bluuebunny/crossref_metadata_2025 huggingface dataset:
TRACKing Excess Deaths (TRACKED) – an interactive online tool to monitor excess deaths associated with COVID-19 pandemic in the United Kingdom
Authors: Poon Michael TC , Brennan Paul M , Jin Kai , Figueroa Jonine D , Sudlow Cathie LM
Published: June 2020

Background

We aimed to describe trends of excess mortality in the United Kingdom (UK) stratified by nation and cause of death, and to develop an online tool for reporting the most up to date data on excess mortality.

Methods

Population statistics agencies in the UK including the Office for National Statistics (ONS), National Records of Scotland (NRS), and Northern Ireland Statistics and Research Agency (NISRA) publish weekly data on deaths. We used mortality data up to 22nd May in the ONS and the NISRA and 24th May in the NRS. Crude mortality for non-COVID deaths (where there is no mention of COVID-19 on the death certificate) calculated. Excess mortality defined as difference between observed mortality and expected average of mortality from previous 5 years.

Results

There were 56,961 excess deaths and 8,986 were non-COVID excess deaths. England had the highest number of excess deaths per 100,000 population (85) and Northern Ireland the lowest (34). Non-COVID mortality increased from 23rd March and returned to the 5-year average on 10th May. In Scotland, where underlying cause mortality data besides COVID-related deaths was available, the percentage excess over the 8-week period when COVID-related mortality peaked was: dementia 49%, other causes 21%, circulatory diseases 10%, and cancer 5%. We developed an online tool (TRACKing Excess Deaths - TRACKED) to allow dynamic exploration and visualisation of the latest mortality trends (http://trackingexcessdeaths.com).

Conclusions

Continuous monitoring of excess mortality trends and further integration of age- and gender-stratified and underlying cause of death data beyond COVID-19 will allow dynamic assessment of the impacts of indirect and direct mortality of the COVID-19 pandemic.
BMI and future risk for COVID-19 infection and death across sex, age and ethnicity: preliminary findings from UK biobank
Authors: Sattar Naveed , Ho Frederick K , Gill Jason MR , Ghouri Nazim , Gray Stuart R , Celis-Morales Carlos A , Katikireddi S Vittal , Berry Colin , Pell Jill P , McMurray John JV , Welsh Paul
Published: June 2020

We examined the link between BMI and risk of a positive test for SARS-CoV-2 and risk of COVID-19-related death among UK Biobank participants. Among 4855 participants tested for SARS-CoV-2 in hospital, 839 were positive and of these 189 died from COVID-19. Poisson models with penalised thin plate splines were run relating exposures of interest to test positivity and case-fatality, adjusting for confounding factors. BMI was associated strongly with positive test, and risk of death related to COVID-19. The gradient of risk in relation to BMI was steeper in those under 70, compared with those aged 70 years or older for COVID-19 related death (Pinteraction=0.03). BMI was more strongly related to test positivity (Pinteraction=0.010) and death (Pinteraction=0.002) in non-whites, compared with whites. These data add support for adiposity being more strongly linked to COVID-19-related deaths in younger people and non-white ethnicities. If future studies confirm causality, lifestyle interventions to improve adiposity status may be important to reduce the risk of COVID-19 in all, but perhaps particularly, non-white communities.
A systematic review of convalescent plasma treatment for COVID19
Authors: Pimenoff Ville N. , Elfström Miriam , Dillner Joakim
Published: June 2020

Background

Transfusion of convalescent immune plasma (CP) is commonly used in epidemics. Several articles now describe clinical report data of CP for treatment of SARS-CoV-2-induced COVID-19 disease.

Methods

A systematic literature review was conducted using the NCBI curated COVID-19 related open-resource literature database LitCovid to identify studies using CP as treatment for COVID-19 patients. We retrieved and curated all COVID-19 related patient and treatment characteristics from previously reported studies. A Poisson model was developed to evaluate the association between age of the patients, older age being the most common risk factor for COVID-19 mortality, and recovery time since CP treatment using data extracted from the literature.

Results

From 18,293 identified COVID-19 related articles, we included ten studies reporting results of CP treatment for COVID-19 from a total of 61 patients. Decreased symptoms of severe COVID-19 and clearance of SARS-CoV-2 RNA were the most direct observations. We found that patients over the age of sixty who received CP treatment for COVID-19 had a significantly prolonged recovery estimated by viral clearance (from 10 to 29 days since first dose of CP) compared to younger patients, who recovered from the infection in less than a week after receiving CP treatment.

Conclusions

Limited published results on plasma transfusion treatment for COVID-19 disease with concomitant treatments suggest that CP therapy for COVID-19 is well tolerated and effective. First randomized clinical trial results, however, revealed no improvements in recovery time for elderly patients with severe COVID-19 between standard treatment alone and added with convalescent plasma. Accordingly, we argue that older patients may need a significantly longer time for recovery. Further randomized clinical trial data for COVID-19 with rigorous ethical standards is urgently needed.
Association between complement component 4A expression, cognitive performance and brain imaging measures in UK Biobank
Authors: O’Connell Kevin S , Sønderby Ida E. , Frei Oleksandr , van der Meer Dennis , Athanasiu Lavinia , Smeland Olav B. , Alnæs Dag , Kaufmann Tobias , Westlye Lars T. , Steen Vidar M. , Andreassen Ole A. , Hughes Timothy , Djurovic Srdjan
Published: June 2020

