mask adherence and reduced COVID-19 rates should influence policy makers and public health officials to focus on ways to improve mask adherence across the population in order to mitigate the spread of COVID-19.

category: health policy


title: Clarifying Values: An Updated and Expanded Systematic Review and Meta-Analysis

abstract:
BackgroundPatient decision aids should help people make evidence-informed decisions aligned with their values. There is limited guidance about how to achieve such alignment.

PurposeTo describe the range of values clarification methods available to patient decision aid developers, synthesize evidence regarding their relative merits, and foster collection of evidence by offering researchers a proposed set of outcomes to report when evaluating the effects of values clarification methods.

Data SourcesMEDLINE, EMBASE, PubMed, Web of Science, the Cochrane Library, CINAHL

Study SelectionWe included articles that described randomized trials of one or more explicit values clarification methods. From 30,648 records screened, we identified 33 articles describing trials of 43 values clarification methods.

Data ExtractionTwo independent reviewers extracted details about each values clarification method and its evaluation.

Data SynthesisCompared to control conditions or to implicit values clarification methods, explicit values clarification methods decreased the frequency of values-disgruent choices (risk difference -0.04 95% CI [-0.06 to -0.02], p<.001) and decisional regret (standardized mean difference -0.20 95% CI [-0.29 to -0.11], p<0.001). Multicriteria decision analysis led to more values-congruent decisions than other values clarification methods (Chi-squared(2)=9.25, p=.01). There were no differences between different values clarification methods regarding decisional conflict (Chi-squared(2)=6.08, p=.05).

LimitationsSome meta-analyses had high heterogeneity. We grouped values clarification methods into broad categories.

ConclusionsCurrent evidence suggests patient decision aids should include an explicit values clarification method. Developers may wish to specifically consider multicriteria decision analysis. Future evaluations of values clarification methods should report their effects on decisional conflict, decisions made, values congruence, and decisional regret.

category: health systems and quality improvement


title: Association between clinical characteristics and laboratory findings with outcome of hospitalized COVID-19 patients, a report from northeast of Iran

abstract: Coronavirus disease 2019 (COVID-19) was first discovered in December 2019 in China and has rapidly spread worldwide. Clinical characteristics, laboratory findings, and their association with the outcome of patients with COVID-19 can be decisive in management and early diagnosis. Data were obtained retrospectively from medical records of 397 hospitalized COVID-19 patients between February and May 2020 in Imam Reza hospital, northeast of Iran. Clinical and laboratory features were evaluated among survivors and non-survivors. The correlation between variables and duration of hospitalization and admission to the Intensive Care Unit (ICU) was determined. Male sex, age, hospitalization duration, and admission to ICU were significantly related to mortality rate. Headache was a more common feature in patients who survived (p = 0.017). It was also related to a shorter stay in the hospital (p = 0.032) as opposed to patients who experienced chest pain (p = 0.033). Decreased levels of consciousness and dyspnea were statistically more frequent in non-survivors (p = 0.003 and p = 0.011, respectively). Baseline white blood cell count (WBC), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) were significantly higher in non-survivors (p < 0.001). Patients with higher WBC and CRP levels were more likely to be admitted to ICU (p = 0.009 and p = 0.001, respectively). Evaluating clinical and laboratory features can help clinicians find ways for risk stratifying patients and even make predictive tools. Chest pain, decreased level of consciousness, dyspnea, and increased CRP and WBC levels seem to be the most potent predictors of severe prognosis.

