bluuebunny/crossref_metadata_2025 huggingface dataset:
Navigating the Valley of Death: Perceptions of Industry and Academia on Production Platforms and Opportunities
Authors: Kampers Linde FC , Garcia Enrique Asin , Schaap Peter J , Wagemakers Annemarie , Martins dos Santos Vitor AP
Published: May 2020

Rational lifestyle engineering using computational methods and synthetic biology has made it possible to genetically improve industrial performance of microbial cell factories for the production of a range of biobased chemicals. However, only an estimated 1 in 5,000 to 10,000 innovations make it through the Valley of Death to market implementation.

To gain in-depth insights into the views of industry and academia on key bottlenecks and opportunities to reach market implementation, a qualitative and exploratory study was performed by conducting 12 in depth interviews with 8 industrial and 4 academic participants. The characteristics that any cell factory must have were schematically listed, and commonly recognised opportunities were identified.

We found that academics are limited by only technical factors in their research, while industry is restricted in their research choices and flexibility by a series of technical, sector dependent and social factors. This leads to a misalignment of interest of academics and funding industrial partners, often resulting in miscommunication. Although both are of the opinion that academia must perform curiosity-driven research to find innovative solutions, there is a certain pressure to aim for short-term industrial applications. All these factors add up to the Valley of Death; the gap between development and market implementation.

A third party, in the form of start-up companies, could be the answer to bridging the Valley of Death.
A structured open dataset of government interventions in response to COVID-19
Authors: Desvars-Larrive Amelie , Dervic Elma , Haug Nils , Niederkrotenthaler Thomas , Chen Jiaying , Di Natale Anna , Lasser Jana , Gliga Diana S. , Roux Alexandra , Chakraborty Abhijit , Ten Alexandr , Dervic Alija , Pacheco Andrea , Cserjan David , Lederhilger Diana , Berishaj Dorontinë , Tames Erwin Flores , Takriti Huda , Korbel Jan , Reddish Jenny , Stangl Johannes , Hadziavdic Lamija , Stoeger Laura , Gooriah Leana , Geyrhofer Lukas , Ferreira Marcia R. , Vierlinger Rainer , Holder Samantha , Álvarez Samuel , Haberfellner Simon , Ahne Verena , Reisch Viktoria , Servedio Vito D.P. , Chen Xiao , Pocasangre-Orellana Xochilt María , Garcia David , Thurner Stefan
Published: May 2020

In response to the COVID-19 pandemic, governments have implemented a wide range of nonpharmaceutical interventions (NPIs). Monitoring and documenting government strategies during the COVID-19 crisis is crucial to understand the progression of the epidemic. Following a content analysis strategy of existing public information sources, we developed a specific hierarchical coding scheme for NPIs. We generated a comprehensive structured dataset of government interventions and their respective timelines of implementation. To improve transparency and motivate collaborative validation process, information sources are shared via an open library. We also provide codes that enable users to visualise the dataset. Standardization and structure of the dataset facilitate inter-country comparison and the assessment of the impacts of different NPI categories on the epidemic parameters, population health indicators, the economy, and human rights, among others. This dataset provides an in-depth insight of the government strategies and can be a valuable tool for developing relevant preparedness plans for pandemic. We intend to further develop and update this dataset on a weekly basis until the end of December 2020.
Identification of neutralizing human monoclonal antibodies from Italian Covid-19 convalescent patients
Authors: Andreano Emanuele , Nicastri Emanuele , Paciello Ida , Pileri Piero , Manganaro Noemi , Piccini Giulia , Manenti Alessandro , Pantano Elisa , Kabanova Anna , Troisi Marco , Vacca Fabiola , Cardamone Dario , De Santi Concetta , Agrati Chiara , Capobianchi Maria Rosaria , Castilletti Concetta , Emiliozzi Arianna , Fabbiani Massimiliano , Montagnani Francesca , Montomoli Emanuele , Sala Claudia , Ippolito Giuseppe , Rappuoli Rino
Published: May 2020

In the absence of approved drugs or vaccines, there is a pressing need to develop tools for therapy and prevention of Covid-19. Human monoclonal antibodies have very good probability of being safe and effective tools for therapy and prevention of SARS-CoV-2 infection and disease. Here we describe the screening of PBMCs from seven people who survived Covid-19 infection to isolate human monoclonal antibodies against SARS-CoV-2. Over 1,100 memory B cells were single-cell sorted using the stabilized prefusion form of the spike protein and incubated for two weeks to allow natural production of antibodies. Supernatants from each cell were tested by ELISA for spike protein binding, and positive antibodies were further tested for neutralization of spike binding to receptor(s) on Vero E6 cells and for virus neutralizationin vitro.From the 1,167 memory B specific for SARS-CoV-2, we recovered 318 B lymphocytes expressing human monoclonals recognizing the spike protein and 74 of these were able to inhibit the binding of the spike protein to the receptor. Finally, 17 mAbs were able to neutralize the virus when assessed for neutralizationin vitro. Lead candidates to progress into the drug development pipeline will be selected from the panel of neutralizing antibodies identified with the procedure described in this study.