Altered expression of the complement componentC4Agene is a known risk factor for schizophrenia. Further, predicted brainC4Aexpression has also been associated with memory function highlighting that altered C4A expression in the brain may be relevant for cognitive and behavioral traits. We investigated if predicted brainC4Aexpression was associated with cognitive performance and brain imaging measures in the UK Biobank. We identified significant negative associations between predictedC4Aexpression and performance on select cognitive tests, and significant associations with MRI-based cortical thickness and surface area in select regions. Finally, we observed significant inconsistent partial mediation of the effects of predictedC4Aexpression on cognitive performance, by specific brain structure measures. These results demonstrate that theC4risk locus is associated with the central endophenotypes of cognitive performance and brain morphology, even when considered independently of other genetic risk factors and in individuals without mental or neurological disorders.
Is the psychological well-being of a population associated with COVID-19 related survival?
Authors: Feys Frederik
Published: June 2020

Abstract

OBJECTIVE

Immunological mind-body research suggests mental health may also be important in the COVID-19 pandemic. This study aimed to investigate the potential influence of mental health as a protective factor for COVID-19 related mortality in the general population. The second goal was to examine this among populations of countries most affected by COVID-19 related mortality.

METHODS

Data sources were the Global Burden of Disease report 2017 and publicly reported situational reports of COVID-19. We described variables; calculated the spearman’s correlation coefficient, calculated the percentage of the variability of the data that is explained by the association. We explored inter-relationships among other variables: aged 70 or older, cardiovascular disease, obesity and diabetes. A correlation matrix with plotted scatter matrix diagrams was produced.

RESULTS

Across 181 countries, the mean total COVID-19 related survivors per million was 999,949 (sd = 125), median = 999,993. The variable had a lognormal distribution; the mean mentally healthy per 100,000 was 85,411 (sd = 1,871), median = 85,634. The test of normality resulted in p-value < 0.001. Correlation of mentally healthy per 100,0000 and totals of COVID-19 related survivors wasϱs= 0.29 (n = 181, 95% CI 0.16–0.43). The variance explained by the relation between mental healthy and totals of COVID-19 related survivors was 8.4% (2.6–18.5%). Across countries most affected by COVID-19 related mortalityϱs= 0.49 (n = 45, 0.28–0.70), explaining 24.2% (7.7–49.3%).

CONCLUSION

A weak association was found between the psychological well-being of a population and COVID-19 related survival. This relationship explained between 2.6 and 18.5% of COVID-19 related survival. For countries most affected by COVID-19 related death, this association was moderate and explained between 7.7 and 49.3%. Confirmation of these important observational findings is needed with future individual patient data research.
Epigenetic and transcriptional regulation of osteoclastogenesis in the pathogenesis of skeletal diseases: a protocol for a systematic review
Authors: Sharma Siddhartha , Mittal Anupam , Mahajan Aditi , Gohil Riddhi
Published: June 2020

Osteoclastogenesis (OCG) is a multi-stage process that involves formation of activated osteoclasts from bone marrow macrophages. The progression of each stage of OCG is governed by a set of transcription factors and gene regulators, which are genetically and epigenetically regulated at both transcription and post-transcription levels. Epigenetic changes are used to denote interactions between genetic material and environment leading to phenotypic alterations that can be inherited, without any variations in DNA sequence. Epigenetic and transcription regulatory events have profound effects on osteoclast formation and activation; these have been implicated in numerous disorders including osteoporosis, osteopetrosis, rheumatoid arthritis, spondyloarthritis, gout and bone metastasis. We aim to conduct a systematic review to assess possible relationship between key epigenetic and transcriptional regulators of osteoclastogenesis, and their role in specific bone disorders. This is a protocol for the proposed review.
Serology confirms SARS-CoV-2 infection in PCR-negative children presenting with Paediatric Inflammatory Multi-System Syndrome
Authors: Perez-Toledo Marisol , Faustini Sian E. , Jossi Sian E. , Shields Adrian M. , Kanthimathinathan Hari Krishnan , Allen Joel D. , Watanabe Yasunori , Goodall Margaret , Wraith David C. , Veenith Tonny V. , Drayson Mark T. , Jyothish Deepthi , Al-Abadi Eslam , Chikermane Ashish , Welch Steven B. , Masilamani Kavitha , Hackett Scott , Crispin Max , Scholefield Barnaby R , Cunningham Adam F. , Richter Alex G.
Published: June 2020

Background

During the COVID-19 outbreak, reports have surfaced of children who present with features of a multisystem inflammatory syndrome with overlapping features of Kawasaki disease and toxic shock syndrome – Paediatric Inflammatory Multisystem Syndrome-temporally associated with SARS-CoV-2 pandemic (PIMS-TS). Initial reports find that many of the children are PCR-negative for SARS-CoV-2, so it is difficult to confirm whether this syndrome is a late complication of viral infection in an age group largely spared the worst consequences of this infection, or if this syndrome reflects enhanced surveillance.

Methods

Children hospitalised for symptoms consistent with PIMS-TS between 28 April and 8 May 2020, and who were PCR-negative for SARS-CoV-2, were tested for antibodies to viral spike glycoprotein using an ELISA test.

Results

Eight patients (age range 7–14 years, 63% male) fulfilled case-definition for PIMS-TS during the study period. Six of the eight patients required admission to intensive care. All patients exhibited significant IgG and IgA responses to viral spike glycoprotein. Further assessment showed that the IgG isotypes detected in children with PIMS-TS were of the IgGl and lgG3 subclasses, a distribution similar to that observed in samples from hospitalised adult COVID-19 patients. In contrast, lgG2 and lgG4 were not detected in children or adults. IgM was not detected in children, which contrasts with adult hospitalised adult COVID-19 patients of whom all had positive IgM responses.