category: infectious diseases


title: Harnessing testing strategies and public health measures to avert COVID-19 outbreaks during ocean cruises

abstract: To ensure the safe operation of schools, workplaces, nursing homes, and other businesses during COVID-19 pandemic there is an urgent need to develop cost-effective public health strategies. Here we focus on the cruise industry which was hit early by the COVID-19 pandemic, with more than 40 cruise ships reporting COVID-19 infections. We apply mathematical modeling to assess the impact of testing strategies together with social distancing protocols on the spread of the novel coronavirus during ocean cruises using an individual-level stochastic model of the transmission dynamics of COVID-19. We model the contact network, the potential importation of cases arising during shore excursions, the temporal course of infectivity at the individual level, the effects of social distancing strategies, different testing scenarios characterized by the tests sensitivity profile, and the testing frequency. Our findings indicate that PCR testing at embarkation and daily testing of all individuals aboard, together with increased social distancing and other public health measures, should allow for rapid detection and isolation of COVID-19 infections and dramatically reducing the probability of onboard COVID-19 community spread. In contrast, relying only on PCR testing at embarkation would not be sufficient to avert outbreaks, even when implementing substantial levels of social distancing measures.


title: Detection of SARS-CoV-2 infection by rapid antigen test in comparison with RT-PCR in a public setting

abstract:
BackgroundRapid and accurate detection of SARS-CoV-2 infection is essential in limiting the spread of infection during the ongoing COVID-19 pandemic. The aim of this study was to determine the accuracy of the STANDARD Q COVID-19 Ag test (SD BIOSENSOR) by comparison with RT-PCR in a public setting.

MethodIndividuals aged 18 years or older who had booked an appointment for a RT-PCR test on December 26-31, 2020 at a public test center in Copenhagen, Denmark, were invited to participate. An oropharyngeal swab was collected for RT-PCR analysis, immediately followed by a nasopharyngeal swab examined by the STANDARD Q COVID-19 Ag test (SD BIOSENSOR). Sensitivity, specificity, positive and negative predictive values of the antigen test were calculated with test results from RT-PCR as reference.

ResultsOverall, 4697 individuals were included (female n=2456, 53.3%; mean age: 44.7 years, SD: 16.9 years); 196 individuals were tested twice or more. Among 4811 paired conclusive test results from the RT-PCR and antigen tests, 221 (4.6%) RT-PCR tests were positive. The overall sensitivity and specificity of the antigen test were 69.7% and 99.5%, the positive and negative predictive values were 87.0% and 98.5%. Ct values were significantly higher among individuals with false negative antigen tests compared to true positives.

ConclusionThe sensitivity, specificity, and predictive values found indicate that the STANDARD Q COVID-19 Ag is a good supplement to RT-PCR testing.


title: Distinct Autoimmune Antibody Signatures Between Hospitalized Acute COVID-19 Patients, SARS-CoV-2 Convalescent Individuals, and Unexposed Pre-Pandemic Controls

abstract:
Increasing evidence suggests that autoimmunity may play a role in the pathophysiology of SARS-CoV-2 infection during both the acute and  long COVID phases of disease. However, an assessment of autoimmune antibodies in convalescent SARS-CoV-2 patients has not yet been reported.

MethodologyWe compared the levels of 18 different IgG autoantibodies (AABs) between four groups: (1) unexposed pre-pandemic subjects from the general population (n = 29); (2) individuals hospitalized with acute moderate-severe COVID-19 (n = 20); (3) convalescent SARS-COV-2-infected subjects with asymptomatic to mild viral symptoms during the acute phase with samples obtained between 1.8 and 7.3 months after infection (n = 9); and (4) unexposed pre-pandemic subjects with systemic lupus erythematous (SLE) (n = 6). Total IgG and IgA levels were also measured from subjects in groups 1-3 to assess non-specific pan-B cell activation.

