title: Differential Effects of Pathological Beta Burst Dynamics Between Parkinson's Disease Phenotypes Across Different Movements

abstract:
BackgroundResting state beta band (13 - 30 Hz) oscillations represent pathological neural activity in Parkinsons disease (PD). It is unknown how the peak frequency or dynamics of beta oscillations may change among fine, limb and axial movements and different disease phenotypes. This will be critical for the development of personalized closed loop deep brain stimulation (DBS) algorithms during different activity states.

MethodsSubthalamic (STN) local field potentials (LFPs) were recorded from a sensing neurostimulator (Activa(R) PC+S, Medtronic PLC.,) in fourteen PD participants (six tremor-dominant, 8 akinetic-rigid) off medication/off STN DBS during thirty seconds of repetitive alternating finger tapping, wrist-flexion extension, stepping in place, and free walking. Beta power peaks and beta burst dynamics were identified by custom algorithms and were compared among movement tasks and between tremor-dominant and akinetic-rigid groups.

ResultsBeta power peaks were evident during fine, limb, and axial movements in 98% of movement trials; the peak frequencies were similar during each type of movement. Burst power and duration were significantly larger in the high beta band, but not in the low beta band, in the akinetic-rigid group compared to the tremor-dominant group.

ConclusionsThe conservation of beta peak frequency during different activity states supports the feasibility of patient-specific closed loop DBS algorithms driven by the dynamics of the same beta band during different activities. Akinetic-rigid participants had greater power and longer burst durations in the high beta band than tremor-dominant participants during movement, which may relate to the difference in underlying pathophysiology between phenotypes.


title: Fatigue in perinatal stroke is associated with the functional connectivity

abstract: Fatigue is prevalent in youth with perinatal stroke, but the causes are unclear. Predictive coding models of adult post-stroke fatigue suggest that fatigue may arise from dysfunction in predictive processing networks. To date, the association between fatigue and neural network connectivity in youth with perinatal stroke has not been examined. The present study examined the association between fatigue and the functional connectivity of predictive processing neural networks, measured using resting-state functional magnetic resonance imaging, in individuals with perinatal stroke. Participants who reported experiencing fatigue had weaker functional connectivity between the non-lesioned middle frontal and supramarginal gyri and between the non-lesioned intracalcarine cortex and the lesioned paracingulate cortex. In contrast, participants reporting fatigue had stronger functional connectivity between the lesioned inferior temporal gyrus and non-lesioned insula. These results suggest that fatigue in youth with hemiparetic cerebral palsy caused by perinatal stroke is associated with the functional connectivity of hubs previously associated with predictive processing and fatigue. These results suggest potential cortical and behavioral targets for the treatment of fatigue in individuals with perinatal stroke.

category: neurology


title: The Longevity-Frailty Hypothesis: Evidence from COVID-19 Death Rates in Europe

abstract: By the end of spring (May 31st), the COVID-19 death rate was remarkably unevenly distributed across the countries Europe. While the risk of COVID-19 mortality is known to increase with age, age-specific COVID-19 death rates across Europe were similarly aberrantly distributed, implying that differences in age structure is an unlikely source of European variation in COVID-19 mortality. To explain these mortality distributions, we present a simple model where more favorable survival environments promote longevity and the accumulation of health frailty among the elderly while less favorable survival environments induce a mortality selection process that results in lower health frailty. Because the age-related conditions of frailty render the elderly less resistant to SARS-CoV-2, pre-existing survival environments may be non-obviously positively related to the COVID-19 death rate. To quantify the survival environment parameter of our model, we collected historic cohort- and period-based age-specific probabilities of death across Europe. We find strong positive relationships between survival indicators and COVID-19 death rates across Europe, a result that is robust to statistical control for the capacity of a healthcare system to treat and survive infected persons, the timing and stringency of non-pharmaceutical interventions, and the volume of inbound international travelers, among other factors. To address possible concerns over reporting heterogeneity across countries, we show that results are robust to the substitution of our response variable for a measure of cumulative excess mortality. Consistent with the intuition of our model, we also show a strong negative association between age-specific COVID-19 death rates and pre-existing all-cause age-specific mortality rates for a subset of European countries. Overall, results support the notion that variation in pre-existing frailty, resulting from heterogeneous survival environments, partially caused striking differences in COVID-19 death during the first wave of the pandemic.

category: epidemiology


title: Exploring health in the UK Biobank: associations with sociodemographic characteristics, psychosocial factors, lifestyle and environmental exposures

abstract: A greater understanding of factors associated with good health may help increase longevity and healthy life expectancy. Here we report associations between multiple health indicators and sociodemographic (age, sex, ethnicity, education, income and deprivation), psychosocial (loneliness and social isolation), lifestyle (smoking, alcohol intake, sleep, BMI, physical activity and stair climbing) and environmental (air pollution, noise and greenspace) factors, using data from 307,378 UK Biobank participants. Low income, being male, neighbourhood deprivation, loneliness, social isolation, short or long sleep duration, low or high BMI and smoking was associated with poor health. Walking, vigorous-intensity physical activity and more frequent alcohol intake was associated with good health. There was some evidence that airborne pollutants (PM2.5, PM10, and NO2) and noise (Lden) were associated with poor health, though findings were inconsistent in adjusted models. Our findings highlight the multifactorial nature of health, the importance of non-medical factors, such as loneliness, healthy lifestyle behaviours and weight management, and the need to examine efforts to improve health outcomes of individuals with low income.


title: Quantitative Trait Loci on Chromosome 21 have Pleiotropic Effects on %FEV1 and Allergen Polysensitization; asthma related traits in the EGEA study

abstract:
To investigate whether the 21q21 region may contain a quantitative trait locus (QTL) with pleiotropic effect on % predicted FEV1 (forced expiratory volume in 1 second) and SPTQ (number of positive skin test responses to 11 allergens), in 295 EGEA families ascertained through asthmatic probands, we conducted a bivariate linkage analysis using two approaches:

(1) a bivariate variance components (VC) analysis and (2) A combined principal components (CPC) analysis, with 13 microsatellites covering the whole chromosome 21. To identify the genetic variants associated with these traits, we performed family-based association analysis (FBAT) for the second principal component (PC2) using two microsatellites and 27 SNPs belonging to three candidate genes, located in the vicinity of the linkage peak. Univariate linkage analyses showed suggestive evidence of linkage to %FEV1 and SPTQ at two positions. Bivariate VC linkage analysis of these phenotypes led to an increase in linkage signals as compared to univariate analysis at the same positions. The peaks obtained by the CPC led to similar results as the full bivariate VC approach; evidence for linkage mainly coming from PC2. The strongest association signal, using single marker analysis for PC2, was obtained with D21S1252 (p=0.003 for global test; p=0.004 for allele 2 and p=0.001 for allele 11) and rs2834213 of IFNGR2 (p=0.003), these two loci being 3 Mb apart. Multi-marker analysis further strengthened this finding. These results indicate that at least two genetic factors may be involved in SPTQ and %FEV1 variability but further genotyping is needed to better understand these findings.

category: respiratory medicine


title: Predicting the epidemic curve of the coronavirus (SARS-CoV-2) disease (COVID-19) using artificial intelligence

abstract: The aim of our study was to predict the epidemic curves (daily new cases) of COVID-19 pandemic using Artificial Intelligence (AI)-based Recurrent Neural Networks (RNNs), then to compare and validate the predicted models with the observed data. We used the publicly available datasets from the World Health Organization and Johns Hopkins University to create a training dataset, then we used RNNs with gated recurring units (Long Short-Term Memory) to create two prediction models. Information collected in the first t time-steps were aggregated with a fully connected (dense) neural network layer and a consequent regression output layer to determine the next predicted value. We also used Root Mean Squared Logarithmic Errors (RMSLE) to compare the predicted models with the observed data. The result of our study underscores that the COVID-19 pandemic is a propagated source epidemic, therefore repeated peaks on the epidemic curve are to be anticipated. Besides, the errors between the predicted and validated data and trends seems to be low. The influence of this pandemic is significant worldwide and has already impacted our daily life. Decision makers must be aware, that even if strict public health measures are executed and sustained, future peaks of infections are possible.


title: Spatial scales in human movement between reservoirs of infection

abstract: The life cycle of parasitic organisms that are the cause of much morbidity in humans often depend on reservoirs of infection for transmission into their hosts. Understanding the daily, monthly and yearly movement patterns of individuals between reservoirs is therefore of great importance to implementers of control policies seeking to eliminate various parasitic diseases as a public health problem. This is due to the fact that the underlying spatial extent of the reservoir of infection, which drives transmission, can be strongly affected by inputs from external sources, i.e., individuals who are not spatially attributed to the region defined by the reservoir itself can still migrate and contribute to it. In order to study the importance of these effects, we build and examine a novel theoretical model of human movement between spatially-distributed focal points for infection clustered into regions defined as  reservoirs of infection. Using our model, we vary the spatial scale of human moment defined around focal points and explicitly calculate how varying this definition can influence the temporal stability of the effective transmission dynamics -- an effect which should strongly influence how control measures, e.g., mass drug administration (MDA), define evaluation units (EUs). Considering the helminth parasites as our main example, by varying the spatial scale of human movement, we demonstrate that a critical scale exists around infectious focal points at which the migration rate into their associated reservoir can be neglected for practical purposes. This scale varies by species and geographic region, but is generalisable as a concept to infectious reservoirs of varying spatial extents and shapes. Our model is designed to be applicable to a very general pattern of infectious disease transmission modified by the migration of infected individuals between clustered communities. In particular, it may be readily used to study the spatial structure of hosts for macroparasites with temporally stationary distributions of infectious focal point locations over the timescales of interest, which is viable for the soil-transmitted helminths and schistosomes. Additional developments will be necessary to consider diseases with moving reservoirs, such as vector-born filarial worm diseases.


title: Early Evidence and Predictors of Mental Distress of Adults One Month in the COVID-19 Epidemic in Brazil

abstract:
ObjectiveWe aim to provide early evidence of mental distress and its associated predictors among adults one month into the COVID-19 crisis in Brazil.