Conclusions

Strong IgG antibody responses can be detected in PCR-negative children with PIMS-TS. The low detection rate of IgM in these patients is consistent with infection having occurred weeks previously and that the syndrome onset occurs well after the control of SARS-CoV-2 viral load. This implies that the disease is largely immune-mediated. Lastly, this indicates that serology can be an appropriate diagnostic tool in select patient groups.
Heterogeneity is essential for contact tracing
Authors: Nielsen Bjarke Frost , Sneppen Kim , Simonsen Lone , Mathiesen Joachim
Published: June 2020

Background

(Dated: June 5, 2020)

The COVID-19 pandemic is most often modelled by well-mixed models, sometimes stratified by age and work. People are, however, different from one another in terms of interaction frequency as well as in formation of social groups. This contact heterogeneity especially challenges models of contact tracing (CT), but also predictions of epidemic severity generally. We explore how heterogeneity affects CT effectiveness and overall epidemic severity, using a real-world contact network.

Methods

Utilizing smartphone proximity data from Danish university students, we simulate the spread of COVID-19 on a network with realistic contact structure. Two modes of network homogenization are implemented to probe effects of heterogeneity. We then simulate a CT scheme on the network and explore the impact of heterogeneity, testing probability and contact threshold for quarantining.

Results

Measuring contact heterogeneity, we find an exponential distribution which persists on a timescale of several weeks. Comparing the true network to edge-swapped and randomized versions, we find that heterogeneity decreases the severity of COVID-19 in general, and that it drastically improves CT.

Conclusions

To capture heterogeneity, it is necessary to reconsider disease transmission models. Our findings show that heterogeneity is essential for CT, and that CT is effective even if only the most frequent contacts can be tracked down. We find that contact heterogeneity impedes the spread of COVID-19 in comparison with well-mixed networks. In perspective, this means that fitting traditional SEIR models to epidemic data is likely to overestimate the severity.
No impact of smoking status on breast cancer tumor infiltrating lymphocytes, response to neoadjuvant chemotherapy and prognosis
Authors: Simon Vanille , Laot Lucie , Laas Enora , Rozette Sonia , Guerin Julien , Balezeau Thomas , Nicolas Marion , Pierga Jean-Yves , Coussy Florence , Laé Marick , de Croze Diane , Grandal Beatriz , Abecassis Judith , Reyal Fabien , Hamy Anne-Sophie
Published: June 2020

INTRODUCTION

Tobacco use is associated with an increase in breast cancer (BC) mortality. Pathologic complete response rate to neoadjuvant chemotherapy (NAC) is influenced by tumor-infiltrating lymphocytes (TILs) levels and is associated with a better long-term survival outcome. Whether tobacco modifies either tumoral microenvironment such as TIL levels, either pCR rates remains unclear. The aim of our study is to evaluate the impact of smoking status on TIL levels, response to NAC and prognosis for BC patients.

METHODS

We retrospectively evaluated pre and post NAC stromal and intra tumoral TIL levels and pCR rates on a cohort of T1-T3NxM0 BC patients treated with NAC between 2002 and 2012 at Institut Curie. Smoking status (current, ever, never smokers) was collected in clinical records. We analyzed the association between smoking status, TIL levels, pCR rates and survival outcomes among the whole population, and after stratification by BC subtype.

RESULTS

A total of 956 BC patients with available smoking status information were included in our analysis [current smokers, n=179 (18.7%); ever smokers, n=154 (16.1%) and never smokers, n = 623 (65.2%)]. Median pre-NAC TIL levels, pCR rates, or median post-NAC TIL levels were not significantly different according to smoking status, neither in the whole population, nor after stratification by BC subtype. With a median follow-up of 101.4 months, relapse free survival (RFS) and overall survival (OS) were not significantly different by smoking status.

CONCLUSION

In this study, we did not find any significant effect of tobacco use on pre and post NAC TILs nor response to NAC and. Though our data seem reassuring, BC treatment should still be considered as a window of opportunity to offer BC patients accurate smoking cessation interventions.
An environmental determinant of viral respiratory disease
Authors: Choi Yeon-Woo , Tuel Alexandre , Eltahir Elfatih A. B.
Published: June 2020

The evident seasonality of influenza suggests a significant role for weather and climate as one of several determinants of viral respiratory disease (VRD), including social determinants which play a major role in shaping these phenomena. Based on the current mechanistic understanding of how VRDs are transmitted by small droplets, we identify an environmental variable, Air Drying Capacity (ADC), as an atmospheric state-variable with significant and direct relevance to the transmission of VRD. ADC dictates the evolution and fate of droplets under given temperature and humidity conditions. The definition of this variable is rooted in the Maxwell theory of droplet evolution via coupled heat and mass transfer between droplets and the surrounding environment. We present the climatology of ADC, and compare its observed distribution in space and time to the observed prevalence of influenza and COVID-19 from extensive global data sets. Globally, large ADC values appear to significantly constrain the observed transmission and spread of VRD, consistent with the significant coherency of the observed seasonal cycles of ADC and influenza. Our results introduce a new environmental determinant, rooted in the mechanism of VRD transmission, with potential implications for explaining seasonality of influenza, and for describing how environmental conditions may impact to some degree the evolution of similar VRDs, such as COVID-19.
On the Spread of Coronavirus Infection. A Mechanistic Model to Rate Strategies for Disease Management
Authors: Wang Shiyan , Ramkrishna Doraiswami
Published: June 2020