ResultsAs expected, in multivariate analysis, AABs were detected at much higher odds in SLE subjects (5 of 6, 83%) compared to non-SLE pre-pandemic controls (11 of 29, 38%) [odds ratio (OR) 19.4,95% CI, 2.0 - 557.0, p = 0.03]. AAB detection (percentage of subjects with one or more autoantibodies) was higher in SARS-CoV-2 infected convalescent subjects (7 of 9, 78%) [OR 17.4, 95% CI, 2.0 - 287.4, p = 0.02] and subjects with acute COVID-19 (12 of 20, 60%) compared with non-SLE pre-pandemic controls, but was not statistically significant among the latter [OR 1.8,95% CI, 0.6 - 8.1, p = 0.23]. Within the convalescent subject group, AABs were detected in 5/5 with reported persistent symptoms and 2/4 without continued symptoms (p = 0.17). The multivariate computational algorithm Partial Least Squares Determinant Analysis (PLSDA) was used to determine if distinct AAB signatures distinguish subject groups 1-3. Of the 18 autoantibodies measured, anti-Beta 2-Glycoprotein, anti-Proteinase 3-ANCA, anti-Mi-2 and anti-PM/Scl-100 defined the convalescent group; anti-Proteinase 3-ANCA, anti-Mi-2, anti-Jo-1 and anti-RNP/SM defined acute COVID-19 subjects; and anti-Proteinase 3-ANCA, anti-Mi-2, anti-Jo-1, anti-Beta 2-Glycoprotein distinguished unexposed controls. The AABs defining SARS-COV-2 infected from pre-pandemic subjects are widely associated with myopathies, vasculitis, and antiphospholipid syndromes, conditions with some similarities to COVID-19. Compared to pre-pandemic non-SLE controls, subjects with acute COVID-19 had higher total IgG concentration (p-value=0.006) but convalescent subjects did not (p-value=0.08); no differences in total IgA levels were found between groups.

ConclusionsOur findings support existing studies suggesting induction of immune responses to self-epitopes during acute, severe COVID-19 with evidence of general B cell hyperactivation. Also, the preponderance of AAB positivity among convalescent individuals up to seven months after infection indicates potential initiation or proliferation, and then persistence of self-reactive immunity without severe initial disease. These results underscore the importance of further investigation of autoimmunity during SARS-CoV-2 infection and its role in the onset and persistence of post-acute sequelae of COVID-19.


title: An interactive COVID-19 virus Mutation Tracker (CovMT) with a particular focus on critical mutations in the Receptor Binding Domain (RBD) region of the Spike protein

abstract: Almost one year has passed since the appearance of SARS-CoV-2, causing the COVID-19 pandemic. The number of confirmed SARS-Cov-2 cases worldwide has now reached [~]92 million, with 2 million reported deaths (https://covid19.who.int). Nearly 400,000 SARS-Cov-2 genomes were sequenced from COVID-19 samples and added to public resources such as GISAID (https://gisaid.org). With the vaccines becoming available or entering trials (https://covid19.trackvaccines.org), it is vital to keep track of mutations in the genome of SARS-CoV-2, especially in the Spike proteins Receptor Binding Domain (RBD) region, which could have a potential impact on disease severity and treatment strategies.1-3 In the wake of a recent increase in cases with a potentially more infective RBD mutation (N501Y) in the United Kingdom, countries worldwide are concerned about the spread of this or similar variants. Impressive sampling and timely increase in sequencing efforts related to COVID-19 in the United Kingdom (UK) helped detect and monitor the spread of the new N501Y variant. Similar sequencing efforts are needed in other countries for timely tracking of this or different variants. To track geographic sequencing efforts and mutations, with a particular focus on RBD region of the Spike protein, we present our daily updated COVID-19 virus Mutation Tracker system, see https://www.cbrc.kaust.edu.sa/covmt.


title: Acute and persistent symptoms in non-hospitalized PCR-confirmed COVID-19 patients

abstract:
BackgroundReports of persistent symptoms after hospitalization with COVID-19 have raised concern of a "long COVID" syndrome. This study aimed at characterizing acute and persistent symptoms in non- hospitalized patients with polymerase chain reaction (PCR) confirmed COVID-19.

MethodsCohort study of 445 non-hospitalized participants identified via the Danish Civil Registration System with a SARS-CoV-2-positive PCR-test and available biobank samples for genetic analyses. Participants received a digital questionnaire on demographics and COVID-19-related symptoms. Persistent symptoms: symptoms >four weeks (in sensitivity analyses >12 weeks).