MethodsWe conducted an online survey of 638 adults in Brazil on March 25-28, 2020, about one month (32 days) cross-sectionally after the first COVID-19 case in South America was confirmed in Sao Paulo. The 638 adults were in 25 states out of the 26 Brazilian states, with the only exception being Roraima, the least populated state in the Amazon. Of all the participating adults, 24%, 20%, and 18% of them were located in Rio de Janeiro state, Santa Catarina state, and Sao Paulo state respectively.

ResultsIn Brazil, 52% (332) of the sampled adults experienced mild or moderate distress, and 18.8% (120) suffered severe distress. Adults who were female, younger, more educated, and exercised less reported higher levels of distress. Each individuals distance from the Brazilian epicenter of Sao Paulo interacted with age and workplace attendance to predict the level of distress. The "typhoon eye effect" was stronger for people who were older or attended their workplace less. The most vulnerable adults were those who were far from the epicenter and did not go to their workplace in the week before the survey.

ConclusionIdentifying the predictors of distress enables mental health services to better target finding and helping the more mentally vulnerable adults during the ongoing COVID-19 crisis.

category: psychiatry and clinical psychology


title: Is there evidence that BCG vaccination has non-specific protective effects for COVID 19 infections or is it an illusion created by lack of testing?

abstract: The goal of this paper is to showcase that the COVID-19 disease pattern is evolving and to study the relationship between mandatory BCG policy and caseload/million or death/per million. We analyze seven recent publications on the impact of BCG vaccinations on the development of COVID19 illness and extend presented findings using the latest data from April 10, 2020. We analyze data from 98 countries and we extend existing models by adding the dimension of COVID-19-related testing conducted by the analyzed countries. Similarly to prior studies, we find that COVID-19 attributable case and death incidences across countries share a relationship with a countrys BCG vaccination inclusion in the national immunization program when testing is not taken into consideration. However, this relationship vanishes when we add the dimension of testing. We observe that case and death incidences conditional on testing do not get affected by the countries BCG vaccination inclusion in the national immunization program. Therefore, we show that there is no statistical evidence to support the assertion that inclusion of BCG vaccination in national immunization program (NIP) has any impact of COVID 19 infections (cases) or mortality.

category: infectious diseases


title: Plasma lipidomics identifies a signature of NAFLD in children that couples with cardiometabolic outcomes in adults

abstract: Non-alcoholic fatty liver disease (NAFLD) is an increasingly common condition in children and adults characterized by insulin resistance and altered lipid metabolism. Affected patients are at increased risk of cardiovascular disease (CVD) and children with NAFLD are likely to be at risk of premature cardiac events. Evaluation of the plasma lipid profile of children with NAFLD offers the opportunity to investigate these perturbations and understand how closely they mimic the changes seen in adults with cardiometabolic disease. We hypothesized that change in the concentration of lipid species in pediatric NAFLD would mimic the alterations known to be associated with CVD in adults (and be largely reflective of insulin resistance). Here, we performed untargeted liquid chromatography mass spectrometry (LC-MS) plasma lipidomics on 287 children: 19 lean controls, 146 from an obese cohort, and 122 NAFLD cases who had undergone liver biopsy. Associations between lipid species and liver histology were assessed using regression adjusted for age and sex. Results were then replicated using data from 9,500 adults with metabolic phenotyping. Phosphatidylcholine (PC) and triglyceride (TG) desaturation and chain length were inversely associated with histological severity of paediatric NAFLD. Nine lipids species (lyso-PC, PC, and TG classes) were also associated with hepatic steatosis and insulin resistance in an independent cohort of adults. Five of the 9 lipids replicated in the adults cohort (including PC(36:4)) have been directly linked to death and cardiometabolic disease in adults, as well as indirectly via genetic variants that influence the concentration of these species. Together, these findings suggest that lipid metabolism is altered in paediatric NAFLD in a similar way as in cardiometabolic disease in adults and it is therefore critical to alleviate insulin resistance in these children to mitigate their long-term morbidity.

category: gastroenterology


title: Audiometric profiles and patterns of benefit. A data-driven analysis of subjective hearing difficulties and handicaps.

abstract:
ObjectiveHearing rehabilitation attempts to compensate for auditory dysfunction, reduce hearing difficulties and minimize participation restrictions that can lead to social isolation. However, there is no systematic approach to assess the quality of the intervention at an individual level that might help to evaluate the need of further hearing rehabilitation in the hearing care clinic.

DesignA data-driven analysis on subjective data reflecting hearing disabilities and handicap was chosen to explore "benefit patterns" as a result of rehabilitation in different audiometric groups. The method was based on: 1) Dimensionality reduction; 2) Stratification; 3) Archetypal analysis; 4) Clustering; and 5) Item importance estimation.

Study sample572 hearing-aid users completed questionnaires of hearing difficulties (speech, spatial and qualities hearing scale; SSQ) and hearing handicap (HHQ).

ResultsThe data-driven approach revealed four benefit profiles that were different for each audiometric group. The groups with low degree of high-frequency hearing loss (HLHF) showed a priority for rehabilitating hearing handicaps, whereas the groups with HLHF > 50 dB HL showed a priority for improvements in speech understanding.

ConclusionsThe patterns of benefit and the stratification approach might guide the clinical intervention strategy and improve the efficacy and quality of service in the hearing care clinic.

category: otolaryngology


title: Clonal chromosomal mosaicism and loss of chromosome Y in men are risk factors for SARS-CoV-2 vulnerability in the elderly

abstract: The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) has an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome events (CME) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (CME and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, CME and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people.

category: genetic and genomic medicine


title: The effect of short-graft preparation with tape suspension and screw fixation on loss of knee extension following anterior cruciate ligament reconstruction: A retrospective cross-sectional analysis of public hospital cases from 2015 - 2017

abstract:
IntroductionThe short graft with tape suspension (SGTS) is a technique for ACL reconstruction that has gained popularity in recent years. Though the construct utilises a hamstring tendon, its biomechanical properties more closely resemble a stiffer graft such as bone-patella-bone. Due to these properties, there are concerns this technique may increase the likelihood of postoperative loss of extension (LOE), particularly if the surgeon does not modify their tensioning technique. This study compared LOE in patients undergoing ACLR with the SGTS technique, versus other ACLR techniques. We hypothesised that with appropriate technique modifications, the SGTS technique would not be inferior to long hamstring graft techniques with respect to LOE observed clinically during supervised rehabilitation.

Materials and MethodsWe retrospectively reviewed 138 patients who received primary ACLR at one of two hospitals between January 2015 and December 2017 and elected to participate in a rehabilitation program with the hospital physiotherapy department. Postoperative knee extension was assessed by a department physiotherapist until satisfactory function was achieved. Patients were classified as SGTS ACLR or non-SGTS ACLR during chart review and LOE compared at initial assessment and at the time of maximum extension, via a noninferiority analysis.

ResultsThe grafts for the SGTS group (N=44) were significantly larger in diameter (median 8.5mm vs. 8.0mm, P <0.001) and less incidence of notchplasties (17.8% vs. 44.7%, P <0.001) compared with the non-SGTS group (N=94). The upper 95% confidence interval for the difference in proportions between groups did not exceed the non-inferiority margin (0.3 or 30%) at either Initial or Maximum timepoints.

ConclusionsThe SGTS technique was not inferior to other hamstring-graft ACLR techniques with respect to postoperative LOE. Surgeons using or considering using the SGTS construct can rule out increased incidence of LOE as a factor in their decision-making, providing the grafts are prepared according to existing guidance and tensioned in full extension. Further studies are recommended to assess longer term functional outcomes and ultimately treatment success.

category: orthopedics


title: Predictive modeling of secondary pulmonary hypertension in left ventricular diastolic dysfunction

abstract: Diastolic dysfunction is a common pathology occurring in about one third of patients affected by heart failure. This condition is not associated with a marked decrease in cardiac output or systemic pressure and therefore is more difficult to diagnose than its systolic counterpart. Compromised relaxation or increased stiffness of the left ventricle with or without mitral valve stenosis induces an increase in the upstream pulmonary pressures, and is classified as secondary or group II (2018 Nice classification) pulmonary hypertension. This may result in an increase in the right ventricular afterload leading to right ventricular failure. Elevated pulmonary pressures are therefore an important clinical indicator of diastolic heart failure (sometimes referred to as heart failure with preserved ejection fraction, HFpEF), showing significant correlation with associated mortality. Accurate measurements of this quantity, however, are typically obtained through invasive catheterization, and after the onset of symptoms. In this study, we use the hemodynamic consistency of a differential-algebraic circulation model to predict pulmonary pressures in adult patients from other, possibly non-invasive, clinical data. We investigate several aspects of the problem, including the ability of model outputs to represent a sufficiently wide pathologic spectrum, identifiability of its parameters, to the accuracy of the predicted pulmonary pressures. We also find that a classifier using the assimilated model parameters as features is free from the problem of missing data and is able to detect pulmonary hypertension with sufficiently high accuracy. For a cohort of 82 patients suffering from various degrees of heart failure severity we show that systolic, diastolic and wedge pulmonary pressures can be estimated on average within 8, 6 and 6 mmHg, respectively. We also show that, in general, increased data availability leads to improved predictions.