Effective policy making based on ongoing COVID-19 pandemic is an urgent issue. We present a mathematical model describing the viral infection dynamics, which reveals two transmissibility parameters influenced by the management strategies in the area for control of the current pandemic. The parameters readily yield the peak infection rate and means for flattening the curve. Model parameters are shown to be correlated to different management strategies by employing machine learning, enabling comparison of different strategies and suggesting timely alterations. Treatment of population data with the model shows that restricted non-essential business closure, school closing and strictures on mass gathering influence the spread of infection. While a rational strategy for initiation of an economic reboot would call for a wider perspective of the local economics, the model can speculate on its timing based on the status of the infection as reflected by its potential for an unacceptably renewed viral onslaught.
Containment of future waves of COVID-19: simulating the impact of different policies and testing capacities for contact tracing, testing, and isolation
Authors: Fiore Vincenzo G. , DeFelice Nicholas , Glicksberg Benjamin S. , Perl Ofer , Shuster Anastasia , Kulkarni Kaustubh , O’Brien Madeline , Andrea Pisauro M. , Chung Dongil , Gu Xiaosi
Published: June 2020

We used multi-agent simulations to estimate the testing capacity required to find and isolate a number of infections sufficient to break the chain of transmission of SARS-CoV-2. Depending on the mitigation policies in place, a daily capacity between 0.7 to 3.6 tests per thousand was required to contain the disease. However, if contact tracing and testing efficacy dropped below 60% (e.g. due to false negatives or reduced tracing capability), the number of infections kept growing exponentially, irrespective of any testing capacity. Under these conditions, the population’s geographical distribution and travel behaviour could inform sampling policies to aid a successful containment.
COVID 19 healthcare facility demand forecasts for rural residents
Authors: Adwibowo Andrio
Published: June 2020

One of the main challenges in dealing with the current COVID 19 pandemic is how to fulfill the healthcare facility demands especially for the residents living in the rural areas that have restricted healthcare access. Correspondingly, this study aims to record the daily COVID 19 cases and continue with the forecasting of the average daily demand (ADD) of healthcare facilities including beds, ICUs, and ventilators using ARIMA model. The forecasts were made for 3 rural populations located in the southern Amazon. The model shows that the healthcare ADD was different in each population. Likewise, the model forecasts that in a rural population that has the highest daily case with projected average cases equal to 67 cases/day (95%CI: 24, 110), that population has to fulfill healthcare ADD consisting of 57 beds/day (95%CI: 21, 93), 8 ICUs/day (95%CI: 2, 14), and 2 ventilators/day (95%CI: 2, 3). To conclude, the ARIMA model has addressed critical questions about ADD for beds, ICUs, and ventilators for rural residents. This ARIMA model based healthcare plan will hopefully provide versatile tool to improve healthcare resource allocations.
Opioid overdose in public libraries: Results from a five state survey
Authors: Feuerstein-Simon Rachel , Lowenstein Margaret , Dupuis Roxanne , Marti Xochitl Luna , Dolan Abby , Cannuscio Carolyn C.
Published: June 2020

Introduction

Public libraries are increasingly impacted by the overdose crisis. A 2017 survey of public librarians in the state of Pennsylvania revealed that 12% had reported an on-site overdose in the previous year. There are increasing public and private efforts to equip public libraries with the opioid overdose antidote, naloxone.

Methods

We conducted a cross-sectional web-based survey of all public library branches in Colorado, Connecticut, Florida, Michigan, and Virginia. Survey questions. We used descriptive statistics to report frequencies of responses and crude odds ratios were calculated to predict the dichotomized variable of endorsement of naloxone uptake.

Results

Library staff reported witnessing on-site alcohol (45%) and injection drug (14%) use in the past month. The one-year cumulative incidence (12% overall) of on-site overdose ranged from a low of 10% in MI, to a high of 17% in FL. Among libraries with on-site overdoses, a minority (21%) stocked naloxone, and 12% had administered naloxone. Overall, 11% of libraries stocked naloxone on-site. Although 24% of respondents reported attending at least one training regarding SUD in the past year, 91% wanted more training on the topic.

Conclusions

Public library staff routinely address issues related to substance use and overdose in their institutions. This work highlights the importance of including public libraries as part of a comprehensive public health strategy to address substance use-related morbidity and mortality in the U.S.
UV-C irradiation is highly effective in inactivating SARS-CoV-2 replication
Authors: Biasin Mara , Bianco Andrea , Pareschi Giovanni , Cavalleri Adalberto , Cavatorta Claudia , Fenizia Claudio , Galli Paola , Lessio Luigi , Lualdi Manuela , Tombetti Enrico , Ambrosi Alessandro , Redaelli Edoardo Maria Alberto , Saulle Irma , Trabattoni Daria , Zanutta Alessio , Clerici Mario
Published: June 2020