Results445 participants were included, of whom 34% were asymptomatic. Most common acute symptoms were fatigue, headache, and sneezing, while fatigue and reduced smell and taste were reported as most severe. Persistent symptoms, most commonly fatigue and memory and concentration difficulties, were reported by 36% of 198 symptomatic participants with follow-up >four weeks. Risk factors for persistent symptoms included female sex (women 44% vs. men 24%, odds ratio 2.7, 95%CI:1.4-5.1, p=0.003) and BMI (odds ratio 1.1, 95%CI:1.0-1.2, p=0.001).

ConclusionAmong non-hospitalized PCR-confirmed COVID-19 patients one third were asymptomatic while one third of symptomatic participants had persistent symptoms illustrating the heterogeneity of disease presentation. These findings should be considered in future health care planning and policy making related to COVID-19.


title: SARS-CoV-2 Control on a Large Urban College Campus Without Mass Testing

abstract:
ObjectiveA small percentage of universities and colleges conduct mass SARS-CoV-2 testing. However, universal testing is resource-intensive, strains national testing capacity, and false negative tests can encourage unsafe behaviors.

ParticipantsA large urban university campus.

MethodsVirus control centered on three pillars: mitigation, containment, and communication, with testing of symptomatic and a random subset of asymptomatic students.

ResultsRandom surveillance testing demonstrated a prevalence among asymptomatic students of 0.4% throughout the term. There were two surges in cases that were contained by enhanced mitigation and communication combined with targeted testing. Cumulative cases totaled 445 for the term, most resulting from unsafe undergraduate student behavior and among students living off-campus. A case rate of 232/10,000 undergraduates equaled or surpassed several peer institutions that conducted mass testing.

ConclusionsAn emphasis on behavioral mitigation and communication can control virus transmission on a large urban campus combined with a limited and targeted testing strategy.


title: COVID-19 Diagnostic Testing For All - Using Non-Dilutive Saliva Sample Collection, Stabilization and Ambient Transport Devices

abstract:
COVID-19 testing is not accessible for millions during this pandemic despite our best efforts. Without greatly expanded testing of asymptomatic individuals, contact tracing and subsequent isolation of spreaders remains as a means for control. In an effort to increase RT-PCR assay testing for the presence of the novel beta-coronavirus SARS-CoV-2 as well as improve sample collection safety, GenTegra LLC has introduced two products for saliva collection and viral RNA stabilization: GTR-STM (GenTegra Saliva Transport Medium) and GTR-STMdk (GenTegra Saliva Transport Medium Direct to PCR). Both products contain a proprietary formulation based on GenTegras novel "Active Chemical Protection" (ACP) technology that gives non-dilutive, error-free saliva sample collection using RNA stabilization chemicals already dried in the collection tube.

GTR-STM can be used for safer saliva-based sample collection at home (or at a test site). Following saliva collection, the sample-containing GTR-STM can be kept at ambient temperature during shipment to an authorized CLIA lab for analysis. SARS-CoV-2 viral RNA in GTR-STM is stable for over a month at ambient temperature, easily surviving the longest transit times from home to lab. GTR-STM enhances patient comfort, convenience, compliance and reduces infectious virus exposure to essential medical and lab professionals.

Alternatively, the GTR-STMdk direct-into-PCR product can be used to improve lab throughput and reduce reagent costs for saliva sample collection and testing at any lab site with access to refrigeration. GTR-STMdk reduces lab process time by 25% and reagent costs by 30% compared to other approaches. Since GTR-STMdk retains SARS-CoV-2 viral RNA stability for three days at ambient temperature, it is optimized for lab test site rather than at home saliva collection. SARS-COV-2 viral RNA levels as low as 0.4 genome equivalents/uL are detected in saliva samples using GTR-STMdk. The increased sensitivity of SARS-CoV-2 detection can expand COVID-19 testing to include asymptomatic individuals using pooled saliva.