category: health informatics


title: White matter variability, cognition, and disorders: a systematic review.

abstract: Inter-individual differences can inform treatment procedures and - if accounted for - have the potential to significantly improve patient outcomes. However, when studying brain anatomy, these inter-individual variations are commonly unaccounted for, despite reports of differences in gross anatomical features, cross-sectional and connectional anatomy. Brain connections are essential to facilitate functional organisation and, when severed, cause impairments or complete loss of function. Hence the study of cerebral white matter may be an ideal compromise to capture inter-individual variability in structure and function. We reviewed the wealth of studies that associate functions and clinical symptoms with individual tracts using diffusion tractography. Our systematic review indicates that tractography has proven to be a sensitive method in neurology, psychiatry, and healthy populations to identify variability and its functional correlates. However, the literature may be biased, as we determined that the most commonly studied tracts are not necessarily those with the highest sensitivity to cognitive functions and pathologies. Additionally, the hemisphere of the studied tract is often unreported, thus neglecting functional laterality and asymmetries. Finally, we demonstrate that tracts, as we define them, are not usually correlated with only one, but rather multiple cognitive domains or pathologies. While our systematic review identified some methodological caveats, it also suggests that tract-function correlations might be a promising biomarker for precision medicine. It characterises variations in brain anatomy, differences in functional organisation, and predicts resilience and recovery in patients.


title: A systematic review and meta-analysis of Anakinra, Sarilumab, Siltuximab and Tocilizumab for Covid-19

abstract:
BackgroundThere is accumulating evidence for an overly activated immune response in severe Covid-19, with several studies exploring the therapeutic role of immunomodulation. Through systematic review and meta-analysis, we assess the effectiveness of specific interleukin inhibitors for the treatment of Covid-19.

MethodsElectronic databases were searched on 7th January 2021 to identify studies of immunomodulatory agents (anakinra, sarilumab, siltuximab and tocilizumab) for the treatment of Covid-19. The primary outcomes were severity on an ordinal scale measured at day 15 from intervention and days to hospital discharge. Key secondary endpoints included overall mortality.

Results71 studies totalling 22,058 patients were included, six were randomised trials. Most explored outcomes in patients who received tocilizumab (59/71). In prospective studies, tocilizumab was associated with improved unadjusted survival (RR 0.83 95%CI 0.72;0.96 I2 = 0.0%), but conclusive benefit was not demonstrated for other outcomes. In retrospective studies, tocilizumab was associated with less severe outcomes on an ordinal scale (Generalised odds ratio 1.34 95%CI 1.10;1.64, I2=98%) and adjusted mortality risk (HR 0.52 95%CI 0.41;0.66, I2 =76.6%). The mean difference in duration of hospitalisation was 0.36 days (95%CI -0.07;0.80, I2 =93.8%). There was substantial heterogeneity in retrospective studies, and estimates should be interpreted cautiously. Other immunomodulatory agents showed similar effects to tocilizumab, but insufficient data precluded meta-analysis by agent.

ConclusionTocilizumab was associated with a lower relative risk of mortality in prospective studies, but effects were inconclusive for other outcomes. Current evidence for the efficacy of anakinra, siltuximab or sarilumab in Covid-19 is insufficient, with further studies urgently needed for conclusive findings.


title: Small-sample estimation of the mutational support and the distribution of mutations in the SARS-Cov-2 genome

abstract:
AO_SCPLOWBSTRACTC_SCPLOWThe problem of estimating unknown features of viral species using a limited collection of observations is of great relevance in computational biology. We consider one such particular problem, concerned with determining the mutational support and distribution of the SARS-Cov-2 viral genome and its open reading frames (ORFs). The mutational support refers to the unknown number of sites that is expected to be eventually mutated in the SARS-Cov-2 genome. It may be used to assess the virulence of the virus or guide primer selection for real-time RT-PCR tests during the early stages of an outbreak. Estimating the unknown distribution of mutations in the genome of different subpopulations while accounting for the unseen may aid in discovering adaptation mechanisms used by the virus to evade the immune system. To estimate the mutational support in the small-sample regime, we use GISAID sequencing data and new state-of-the-art polynomial estimation techniques based on weighted and regularized Chebyshev approximations. For distribution estimation, we adapt the well-known Good-Turing estimator. We also perform a differential analysis of mutations and their sites across different populations. Our analysis reveals several findings: First, the mutational supports exhibit significant differences in the ORF6 and ORF7a regions (older vs younger patients), ORF1b and ORF10 regions (females vs males) and as may be expected, in almost all ORFs (for Asia versus Europe and North America). Second, despite the fact that the N region of SARS-Cov-2 has a predicted 10% mutational support, almost all observed mutations fall outside of the two regions of paired primers recommended for testing by the CDC.

Author SummaryWe introduce the new problem of small-sample estimation of the number of mutations and the distribution of mutations in viral and bacterial genomes, and in particular, in the SARS-Cov-2 genome. The approach is of interest due to the fact that it aims to predict which regions in the genome will mutate in the future and with what frequency, given only a very limited number of complete viral sequences. This setting is usually encountered during the early stages of an outbreak when it is critical to assess the potential of the virus to gain mutations advantageous for its spreading. The results may also be used to guide the selection of genomic (primer) regions that are not subject to mutational pressure and can consequently be used as identifiers in the process of testing for the disease. They can also highlight differences in the mutation rates and locations of the SARS-Cov-2 virus affecting diverse subpopulations and therefore potentially suggest the role of certain mutations in evading the immune system. Our approach uses a new class of estimation methods that may find other applications in bioinformatics.


title: Resilient SARS-CoV-2 diagnostics workflows including viral heat inactivation

abstract: There is a worldwide need for reagents to perform SARS-CoV-2 detection. Some laboratories have implemented kit-free protocols, but many others do not have the capacity to develop these and/or perform manual processing. We provide multiple workflows for SARS-CoV-2 nucleic acid detection in clinical samples by comparing several commercially available RNA extraction methods: QIAamp Viral RNA Mini Kit (QIAgen), RNAdvance Blood/Viral (Beckman) and Mag-Bind Viral DNA/RNA 96 Kit (Omega Bio-tek). We also compared One-step RT-qPCR reagents: TaqMan Fast Virus 1-Step Master Mix (FastVirus, ThermoFisher Scientific), qPCRBIO Probe 1-Step Go Lo-ROX (PCR Biosystems) and Luna(R) Universal Probe One-Step RT-qPCR Kit (Luna, NEB). We used primer-probes that detect viral N (EUA CDC) and RdRP (PHE guidelines). All RNA extraction methods provided similar results. FastVirus and Luna proved most sensitive. N detection was more reliable than that of RdRP, particularly in samples with low viral titres. Importantly, we demonstrate that treatment of nasopharyngeal swabs with 70 degrees for 10 or 30 min, or 90 degrees for 10 or 30 min (both original variant and B 1.1.7) inactivates SARS-CoV-2 employing plaque assays, and that it has minimal impact on the sensitivity of the qPCR in clinical samples. These findings make SARS-CoV-2 testing portable to settings that do not have CL-3 facilities. In summary, we provide several testing pipelines that can be easily implemented in other laboratories and have made all our protocols and SOPs freely available at https://osf.io/uebvj/.


title: Reacting to outbreaks at neighboring localities

abstract: We study the dynamics of epidemics in a networked metapopulation model. In each subpopulation, representing a locality, the disease propagates according to a modified susceptible-exposed-infected-recovered (SEIR) dynamics. In the modified SEIR dynamics, individuals reduce their number of contacts as a function of the weighted sum of cumulative number of cases within the locality and in neighboring localities. We consider a scenario with two localities where disease originates in one locality and is exported to the neighboring locality via travel of exposed (latently infected) individuals. We establish a lower bound on the outbreak size at the origin as a function of the speed of spread. Using the lower bound on the outbreak size at the origin, we establish an upper bound on the outbreak size at the importing locality as a function of the speed of spread and the level of preparedness for the low mobility regime. We evaluate the critical levels of preparedness that stop the disease from spreading at the importing locality. Finally, we show how the benefit of preparedness diminishes under high mobility rates. Our results highlight the importance of preparedness at localities where cases are beginning to rise such that localities can help stop local outbreaks when they respond to the severity of outbreaks in neighboring localities.


title: Reconstructed diagnostic sensitivity and specificity of the RT-PCR test for COVID-19

abstract: Real-time reverse transcription polymerase chain reaction (RT-PCR) targeting select genes of the SARS-CoV-2 RNA has been the main diagnostic tool in the global response to the COVID-19 pandemic. This study was aimed at the estimation of diagnostic sensitivity and specificity of the first RT-PCR test developed by China CDC in January 2020. The study design is a secondary analysis of published findings on 1014 patients in Wuhan, China, of whom 59.3% tested positive for COVID-19 in RT-PCR tests and 87.6% tested positive in chest CT exams. We utilized previously ignored expert opinions in the form of verbal probability classifications of patients with conflicting test results to estimate the informative prior distribution of the infected proportion. It was then used in a Bayesian version of a previously developed model to reconstruct the sensitivity and specificity of the diagnostic tests without the need for specifying an inaccurate test as the gold standard. The sensitivity of the RT-PCR diagnostic test was estimated to be 0.707 (95% CI: 0.668, 0.749), while the specificity was 0.851 (95% CI: 0.774, 0.941). Caution is advised in generalizing these findings to other versions of the RT-PCR test that are being used in diverse geographic regions.