The potential virucidal effects of UV-C irradiation on SARS-CoV-2 were experimentally evaluated for different illumination doses and virus concentrations (1000, 5, 0.05 MOI). At a virus density comparable to that observed in SARS-CoV-2 infection, an UV-C dose of just 3.7 mJ/cm2 was sufficient to achieve a more than 3-log inactivation without any sign of viral replication. Moreover, a complete inactivation at all viral concentrations was observed with 16.9 mJ/cm2. These results could explain the epidemiological trends of COVID-19 and are important for the development of novel sterilizing methods to contain SARS-CoV-2 infection.
Predictors of disease duration and symptom course of outpatients with acute covid-19: a retrospective cohort study
Authors: O’Keefe James B. , Tong Elizabeth J. , O’Keefe Ghazala A. Datoo , Tong David C.
Published: June 2020

Objective

Describe the disease course in a cohort of outpatients with covid-19 and evaluate factors predicting duration of symptoms

Design

Retrospective cohort study

Setting

Telemedicine clinic at a large medical system in Atlanta, Georgia

Participants

273 patients with COVID-19. Exclusion criteria included: (1) intake more than 10 days after symptom onset, (2) hospitalization for covid-19, (3) symptoms at less than two visits.

Main outcome measures

Symptom duration in days

Results

Common symptoms at diagnosis are upper respiratory (64% cough, 53% loss of smell or taste, 50% sinus congestion, 22% sore throat), systemic (50% headache, 48% body aches, 36% chills, 22% dizziness, 18% fever). The most frequent remaining symptoms at 30 days were cough (7%), loss of smell or taste (5%), body aches (5%), nasal congestion (5%), shortness of breath with exertion (5%), and joint pain (5%). Day of symptom onset was earliest for upper respiratory symptoms (mean 1.26 days, 95% confidence interval 1.15 to 1.4), followed by systemic symptoms (1.54, 1.39 to 1.7), with later onset of lower respiratory (2.86, 2.54 to 3.22) and gastrointestinal symptoms (3.46, 3.07 to 3.89), when present. Cough had the longest duration when present with 12.2 days (10.9 to 13.6). Loss of smell or taste had the second longest duration with 11.0 days (9.9 to 12.2). Provider-Assessed Symptom Severity (PASS) is the best predictor of symptom duration (P <0.005 for multiple symptoms) and patients with “Moderate” PASS compared to “Mild” at their intake visit have higher rates of symptoms at 30 days, including cough (12%), nasal congestion (10%), joint pain (10%), body aches (9%), loss of taste or smell (7%), headache (7%), and shortness of breath with exertion (6%).

Conclusions

Covid-19 illness in outpatients follows a pattern of progression from systemic symptoms to lower respiratory symptoms and persistent symptoms are common across categories. Provider-assessed symptom severity is the best predictor of disease duration.
Predicted COVID-19 fatality rates based on age, sex, comorbidities, and health system capacity
Authors: Ghisolfi Selene , Almås Ingvild , Sandefur Justin , von Carnap Tillmann , Heitner Jesse , Bold Tessa
Published: June 2020

Early reports suggest the fatality rate from COVID-19 varies greatly across countries, but non-random testing and incomplete vital registration systems render it impossible to directly estimate the infection fatality rate (IFR) in many low- and middle-income countries. To fill this gap, we estimate the adjustments required to extrapolate estimates of the IFR from high- to lower-income regions. Accounting for differences in the distribution of age, sex, and relevant comorbidities yields substantial differences in the predicted IFR across 21 world regions, ranging from 0.11% in Western Sub-Saharan Africa to 0.95% for High Income Asia Pacific. However, these predictions must be treated as lower bounds, as they are grounded in fatality rates from countries with advanced health systems. In order to adjust for health system capacity, we incorporate regional differences in the relative odds of infection fatality from childhood influenza. This adjustment greatly diminishes, but does not entirely erase, the demography-based advantage predicted in the lowest income settings, with regional estimates of the predicted COVID-19 IFR ranging from 0.43% in Western Sub-Saharan Africa to 1.74% for Eastern Europe.
A shred of evidence that BCG vaccine may protect against COVID-19: Comparing cohorts in Spain and Italy
Authors: Levine David I.
Published: June 2020

Introduction

There is evidence that the BCG vaccine against tuberculosis also helps prevent other diseases – perhaps including COVD-19. Spain had a program for universal BCG vaccination until 1981.

Objective

To see whether cohorts born when Spain had a program of universal BCG vaccination had lower rates of confirmed cases of COVID-19 and mortality (relative to similar cohorts in Italy).

Methods

We compare COVID-19 mortality and confirmed cases for those born roughly a decade before and after 1981. We compare the outcomes to the same age cohorts in Italy, which never had universal BCG vaccination.

Results

The Spanish cohort that received BCG had a relative risk of 0.962 of having a confirmed case of COVID-19. This risk is statistically significantly below unity (95% CI 0.952 to 0.972, P< 0.001). There is also suggestive evidence the BCG cohort in Spain had lower mortality (relative risk 0.929, CI 0.850 to 1.01, P = 0.11). The small sample size makes this test underpowered.