One Sentence SummaryGTR-STM and Direct-into-PCR GTR-STMdk offer substantive improvements in SARS-CoV-2 viral RNA stability, safety, and RT-PCR process efficiency for COVID-19 testing by using a non-dilutive saliva sample collection system for individuals at home or onsite respectively.


title: High-altitude is associated with better short-term survival in critically ill COVID-19 patients admitted to the ICU

abstract:
BackgroundThe novel human coronavirus, SARS-CoV-2, has affected at least 218 countries worldwide. Some geographical and environmental factors are positively associated with a better or worse prognosis concerning COVID-19 disease and with lower or higher SARS-CoV-2 transmission. High altitude exposure has been associated with lower SARS-CoV-2 attack rates; nevertheless, the role of chronic high-altitude exposure on the clinical outcome of critically ill COVID-19 patients has not been studied.

ObjectiveTo compare the clinical course and outcomes of critically ill patients with COVID-19 hospitalized in two intensive care units (ICU) located at low and high altitude.

Exposure and OutcomeTo explore the effect of two different elevations (10 m vs 2,850 m above sea level) on COVID-19 clinical outcome and survival.

MethodsA prospective cohort, two-center study in confirmed COVID-19 adult patients admitted to a low altitude (Sea level) and high altitude (2,850 m) ICU units in Ecuador was conducted. Two hundred and thirty confirmed COVID-19 patients were enrolled from March 15th to July 15th, 2020. Sociodemographic, clinical, laboratory and imaging parameters including supportive therapies, pharmacological treatments and medical complications were reported and compared between the low and high-altitude groups.

ResultsThe median age of all the patients was 60 years, 64.8% were men and 35.2% were women. A total of 105 (45.7%) patients had at least one underlying comorbidity, the most frequent being chronic diseases, such as hypertension (33.5%), diabetes (16.5%), and chronic kidney failure (5.7%). The APACHE II scale at 72 hours was especially higher in the low-altitude group with a median of 18 points (IQR: 9.5-24.0), compared to 9 points (IQR: 5.0-22.0) obtained in the group of high altitude. There is evidence of a difference in survival in favor of the high-altitude group (p = 0.006), the median survival being 39 days, compared to 21 days in the low altitude group.

ConclusionThere has been a substantial improvement in survival amongst people admitted to the high-altitude critical care unit. High altitude living was associated with improved survival, especially among patients with no comorbidities. COVID-19 patients admitted to the high-altitude ICU unit have improved severity-of-disease classification system scores at 72 hours and reported better respiratory and ventilatory profiles than the low altitude group.

category: intensive care and critical care medicine


title: Numbers of close contacts of individuals infected with SARS-CoV-2 and their association with government intervention strategies.

abstract:
BackgroundContact tracing is conducted with the primary purpose of interrupting transmission from individuals who are likely to be infectious to others. Secondary analyses of data on the numbers of close contacts of confirmed cases could also: provide an early signal of increases in contact patterns that might precede larger than expected case numbers; evaluate the impact of government interventions on the number of contacts of confirmed cases; or provide data information on contact rates between age cohorts for the purpose of epidemiological modelling.

MethodsWe analysed data from 140,204 contacts of 39861 cases in Ireland from 1st May to 1st December 2020. Only  close contacts were included in the analysis. A close contact was defined as any individual who had had > 15 minutes face-to-face (<2 m) contact with a case; any household contact; or any individual sharing a closed space for longer than 2 hours, in any setting.

ResultsThe number of contacts per case was overdispersed, the mean varied considerably over time, and was temporally associated with government interventions. Negative binomial regression models highlighted greater numbers of contacts within specific population demographics, after correcting for temporal associations. Separate segmented regression models of the number of cases over time and the average number of contacts per case indicated that a breakpoint indicating a rapid decrease in the number of contacts per case in October 2020 preceded a breakpoint indicating a reduction in the number of cases by 11 days.

DiscussionThese data were collected for a specific purpose and therefore any inferences must be made with caution. The data are representative of contact rates of cases, and not of the overall population. However, the data may be a more accurate indicator of the likely degree of onward transmission than might be the case if a random sample of the population were taken. Furthermore, since we analysed only the number of close contacts, the total number of contacts per case would have been higher. Nevertheless, this analysis provides useful information for monitoring the impact of government interventions on the number of contacts; for helping pre-empt increases or decreases in case numbers, and for triangulating assumptions regarding the contact mixing rates between different age cohorts for epidemiological modelling.


title: Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities

abstract:
BackgroundSimulation models can be used to quantify the projected health impact of interventions. Quantifying heterogeneity in these impacts, for example by socioeconomic status, is important to understand impacts on health inequalities.

