bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating the determinants of COVID-19 mortality: A cross-country study
Authors: Squalli Jay
Published: May 2020

As the COVID-19 pandemic has spread to the entire world, a race to understand the virus and to find an effective and safe vaccine or treatment has triggered interest in the factors contributing to mortality. For instance, some studies have suggested that the BCG vaccine could protect from COVID-19 and nicotine patches could be therapeutic against the virus. This study makes use of data for about 140 countries to evaluate the determinants of COVID-19 mortality. It finds that a country's share of spending on health care (as a measure of a country's effectiveness in tracking, recording, and reporting COVID-19 deaths) is positively associated with COVID-19 deaths. It also finds that the share of people above 65 years of age, obesity, and urbanization are all positively associated with COVID-19 mortality. There is no evidence that BCG vaccination, smoking prevalence, and PM25 pollution have any link to COVID-19 mortality. These estimation results are robust to alternative specifications and after controlling for confounding factors and excluding outliers. Policymakers should allocate resources towards the protection of the elderly and those suffering from underlying conditions such as obesity. They should also exercise caution about administering nicotine patches or the BCG vaccine to fight COVID-19 without the backing of concrete scientific evidence.
Modelling and data-based analysis of COVID-19 outbreak in India : a study on impact of social distancing measures
Authors: SINGH ANURADHA , Barai Ankit Khushal , Shinde Amol
Published: May 2020

In this manuscript, we model and visualize the region-wise trends of the evolution to COVID-19
infections employing a SIR epidemiological model. The SIR dynamics are expressed using stochastic differential equations. We first optimize the parameters of the model using RMSE as loss function on the available data using L-BFGS-B gradient descent optimisation to minimise this loss function. This helps to gain better approximation of the models parameter for specific country or region. The derived parameters are aggregated to project future trends for the Indian subcontinent for next 180 days, which is currently at an early stage within the infection cycle. The projections are meant to function a suggestion for strategies for the socio-political counter measures to mitigate COVID-19. This study considers the current data for India from various open sources. The SIR models prediction is found following the actual trends till date. The inflection point analysis is important to find out which countries have reached their inflection point of the number of infection.
We found that if current restrictions like lockdown in India continues with same control till 20 May 2020 then,the number of infected patients will start decreasing after this date.
FORECASTING COVID-19 PANDEMIC: A DATA-DRIVEN ANALYSIS
Authors: Nabi Khondoker Nazmoon
Published: May 2020

In this paper, a new Susceptible-Exposed-Symptomatic Infectious-Asymptomatic Infectious-Quarantined-Hospitalized-Recovered-Dead (SEIDIUQHRD) deterministic compartmental model has been proposed and calibrated for interpreting the transmission dynamics of the novel coronavirus disease (COVID-19). The purpose of this study is to give a tentative prediction of the epidemic peak for Russia, Brazil, India and Bangladesh which could become the next COVID-19 hotspots in no time by using a Trust-region-reflective (TRR) algorithm which one of the well-known real data fitting techniques. Based on the publicly available epidemiological data from late January until 10 May, it has been estimated that the number of daily new symptomatic infectious cases for the above mentioned countries could reach the peak around the beginning of June with the peak size of ~ 15, 774 (95% CI, 13,814-17,734) symptomatic infectious cases in Russia, ~ 26, 449 (95% CI, 23,489-29,409) cases in Brazil, ~ 9, 504 (95% CI, 8,378-10,630) cases in India and ~ 2, 209 (95% CI, 1,878-2,540) cases in Bangladesh. As of May 11, 2020, incorporating the infectiousness capability of asymptomatic carriers, our analysis estimates the value of the basic reproduction number (R0) as of May 11, 2020 was found to be ~ 4.234 (95% CI, 3.764-4.7) in Russia,~ 5.347 (95% CI, 4.737-5.95) in Brazil, ~ 5.218 (95% CI, 4.56-5.81)in India, ~ 4.649 (95% CI, 4.17-5.12) in the United Kingdom and ~ 3.53 (95% CI, 3.12-3.94) in Bangladesh. Moreover, Latin hypercube sampling-partial rank correlation coefficient (LHS-PRCC) which is a global sensitivity analysis (GSA) method is applied to quantify the uncertainty of our model mechanisms, which elucidates that for Russia, the recovery rate of undetected asymptomatic carriers, the rate of getting home-quarantined or self-quarantined and the transition rate from quarantined class to susceptible class are the most influential parameters, whereas the rate of getting home-quarantined or self-quarantined and the inverse of the COVID-19 incubation period are highly sensitive parameters in Brazil, India, Bangladesh and the United Kingdom which could significantly affect the trans-mission dynamics of the novel coronavirus. Our analysis also suggests that relaxing social distancing restrictions too quickly could exacerbate the epidemic outbreak in the above-mentioned countries.
The impact of containment measures and air temperature on mitigating COVID-19 transmission: non-classical SEIR modeling and analysis
Authors: Liu Di , Tai Qidong , Wang Yaping , Pu Miao , Ge Sikai , Ji Tingting , Zhang Lei , Su Bo
Published: May 2020