title: Predicting the COVID-19 epidemic in Algeria using the SIR model

abstract: The aim of this study is to predict the daily infected cases with Coronavirus (COVID-19) in Algeria. We apply the SIR model on data from 25 February 2020 to 24 April 2020 for the prediction. Following Huang et al (12), we develop two SIR models, an optimal model and a model in a worst-case scenario COVID-19. We estimate the parameters of our models by minimizing the negative log likelihood function using the Nelder-Mead method. Based on the simulation of the two models, the epidemic peak of COVID-19 is predicted to attain 24 July 2020 in a worst-case scenario, and the COVID-19 disease is expected to disappear in the period between September 2020 and November 2020 at the latest. We suggest that Algerian authorities need to implement a strict containment strategy over a long period to successfully decrease the epidemic size, as soon as possible.


title: Mathematical Modeling of Listeriosis Incorporating Effects of Awareness Programs

abstract: Awareness programs by the media play a pivotal role in the control of infectious diseases. In this paper, we formulate and analyse a mathematical model for listeriosis incorporating aware individuals. Mathematical analyses of the model are done and equilibrium points determined. The model has three equilibria; namely; the disease-free, the bacteria-free, and the endemic equilibria. Local asymptotic stability of the equilibria is established based on the food contamination number [R]f. Numerical simulations are carried out and the effects of various parameters on the model state variables investigated. The results from numerical simulations reveal that an increase in the efficacy of awareness programs, the rate of implementation of awareness programs, and the rate at which unaware susceptible become aware result in the reduction of listeriosis in the human population. The results have important implications in the control and management of listeriosis.


title: Knowledge, attitudes, and practices (KAP) towards COVID-19: A quick online cross-sectional survey among Tanzanian residents.

abstract:
BackgroundThe Corona Virus Disease -19 (COVID-19) pandemic is a global health emergency that requires the adoption of unprecedented measures to control its rapid spread. Tanzanians adherence to control measures is affected by their knowledge, attitudes, and practices (KAP) towards the disease. This study was carried out to investigate knowledge, attitudes and practices towards COVID-19 among residents in Tanzania during the April - May 2020 period of the epidemic.

MethodsThis cross-sectional study analyzes responses of self-selected Tanzanians who responded to an invitation to complete an online questionnaire. Survey Monkey tool was used to develop the questionnaire used for data collection. The survey assessed demographic characteristics of participants as well as their knowledge, attitudes, and practices toward COVID-19. A Chi-square analysis was used to compare proportions. Analysis of variance (ANOVA) was used to determine differences among age groups, whereas results were considered significant if the p-value was <0.05

ResultsFour hundred residents completed the survey. The mean age of study participants was 32 years, and the majority was female (n= 216,54.0%). There were no significant differences in demographic variables). Participants with a bachelors degree or above (n= 241, 60.3%) had higher scores. Overall, 84.4% (n=338) of participants had good knowledge, which was significantly associated with education level (p=0.001). Nearly all participants (n=384, 96.0%) had confidence that COVID-19 will be eliminated. The majority of respondents (n=308, 77.0%) did not go to a crowded place in recent days. Multiple linear regression analysis showed that males, age-group 16-29 years, and education of secondary or lower (OR = 1.2, CI = 1.3-1.5) were significantly associated with lower knowledge score.

ConclusionsOur findings revealed good knowledge, optimistic attitudes, and appropriate practices towards preventing COVID-19 infection. Suggesting that community-based health education programs about COVID-19 is helpful and necessary to control the disease.


title: Indications that Chymotrypsin-like Elastase 1 is Involved in Emphysema

abstract:
Emphysema is a major contributor to the morbidity and mortality of chronic obstructive pulmonary disease (COPD), and there are no disease modifying therapies. Three leading pathophysiologic models are the altered protease/antiprotease balance model, the biomechanical model in which loss of one alveolar wall increases strain on adjacent wall predisposing them to failure, and the accelerated aging model. Chymotrypsin-like elastase 1 (CELA1) is a novel serine protease with a physiological role in reducing postnatal lung elastance that mechanistically links these three models. CELA1 is expressed by alveolar type 2 (AT2) cells and is found adjacent to lung elastin fibers. The KF4 antibody neutralizes CELA1 by binding to its catalytic triad. CELA1 binding to lung elastin fibers increases 4-fold with strain, and application of biaxial strain induces lung elastase activity which is blocked with the KF4 anti-CELA1 antibody. Cela1-/- mice were protected from airspace simplification in hyperoxia, elastase and cigarette-smoke induced emphysema, and age-related airspace simplification. CELA1 mRNA was correlated with human lung elastolytic activity, and anti-CELA1 KF4 antibody protected mice from hyperoxia-induced alveolar simplification and elastase emphysema. CELA1-mediated lung matrix remodeling in response to strain is an important contributor to postnatal airspace simplification. Matrix stabilization by KF4 represents a potential therapeutic approach to preventing emphysema progression.

One Sentence SummaryNeutralization of chymotrypsin-like elastase 1 prevents strain-induced emphysema.


title: Anti-CELA1 KF4 Antibody Prevents Emphysema by Inhibiting Stretch-Mediated Remodeling


title: Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold

abstract:
Individual variation in susceptibility and exposure is subject to selection by natural infection, accelerating the acquisition of immunity, and reducing herd immunity thresholds and epidemic final sizes. This is a manifestation of a wider population phenomenon known as "frailty variation". Despite theoretical understanding, public health policies continue to be guided by mathematical models that leave out considerable variation and as a result inflate projected disease burdens and overestimate the impact of interventions. Here we focus on trajectories of the coronavirus disease (COVID-19) pandemic in England and Scotland until November 2021. We fit models to series of daily deaths and infer relevant epidemiological parameters, including coefficients of variation and effects of non-pharmaceutical interventions which we find in agreement with independent empirical estimates based on contact surveys. Our estimates are robust to whether the analysed data series encompass one or two pandemic waves and enable projections compatible with subsequent dynamics. We conclude that vaccination programmes may have contributed modestly to the acquisition of herd immunity in populations with high levels of pre-existing naturally acquired immunity, while being critical to protect vulnerable individuals from severe outcomes as the virus becomes endemic.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/20081893v5_ufig1.gif" ALT="Figure 1">
View larger version (19K):
org.highwire.dtl.DTLVardef@aeb87forg.highwire.dtl.DTLVardef@d2c441org.highwire.dtl.DTLVardef@152aeceorg.highwire.dtl.DTLVardef@1526779_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsO_LIVariation in susceptibility/exposure responds to selection by natural infection
C_LIO_LISelection on susceptibility/exposure flattens epidemic curves
C_LIO_LIModels with incomplete heterogeneity overestimate intervention impacts
C_LIO_LIIndividual variation lowered the natural herd immunity threshold for SARS-CoV-2
C_LI


title: Predicted impact of the COVID-19 pandemic on global tuberculosis deaths in 2020

abstract: Policies widely adopted in response to the ongoing pandemic of Covid-19, particularly lockdowns and reassignments of health personnel and equipment, are impacting the performance of TB prevention and care programmes. Estimates of the impact of reductions in the performance of global TB detection and care on TB mortality over 2020 are presented. A global TB case detection decrease by an average 25% over a period of 3 months (as compared to the level of detection before the pandemic), will lead to a predicted additional 190 000 (56 000 - 406 000) TB deaths.


title: Cohort Profile: A national prospective cohort study of SARS-CoV-2 pandemic outcomes in the U.S. - The CHASING COVID Cohort Study

abstract:
PurposeThe CHASING COVID Cohort study is a U.S.-based prospective cohort study launched during the upswing of the U.S. COVID-19 epidemic. The objectives are to: 1) estimate and evaluate determinants of the cumulative incidence of SARS-CoV-2 infection, disease, and deaths; 2) assess the impact of the pandemic on psychosocial and economic outcomes; and 3) assess the uptake of pandemic mitigation strategies.

ParticipantsWe began enrolling participants March 28, 2020 using internet-based strategies. Adults [≥]18 years residing anywhere in the U.S. or U.S. territories were eligible. 6,753 people are enrolled in the cohort, including participants from all 50 U.S. states, the District of Columbia, Puerto Rico, and Guam. Participants are contacted regularly to complete study assessments, including interviews and specimen collection.

Findings to dateOf 4,247 participants who provided a specimen for baseline serologic testing, 135 were seropositive by screening antibody testing (3.2%, 95% CI 2.7%-3.5%) and 90 were seropositive by confirmatory antibody testing (2.1%, 95% CI 1.7%-2.6%). Cohort data have been used to assess the role of household crowding and the presence of children in the household as potential risk factors for severe COVID-19 early in the U.S. pandemic; to describe the prevalence of anxiety symptoms and its relationship to COVID-19 outcomes and other potential stressors; and to identify preferences for SARS-CoV-2 diagnostic testing when community transmission is on the rise via a discrete choice experiment.