We aim to disaggregate one type of Markov macro-simulation model, the proportional multistate lifetable, ensuring that under business-as-usual (BAU) the sum of deaths across disaggregated strata in each time step returns the same as the initial non-disaggregated model. We then demonstrate the application by deprivation quintiles for New Zealand (NZ), for: hypothetical interventions (50% lower all-cause mortality, 50% lower coronary heart disease mortality) and a dietary intervention to substitute 59% of sodium with potassium chloride in the food supply.

MethodsWe developed a disaggregation algorithm that iteratively rescales mortality, incidence and case fatality rates by time-step of the model to ensure correct total population counts were retained at each step.

To demonstrate the algorithm on deprivation quintiles in NZ, we used the following inputs: overall (non-disaggregated) all-cause mortality &morbidity rates, coronary heart disease incidence &case fatality rates; stroke incidence &case fatality rates. We also obtained rate ratios by deprivation for these same measures. Given all-cause and cause-specific mortality rates by deprivation quintile, we derived values for the incidence, case fatality and mortality rates for each quintile, ensuring rate ratios across quintiles and the total population mortality and morbidity rates were returned when averaged across groups.

The three interventions were then run on top of these scaled BAU scenarios.

ResultsThe algorithm exactly disaggregated populations by strata in BAU. The intervention scenario life years and health adjusted life years (HALYs) gained differed slightly when summed over the deprivation quintile compared to the aggregated model, due to the stratified model (appropriately) allowing for differential background mortality rates by strata. Modest differences in health gains (health adjusted life years) resulted from rescaling of sub-population mortality and incidence rates to ensure consistency with the aggregate population.

ConclusionPolicy makers ideally need to know the effect of population interventions estimated both overall, and by socioeconomic and other strata. We demonstrate a method and provide code to do this routinely within proportional multistate lifetable simulation models and similar Markov models.


title: On mobility trends analysis of COVID-19 dissemination in Mexico City

abstract: This work presents a forecast of the spread of the new coronavirus in Mexico City based on a mathematical model with metapopulation structure by using Bayesian Statistics inspired in a data-driven approach. The mobility of humans on a daily basis in Mexico City is mathematically represented by a origin-destination matrix using the open mobility data from Google and a Transportation Mexican Survey. This matrix, is incorporated in a compartmental model. We calibrate the model against borough-level incidence data collected between February 27, 2020 and October 27, 2020 using Bayesian inference to estimate critical epidemiological characteristics associated with the coronavirus spread. Since working with metapopulation models lead to rather high computational time consume, we do a clustering analysis based on mobility trends in order to work on these clusters of borough separately instead of taken all the boroughs together at once. This clustering analysis could be implemented in smaller or lager scale in different part of the world. In addition, this clustering analysis is divided in the phases that the government of Mexico City has set up to restrict the individuals movement in the city. Also, we calculate the reproductive number in Mexico City using the next generation operator method and the inferred model parameters. The analysis of mobility trends can be helpful in public health decisions.


title: Predictive power of SARS-CoV-2 wastewater surveillance for diverse populations across a large geographical range

abstract: The COVID-19 pandemic has exacerbated the disparities in healthcare delivery in the US. Many communities had, and continue to have, limited access to COVID-19 testing, making it difficult to track the spread and impact of COVID-19 in early days of the outbreak. To address this issue we monitored severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA at the population-level using municipal wastewater influent from 19 cities across the state of Minnesota during the COVID-19 outbreak in Summer 2020. Viral RNA was detected in wastewater continually for 20-weeks for cities ranging in populations from 500 to >1, 000, 000. Using a novel indexing method, we were able to compare the relative levels of SARS-CoV-2 RNA for each city during this sampling period. Our data showed that viral RNA trends appeared to precede clinically confirmed cases across the state by several days. Lag analysis of statewide trends confirmed that wastewater SARS-CoV-2 RNA levels preceded new clinical cases by 15-17 days. At the regional level, new clinical cases lagged behind wastewater viral RNA anywhere from 4-20 days. Our data illustrates the advantages of monitoring at the population-level to detect outbreaks. Additionally, by tracking infections with this unbiased approach, resources can be directed to the most impacted communities before the need outpaces the capacity of local healthcare systems.