Early non-pharmaceutical interventions (NPIs) are crucial to prevent and control of COVID-19 pandemic. We established a stochastic non-classical SEIR NPIs model (ScEIQRsh) which can quantify the three kinds of NPIs measures simultaneously to mimic the clustered intra-family or intra-acquaintance spreading pattern of COVID-19 under the effective integrated NPIs in Mainland China. Model simulation demonstrated that measures to diminish contactable susceptible (Sc), such as home confinement, travel constraint, social distancing etc. and measures to avoid delay of diagnosis and hospitalized isolation (η) were more effective but consumptive than contact tracing (κ, ρ). From fitted model by MCMC method, the proportion of asymptomatic infectors was 14.88% (IQR 8.17%, 25.37%). The association between air temperature and the fitted transmission rate (β) of COVID-19 suggests that COVID-19 pandemic would be seasonal with the optimal temperature range of 5°C-14°C and peak of 10°C for spreading, and vaccine is indispensable to ultimate prevention COVID-19.
THE MUC5B PROMOTOR POLYMORPHISM ASSOCIATES WITH SEVERE COVID-19
Authors: van Moorsel Coline H.M. , van der Vis Joanne J. , Benschop Claudia , Ruven Henk J.T. , Quanjel Marian , Grutters Jan C.
Published: May 2020

Background

Diversity in response to exposition to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is common and may be related to the innate immune response. The mucin MUC5B is an important component of the innate immune response and expression levels are associated with the MUC5B promoter polymorphism, rs35705950. The high expressing T-allele of rs35705950 is an accepted risk allele for a non-infectious aging lung disease called idiopathic pulmonary fibrosis (IPF). However, given the theory of trade-offs in aging lung disease and the importance of high expression for an adequate immune response, we hypothesize that the T-allele is protective against severe coronavirus disease 2019 (COVID-19).

Methods

We collected demographics, radiology, survival data and MUC5B rs35705950 allele status for 108 patients requiring hospitalisation for COVID-19 at St Antonius Hospital in The Netherlands. For comparison of allele frequencies and allele carriership with a white control cohort, the patient cohort was divided in a white (n=83) and non-white cohort.

Results

The patients had a median age of 66 years and consisted predominantly of males (74%) and 23 patients (21 %) died. The T-allele frequencies of rs35705950 in white patients was 0.04 which was significantly lower than the T-allele frequency of 0.10 in white controls (p= 0.02). Moreover, comparison of the number of carriers and non-carriers of the T allele showed that only 8.4% of patients carried the T-allele versus 18% of controls (p=0.029; OR= 0.41, CI=0.19-0.94).

Conclusions

The MUC5B rs35705950 promoter polymorphism associates with COVID-19. The risk allele (T) for IPF is protective against the development of severe COVID-19 disease. This is a further example of a trade-off between optimal expression levels in the respiratory system which associates with aging diseases. However, these results require further investigation.
Factors linked to changes in mental health outcomes among Brazilians in quarantine due to COVID-19
Authors: Stults-Kolehmainen Matthew , Filgueiras Alberto , Blacutt Miguel
Published: May 2020