Conclusion

These suggestive results provide a shred of evidence that BCG vaccinations help protect against COVID. I outline many limitations to this study and point how better data can help be more convincing.
Multiscale dynamics of COVID-19 and model-based recommendations for 105 countries
Authors: Timothy Jithender J. , Holla Vijaya , Meschke Günther
Published: June 2020

We analyse the dynamics of COVID-19 using computational modelling at multiple scales. For large scale analysis, we propose a 2-scale lattice extension of the classical SIR-type compartmental model with spatial interactions called the Lattice-SIRQL model. Computational simulations show that global quantifiers are not completely representative of the actual dynamics of the disease especially when mitigation measures such as quarantine and lockdown are applied. Furthermore, using real data of confirmed COVID-19 cases, we calibrate the Lattice-SIRQL model for 105 countries. The calibrated model is used to make country specific recommendations for lockdown relaxation and lockdown continuation. Finally, using an agent-based model we analyse the influence of cluster level relaxation rate and lockdown duration on disease spreading.
Non-COVID-19 Deaths After Social Distancing in Norway
Authors: Catalano Ralph , Casey Joan A. , Bruckner Tim A. , Gemmill Alison
Published: June 2020

Lay persons and policy makers have speculated on how the imposition of social distancing to reduce SARS CoV-2 (severe acute respiratory syndrome coronavirus 2) infection has affected non-COVID-19 (coronavirus disease of 2019) deaths. No rigorous estimation of the effect appears in the scholarly literature. We use time-series methods to compare non-COVID-19 deaths observed in Norway before and during the epidemic to those expected from non-COVID-19 deaths in Sweden as well as from the history of Norwegian mortality trends. We find that in the first 6 weeks after the divergence between Swedish and Norwegian policies -- the only period for which dependable data can be had – approximately 414 fewer Norwegians died than expected.
Evaluation of Knowledge, Practices, Attitude and Anxiety of Pakistan’s Nurses towards COVID-19 during the Current Outbreak in Pakistan
Authors: Alwani SS , Majeed MM , Hirwani MZ , Rauf S , Saad SM , Shah H , Hamirani F
Published: June 2020

Since the emergence of the novel corona virus, the front line soldiers during this pandemic are the healthcare professionals because of their direct association with COVID19 patients. In the management of such patients, nurses play a significant role through proper care and preventive measures. Due to its contagious nature, fatality and no proper medicine, it is a risk to the health and life of nurses and has an impact on their psychological health.

In the current study we assessed the knowledge, attitude, practices and anxiety levels of nurses who are directly involved in the management of COVID-19 patients.

It was an online questionnaire based cross sectional survey targeting only those nurses involved in the management of COVID-19 patients from different hospitals of Karachi, Pakistan. SPSS 21 was used for data analysis. Descriptive analysis, Chi Square and t-tests were applied. P value < 0.05 was considered significant.

Data of 78 nurses was analyzed. We observed that nurses possess good knowledge about COVID-19, its sources, symptoms and routes of transmission of the Virus etc. The knowledge mean score was calculated 14.67±3.36. Health department /Hospital and social media are the main sources of information regarding COVID-19. We investigated that 92.3% of the nurses had mild to very severe anxiety and anxiety levels are significantly higher among females (P< 0.05).

We concluded that the nurses performing their duties with COVID-19 positive patients have good knowledge and attitude. But their anxiety levels are high. Psychological interventions along with training should be given.
Prevention of household transmission crucial to stop the catastrophic spread of COVID-19 in cities
Authors: Brizuela Noel Gutiérrez , Pulido Humberto Gutiérrez , Roosa Kimberlyn , Chan Néstor García , Hernández-Bello Jorge , Muñoz-Valle José Francisco , Macedo-Ojeda Gabriela , González-Estevez Guillermo , López-Chávez Javier Alonso , Villanueva-Lomelí Ricardo , Chowell Puente Gerardo
Published: June 2020

After weeks under lockdown, metropolitan areas fighting the spread of COVID-19 aim to balance public health goals with social and economic standards for well-being. Mathematical models of disease transmission seeking to evaluate mitigation strategies must assess the possible impacts of social distancing, economic lockdowns and other measures. However, obscure relations between model parameters and real-world phenomena complicate such analyses. Here, we use a high-resolution metapopulation model of Guadalajara (GDL, Western Mexico) to represent daily mobility patterns driven by economic activities and their relation to epidemic growth. Given the prominence of essential activities in the city’s economy, we find that strategies aiming to mitigate the risk of out-of-home interactions are insufficient to stop the catastrophic spread of COVID-19. Using baseline reproduction numbers R0 = [2.5, 3.0] in the absence of interventions, our simulations suggest that household transmission alone can make Rt ∼ 1, and is estimated to drive 70 ±15% of current epidemic growth. This sets an upper bound for the impact of mobility-based interventions, which are unlikely to lower Rt below 1.3 and must be complemented with aggressive campaigns for early case detection and isolation. As laboratory testing and health services become insufficient to meet demand in GDL and most other cities, we propose that cities facilitate guidelines and equipment to help people curb spreading within their own homes. Postponing these actions will increase their economic cost and decrease their potential returns.

Author summary

Public health strategies to mitigate the spread of COVID-19 in metropolitan areas have focused on preventing transmission in schools, work sites and other public spaces. Here, we use a demographically- and spatially-explicit model of Guadalajara (GDL, Western Mexico) to represent economic lockdowns and their impact on disease spread. Our findings suggest that viral exposure within households accounts for 70±15% of the epidemic’s current growth rate. This highlights the importance of early case detection and isolation as necessary measures to prevent the spread of COVID-19 between strangers and close contacts alike.
Changes in non-linear and time-domain heart rate variability indices between critically ill COVID-19 and all-cause sepsis patients – a retrospective study
Authors: Kamaleswaran Rishikesan , Sadan Ofer , Kandiah Prem , Li Qiao , Blum James M. , Coopersmith Craig M. , Buchman Timothy G.
Published: June 2020

Objective

To measure heart rate variability metrics in critically ill COVID-19 patients with comparison to all-cause critically ill sepsis patients.