One Sentence Summary

Neutralizing human monoclonal antibodies isolated from Covid-19 convalescent patients for therapeutic and prophylactic interventions.
A phylodynamic workflow to rapidly gain insights into the dispersal history and dynamics of SARS-CoV-2 lineages
Authors: Dellicour Simon , Durkin Keith , Hong Samuel L. , Vanmechelen Bert , Martí-Carreras Joan , Gill Mandev S. , Meex Cécile , Bontems Sébastien , André Emmanuel , Gilbert Marius , Walker Conor , De Maio Nicola , Faria Nuno R. , Hadfield James , Hayette Marie-Pierre , Bours Vincent , Wawina-Bokalanga Tony , Artesi Maria , Baele Guy , Maes Piet
Published: May 2020

Since the start of the COVID-19 pandemic, an unprecedented number of genomic sequences of the causative virus (SARS-CoV-2) have been generated and shared with the scientific community. The unparalleled volume of available genetic data presents a unique opportunity to gain real-time insights into the virus transmission during the pandemic, but also a daunting computational hurdle if analysed with gold-standard phylogeographic approaches. We here describe and apply an analytical pipeline that is a compromise between fast and rigorous analytical steps. As a proof of concept, we focus on the Belgium epidemic, with one of the highest spatial density of available SARS-CoV-2 genomes. At the global scale, our analyses confirm the importance of external introduction events in establishing multiple transmission chains in the country. At the country scale, our spatially-explicit phylogeographic analyses highlight that the national lockdown had a relatively low impact on both the lineage dispersal velocity and the long-distance dispersal events within Belgium. Our pipeline has the potential to be quickly applied to other countries or regions, with key benefits in complementing epidemiological analyses in assessing the impact of intervention measures or their progressive easement.
Knowledge, attitude and practice towards the novel corona virus among Bangladeshi people: Implications for mitigation measures
Authors: Paul Alak , Sikdar Dwaipayan , Hossain Mohammad Mosharraf , Amin Md Robed , Deeba Farah , Mahanta Janardan , Jabed Md. Akib , Islam Mohammad Mohaiminul , Noon Sharifa Jahan , Nath Tapan Kumar
Published: May 2020

The current novel coronavirus (nCoV) outbreak, COVID-19, was first reported in December 2019 in Wuhan, China has spread all over the world causing startling loss of lives, stalling the global economy and disrupting the social life. One of the challenges to contain the COVID-19 is making people adopt personal hygiene, social distancing and self-quarantine practices which are all related to knowledge, attitude and practice (KAP) of the people in respective countries. Bangladesh, the most densely populated countries with a fast-growing economy and moderate literacy rate, has shown many hiccups in its efforts to implement COVID-19 policies. Understanding KAP may give the policy makers to make informed decisions. Hence, this study aimed to make a quick assessment of KAP of people in relation to COVID-19 in Bangladesh. An online survey using a pre-tested questionnaire conducted in late March 2020 attained 1837 responses across Bangladesh. However, 1589 completed responses were included in statistical analysis to calculate KAP scores, their interrelations with socio-demographic variables. The overall KAP is poor with only 10% of the respondents showed good knowledge with parallel attitudes and practices. Socio-demographic factors have strong bearings on the KAP scores. Significantly higher KAP score is evident in female over male respondents, among aged (45 years and above) over younger respondents and among retired and homemakers above students and public service holders. The study indicated a panic fuelled by poor understanding of COVID-19 associated facts and the need for the government to ensure more granular and targeted awareness campaigns in a transparent and factual manner to gain public confidence and arrest more meaningful public participation in mitigation measures. The study provides a baseline of KAP among people in Bangladesh on COVID-19.
Optimal control of an SIR epidemic through finite-time non-pharmaceutical intervention
Authors: Ketcheson David I.
Published: May 2020

We consider the problem of controlling an SIR-model epidemic by temporarily reducing the rate of contact within a population. The control takes the form of a multiplicative reduction in the contact rate of infectious individuals. The control is allowed to be applied only over a finite time interval, while the objective is to minimize the total number of individuals infected in the long-time limit, subject to some cost function for the control. We first consider the no-cost scenario and analytically determine the optimal control and solution. We then study solutions when a cost of intervention is included, as well as a cost associated with overwhelming the available medical resources. Examples are studied through the numerical solution of the associated Hamilton-Jacobi-Bellman equation. Finally, we provide some examples related directly to the current pandemic.

AMS subject classification. 92D30, 34H05, 49N90, 92-10, 49L12
Epidemic Situation and Forecasting if COVID-19 in Saudi Arabia using SIR model
Authors: Khoj Haitham , Mujallad Alaa F
Published: May 2020

Background

Saudi Arabia is one of the countries affected by COVID-19 pandemic. This will lead to negative impacts in many sectors. Saudi Arabia not only plays an important role on the economical side because it is the leading country in oil production, but also because it is considered the heart of the Islamic countries. Although protective measures have been implemented in Saudi Arabia, the number of COVID-19 cases has increased.

Aims of the study

This study aimed to employ SIR model to forecast the peak of COVID-19 progression and an estimation of it is end in Saudi Arabia.

Method

Based on the World Health Organization data on COVID-19 progression in Saudi Arabia from March 3rd to April 29th, 2020, we reliably estimate the constant parameters and make predictions on the inflection point and potential ending time. Susceptible, Infected, and Recovered are the main components of the SIR model that were used to run the analysis.

Result

The data showed an interesting result about the peak of the disease progression. It is projected to occur around the 20th day after running the model. According to the model, the peak time will be around the 20th of May. Then the cases will decrease until the 55th day, which is around June 20th.