This aim of this investigation was to track changes and risk factors for mental health outcomes during state-mandated quarantine in Brazil. Adults residing in Brazil (n = 360, 37.9 years old, 68.9% female) were surveyed at the start of quarantine and approximately three weeks later. Outcomes assessed included perceived stress, state anxiety and symptoms of depression. Aside from demographics, behaviours and attitudes assessed included exercise, diet, use of tele-psychotherapy and number of COVID-19 related risk factors, such as perceived risk of COVID-19, information overload, and feeling imprisoned. Overall, all mental health outcomes worsened from Time 1 to time 2, although there was a significant gender x time interaction for stress. 9.7% of the sample reported stress above the clinical cut-off (2 SD above mean), while 8.0% and 9.4% were above this cut-off for depression and anxiety, respectively. In repeated measures analysis, female gender, worsening diet and an excess of COVID-19 information was related to all mental health outcomes. Positive dietary changes were associated with decreases in depression and anxiety. Exercise frequency was positively related to state anxiety and perceived stress (0 days/week > 6 days/week). Those who did aerobic exercise did not have significantly increase in depression. Use of tele-psychotherapy predicted lower levels of depression and anxiety. In multiple regression, anxiety was predicted by the greatest number of COVID-19 specific factors. In conclusion, mental health outcomes worsened for Brazilians within the first month of quarantine and these changes are associated with a variety of risk factors.
Greater Severity and Functional Impact of Post-Traumatic Headache in Veterans with Comorbid Neck Pain following Traumatic Brain Injury
Authors: Shahidi Bahar , Bursch Robyn W , Carmel Jennifer S , Carranza Ashleigh C , Cooper Kelsey M , Lee Jayme V , O'Connor Colleen N , Sorg Scott F , Maluf Katrina S , Schiehser Dawn M
Published: May 2020

Purpose/Hypothesis: Traumatic brain injury (TBI) affects 1.7 million people in the U.S. annually, the majority being mild in severity (mTBI). Post-traumatic headache (PTH) is one of the most common symptoms experienced after mTBI caused by head or neck trauma and is often refractory to treatment. Although military Veterans commonly experience mTBI after blast or blunt injuries that likely affect musculoskeletal structures in the neck, the prevalence of cervical symptoms in Veterans with PTH following mTBI have not been well characterized. Similarly, the impact of comorbid neck pain on physical and psychosocial functioning in this population is unknown. This study aims to assess the prevalence of neck pain in Veterans with PTH following mTBI, and to compare the severity and functional impact of PTH between those with and without comorbid neck pain.
Number of Subjects: 33 Veterans with PTH after a military-related mTBI were identified from a secondary analysis of data from a prior study.
Materials and Methods: Participants were determined to have PTH if they responded to questions on the Patient Headache History Questionnaire (PHHQ), attributed PTH to an accident or injury, and reported PTH in the TBI history. Individuals with both PTH and comorbid neck pain (PTH+NP) were identified based on an affirmative response to one or more questions on the PHHQ indicating that HA episodes were either preceded or accompanied by neck pain. Standardized measures of HA severity and frequency, insomnia, fatigue, mood disorders (Depression, Anxiety, and Posttraumatic Stress Disorder), and physical and emotional role function (SF-36) were compared between groups with and without comorbid neck pain.
Results: Of the 33 participants with PTH, 22 (67%) also had neck pain. There were no differences in demographic or TBI-specific characteristics between groups (p>0.069). Sixty-three percent of the PTH+NP group reported severe or incapacitating HA, compared to 27% of those with PTH alone (P=0.049). Insomnia severity and fatigue were significantly greater in the PTH+NP group (P<0.040), and physical function due to bodily pain and physical role function was significantly lower in the PTH+NP group (P<0.036). There were no significant differences between groups for any of the mood or emotional-role functioning scales (P>0.326).
Conclusions: The majority of Veterans with mTBI and PTH reported comorbid neck pain. Veterans with PTH and NP reported increased severity of HA, insomnia, fatigue, and a greater physical, but not emotional functional limitations compared to those without NP.
A Risk Score to Predict Admission to Intensive Care Unit in Patients With COVID-19: The ABC-GOALS Score
Authors: Mejía-Vilet Juan M. , Córdova-Sánchez Bertha M. , Fernández-Camargo Dheni A. , Méndez-Pérez R. Angélica , Morales Buenrostro Luis E. , Hernández-Gilsoul Thierry
Published: May 2020

Objectives

COVID-19 pandemic poses a burden on hospital resources and intensive care unit (ICU) occupation. This study aimed to provide a scoring system that, assessed upon first-contact evaluation at the emergency department, predicts the need for ICU admission.

Methods

We prospectively assessed patients admitted to a COVID-19 reference center in Mexico City between March 16th and May 21st, and split them into development and validation cohorts. Patients were segregated into a group that required admission to ICU, and a group that never required ICU admission and was discharged from hospitalization. By logistic regression, we constructed predictive models for ICU admission, including clinical, laboratory, and imaging findings from the emergency department evaluation. The ABC-GOALS score was created by assigning values to the weighted odd ratios. The score was compared to other COVID-19 and pneumonia scores through the area under the curve (AUC).