title: Mathematical Relationship between Effective Reproduction Number Rt and Epidemic Curve of Daily Cases -- Demonstration and Details

abstract: The strict mathematical relationship between Rt and the curve of daily cases f(t) is shown. Up-to-date and statistically robust Rt from the curve of daily cases can be estimated as soon as new cases are added to the curve. That is equivalent to estimating Rt by averaging all detected cases of infection, without any distortion induced by the difficulty of following and weighting trees of secondary cases from original ones, and without needing to wait for secondary cases to manifest infection. With this method, if Rt scaled numbers are of interest, only the average duration of infectivity of subjects has to be estimated directly, but independently of linking secondary cases to primary ones. A new index, instantaneous reproduction number Rist is introduced, which does not depend on the duration of infectivity of subjects. Rist, Rt and the doubling/halving time of the epidemics may be estimated by simple computations at the very detection time of new daily cases. Any smoothed curve of daily cases gives smooth Rt and Rist. No phase lag on Rt estimate is introduced by this method.


title: Determinants of the incidence and mortality rates of COVID-19 during the first six months of the pandemic; A cross-country study

abstract:
COVID-19 pandemic raises an extraordinary challenge to the healthcare systems globally. The governments are taking key measures to constrain the corresponding health, social, and economic impacts, however, these measures vary depending on the nature of the crisis and country-specific circumstances.

ObjectivesConsidering different incidence and mortality rates across different countries, we aimed at explaining variance of these variables by performing accurate and precise multivariate analysis with aid of suitable predictors, accordingly, the model would proactively guide the governmental responses to the crisis.

MethodsUsing linear and exponential time series analysis, this research aimed at studying the incidence and mortality rates of COVID-19 in 18 countries during the first six months of the pandemic, and further utilize multivariate techniques to explain the variance in monthly exponential growth rates of cases and deaths with aid of a set of different predictors: the recorded Google mobility trends towards six categories of places, daily average temperature, daily humidity, and key socioeconomic attributes of each country.

ResultsThe analysis showed that changes in mobility trends were the most significant predictors of the incidence and mortality rates, temperature and humidity were also significant but to a much lesser extent, on the other hand, the socioeconomic attributes did not contribute significantly to explaining different incidence and mortality rates across countries.

ConclusionChanges in mobility trends across countries dramatically affected the incidence and mortality rates across different countries, thus, it might be used as a proxy measure of contact frequency.


title: Social, economic, and environmental factors influencing the basic reproduction number of COVID-19 across countries

abstract:
ObjectiveTo assess whether the basic reproduction number (R0) of COVID-19 is different across countries and what national-level demographic, social, and environmental factors characterize initial vulnerability to the virus.

MethodsWe fit logistic growth curves to reported daily case numbers, up to the first epidemic peak. This fitting estimates R0. We then use a generalized additive model to discern the effects, and include 5 random effect covariates to account for potential differences in testing and reporting that can bias the estimated R0.

FindingsWe found that the mean R0 is 1.70 (S.D. 0.57), with a range between 1.10 (Ghana) and 3.52 (South Korea). We identified four factors-population between 20-34 years old (youth), population residing in urban agglomerates over 1 million (city), social media use to organize offline action (social media), and GINI income inequality-as having strong relationships with R0. An intermediate level of youth and GINI inequality are associated with high R0, while high city population and high social media use are associated with high R0. Environmental and climate factors were not found to have strong relationships with R0.

ConclusionStudies that aim to measure the effectiveness of interventions should account for the intrinsic differences between populations.