Conclusion

The result predicts a second peak and an estimation end of COVID-19 in Saudi Arabia. This data can inform the policy makers, who should try to contain the virus, to be prepared for what is coming next.

Key Messages:
Prevalence and factors associated with effective helmet use among motorcyclists in Mysuru city of Southern India
Authors: Setty Naveen Kikkeri Hanumantha , Sukumar Gautham Melur , Majgi Sumanth Mallikarjun , Goel Akhil Dhanesh , Sharma Prem Prakash , Anand Manasa Brahmanandam
Published: May 2020

Background

Helmet use reduces the risk and severity of head injury and death due to road traffic crash among motorcyclists. The protective efficacy of different types of helmets varies. Wearing firmly fastened full face helmet termed as effective helmet use provides greatest protection. This study estimates the prevalence and factors associated with effective helmet use among motorcyclists in Mysuru, a tier II city in Southern India.

Methodology

Cross sectional road side observational study of 3499 motorcyclists (2134 motorcycle riders and 1365 pillion riders) at four traffic intersections was done followed by interview of random sample of 129 of the above riders. Effective helmet use proportion and effective helmet use per 100 person-minutes of observation was calculated. Multivariate logistic regression analysis was done to identify factors associated with effective helmet use.

Results

Prevalence of effective helmet use was 28 per 100 riders and 19.5 per 100 person-minutes of observation in traffic intersections. Specific prevalence rates was higher in riders (34.5%), female riders (51.3%), male pillion riders (30.5%) . Riders commuting for work and school and those ever stopped by the police in the past 3 months had significantly higher odds of effective helmet use.

Conclusion

The effective helmet use among the motorcyclists in Mysore is very low. Strict enforcement and frequent checks by the police are necessary to increase the effective helmet use.
A retrospective comparison of deep learning to manual annotations for optic disc and optic cup segmentation in fundus photos
Authors: Fu Huazhu , Li Fei , Xu Yanwu , Liao Jingan , Xiong Jian , Shen Jianbing , Liu Jiang , Zhang Xiulan ,   for iChallenge-GON study group
Published: May 2020

Purpose

Optic disc (OD) and cup (OC) segmentation are fundamental for fundus image analysis. Manual annotation is time consuming, expensive, and highly subjective, while an automated system is invaluable to the medical community. The aim of this study is to develop a deep learning system to segment OD and OC in fundus photos, and evaluate how the algorithm compares against manual annotations.

Methods

A total of 1200 fundus photos with 120 glaucoma cases were collected. The OD and OC annotations were labeled by seven licensed ophthalmologists, and glaucoma diagnoses were based on comprehensive evaluations of the subject medical records. A deep learning system for OD and OC segmentation was developed. The performances of segmentation and glaucoma discriminating based on the cup-to-disc ratio (CDR) of automated model were compared against the manual annotations.

Results

The algorithm achieved an OD dice of 0.938 (95% confidence interval (CI), 0.934-0.941), OC dice of 0.801 (95% CI, 0.793-0.809), and CDR mean absolute error (MAE) of 0.077 (95% CI, 0.073-0.082). For glaucoma discriminating based on CDR calculations, the algorithm obtained an area under receiver operator characteristic curve (AUC) of 0.948 (95% CI, 0.920-0.973), with a sensitivity of 0.850 (95% CI, 0.794-0.923) and specificity of 0.853 (95% CI, 0.798-0.918).

Conclusions

We demonstrated the potential of the deep learning system to assist ophthalmologists in analyzing OD and OC segmentation and discriminating glaucoma from non-glaucoma subjects based on CDR calculations.

Translational Relevance

We investigate the segmentation of OD and OC by deep learning system compared against the manual annotations.
Elevated RDW is Associated with Increased Mortality Risk in COVID-19
Authors: Foy Brody H. , Carlson Jonathan C.T. , Reinertsen Erik , Valls Raimon Padros , Lopez Roger Pallares , Palanques-Tost Eric , Mow Christopher , Westover M. Brandon , Aguirre Aaron D. , Higgins John M.
Published: May 2020

Background

Coronavirus disease 2019 (COVID-19) is an acute respiratory illness with a high rate of hospitalization and mortality. Prognostic biomarkers are urgently needed. Red blood cell distribution width (RDW), a component of complete blood counts that reflects cellular volume variation, has been shown to be associated with elevated risk for morbidity and mortality in a wide range of diseases.

Methods

We retrospectively studied the relationship between RDW and COVID-19 mortality risk for 1198 adult patients diagnosed with SARS-CoV-2 at 4 Partners Healthcare Network Hospitals between March 4, 2020, and April 28, 2020.

Findings

Elevated RDW (> 14.5%) was associated with increased mortality in patients of all ages with a risk ratio of 2.5 (95% CI, 2.3 – 2.8). Stratified by age, the risk ratio was 6.2 (4.4 – 7.9, N = 312) < 50 years, 3.2 (2.5 – 4.1, N = 230) 50-60, 2.3 (1.6 – 3.1, N = 236) 60-70, 1.2 (0.7 – 1.8, N = 203) 70-80, and 1.9 (1.5 – 2.3, N = 216) > 80 years. RDW was significantly associated with mortality in Cox proportional hazards models adjusted for age, D-Dimer, absolute lymphocyte count, and common comorbidities (p < 1e-4 for RDW in all cases). Patients whose RDW increased during admission had a ~3-fold elevation in mortality risk compared to those whose RDW did not change.