Results

We included 569 patients divided into development (n=329) and validation (n=240) cohorts. One-hundred-fifteen patients from each cohort required admission to ICU. The clinical model (ABC-GOALSc) included sex, obesity, the Charlson comorbidity index, dyspnea, arterial pressure, and respiratory rate at triage evaluation. The clinical plus laboratory model (ABC-GOALScl) added serum albumin, glucose, lactate dehydrogenase, and S/F ratio to the clinical model. The model that included imaging (ABC-GOALSclx) added the CT scan finding of >50% lung involvement. The model AUC were 0.79 (95%CI 0.74-0.83) and 0.77 (95%CI 0.71-0.83), 0.86 (95%CI 0.82-0.90) and 0.87 (95%CI 0.83-0.92), 0.88 (95%CI 0.84-0.92) and 0.86 (95%CI 0.81-0.90) for the clinical, laboratory and imaging models in the development and validation cohorts, respectively. The ABC-GOALScl and ABC-GOALSclx scores outperformed other COVID-19 and pneumonia-specific scores.

Conclusion

The ABC-GOALS score is a tool to evaluate patients with COVID-19 at admission to the emergency department, which allows to timely predict their risk of admission to an ICU.
The Evaluation of Deep Neural Networks and X-Ray as a Practical Alternative for Diagnosis and Management of COVID-19
Authors: Elgendi Mohamed , Fletcher Rich , Howard Newton , Menon Carlo , Ward Rabab
Published: May 2020

High-resolution computed tomography radiology is a critical tool in the diagnosis and management of COVID-19 infection; however, in smaller clinics around the world, there is a shortage of radiologists available to analyze these images. In this paper, we compare the performance of 16 available deep learning algorithms to help identify COVID19. We utilize an already existing diagnostic technology (X-ray) and an already existing neural network (ResNet-50) to diagnose COVID-19. Our approach eliminates the extra time and resources needed to develop new technology and associated algorithm, thus aiding the front-line in the race against the COVID-19 pandemic. Results show that ResNet-50 is the optimal pretrained neural network for the detection of COVID-19, using three different cross-validation ratios, based on training time, accuracy, and network size. We also present a custom visualization of the results that can be used to highlight important visual biomarkers of the disease and disease progression.
Validity of Computer Based Administration of Cognitive Assessments compared to Traditional Paper-based Administration
Authors: Ye Siao , Ko Brian , Phi Huy , Eagleman David , Flores Benjamin , Katz Yael , Huang Bin , Hosseini Ghomi Reza
Published: May 2020

Traditional pen and paper based neuropsychological tests (NPT) for cognition assessment have several challenges limiting their use. They are time consuming, expensive, and require highly trained specialists to administer. This leads to testing being available to only a small portion of the population and often with wait times of several months. In clinical practice, we have found results tend not to be integrated effectively into assessment and plans of the ordering provider. Here we compared several tests using BrainCheck (BC), a computer-based NPT battery, to traditional paper-based NPT, by evaluating individual tests as well as comparing composite scores to scores on traditional screening tools. 26 volunteers took both paper-based tests and BC. We found scores of four assessments (Ravens Matrix, Digit Symbol Modulation, Stroop Color Word Test and Trails Making A&B Test) were highly correlated. The Balance Examination and Immediate/Delayed Hopkins Verbal Learning, however, were not correlated. The BC composite score was correlated to results of the Saint Louis University Mental Status (SLUMS) exam [1], the Mini-Mental State Examination (MMSE) [2], and the Montreal Cognitive Assessment (MoCA). Our results suggest BC may offer a computer-based avenue to address the gap between basic screening and formal neuropsychological testing.
Characterization of Neonatal Abstinence Syndrome in Arizona from 2010-2017
Authors: Eaves Emery R , Barber Jarret , Whealy Ryann , Clancey Sara A , Wright Rita , Cocking Jill Hager , Spadafino Joseph , Hepp Crystal M
Published: May 2020