Design and patients

Retrospective analysis of COVID-19 patients admitted to an ICU for at least 24h at any of Emory Healthcare ICUs between March and April 2020. The comparison group was a cohort of all-cause sepsis patients prior to COVID-19 pandemic.

Interventions

none.

Measurements

Continuous waveforms were captured from the patient monitor. The EKG was then analyzed for each patient over a 300 second (s) observational window, that was shifted by 30s in each iteration from admission till discharge. A total of 23 HRV metrics were extracted in each iteration. We use the Kruskal–Wallis and Steel–Dwass tests (p < 0.05) for statistical analysis and interpretations of HRV multiple measures.

Results

A total of 141 critically-ill COVID-19 patients met inclusion criteria, who were compared to 208 patients with all-cause sepsis. Demographic parameters were similar apart from a high proportion of African-Americans in the COVID-19 cohort. Three non-linear markers, including SD1:SD2, sample entropy, approximate entropy and four linear features mode of Beat-to-Beat interval (NN), Acceleration Capacity (AC), Deceleration Capacity (DC), and pNN50, were statistical significance between more than one binary combinations of the sub-groups (comparing survivors and non-survivors in both the COVID-19 and sepsis cohorts). The three nonlinear features and AC, DC, and NN (mode) were statistically significant across all four combinations. Temporal analysis of the main markers showed low variability across the 5 days of analysis, compared with sepsis patients.

Conclusions

Heart rate variability is broadly implicated across patients infected with SARSCoV-2, and admitted to the ICU for critical illness. Comparing these metrics to patients with all-cause sepsis suggests a unique set of expressions that differentiate this viral phenotype. This finding could be investigated further as a potential biomarker to predict poor outcome in this patient population, and could also be a starting point to measure potential autonomic dysfunction in COVID-19.
Interplay of global multi-scale human mobility, social distancing, government interventions, and COVID-19 dynamics
Authors: Adiga Aniruddha , Wang Lijing , Sadilek Adam , Tendulkar Ashish , Venkatramanan Srinivasan , Vullikanti Anil , Aggarwal Gaurav , Talekar Alok , Ben Xue , Chen Jiangzhuo , Lewis Bryan , Swarup Samarth , Tambe Milind , Marathe Madhav
Published: June 2020

This work quantifies mobility changes observed during the different phases of the pandemic world-wide at multiple resolutions – county, state, country – using an anonymized aggregate mobility map that captures population flows between geographic cells of size 5 km2. As we overlay the global mobility map with epidemic incidence curves and dates of government interventions, we observe that as case counts rose, mobility fell and has since then seen a slow but steady increase in flows. Further, in order to understand mixing within a region, we propose a new metric to quantify the effect of social distancing on the basis of mobility.Taking two very different countries sampled from the global spectrum, We analyze in detail the mobility patterns of the United States (US) and India. We then carry out a counterfactual analysis of delaying the lockdown and show that a one week delay would have doubled the reported number of cases in the US and India. Finally, we quantify the effect of college students returning back to school for the fall semester on COVID-19 dynamics in the surrounding community. We employ the data from a recent university outbreak (reported on August 16, 2020) to infer possible Reffvalues and mobility flows combined with daily prevalence data and census data to obtain an estimate of new cases that might arrive on a college campus. We find that maintaining social distancing at existing levels would be effective in mitigating the extra seeding of cases. However, potential behavioral change and increased social interaction amongst students (30% increase in Reff) along with extra seeding can increase the number of cases by 20% over a period of one month in the encompassing county. To our knowledge, this work is the first to model in near real-time, the interplay of human mobility, epidemic dynamics and public policies across multiple spatial resolutions and at a global scale.
Multi-model evaluation of phenology prediction for wheat in Australia
Authors: Wallach Daniel , Palosuo Taru , Thorburn Peter , Hochman Zvi , Andrianasolo Fety , Asseng Senthold , Basso Bruno , Buis Samuel , Crout Neil , Dumont Benjamin , Ferrise Roberto , Gaiser Thomas , Gayler Sebastian , Hiremath Santosh , Hoek Steven , Horan Heidi , Hoogenboom Gerrit , Huang Mingxia , Jabloun Mohamed , Jansson Per-Erik , Jing Qi , Justes Eric , Kersebaum Kurt Christian , Launay Marie , Lewan Elisabet , Luo Qunying , Maestrini Bernardo , Moriondo Marco , Padovan Gloria , Olesen Jørgen Eivind , Poyda Arne , Priesack Eckart , Pullens Johannes Wilhelmus Maria , Qian Budong , Schütze Niels , Shelia Vakhtang , Souissi Amir , Specka Xenia , Srivastava Amit Kumar , Stella Tommaso , Streck Thilo , Trombi Giacomo , Wallor Evelyn , Wang Jing , Weber Tobias K.D. , Weihermüller Lutz , de Wit Allard , Wöhling Thomas , Xiao Liujun , Zhao Chuang , Zhu Yan , Seidel Sabine J.
Published: June 2020