Interpretation

Elevated RDW at diagnosis and an increase in RDW during admission are both associated with increased mortality risk for adult COVID-19 patients at a large academic medical center network.

Funding

This study was supported by funding from the One Brave Idea Initiative and the CRICO Risk Management Fund.
The race to find a SARS-CoV-2 drug can only be won by a few chosen drugs: a systematic review of registers of clinical trials of drugs aimed at preventing or treating COVID-19
Authors: Martinez-Vizcaino Vicente , Mesas Arthur E. , Cavero-Redondo Iván , Saz-Lara Alicia , Sequí-Dominguez Irene , Pascual-Morena Carlos , Álvarez-Bueno Celia
Published: May 2020

Considering the massive amount of clinical trial registers aimed to find effective drugs for the prevention and treatment of COVID-19, it is challenging to have a comprehensive view of which drugs are being studied more extensively and when is expected that we will have consistent results regarding their effectiveness. This systematic review included all clinical trials on pharmacological therapy related to COVID-19 and SARS-CoV-2 registered at the International Clinical Trials Registry Platform (WHO-ICTRP) up to April 22, 2020. Clinical trials characteristics (country, design, sample size, main outcomes, expected completion data, type of participants, length of the interventions, main outcomes). How many trials and the accumulated sample size by drug or combination of drugs, and by month in 2020 was depicted. We identified 412 clinical trials registers addressing the effect of pharmacological treatments on COVID-19, predominantly from Asia and Europe (42.2% and 31.1% of clinical trials registers, respectively). The most main outcomes studied were clinical recovery (54.4% of the clinical trials registers, respiratory recovery (28.2%) mortality (27.4%), viral load/negativity (20.4%). During 2020, a huge amount of clinical trials are expected to be completed: 41 trials (60,366 participants) using hydroxychloroquine, 20 trials (1,588 participants) using convalescent’s plasma, 18 trials (6,830 participants) using chloroquine, 12 trials (9,938 participants using lopinavir/ritonavir, 11 trials (1,250 participants) using favipiravir, 10 trials (2,175 participants) using tocilizumab and 6 trials (13,540 participants) using Remdesivir. The distribution of the number of registered clinical trials among the different therapeutic options leads to an excess of sample size for some and a lack for others. Our data allow us to conclude that by the end of June we will have results of almost 20 trials involving 40000 patients for hydroxychloroquine and 5 trials with 4500 patients for remdesivir; however, low statistical power is expected from the 9 clinical trials testing the efficacy of favipiravir or the 5 testing tocilizumab, since they will recruit less than 1000 patients each one.
Functional connectivity of white matter as a biomarker of cognitive decline in Alzheimer’s disease
Authors: Gao Yurui , Sengupta Anirban , Li Muwei , Zu Zhongliang , Rogers Baxter P. , Anderson Adam W. , Ding Zhaohua , Gore John C. ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: May 2020

Objective

In vivo functional changes in white matter during the progression of Alzheimer’s disease (AD) have not been previously reported. Our objectives are to measure changes in white matter functional connectivity (FC) in an aging population undergoing cognitive decline as AD develops, to establish their relationship to neuropsychological scores of cognitive abilities, and to assess their performance as predictors of AD.

Methods

Analyses were conducted using resting state functional MRI (rsfMRI) and neuropsychological data from 383 ADNI participants, including 136 cognitive normal (CN) controls, 46 with significant memory concern, 83 with early mild cognitive impairment (MCI), 37 with MCI, 46 with late MCI, and 35 with AD dementia. We used novel analyses of whole brain rsfMRI data to derive FC metrics between white matter tracts and discrete cortical volumes, as well as FC metrics between different white matter tracts, and their relationship to 6 cognitive measures. We then implemented supervised machine learning on white matter FCs to classify the participants and evaluated the performance.

Results

Significant decreases were found in white matter FCs with prominent, specific, regional deficits appearing in late MCI and AD dementia patients relative to CN. These changes significantly correlated with behavioral measurements of impairments in cognition and memory. The sensitivity and specificity for distinguishing AD dementia and CN using white matter FCs were 0.83 and 0.81 respectively.

Conclusions and Relevance

The white matter FC decreased in late MCI and AD dementia patients compared to CN participants, and the white matter FC correlates with cognitive measures. White matter FC based classification shows promise for differentiating AD patients from CN. It is suggested that white matter FC may be a novel imaging biomarker of AD progression.
Identification and Analysis of Shared Risk Factors in Sepsis and High Mortality Risk COVID-19 Patients
Authors: Das Sayoni , Taylor Krystyna , Pearson Matthew , Kozubek James , Pawlowski Marcin , Jensen Claus Erik , Skowron Zbigniew , Møller Gert Lykke , Strivens Mark , Gardner Steve
Published: May 2020

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a novel coronavirus strain disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease is highly transmissible and severe disease including viral sepsis has been reported in up to 16% of hospitalized cases. The admission characteristics associated with increased odds of hospital mortality among confirmed cases of COVID-19 include severe hypoxia, low platelet count, elevated bilirubin, hypoalbuminemia and reduced glomerular filtration rate. These symptoms correlate highly with severe sepsis cases. The diseases also share similar comorbidity risks including dementia, type 2 diabetes mellitus, coronary heart disease, hypertension and chronic renal failure. Sepsis has been observed in up to 59% of hospitalized COVID-19 patients.