This study aimed to characterize the population of newborn infants with neonatal abstinence syndrome (NAS) and mothers who were opioid dependent at the time of giving birth, in Arizona. We analyzed approximately 1.2 million electronic medical records from the Arizona Department of Health Services Hospital Discharge Database to identify patterns and disparities across socioeconomic, ethnic/racial, and/or geographic groupings. In addition, we identified comorbid conditions that are differentially associated with NAS in infants or opioid dependence in mothers. Our analysis was designed to assess whether indicators such as race/ethnicity, insurance payer, marital status, and comorbidities are related to the use of opioids while pregnant.
In this paper, we describe a population of mothers who are opioid dependent at the time of giving birth and infants who experience withdrawal due to opioid exposure in utero. While there have been studies of national trends in this population (see Patrick et al.), regional trends and issues are less well understood. Using data from the Arizona Department of Health Services Hospital Discharge Database, we find that women and infants who are non-Hispanic White and economically disadvantaged, tend be part of our populations of interest more frequently than expected. Additionally, we find that women who are opioid dependent at the time of giving birth are unmarried more often than expected, and we suggest that marital status could be a proxy for support. Finally, we report comorbidities, some of which have not been previously reported, associated with infants who have NAS and mothers who are opioid dependent.
Modelling lockdown measures in epidemic outbreaks using selective socio-economic containment with uncertainty
Authors: Albi Giacomo , Pareschi Lorenzo , Zanella Mattia
Published: May 2020

Abstract

After the introduction of drastic containment measures aimed at stopping the epidemic contagion from SARS-CoV2, many governments have adopted a strategy based on a periodic relaxation of such measures in the face of a severe economic crisis caused by lockdowns. Assessing the impact of such openings in relation to the risk of a resumption of the spread of the disease is an extremely difficult problem due to the many unknowns concerning the actual number of people infected, the actual reproduction number and infection fatality rate of the disease. In this work, starting from a compartmental model with a social structure and stochastic inputs, we derive models with multiple feedback controls depending on the social activities that allow to assess the impact of a selective relaxation of the containment measures in the presence of uncertain data. Specific contact patterns in the home, work, school and other locations have been considered. Results from different scenarios concerning the first wave of the epidemic in some major countries, including Germany, France, Italy, Spain, the United Kingdom and the United States, are presented and discussed.
Progression, recovery and fatality in patients with SARS-CoV-2 related pneumonia in Wuhan, China: a single-centered, retrospective, observational study
Authors: Wang Hua , Lu Yirong , Lv Qingquan , Wu Xiping , Hu Tian , Wang Kai , Liu Yumei , Hu Yuhai , Yu Lan , Fei Hexuan , Ba Zheng , Lin Xiaohua
Published: May 2020

Objectives To determine the case fatality rates and death risk factors.
Design Retrospective case series.
Setting A COVID-19 ward of a secondary Hospital in Wuhan, China.
Participants Consecutively hospitalized COVID-19 patients between Jan 3, 2020 and Feb 27, 2020. Outcomes were followed up to discharge or death.
Results Of 121 patients included, 66 (54.6%) were males. The median age was 59 (IQR: 46 to 67) years, and hypertension (33 patients; 27.3%) the leading comorbidity. Lymphopenia (83 of 115 patients; 72.2%) frequently occurred and then normalized on day 4 (IQR: 3 to 6) after admission in the survivors, with lung lesion absorbed gradually on day 8 (IQR: 6 to10) after onset (33 of 57 patients; 57.9%). The real-time polymerase chain reaction (RT-PCR) assays for SARS-CoV-2 were positive in 78 (78/108; 72.2%) patients, and a false-negative RT-PCR occurred in 15 (13.9%) patients. Hypoxemia occurred in 94 (94/117; 80.3%) patients, and supplemental oxygen was given in 88 (72.7%) patients, and mon-invasive or invasive ventilation in 20 (16.5%) cases. Corticosteroid use might link to death. The case fatality rates were 4.4% (one of 23 patients), 29.3% (12/41), 22.8% (13/57) or 45% (9/20) for patients with moderate, severe, critical illness or on ventilator. The length of hospital stay was 14 (IQR: 10 to 20) days, and selfcare ability worsened in 21 patients (21/66; 31.8%) cases. Patients over 60 years were most likely to have poorer outcomes, and increasing in age by one-year increased risk for death by 18% (CI: 1.04-1.32).
Conclusions In management of patients with SARS-CoV-2 pneumonia, especially the elderly with hypertension, close monitoring and appropriate supportive treatment should be taken earlier and aggressively to prevent from developing severe or critical illness. Corticosteroid use might link to death. Repeated RT-PCR tests or novel detection methods for SARS-CoV-2 should be adopted to improve diagnostic efficiency.
Environmental indicator for effective control of COVID-19 spreading
Authors: Lian Xinbo , Huang Jianping , Zhang Li , Liu Chuwei , Liu Xiaoyue , Wang Lina
Published: May 2020