Future plansThe CHASING COVID Cohort Study has outlined a research agenda that involves ongoing monitoring of the cumulative incidence and determinants of SARS-CoV-2 outcomes, mental health outcomes and economic outcomes. Additional priorities include COVID-19 vaccine hesitancy, uptake and effectiveness; incidence, prevalence and correlates of long-haul COVID-19; and the extent and duration of the protective effect of SARS-CoV-2 antibodies.


title: ai-corona: Radiologist-Assistant Deep Learning Framework for COVID-19 Diagnosis in Chest CT Scans

abstract: Generation of medical assisting tools using recent artificial intelligence advances is beneficial for the medical workers in the global fight against COVID-19 outbreak. In this article we introduce ai-corona, a radiologist-assistant deep learning framework for COVID-19 infection diagnosis using the chest CT scans. Our framework incorporates an Efficient NetB3-based feature extractor. We employed three independent dataset in this work named: CC-CCII, MDH, and MosMedData; all includes 7184 scans from 5693 subjects which contained pneumonia, common pneumonia (CP), non-pneumonia, normal and COVID-19 classes. We evaluated ai-corona on test sets from the CC-CCII set and MDH cohort and the entirety of the MosMedData cohort, for which it gained AUC score of 0.997, 0.989, and 0.954, respectively. We further compared our frameworks performance with other deep learning models developed on our employed data sets, as well as RT-PCR. Our results show that ai-corona outperforms all. Lastly, our frameworks diagnosis capabilities was evaluated as assistant to several experts. We demonstrated an increase in both speed and accuracy of expert diagnosis when incorporating ai-coronas assistance.


title: Pandemic Lock-down, Isolation, and Exit Policies Based on Machine Learning Predictions

abstract:
The widespread lockdowns imposed in many countries at the beginning of the COVID-19 pandemic elevated the importance of research on pandemic management when medical solutions such as vaccines are unavailable. We present a framework that combines a standard epidemiological SEIR (susceptible-exposed-infected-removed) model with an equally standard machine learning classification model for clinical severity risk, defined as an individuals risk needing intensive care unit (ICU) treatment if infected. Using COVID-19-related data and estimates for France as of spring 2020, we then simulate isolation and exit policies. Our simulations show that policies considering clinical risk predictions could relax isolation restrictions for millions of the lowest-risk population months earlier while consistently abiding by ICU capacity restrictions. Exit policies without risk predictions, meanwhile, would considerably exceed ICU capacity or require the isolation of a substantial portion of population for over a year in order to not overwhelm the medical system. Sensitivity analyses further decompose the impact of various elements of our models on the observed effects.

Our work indicates that predictive modelling based on machine learning and artificial intelligence could bring significant value to managing pandemics. Such a strategy, however, requires governments to develop policies and invest in infrastructure to operationalize personalized isolation and exit policies based on risk predictions at scale. This includes health data policies to train predictive models and apply them to all residents, as well as policies for targeted resource allocation to maintain strict isolation for high-risk individuals.


title: Beyond Deaths per Capita: Comparative CoViD-19 Mortality Indicators

abstract: The number of CoViD-19 deaths more reliably tracks the progression of the disease across populations than the number of confirmed cases, but substantial age and sex differences in CoViD-19 mortality imply that the number of deaths should be adjusted for the age-and-sex composition of the population as well as its total size. Following well-established practices in demography, this article discusses several measures based on the cumulative number of CoViD-19 deaths and illustrate them with data from 362 national and subnational populations. The first measure is an unstandardized occurrence/exposure rate comparable to the Crude Death Rate. To date, we measured the highest value in New York, exceeding at its peak the states most recent annual Crude Death Rate. The second measure is an indirectly standardized rate which we show to perform quite like a directly standardized rate but without requiring a breakdown of CoViD-19 deaths by age and sex. Either way, standardization substantially modifies comparisons across populations: New Jersey has the highest unstandardized rate to date, but four states in Mexico and one in Brazil have higher standardized rates. Finally, extant life tables allow to estimate reductions in 2020 life expectancies, which are projected to exceed two years for New York, New Jersey and Peru, and possibly three years in Ecuador. To put these in perspective, with a 1.1-year projected reduction, the US life expectancy at birth should have in 2020 its largest annual decline since World War II and reach its lowest level since 2006.


title: Lack of Evidence for a Reduced Late Positive Potential in Major Depressive Disorder

abstract:
BackgroundIndividuals with major depressive disorder (MDD) present with deficits in emotional reactivity. Conflicting models have been proposed to explain this effect. We sought to test the emotional context insensitivity hypothesis, which suggests that reactivity to positive and negatively-valenced emotional stimuli is blunted in depression, in a preregistered study.

MethodsForty-one depressed participants and 41 age- and gender-matched healthy controls were presented a series of unpleasant and neutrally-valenced pictures in a passive view paradigm while acquiring electroencephalography (EEG). The late positive potential (LPP), an EEG correlate of emotional reactivity, was compared between groups using mixed-effects repeated-measures models and exploratory cluster-based permutation tests. A sensitivity analysis was performed to assess the robustness of LPP findings by reanalysing the LPPs using 22 EEG pipelines from studies identified in the literature.

ResultsWe found no difference in LPP amplitudes between MDD and healthy individuals using the preregistered analysis pipeline. The sensitivity analysis revealed that the magnitude and direction of LPP effect sizes were affected by the analysis pipeline. Exploratory permutation analyses revealed an electrode cluster that showed a significant reduction in the LPP for MDD participants while viewing unpleasant pictures.

ConclusionsThese results do not provide evidence in support of the emotional context insensitivity hypothesis, except for the exploratory data-driven approach. Methodological differences, in particular in the analysis pipeline, contribute to the heterogeneity of LPP modulation in depression. A standardised approach to quantify EEG correlates of emotional reactivity is needed to evaluate alternative models of emotional reactivity in depression.


title: Using viral load and epidemic dynamics to optimize pooled testing in resource constrained settings

abstract: Extensive virological testing is central to SARS-CoV-2 containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combine a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence, and to ratify losses in sensitivity against the time course of individual infections. Using this framework, we show that prevalence can be accurately estimated across four orders of magnitude using only a few dozen pooled tests without the need for individual identification. We then exhaustively evaluate the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many positives compared to individual testing with a given budget. We illustrate how pooling affects sensitivity and overall detection capacity during an epidemic and on each day post infection, finding that sensitivity loss is mainly attributed to individuals sampled at the end of infection when detection for public health containment has minimal benefit. Crucially, we confirm that our theoretical results can be accurately translated into practice using pooled human nasopharyngeal specimens. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect epidemiologically relevant infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings.


title: Spatial Inequities in COVID-19 Testing, Positivity, Confirmed Cases and Mortality in 3 US Cities: an Ecological Study

abstract:
BackgroundPreliminary evidence has shown inequities in COVID-19 related cases and deaths in the US.

ObjectiveWe explored the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York City, Philadelphia, and Chicago during the first six months of the pandemic.

DesignEcological, observational study at the zip code tabulation area (ZCTA) level from March to September 2020.

SettingChicago, New York City and Philadelphia.

ParticipantsAll populated ZCTAs in the three cities.

MeasuresOutcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September. Predictors were the CDC social vulnerability index and its four domains, obtained from the 2014-2018 American Community Survey. We examined the spatial autocorrelation of COVID-19 outcomes using global and local Morans I and estimated associations using spatial conditional autoregressive negative binomial models.

ResultsWe found spatial clusters of high and low positivity, confirmed cases and mortality, co-located with clusters of low and high social vulnerability. We also found evidence for the existence of spatial inequities in testing, positivity, confirmed cases and mortality for the three cities. Specifically, neighborhoods with higher social vulnerability had lower testing rates, higher positivity ratios, confirmed case rates and mortality rates.

LimitationsZCTAs are imperfect and heterogeneous geographical units of analysis. We rely on surveillance data, which may be incomplete.

ConclusionWe found spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in three large cities of the US.

RegistrationN/A

Funding sourceNIH (DP5OD26429) and RWJF (77644)


title: Evaluating growth pattern and assessing future scenario of COVID-19 epidemic of India

abstract: COVID-19 the modern pandemic has spread across the world at a rapid pace. SARS-CoV 2 is highly transmissible and the rate of infection is exponential for heavily infected countries. Asymptotic carriers and longer incubation period have been key towards such a large-scale distribution of disease. Data released by official authorities on COVID-19 cases is significantly affected by various factors such as size of sample, incubation period of disease and time taken to test the sample. These factors mask the useful pattern (signal) of disease spread. Thus, an ingenious method to group data into cycles of five and seven days, for studying pattern of disease spread is undertaken. Occurrence of recurrent peaks as indicated by Adjusted Rate of infection per day indicated the spread of disease has been non-uniform. Currently, India is yet to reach the critical point (peak of epidemic) with adjusted daily cases more than 1000. Increasing testing capacity along with random sampling and sample pooling can help in preventing formation of these peaks in future. The proposed method helps in assessing the current state and for predicting future scenarios epidemics.


title: Real-time tracking and forecasting of the COVID-19 outbreak in Kuwait: a mathematical modeling study

abstract:
BackgroundMany countries have succeeded in curbing the outbreak of COVID-19 by employing strict public health control measures. However, little is known about the effectiveness of such control measures in curbing the outbreak in developing countries. In this study, we seek to assess the impact of various outbreak control measures in Kuwait to gain more insight into the outbreak progression and the associated healthcare burden.

MethodsWe use a SEIR mathematical model to simulate the epidemic outbreak of COVID-19 in Kuwait with additional testing and hospitalization compartments. We use a NBD observational framework for confirmed case and death counts. We forecast model trajectories and assess the effectiveness of public health interventions by using maximum likelihood to estimate both the basic and effective reproduction numbers.

ResultsOur results indicate that the early strict control measures had the effect of delaying the intensity of the outbreak but were unsuccessful in reducing the effective reproduction number below 1. Forecasted model trajectories suggest a need to expand the healthcare system capacity to cope with the associated epidemic burden of such ineffectiveness.

ConclusionStrict public health interventions may not always lead to the same desired outcomes, particularly when population and demographic factors are not accounted for as in the case in some developing countries. Real-time dynamic modeling can provide an early assessment of the impact of such control measures as well as a forecasting tool to support outbreak surveillance and the associated healthcare expansion planning.

SUMMARY BOXO_ST_ABSWhat is already known on the subject?C_ST_ABSEvidence is accumulating about the positive impact of various strict public health interventions on the transmission of COVID-19 in the developed world. Currently, however, many developing countries are still struggling to control and suppress the initial wave of the outbreak. In particular, less attention is given to assessing the impact of taking similar strict control measures.