It is highly desirable to identify risk factors and novel therapy/drug repurposing avenues for late-stage severe COVID-19 patients. This would enable better protection of at-risk populations and clinical stratification of COVID-19 patients according to their risk for developing life threatening disease.

METHODS

As there is currently insufficient data available for confirmed COVID-19 patients correlating their genomic profile, disease severity and outcome, co-morbidities and treatments as well as epidemiological risk factors (such as ethnicity, blood group, smoking, BMI etc.), a direct study of the impact of host genomics on disease severity and outcomes is not yet possible. We therefore ran a study on the UK Biobank sepsis cohort as a surrogate to identify sepsis associated signatures and genes, and correlated these with COVID-19 patients.

Sepsis is itself a life-threatening inflammatory health condition with a mortality rate of approximately 20%. Like the initial studies for COVID-19 patients, standard genome wide association studies (GWAS) have previously failed to identify more than a handful of genetic variants that predispose individuals to developing sepsis.

RESULTS

We used a combinatorial association approach to analyze a sepsis population derived from UK Biobank. We identified 70 sepsis risk-associated genes, which provide insights into the disease mechanisms underlying sepsis pathogenesis. Many of these targets can be grouped by common mechanisms of action such as endothelial cell dysfunction, PI3K/mTOR pathway signaling, immune response regulation, aberrant GABA and neurogenic signaling.

CONCLUSION

This study has identified 70 sepsis related genes, many of them for the first time, that can reasonably be considered to be potentially relevant to severe COVID-19 patients. We have further identified 59 drug repurposing candidates for 13 of these targets that can be used for the development of novel therapeutic strategies to increase the survival rate of patients who develop sepsis and potentially severe COVID-19.
A Computational Model for Estimating the Evolution of COVID-19 in Rondônia-Brazil
Authors: Junior Tito Dias , Machado Camila Bueno
Published: May 2020

In this work, the modified SEIR model was proposed to account separately for the tested and isolated cases, with severe and critical symptoms, from those not tested, with mild and moderate symptoms. Two parameters were estimated and evaluated for the cases registered in Rondônia, Brazil, between March 20 and April 22. The basic reproduction rate did not remain constant during the period, showing eventual variations due to social behavior. The results show that an increase in the proportion of testing to about 56% provided a significant decrease in confirmed cases, for the expansion of tested cases beyond the current testing criterion (20%) would help to identify and isolate also mild and moderate cases, generally referred to as asymptomatic.
BCG Vaccine Protection from Severe Coronavirus Disease 2019 (COVID19)
Authors: Escobar Luis E. , Molina-Cruz Alvaro , Barillas-Mury Carolina
Published: May 2020

A series of epidemiological explorations has suggested a negative association between national BCG vaccination policy and the prevalence and mortality of COVID-19. However, these comparisons are difficult to validate due to broad differences between countries such as socioeconomic status, demographic structure, rural vs. urban settings, time of arrival of the pandemic, number of diagnostic tests and criteria for testing, and national control strategies to limit the spread of COVID-19. We review evidence for a potential biological basis of BCG cross-protection from severe COVID-19, and refine the epidemiological analysis to mitigate effects of potentially confounding factors (e.g., stage of the COVID-19 epidemic, development, rurality, population density, and age structure). A strong correlation between the BCG index, an estimation of the degree of universal BCG vaccination deployment in a country, and COVID-19 mortality in different socially similar European countries was observed (r2= 0.88;p= 8×10-7), indicating that every 10% increase in the BCG index was associated with a 10.4% reduction in COVID-19 mortality. Results fail to confirm the null hypothesis of no-association between BCG vaccination and COVID-19 mortality, and suggest that BCG could have a protective effect. Nevertheless, the analyses are restricted to coarse-scale signals and should be considered with caution. BCG vaccination clinical trials are required to corroborate the patterns detected here, and to establish causality between BCG vaccination and protection from severe COVID-19. Public health implications of a plausible BCG cross-protection from severe COVID-19 are discussed.

Significance Statement

The COVID-19 pandemic is one of the most devastating in recent history. The bacillus Calmette-Guérin (BCG) vaccine against tuberculosis also confers broad protection against other infectious diseases, and it has been proposed that it could reduce the severity of COVID-19. This epidemiological study assessed the global linkage between BCG vaccination and COVID-19 mortality. Signals of BCG vaccination effect on COVID-19 mortality are influenced by social, economic, and demographic differences between countries. After mitigating multiple confounding factors, several significant associations between BCG vaccination and reduced COVID-19 deaths were observed. This study highlights the need for mechanistic studies behind the effect of BCG vaccination on COVID-19, and for clinical evaluation of the effectiveness of BCG vaccination to protect from severe COVID-19.
Severe obesity is associated with higher in-hospital mortality in a cohort of patients with COVID-19 in the Bronx, New York
Authors: Palaiodimos Leonidas , Kokkinidis Damianos G. , Li Weijia , Karamanis Dimitrios , Ognibene Jennifer , Arora Shitij , Southern William N. , Mantzoros Christos S.
Published: May 2020

Background & Aims

New York is the current epicenter of Coronavirus disease 2019 (COVID-19) pandemic. The underrepresented minorities, where the prevalence of obesity is higher, appear to be affected disproportionally. Our objectives were to assess the characteristics and early outcomes of patients hospitalized with COVID-19 in the Bronx and investigate whether obesity is associated with worse outcomes.