Predicting wheat phenology is important for cultivar selection, for effective crop management and provides a baseline for evaluating the effects of global change. Evaluating how well crop phenology can be predicted is therefore of major interest. Twenty-eight wheat modeling groups participated in this evaluation. Our target population was wheat fields in the major wheat growing regions of Australia under current climatic conditions and with current local management practices. The environments used for calibration and for evaluation were both sampled from this same target population. The calibration and evaluation environments had neither sites nor years in common, so this is a rigorous evaluation of the ability of modeling groups to predict phenology for new sites and weather conditions. Mean absolute error (MAE) for the evaluation environments, averaged over predictions of three phenological stages and over modeling groups, was 9 days, with a range from 6 to 20 days. Predictions using the multi-modeling group mean and median had prediction errors nearly as small as the best modeling group. About two thirds of the modeling groups performed better than a simple but relevant benchmark, which predicts phenology by assuming a constant temperature sum for each development stage. The added complexity of crop models beyond just the effect of temperature was thus justified in most cases. There was substantial variability between modeling groups using the same model structure, which implies that model improvement could be achieved not only by improving model structure, but also by improving parameter values, and in particular by improving calibration techniques.
Partial rescue of neuronal genes deregulated in Cornelia de Lange Syndrome by cohesin
Authors: Weiss Felix D. , Calderon Lesly , Wang Yi-Fang , Georgieva Radina , Guo Ya , Cvetesic Nevena , Kaur Maninder , Dharmalingam Gopuraja , Krantz Ian D. , Lenhard Boris , Fisher Amanda G. , Merkenschlager Matthias
Published: June 2020

Cornelia de Lange Syndrome (CdLS) is a human developmental disorder caused by mutations that compromise the function of cohesin, a major regulator of 3D genome organization. Cognitive impairment is a universal and as yet unexplained feature of CdLS. We characterized the transcriptional profile of cortical neurons from CdLS patients and found deregulation of hundreds of genes enriched for neuronal functions related to synaptic transmission, signalling processes, learning and behaviour. Inducible proteolytic cleavage of cohesin disrupted 3-D genome organization and transcriptional control in post-mitotic cortical mouse neurons. The genes affected belonged to similar gene ontology classes and showed significant numerical overlap with those deregulated in CdLS. Interestingly, gene expression was largely rescued by subsequent reconstitution of cohesin function. These experiments show that cohesin is continuously required for neuronal gene expression and provide a tractable approach for addressing mechanisms of neuronal dysfunction in CdLS.
Human alveolar Type 2 epithelium transdifferentiates into metaplastic KRT5+ basal cells during alveolar repair
Authors: Kathiriya Jaymin J. , Wang Chaoqun , Brumwell Alexis , Cassandras Monica , Le Saux Claude , Wolters Paul , Matthay Michael , Chapman Harold A , Peng Tien
Published: June 2020

Understanding differential lineage potential of orthologous stem cells across species can shed light on human disease. Here, utilizing 3D organoids, single cell RNAseq, and xenotransplants, we demonstrate that human alveolar type 2 cells (hAEC2s), unlike murine AEC2s, are multipotent and able to transdifferentiate into KRT5+ basal cells when co-cultured with primary fibroblasts in 3D organoids. Trajectory analyses and immunophenotyping of epithelial progenitors in idiopathic pulmonary fibrosis (IPF) indicate that hAEC2s transdifferentiate into metaplastic basal cells through alveolar-basal intermediate (ABI) cells that we also identify in hAEC2-derived organoids. Modulating hAEC2-intrinsic and niche factors dysregulated in IPF can attenuate metaplastic basal cell transdifferentiation and preserve hAEC2 identity. Finally, hAEC2s transplanted into fibrotic immune-deficient murine lungs engraft as either hAEC2s or differentiated KRT5+ basal cells. Our study indicates that hAEC2s-loss and expansion of alveolar metaplastic basal cells in IPF are causally connected, which would not have been revealed utilizing murine AEC2s as a model.

Highlights

Human AEC2s transdifferentiate into KRT5+ basal cells when accompanied by primary adult human lung mesenchyme in 3D organoid culture.

Alterations of hAEC2-intrinsic and niche factors dysregulated in IPF can modify metaplastic hAEC2 transdifferentiation.

hAEC2s engraft into fibrotic lungs of immune-deficient mice and transdifferentiate into metaplastic basal cells.

Transcriptional trajectory analysis suggests that hAEC2s in IPF gives rise to metaplastic basal cells via alveolar-basal intermediate cells.
Chromatin and transcriptional response to loss of TBX1 in early differentiation of mouse cells
Authors: Cirino Andrea , Aurigemma Ilaria , Franzese Monica , Lania Gabriella , Righelli Dario , Ferrentino Rosa , Illingworth Elizabeth , Angelini Claudia , Baldini Antonio
Published: June 2020

The T-box transcription factor TBX1 has critical roles in the cardiopharyngeal lineage and the gene is haploinsufficient in DiGeorge syndrome, a typical developmental anomaly of the pharyngeal apparatus. Despite almost two decades of research, if and how TBX1 function triggers chromatin remodeling is not known.

Here, we explored genome-wide gene expression and chromatin remodeling in two independent cellular models of Tbx1 loss of function, mouse embryonic carcinoma cells P19Cl6, and mouse embryonic stem cells (mESCs). The results of our study revealed that the loss or knockdown of TBX1 caused extensive transcriptional changes, some of which were cell type-specific, some were in common between the two models. However, unexpectedly we observed only limited chromatin changes in both systems. In P19Cl6 cells, differentially accessible regions (DARs) were not enriched in T-BOX binding motifs; in contrast, in mESCs, 34% (n=47) of all DARs included a T-BOX binding motif and almost all of them gained accessibility in Tbx1-/- cells.

In conclusion, despite a clear transcriptional response of our cell models to loss of TBX1 in early cell differentiation, chromatin changes were relatively modest.