What does this study add?Our modeling study provides the first evidence showing how the imposition of strict public health measures has not led to a reduction in COVID-19 transmission in Kuwait. It highlights the importance of performing systematic epidemiological and public health investigations of the population factors which may limit the effectiveness of standard public health interventions in developing countries. It also emphasizes the utility of adopting dynamic modeling approaches for intervention assessment and healthcare capacity re-adjustment at the earliest stages of the outbreak.

category: public and global health


title: Risk Stratification tool for Healthcare workers during the CoViD-19 Pandemic; using published data on demographics, co-morbid disease and clinical domain in order to assign biological risk

abstract:
ObjectivesHealthcare workers have a greater exposure to individuals with confirmed SARS-novel coronavirus 2, and an estimated 5-fold higher probability of contracting coronavirus disease (COVID)-19, than the general population. Many organisations have called for risk assessments to be put in place to minimise this risk. We wished to explore the predictive role of basic demographics in order to establish a simple tool that could help risk stratify healthcare workers.

SettingWe undertook a review of the published literature (including multiple search strategies in MEDLINE with PubMed interface) and critically assessed early reports on medRxiv, a pre-print server (https://www.medrxiv.org: date of last search: December 21, 2020). We explored the relative risk of mortality from readily available demographics in order to identify the population at highest risk.

ResultsThe only published studies specifically assessing the risk of healthcare workers had limited demographics available, therefore we explored the general population in the literature.

Clinician DemographicsMortality increased with increasing age from 50 years onwards. Male sex at birth, people of black and minority ethnicity groups had higher susceptibility to both hospitalisation and mortality. Co-morbid Disease. Vascular disease, renal disease, diabetes and chronic pulmonary disease further increased risk.

Risk stratification toolA risk stratification tool was compiled using a Caucasian female <50years with no comorbidities as a reference. A point allocated to risk factors associated with an approximate doubling in risk. This tool provides numerical support for healthcare workers when determining which team members should be allocated to patient facing clinical duties compared to remote supportive roles.

ConclusionsWe have generated a tool which can provide a framework for objective risk stratification of doctors and health care professionals during the COVID-19 pandemic, without requiring disclosure of information that an individual may not wish to share with their direct line manager during the risk assessment process.

Strengths and limitations of this studyO_LIThere is an increased risk of mortality in the clinical workforce due to the effects of COVID-19.
C_LIO_LIThis manuscript outlines a simple risk stratification tool that helps to quantify an individuals biological risk
C_LIO_LIThis will assist team leaders when allocating roles within clinical departments.
C_LIO_LIThis tool does not incorporate other external factors, such as high-risk household members or those at higher risk of mental health issues, that may require additional consideration when allocating clinical duties in an appropriate clinical domain.
C_LIO_LIThis population-based analysis did not explain for the very high risk observed in BAME healthcare workers suggesting there are other issues at play that require addressing.
C_LI

category: health policy


title: Study of Hepatitis C Virus infection among multi-transfused patients with inherited β-globin synthesis gene defect, in the eastern region of India.

abstract:
BackgroundPost transfusion acquired HCV infection is common in high-risk group individuals such as multi-transfused {beta}-thalassemia patients who depend on regular blood transfusions. This study was conducted to determine epidemiology and distribution of HCV in multi-transfused {beta}-thalassemia patients, in West Bengal, India.

MethodsOver a span of six years blood samples were collected from HCV sero-reactive {beta}-thalassemic patients and processed for viral RNA isolation followed by nested RT-PCR for qualitative viremia detection. HCV genotype was determined by amplifying partial HCV core gene by nested RT-PCR, DNA sequencing and using NCBI genotyping tools. Phylogenetic and phylogeographic studies were performed with online MEGA-X and BEAST 1.10.0 software respectively.

ResultsOut of 917 multi-transfused HCV sero-reactive {beta}-thalassemic patients, 598 (65.21%) were positive for HCV RNA while 250 (41.80%) had spontaneously cleared the virus. Female thalassemic patients and individuals belonging to ages 10-14 years had higher chances of spontaneous clearance. The most prevalent circulatory HCV genotype was 3a (78.11%) followed by 1b (12.20%). Phylogeographic analyses revealed that the 3a strains share similarity with Pakistan, Sri Lanka and Thailand whereas the 1b strains share similarity with Thailand, Vietnam, Russia and China.

ConclusionThe prevalence of HCV infection is very high among Indian {beta}-thalassemic patients, necessitates a critical look into the prevailing transfusion practices and requires implementation of more rigid donor screening criteria to decrease the rate of transfusion transmitted HCV infection, especially in multi-transfused thalassemic patients. The use of more sensitive NAT based assays for HCV detection in donor blood is a compressing need of the hour.


title: Parental criticism and adolescent internalising symptoms: Using a Children-of-Twins design with power calculations to account for genetic influence

abstract:
BackgroundParental criticism is correlated with internalising symptoms in adolescent offspring. This correlation could in part reflect their genetic relatedness, if the same genes influence behaviours in both parents and offspring. We use a Children-of-Twins design to assess whether parent-reported criticism and offspring internalising symptoms remain associated after controlling for shared genes. To aid interpretation of our results and those of previous Children-of-Twins studies, we examine statistical power for the detection of genetic effects and explore the direction of possible causal effects between generations.

MethodsData were drawn from two Swedish twin samples, comprising 876 adult twin pairs with adolescent offspring and 1030 adolescent twin pairs with parents. Parent reports of criticism towards their offspring were collected concurrently with parent and offspring reports of adolescent internalising symptoms. Children-of-Twins structural equation models were used to control for genetic influence on the intergenerational association between parental criticism and adolescent internalising.

ResultsParental criticism was associated with adolescent internalising symptoms after controlling for genetic influence. No significant role was found for shared genes influencing phenotypes in both generations, although power analyses suggested that some genetic effects may have gone undetected. Models could not distinguish directionality for non-genetic, causal effects between generations.

ConclusionsParental criticism may be involved in psychosocial family processes in the context of adolescent internalising. Future studies should seek to identify these processes and provide clarity on the direction of potential causal effects.


title: Multi-omics study revealing putative drug targets of COVID-19 severity and other viral infection diseases

abstract:
Recent omic studies prioritised several drug targets associated with coronavirus disease 2019 (COVID-19) severity. However, little evidence was provided to systematically estimate the effect of drug targets on COVID-19 severity in multiple ancestries. In this study, we applied Mendelian randomization (MR) and colocalization approaches to understand the putative causal effects of 16,059 transcripts and 1,608 proteins on COVID-19 severity in European and effects of 610 proteins on COVID-19 severity in African ancestry. We further integrated genetics, clinical and literature evidence to prioritised additional drug targets. Additional sensitivity analyses including multi-trait colocalization and phenome-wide MR were conducted to test for MR assumptions.

MR and colocalization prioritized four protein targets, FCRL3, ICAM5, ENTPD5 and OAS1 that showed effect on COVID-19 severity only in European ancestry and one protein target, SERPINA1, only showed effect in African ancestry (odds ratio [OR] in Africans=0.369, 95%CI=0.203 to 0.668, P=9.96x10-4; OR in Europeans=1.021, P=0.745). One protein, ICAM1, showed suggestive effect on COVID-19 severity in both ancestries (OR in Europeans=1.152, 95%CI=1.063 to 1.249, P=5.94x10-4; OR in Africans=1.481, 95%CI=1.008 to 2.176; P=0.045). The phenome-wide MR of the prioritised targets on 622 complex traits identified 726 potential causal effects on other diseases, providing information on potential beneficial and adverse effects. Our study prioritised six proteins as potential drug targets for COVID-19 severity. Several of them were targets of existing drug under trials of COVID-19 or related to the immune system. Most of these targets showed different effects in European and African ancestries, which highlights the value of multi-ancestry MR in informing the generalizability of COVID-19 drug targets across ancestries. This study provides a first step towards clinical investigation on COVID-19 and other types of coronaviruses.

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched key terms in PUBMED published before Feb 1st 2022, with the terms: ("COVID-19, "coronavirus") AND ("omics" or "protein" or "transcript") AND ("Genome-wide association study" or "Mendelian randomization"). We found multiple studies identified targeted genes or proteins associated with COVID-19. However, there is little human genetics evidence support the ancestry-consistent or ancestry-specific genes/proteins associated with COVID-19.

Added value of this studyTo our knowledge, this is the first comprehensive genetic study that identified protein targets that showed effect on COVID-19 severity in European and African ancestries. Our study identified one protein, SERPINA1, that showed effects on COVID-19 in African ancestry (OR=0.369, P=9.96x10-4), but not in European ancestry (OR=1.021, P=0.745). In addition, our study identified four additional protein targets, FCRL3, ICAM5, ENTPD5 and OAS1, that showed effect on COVID-19 severity in Europeans. One protein ICAM1 showed suggestive effect in both ancestries. Some of these proteins are related to the immune system and/or are targets of existing drug under trials of COVID-19.