Methods

This retrospective study included the first 200 patients admitted to a tertiary medical center with COVID-19. The electronic medical records were reviewed at least three weeks after admission. The primary endpoint was in-hospital mortality.

Results

200 patients were included (female sex: 102, African American: 102). The median BMI was 30 kg/m2. The median age was 64 years. Hypertension (76%), hyperlipemia (46.2%), and diabetes (39.5%) were the three most common comorbidities. Fever (86%), cough (76.5%), and dyspnea (68%) were the three most common symptoms. 24% died during hospitalization (BMI <25 kg/m2: 31.6%, BMI 25-34 kg/m2: 17.2%, BMI≥35 kg/m2: 34.8%, p= 0.03). The multivariate analysis for mortality, demonstrates that BMI≥35 kg/m2 (OR: 3.78; 95% CI: 1.45 - 9.83; p=0.006), male sex (OR: 2.74; 95% CI: 1.25 - 5.98; p=0.011) and increasing age (OR: 1.73; 95% CI: 1.13 - 2.63; p=0.011) were independently associated with higher in hospital mortality. Similar results were obtained for the outcomes of increasing oxygen requirement and intubation.

Conclusions

In this cohort of hospitalized patients with COVID-19 in a minority-predominant population, severe obesity, increasing age, and male sex were associated with higher in-hospital mortality and in general worse in-hospital outcomes.
Comprehensive Testing Highlights Racial, Ethnic, and Age Disparities in the COVID-19 Outbreak: Epidemiological and Clinical Characteristic of Cases in Utah
Authors: Ahmed Sharia M , Shah Rashmee U. , Bale Margaret , Peacock Jordan B. , Berger Ben , Brown Alyssa , Mann Sara , West William , Martin Valerie , Fernandez Valerie , Grineski Sara , Brintz Benjamin , Samore Matthew H. , Ferrari Matthew J. , Leung Daniel T. , Keegan Lindsay T.
Published: May 2020

The United States (US), which is currently the epicenter for the COVID-19 pandemic, is a country whose demographic composition differs from that of other highly-impacted countries. US-based descriptions of SARS-CoV-2 infections have, for the most part, focused on patient populations with severe disease, captured in areas with limited testing capacity. The objective of this study is to compare characteristics of positive and negative SARS-CoV-2 patients, in a population primarily comprised of mild and moderate infections, identified from comprehensive population-level testing. Here, we extracted demographics, comorbidities, and vital signs from 20,088 patients who were tested for SARS-CoV-2 at University of Utah Health clinics, in Salt Lake County, Utah; and for a subset of tested patients, we performed manual chart review to examine symptoms and exposure risks. To determine risk factors for testing positive, we used logistic regression to calculate the odds of testing positive, adjusting for symptoms and prior exposure. Of the 20,088 individuals, 1,229 (6.1%) tested positive for SARS-CoV-2. We found that Non-White persons were more likely to test positive compared to non-Hispanic Whites (adjOR=1.1, 95% CI: 0.8, 1.6), and that this increased risk is more pronounced among Hispanic or Latino persons (adjOR=2.0, 95%CI: 1.3, 3.1). However, we did not find differences in the duration of symptoms nor type of symptom presentation between non-Hispanic White and non-White individuals. We found that risk of hospitalization increases with age (adjOR=6.9 95% CI: 2.1, 22.5 for age 60+ compared to 0-19), and additionally show that younger individuals (aged 019), were underrepresented both in overall rates of testing as well as rates of testing positive. We did not find major race/ethnic differences in hospitalization rates. In this analysis of predominantly non-hospitalized individuals tested for SARS-CoV-2, enabled by expansive testing capacity, we found disparities in both testing and SARS-CoV-2 infection status by race/ethnicity and by age. Further work on addressing racial and ethnic disparities, particularly among Hispanic/Latino communities (where SARS-CoV-2 may be spreading more rapidly due to increased exposure and comparatively reduced testing), will be needed to effectively combat COVID-19 in the US.
Using viral genomics to estimate undetected infections and extent of superspreading events for COVID-19
Authors: Li Lucy M. , Ayscue Patrick
Published: May 2020

Asymptomatic infections and limited testing capacity have led to under-reporting of SARS-CoV-2 cases. This has hampered the ability to ascertain true infection numbers, evaluate the effectiveness of surveillance strategies, determine transmission dynamics, and estimate reproductive numbers. Leveraging both viral genomic and time series case data offers methods to estimate these parameters.

Using a Bayesian inference framework to fit a branching process model to viral phylogeny and time series case data, we estimated time-varying reproductive numbers and their variance, the total numbers of infected individuals, the probability of case detection over time, and the estimated time to detection of an outbreak for 12 locations in Europe, China, and the United States.

The median percentage of undetected infections ranged from 13% in New York to 92% in Shanghai, China, with the length of local transmission prior to two cases being detected ranging from 11 days (95% CI: 4-21) in California to 37 days (9-100) in Minnesota. The probability of detection was as low as 1% at the start of local epidemics, increasing as the number of reported cases increased exponentially. The precision of estimates increased with the number of full-length viral genomes in a location. The viral phylogeny was informative of the variance in the reproductive number with the 32% most infectious individuals contributing 80% of total transmission events.

This is the first study that incorporates both the viral genomes and time series case data in the estimation of undetected COVID-19 infections. Our findings suggest the presence of undetected infections broadly and that superspreading events are contributing less to observed dynamics than during the SARS epidemic in 2003. This genomics-informed modeling approach could estimate in near real-time critical surveillance metrics to inform ongoing COVID-19 response efforts.

Funding

AWS provided computational credit via the Diagnostic Development Initiative.
Impact of small-area lockdowns for the control of the COVID-19 pandemic
Authors: Cuadrado Cristóbal , Monsalves María José , Gajardo Jean , Bertoglia María Paz , Nájera Manuel , Alfaro Tania , Canals Mauricio , Kaufman Jay S. , Peña Sebastián
Published: May 2020

Background

Countries confronting the COVID-19 pandemic are implementing different social distancing strategies. We evaluated the impact of small-area lockdowns in Chile, aimed to reduce viral transmission while minimizing the population disrupted. The effectiveness of this intervention on the outbreak control is unknown.

Methods

A natural experiment assessing the impact of small-area lockdowns between February 15th and April 25th, 2020. We used mobility data and official governmental reports to compare regions with small-area lockdowns versus regions without. The primary outcome was the mean difference in the effective reproductive number (Re) of COVID-19. Secondary outcomes were changes in mobility indicators. We used quasi-experimental methods for the analysis and examined the impact of other concurrent public health interventions to disentangle their effects.

Results

Small-area lockdown produced a sizable reduction in human mobility, equivalent to an 11.4% reduction (95%CI −14.4% to −8.38%) in public transport and similar effects in other mobility indicators. Ten days after implementation, the small-area lockdown produced a reduction of the effective reproductive number (Re) of 0.86 (95%CI −1.70 to −0.02). School and university closures, implemented earlier, led to a 40% reduction in urban mobility. Closure of educational institutions resulted in an even greater Re reduction compared with small-area lockdowns.

Conclusions

Small-area lockdowns produced a reduction in mobility and viral transmission, but the effects were smaller than the early closures of schools and universities. Small-area lockdowns may have a relevant supporting role in reducing SARS-CoV-2 transmission and could be useful for countries considering scaling-down stricter social distancing interventions.
Phasic containment of COVID-19 in substantially affected states of India
Authors: Mandal Manisha , Mandal Shyamapada
Published: May 2020

The spread of COVID-19 epidemic in some highly-impacted Indian states displayed a characteristic sub-exponential growth projected up to 3 May 2020, as a consequence of lockdown strategies, in addition to improvement of reproduction number (R), serial interval, and daily growth rate, but not case fatality rate (CFR). The effect of COVID-19 containment was more prominent in second phase of lockdown with declining R, which was still >1, suggesting the requirement of sustained interventions for effective containment of COVID-19 pandemic in Indian context.
A Divide and Conquer Strategy against the Covid-19 Pandemic?!
Authors: Mangat Patrick
Published: May 2020

The concern about (socio-)economic consequences of collective lockdowns in the Covid-19 pandemic calls for alternative strategies. We consider adivide and conquer strategyin which a high risk group (HRG) is put on strict isolation, whereas the remainder of the population is exposed to the virus, building up immunity against Covid-19. The question is whether this strategy may suppress the effective reproduction number below the critical value ofwithout further lockdown once the HRG is released from isolation. While this proposal appears already rather academic, we show thatcan only be obtained provided that the HRG is less than ~ 20 − 30% of the total population. Hence, this strategy is likely to fail in countries with a HRG larger than the given upper bound. In addition, we argue that the maximum infection rate occurring in this strategy is likely to exceed realistic capacities of most health care systems. While the conclusion is rather negative in this regard, we emphasise that the strategy ofstopping the curveat an early stage of the Covid-19 pandemic has a chance to work out. The required duration of the lockdown is estimated to be τ ~ 14 days/(up to some order one factor) for, provided a systematic tracing strategy of new infections exists for the subsequent relaxation phase. In this context we also argue whyremains the crucial parameter which needs to be accurately monitored and controlled.
Containing Covid-19 outbreaks with spatially targeted short-term lockdowns and mass-testing
Authors: Alsing Justin , Usher Naïri , Crowley Philip JD
Published: May 2020

We assess the efficacy of spatially targeted lockdown or mass-testing and case-isolation in individual communities, as a complement to contact-tracing and social-distancing, for containing SARS-CoV-2 outbreaks. Using the UK as a case study, we construct a stochastic branching process model for the virus transmission, embedded on a network interaction model encoding mobility patterns in the UK. The network model is based on commuter data from the 2011 census, a catchment area model for schools, and a phenomenological model for mobility and interactions outside of work, school, and the home. We show that for outbreak scenarios where contact-tracing and moderate social distancing alone provide suppression but do not contain the spread, targeted lockdowns or mass-testing interventions at the level of individual communities (with just a few thousand inhabitants) can be effective at containing outbreaks. For spatially targeted mass-testing, a moderate increase in testing capacity would be required (typically < 40000 additional tests per day), while for local lockdowns we find that only a small fraction (typically < 0.1%) of the population needs to be locked down at any one time (assuming that one third of transmission occurs in the home, at work or school, and out in the wider community respectively). The efficacy of spatially targeted interventions is contingent on an appreciable fraction of transmission events occurring within (relative to across) communities. Confirming the efficacy of community-level interventions therefore calls for detailed investigation of spatial transmission patterns for SARS-CoV-2, accounting for sub-community-scale transmission dynamics, and changes in mobility patterns due to the presence of other containment measures (such as social distancing and travel restrictions).
Awareness, knowledge, attitude and practice towards measures for prevention of the spread of COVID-19 in the Ugandans: A nationwide online cross-sectional Survey
Authors: Ssebuufu Robinson , Sikakulya Franck Katembo , Binezero Simon Mambo , Wasingya Lucien , Nganza Sifa K. , Ibrahim Bwaga , Kyamanywa Patrick
Published: May 2020