Implications of all available evidenceOur study prioritised six drug targets for COVID-19 severity, five of them showed different effects in European and African ancestries. This suggested that drug targets may have different responses on COVID-19 severity in different ancestries. Our study also highlights the value of intercellular adhesion molecule (ICAM) family in relation with COVID-19 severity in both ancestries.


title: Multi-ancestry omic Mendelian randomization revealing putative drug targets of COVID-19 severity


title: Replicating extensive brain structural heterogeneity in individuals with schizophrenia and bipolar disorder

abstract: Identifying brain processes involved in the risk and development of mental disorders is a major aim. We recently reported substantial inter-individual heterogeneity in brain structural aberrations among patients with schizophrenia and bipolar disorder. Estimating the normative range of voxel-based morphometry (VBM) data among healthy individuals using a gaussian process regression (GPR) enables us to map individual deviations from the healthy range in unseen datasets. Here we aim to replicate our previous results in two independent samples of patients with schizophrenia (n1=94; n2=105), bipolar disorder (n1=116; n2=61) and healthy individuals (n1=400; n2=312). In line with previous findings with exception of the cerebellum our results revealed robust group level differences between patients and healthy individuals, yet only a small proportion of patients with schizophrenia or bipolar disorder exhibited extreme negative deviations from normality in the same brain regions. These direct replications support that group level-differences in brain structure disguise considerable individual differences in brain aberrations, with important implications for the interpretation and generalization of group-level brain imaging findings to the individual with a mental disorder.


title: Modelling safe protocols for reopening schools during the COVID-19 pandemic in France

abstract: As countries in Europe implement strategies to control COVID-19 pandemic, different options are chosen regarding schools. Through a stochastic age-structured transmission model calibrated to the observed epidemic in Ile-de-France in the first wave, we explored scenarios of partial, progressive, or full school reopening. Given the uncertainty on childrens role, we found that reopening schools after lockdown may increase COVID-19 cases, yet protocols exist that maintain the epidemic controlled. Under a scenario with stable epidemic activity if schools were closed, reopening pre-schools and primary schools would lead up to 76% [67, 84]% occupation of ICU beds if no other school level reopened, or if middle and high schools reopened later. Immediately reopening all school levels may overwhelm the ICU system. Priority should be given to pre- and primary schools allowing younger children to resume learning and development, whereas full attendance in middle and high schools is not recommended for stable or increasing epidemic activity. Large-scale test and trace are required to maintain the epidemic under control. Ex-post assessment shows that progressive reopening of schools, limited attendance, and strong adoption of preventive measures contributed to a decreasing epidemic after lifting the first lockdown.


title: Genetic drift and regional spreading dynamics of COVID-19

abstract:
BackgroundCurrent propagation models of COVID-19 are poorly consistent with existing epidemiological data and with evidence that the SARS-CoV-2 genome is mutating, for potential aggressive evolution of the disease.

MethodsWe challenged regional versus genetic evolution models of COVID-19 at a whole-population level, over 168,089 laboratory-confirmed SARS-CoV-2 infection cases in Italy, Spain and Scandinavia. Diffusion data in Germany, France and UK provided a validation dataset of 210,239 additional cases.

ResultsThe mean doubling time of COVID-19 cases was 6.63 days in Northern versus 5.38 days in Southern Italy. Spain extended this trend of faster diffusion in Southern Europe, with a doubling time of 4.2 days. Slower doubling times were observed in Sweden (9.4 days), Finland (10.8 days), Norway (12.95 days). COVID-19 doubling time in Germany (7.0 days), France (7.5 days) and UK (7.2 days) supported the North/South gradient model. Clusters of SARS-CoV-2 mutations upon sequential diffusion across distinct geographic areas were not found to clearly correlate with regional distribution dynamics.

ConclusionsAcquisition of mutations, upon SARS-CoV-2 spreading across distinct geographic areas, did not distinctly associate to enhanced virus aggressiveness, and failed to explain regional diffusion heterogeneity at early phases of the pandemic. Our findings indicate that COVID-19 transmission rates associate to a sharp North/South climate gradient, with faster spreading in Southern regions. Thus, warmer climate conditions may not limit SARS-CoV-2 infectivity. Very cold regions may be better spared by recurrent courses of SARS-CoV-2 infection.


title: Easing COVID-19 lockdown measures while protecting the older restricts the deaths to the level of the full lockdown

abstract: Guided by a rigorous mathematical result, we have earlier introduced a numerical algorithm, which using as input the cumulative number of deaths caused by COVID-19, can estimate the effect of easing of the lockdown conditions. Applying this algorithm to data from Greece, we extend it to the case of two subpopulations, namely, those consisting of individuals below and above 40 years of age. After supplementing the Greek data for deaths with the data for the number of individuals reported to be infected by SARS-CoV-2, we estimated the effect on deaths and infections in the case that the easing of the lockdown measures is different for these two subpopulations. We found that if the lockdown measures are partially eased only for the young subpopulation, then the effect on deaths and infections is small. However, if the easing is substantial for the older population, this effect may be catastrophic.


title: COVID-19 transmission risk factors

abstract: We analyze risk factors correlated with the initial transmission growth rate of the recent COVID-19 pandemic in different countries. The number of cases follows in its early stages an almost exponential expansion; we chose as a starting point in each country the first day di with 30 cases and we fitted for 12 days, capturing thus the early exponential growth. We looked then for linear correlations of the exponents  with other variables, for a sample of 126 countries. We find a positive correlation, i.e. faster spread of COVID-19, with high confidence level with the following variables, with respective p-value: low Temperature (4 {middle dot} 10-7), high ratio of old vs. working-age people (3 {middle dot} 10-6), life expectancy (8 {middle dot} 10-6), number of international tourists (1{middle dot} 10-5), earlier epidemic starting date di (2{middle dot} 10-5), high level of physical contact in greeting habits (6 {middle dot} 10-5), lung cancer prevalence (6 {middle dot} 10-5), obesity in males (1{middle dot} 10-4), share of population in urban areas (2{middle dot} 10-4), cancer prevalence (3{middle dot} 10-4), alcohol consumption (0.0019), daily smoking prevalence (0.0036), UV index (0.004, 73 countries). We also find a correlation with low Vitamin D serum levels (0.002-- 0.006), but on a smaller sample, 50 countries, to be confirmed on a larger sample. There is highly significant correlation also with blood types: positive correlation with types RH-(3{middle dot} 10-5) and A+ (3 {middle dot}10-3), negative correlation with B+ (2 {middle dot}10-4). We also find positive correlation with moderate confidence level (p-value of 0.02[~] 0.03) with: CO2/SO emissions, type-1 diabetes in children, low vaccination coverage for Tuberculosis (BCG). Several of the above variables are correlated with each other and so they are likely to have common interpretations. We thus performed a Principal Component Analysis, in order to find the significant independent linear combinations of such variables. We also analyzed the possible existence of a bias: countries with low GDP-per capita might have less intense testing and we discuss correlation with the above variables.


title: Total predicted MHC-I epitope load is inversely associated with mortality from SARS-CoV-2

abstract: AO_SCPLOWBSTRACTC_SCPLOWPolymorphisms in MHC-I protein sequences across human populations significantly impacts viral peptide binding capacity and thus alters T cell immunity to infection. Consequently, allelic variants of the MHC-I protein have been found to be associated with patient outcome to various viral infections, including SARS-CoV. In the present study, we assess the relationship between observed SARS-CoV-2 population mortality and the predicted viral binding capacities of 52 common MHC-I alleles. Potential SARS-CoV-2 MHC-I peptides were identified using a consensus MHC-I binding and presentation prediction algorithm, called EnsembleMHC. Starting with nearly 3.5 million candidates, we resolved a few hundred highly probable MHC-I peptides. By weighing individual MHC allele-specific SARS-CoV-2 binding capacity with population frequency in 23 countries, we discover a strong inverse correlation between the predicted population SARS-CoV-2 peptide binding capacity and observed mortality rate. Our computations reveal that peptides derived from the structural proteins of the virus produces a stronger association with observed mortality rate, highlighting the importance of S, N, M, E proteins in driving productive immune responses. The correlation between epitope binding capacity and population mortality risk remains robust across a range of socioeconomic and epidemiological factors. A combination of binding capacity, number of deaths due to COPD complications, gender demographics. and the proportions of the population that were over the age of 65 and overweight offered the strongest determinant of at-risk populations. These results bring to light how molecular changes in the MHC-I proteins may affect population-level outcomes of viral infection.

category: allergy and immunology


title: Depression and anxiety during 2019 coronavirus disease pandemic in Saudi Arabia: a cross-sectional study

abstract:
AimsThe emergence of the COVID-19 global pandemic, with a high transmission and mortality rate, has created an extraordinary crisis worldwide. Such an unusual situation may have an undesirable impact on the mental health of individuals which, in turn, may influence their outcomes. This study aimed to explore the influence of the COVID-19 pandemic on the psychological disposition of residents of the Kingdom of Saudi Arabia.

MethodsA cross-sectional study using an online survey was conducted in Saudi Arabia between 27 March and 27 April 2020. The Patient Health Questionnaire (PHQ-9) and Generalised Anxiety Disorder-7 (GAD-7) were used to assess depression and anxiety. Logistic regression analysis was used to identify predictors of these.

ResultsA total of 2,081 individuals participated in the study. The prevalence of depression and anxiety among the study participants was 9.4% and 7.3%, respectively. Non-Saudi residents, individuals aged 50 years and above, divorced people, retired people, university students, and those with an income between 2,000 and 10,000 SR were at higher risk of developing depression. Saudi individuals, married people, the unemployed, and those with a high income (> 10,000 RS) were at higher risk of developing anxiety.

ConclusionWe found that there is a wide range of Saudi residents who are at higher risk of developing mental illness during the current COVID-19 pandemic. Policymakers and mental healthcare providers are advised to provide continuous monitoring of the psychological consequences during this pandemic and provide the required health support.

What is already known about this subject?- The emergence of the COVID-19 global pandemic, with a high transmission and mortality rate, has created an extraordinary crisis worldwide.
- The COVID-19 pandemic might have an undesirable impact on the mental health of individuals.