Background

The world is facing the Coronavirus pandemic which is highly infectious. A number of measures have been put in place to prevent its spread among the population. However, for these preventive measures to be effective, the population requires an appropriate and sufficient knowledge. Thus, a survey was conducted with the aim of assessing the awareness, knowledge, attitude and practices towards measures for prevention of the spread of Covid-19 amongst Ugandans.

Methods

This was a cross-sectional study conducted during the lockdown in Uganda. An online questionnaire and a snowballing approach was used for participant recruitment of 18 years above literate Ugandans. Data collection was done from 6thto 15thApril 2020 during which 1763 people participated. We analyzed all data using STATA 14.2, applying appropriate statistical tests.

Results

Out of 1763 participants, 97.6% were aware of the current pandemic. 83.9% of participants had a good knowledge score (21.8/27), 72.4% had a good attitude and 85.3% were practicing measures to prevent the spread of the Coronavirus disease. The ordered logistic regression showed that being a Health worker was significantly associated with a high knowledge (aOR:6 (3.32-10.93); a good attitude (aOR:2.5(1.68-3.8)]) and good practice (aOR:2.9 (1.95-4.2). On contrary, being a driver, business entrepreneur and a security personnel were found to have less rate in awareness, knowledge, attitude and practice.

Conclusions

Ugandans had a good overall awareness, knowledge, attitude and practice. However, there is still a gap of knowledge, attitude and practice among drivers, business entrepreneur and security personnel. There is a need to mobilize the population in the country to have the same degree of awareness and knowledge which will have an impact on attitude and practice to prevent spread of COVID-19.
Impact of essential workers in the context of social distancing for epidemic control
Authors: Milligan William R. , Fuller Zachary L. , Agarwal Ipsita , Eisen Michael B. , Przeworski Molly , Sella Guy
Published: May 2020

Many governments have responded to the ongoing COVID-19 pandemic by imposing social policies that restrict interactions outside of the home, resulting in a large fraction of the workforce either working from home or not working. However, to maintain essential services, a substantial number of workers are not subject to these limitations, and maintain many of their pre-intervention interactions. To explore how interactions among such “essential” workers, and between essential workers and the rest of the population, impact disease risk and the effectiveness of pandemic control, we evaluated several models of essential worker interactions within a standard epidemiology framework. The models were designed to correspond to key characteristics of, respectively, cashiers, factory employees, and healthcare workers. We find in all three models that essential workers are at substantially elevated risk of infection compared to the rest of the population, and that increasing the numbers of essential workers necessitates the imposition of more stringent interaction controls on the rest of the population in order to manage the pandemic. However, different archetypes of essential workers differ in both their individual probability of infection and impact on the broader pandemic, highlighting the need to understand and target for intervention the specific risks faced by different groups of essential workers.
Screening for SARS-CoV-2 infections with colorimetric RT-LAMP and LAMP sequencing
Authors: Thi Viet Loan Dao , Herbst Konrad , Boerner Kathleen , Meurer Matthias , Kremer Lukas PM , Kirrmaier Daniel , Freistaedter Andrew , Papagiannidis Dimitrios , Galmozzi Carla , Klein Steffen , Chlanda Petr , Khalid Dina , Miranda Isabel Barreto , Schnitzler Paul , Kräusslich Hans-Georg , Knop Michael , Anders Simon
Published: May 2020

The COVID-19 pandemic caused by the novel SARS-CoV-2 virus poses a significant public-health problem. In order to control the pandemic, rapid tests for detecting existing infections and assessing virus spread are critical.

Approaches to detect viral RNA based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) hold outstanding promise towards greatly simplified and broadly applicable testing methods. RT-LAMP assays appear more robust than qPCR-based methods and only require incubation at a constant temperature, thus eliminating the need for sophisticated instrumentation.

Here, we tested a two-color RT-LAMP protocol using clinical SARS-CoV-2 samples and also established a protocol that does not require prior RNA isolation (“swab-to-RT-LAMP”). Our study is based on several hundred clinical patient samples with a wide range of viral loads, thus allowing, for the first time, to accurately determine the sensitivity and specificity of the RT-LAMP assay for the detection of SARS-CoV-2 in patients. We found that RT-LAMP can reliably detect SARS-CoV-2 samples with a qPCR threshold cycle number (CT value) of up to 30 in the standard RT-qPCR assay. We used both, either purified RNA or direct pharyngeal swab specimens and showed that RT-LAMP assays have, despite a decreased sensitivity compared to RT-qPCR, excellent specificity. We also developed a multiplexed LAMP-sequencing protocol as a diagnostic and validation procedure to detect and record the outcome of RT-LAMP assays. LAMP-sequencing is fully scalable and can assess the results of thousands of LAMP reactions in parallel. Finally, we propose applications of RT-LAMP based assays for SARS-CoV-2 detection.