What does this article add?- Depression and anxiety are common among the Saudi population.
- A considerable proportion of the Saudi population is concerned about contracting COVID-19 or transmitting it to family members.
- Unemployed individuals and university students are at higher risk of depression and anxiety.


title: Covasim: an agent-based model of COVID-19 dynamics and interventions

abstract: The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.


title: Factors linked to changes in mental health outcomes among Brazilians in quarantine due to COVID-19

abstract: This aim of this investigation was to track changes and risk factors for mental health outcomes during state-mandated quarantine in Brazil. Adults residing in Brazil (n = 360, 37.9 years old, 68.9% female) were surveyed at the start of quarantine and approximately three weeks later. Outcomes assessed included perceived stress, state anxiety and symptoms of depression. Aside from demographics, behaviours and attitudes assessed included exercise, diet, use of tele-psychotherapy and number of COVID-19 related risk factors, such as perceived risk of COVID-19, information overload, and feeling imprisoned. Overall, all mental health outcomes worsened from Time 1 to time 2, although there was a significant gender x time interaction for stress. 9.7% of the sample reported stress above the clinical cut-off (2 SD above mean), while 8.0% and 9.4% were above this cut-off for depression and anxiety, respectively. In repeated measures analysis, female gender, worsening diet and an excess of COVID-19 information was related to all mental health outcomes. Positive dietary changes were associated with decreases in depression and anxiety. Exercise frequency was positively related to state anxiety and perceived stress (0 days/week > 6 days/week). Those who did aerobic exercise did not have significantly increase in depression. Use of tele-psychotherapy predicted lower levels of depression and anxiety. In multiple regression, anxiety was predicted by the greatest number of COVID-19 specific factors. In conclusion, mental health outcomes worsened for Brazilians within the first month of quarantine and these changes are associated with a variety of risk factors.


title: Country-level Determinants of the Severity of the First Global Wave of the COVID-19 Pandemic: An Ecological Study

abstract:
ObjectiveWe aimed to identify the country-level determinants of the severity of the first wave of the COVID-19 pandemic.

DesignAn ecological study design of publicly available data was employed. Countries reporting >25 COVID-related deaths until 08/06/2020 were included. The outcome was log mean mortality rate from COVID-19, an estimate of the country-level daily increase in reported deaths during the ascending phase of the epidemic curve. Potential determinants assessed were most recently published demographic parameters (population and population density, percentage population living in urban areas, median age, average body mass index, smoking prevalence), Economic parameters (Gross Domestic Product per capita); environmental parameters: pollution levels, mean temperature (January-May)), co-morbidities (prevalence of diabetes, hypertension and cancer), health system parameters (WHO Health Index and hospital beds per 10,000 population); international arrivals, the stringency index, as a measure of country-level response to COVID-19, BCG vaccination coverage, UV radiation exposure and testing capacity. Multivariable linear regression was used to analyse the data.

Primary OutcomeCountry-level mean mortality rate: the mean slope of the COVID-19 mortality curve during its ascending phase.

ParticipantsThirty-seven countries were included: Algeria, Argentina, Austria, Belgium, Brazil, Canada, Chile, Colombia, the Dominican Republic, Ecuador, Egypt, Finland, France, Germany, Hungary, India, Indonesia, Ireland, Italy, Japan, Mexico, the Netherlands, Peru, the Philippines, Poland, Portugal, Romania, the Russian Federation, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, Ukraine, the United Kingdom and the United States.

ResultsOf all country-level predictors included in the multivariable model, total number of international arrivals (beta 0.033 (95% Confidence Interval 0.012,0.054)) and BCG vaccination coverage (-0.018 (-0.034,-0.002)), were significantly associated with the mean death rate.

ConclusionsInternational travel was directly associated with the mortality slope and thus potentially the spread of COVID-19. Very early restrictions on international travel should be considered to control COVID outbreak and prevent related deaths.

ARTICLE SUMMARYO_ST_ABSStrengths and limitationsC_ST_ABSO_LIA comparable and relevant outcome variable quantifying country-level increases in the COVID-19 death rate was derived which is largely independent of different testing policies adopted by each country
C_LIO_LIOur multivariable regression models accounted for public health and economic measures which were adopted by each country in response to the COVID-19 pandemic by adjusting for the Stringency Index
C_LIO_LIThe main limitation of the study stems from the ecological study design which does not allow for conclusions to be drawn for individual COVID-19 patients
C_LIO_LIOnly countries that had reported at least 25 daily deaths over the analysed period were included, which reduced our sample and consequently the power.
C_LI


title: Gene expression signatures identify biologically and clinically distinct tuberculosis endotypes

abstract:
BackgroundIn vitro, animal model, and clinical evidence suggests that tuberculosis is not a monomorphic disease, and that host response to tuberculosis is protean with multiple distinct molecular pathways and pathologies (endotypes). We applied unbiased clustering to identify separate tuberculosis endotypes with classifiable gene expression patterns and clinical outcomes.

MethodsA cohort comprised of microarray gene expression data from microbiologically confirmed tuberculosis patients were used to identify putative endotypes. One microarray cohort with longitudinal clinical outcomes was reserved for validation, as was one RNA-seq cohorts. Finally, a separate cohort of tuberculosis patients with functional immune results was evaluated to clarify stimulated from unstimulated immune responses.

ResultsA discovery cohort, including 435 tuberculosis patients and 533 asymptomatic controls, identified two tuberculosis endotypes. Tuberculosis patient endotype A is characterized by increased expression of genes related to inflammation and immunity and decreased metabolism and proliferation; in contrast, endotype B increased activity of metabolism and proliferation pathways. An independent RNA-seq validation cohort, including 118 tuberculosis patients and 179 controls, validated the discovery results. Gene expression signatures for treatment failure were elevated in endotype A in the discovery cohort, and a separate validation cohort confirmed that endotype A patients had slower time to culture conversion, and a reduced incidence of cure. These observations suggest that endotypes reflect functional immunity, supported by the observation that tuberculosis patients with a hyperinflammatory endotype have less responsive cytokine production upon stimulation.

ConclusionThese findings provide evidence that metabolic and immune profiling could inform optimization of endotype-specific host-directed therapies for tuberculosis.


title: Modelling lockdown measures in epidemic outbreaks using selective socio-economic containment with uncertainty

abstract: AO_SCPLOWBSTRACTC_SCPLOWAfter the introduction of drastic containment measures aimed at stopping the epidemic contagion from SARS-CoV2, many governments have adopted a strategy based on a periodic relaxation of such measures in the face of a severe economic crisis caused by lockdowns. Assessing the impact of such openings in relation to the risk of a resumption of the spread of the disease is an extremely difficult problem due to the many unknowns concerning the actual number of people infected, the actual reproduction number and infection fatality rate of the disease. In this work, starting from a compartmental model with a social structure and stochastic inputs, we derive models with multiple feedback controls depending on the social activities that allow to assess the impact of a selective relaxation of the containment measures in the presence of uncertain data. Specific contact patterns in the home, work, school and other locations have been considered. Results from different scenarios concerning the first wave of the epidemic in some major countries, including Germany, France, Italy, Spain, the United Kingdom and the United States, are presented and discussed.


title: Empirical Model of Spring 2020 Decrease in Daily Confirmed COVID-19 Cases in King County, Washington

abstract: Projections of the near future of daily case incidence of COVID-19 are valuable for informing public policy. Near-future estimates are also useful for outbreaks of other diseases. Short-term predictions are unlikely to be affected by changes in herd immunity. In the absence of major net changes in factors that affect reproduction number (R), the two-parameter exponential model should be a standard model - indeed, it has been standard for epidemiological analysis of pandemics for a century but in recent decades has lost popularity to more complex compartmental models. Exponential models should be routinely included in reports describing epidemiological models as a reference, or null hypothesis. Exponential models should be fitted separately for each epidemiologically distinct jurisdiction. They should also be fitted separately to time intervals that differ by any major changes in factors that affect R. Using an exponential model, incidence-count half-life (t1/2) is a better statistic than R. Here an example of the exponential model is applied to King County, Washington during Spring 2020. During the pandemic, the parameters and predictions of this model have remained stable for intervals of one to four months, and the accuracy of model predictions has outperformed models with more parameters. The COVID pandemic can be modeled as a series of exponential curves, each spanning an interval ranging from one to four months. The length of these intervals is hard to predict, other than to extrapolate that future intervals will last about as long as past intervals.


title: Agent-Based Simulation for Evaluation of Contact-Tracing Policies Against the Spread of SARS-CoV-2

abstract:
BackgroundMany countries have already gone through several infection waves and mostly managed to successfully stop the exponential spread of SARS-CoV-2 through bundles of restrictive measures. Still, the danger of further waves of infections is omnipresent and it is apparent that every containment policy must be carefully evaluated and possibly replaced by a different, less restrictive policy, before it can be lifted. Tracing of contacts and consequential breaking of infection chains is a promising strategy to help containing the disease, although its precise impact on the epidemic is unknown.

ObjectiveIn this work we aim to quantify the impact of tracing on the containment of the disease and investigate the dynamic effects involved.

DesignWe developed an agent-based model that validly depicts the spread of the disease and allows for exploratory analysis of containment policies. We apply this model to quantify the impact of divverent variants of contact tracing in Austria and to derive general conclusions on contract tracing.

ResultsThe study displays that strict tracing can supplement up to 5% reduction of infectivity and that household quarantine comes at the smallest price regarding preventively quarantined people.

LimitationsThe results are limited by the validity of the modeling assumptions, model parameter estimates, and the quality of the parametrization data.

ConclusionsThe study shows that tracing is indeed an efficient measure to keep case numbers low but comes at a high price if the disease is not well contained. Therefore, contact tracing must be executed strictly and adherence within the population must be held up to prevent uncontrolled outbreaks of the disease.