Recently, a novel coronavirus (COVID-19) has caused viral pneumonia worldwide, spreading to more than 200 countries, posing a major threat to international health. To prevent the spread of COVID-19, in this study, we report that the city lockdown measure was an effective way to reduce the number of new cases, and the nitrogen dioxide (NO2) concentration can be adopted as an environmental lockdown indicator. In China, after strict city lockdown, the average NO2concentration decreased 55.7% (95% confidence interval (CI): 51.5-59.6%) and the total number of newly confirmed cases decreased significantly. Our results also indicate that the global airborne NO2concentration steeply decreased over the vast majority of COVID-19-hit areas based on satellite measurements. We found that the total number of newly confirmed cases reached an inflection point about two weeks after the lockdown. The total number of newly confirmed cases can be reduced by about 50% within 30 days of the lockdown. The stricter lockdown will help newly confirmed cases to decline earlier and more rapidly. Italy, Germany and France are good examples. Our results suggest that NO2satellite measurement can help decision makers effectively monitor control regulations to reduce the spread of COVID-19.
Tracking the COVID-19 pandemic in Australia using genomics
Authors: Seemann Torsten , Lane Courtney , Sherry Norelle , Duchene Sebastian , Goncalves da Silva Anders , Caly Leon , Sait Michelle , Ballard Susan A , Horan Kristy , Schultz Mark B , Hoang Tuyet , Easton Marion , Dougall Sally , Stinear Tim , Druce Julian , Catton mike , Sutton Brett , van Diemen Annaliese , Alpren Charles , Williamson Deborah , Howden Benjamin P
Published: May 2020

BACKGROUND: Whole-genome sequencing of pathogens can improve resolution of outbreak clusters and define possible transmission networks. We applied high-throughput genome sequencing of SARS-CoV-2 to 75% of cases in the State of Victoria (population 6.24 million) in Australia.

METHODS: Cases of SARS-CoV-2 infection were detected through active case finding and contact tracing. A dedicated SARS-CoV-2 multidisciplinary genomic response team was formed to enable rapid integration of epidemiological and genomic data. Phylodynamic analysis was performed to assess the putative impact of social restrictions.

RESULTS: Between 25 January and 14 April 2020, 1,333 COVID-19 cases were reported in Victoria, with a peak in late March. After applying internal quality control parameters, 903 samples were included in genomic analyses. Sequenced samples from Australia were representative of the global diversity of SARS-CoV-2, consistent with epidemiological findings of multiple importations and limited onward transmission. In total, 76 distinct genomic clusters were identified; these included large clusters associated with social venues, healthcare facilities and cruise ships. Sequencing of sequential samples from 98 patients revealed minimal intra-patient SARS-CoV-2 genomic diversity. Phylodynamic modelling indicated a significant reduction in the effective viral reproductive number (Re) from 1.63 to 0.48 after the implementation of travel restrictions and population-level physical distancing.

CONCLUSIONS: Our data provide a comprehensive framework for the use of SARS-CoV-2 genomics in public health responses. The application of genomics to rapidly identify SARS-CoV-2 transmission chains will become critically important as social restrictions ease globally. Public health responses to emergent cases must be swift, highly focused and effective.
A municipality-based approach using commuting census data to characterise the vulnerability to influenza-like epidemic: the COVID-19 application in Italy.
Authors: Savini Lara , Candeloro Luca , Calistri Paolo , Conte Annamaria
Published: May 2020

In February 2020, Italy became the epicentre for COVID-19 in Europe and at the beginning of March, in response to the growing epidemic, the Italian Government put in place emergency measures to restrict the movement of the population. Human mobility represents a crucial element to be considered in modelling human infectious diseases.
In this paper, we examined the mechanisms underlying COVID-19 propagation using a Susceptible-Infected stochastic model (SI) driven mainly by commuting network in Italy. We modelled a municipality-specific contact rate to capture the disease permeability of each municipality, considering the population at different times of the day and describing the characteristic of the municipalities as attractors of commuters or places that make their workforce available elsewhere.
The purpose of our analysis is to provide a better understanding of the epidemiological context of COVID-19 in Italy and to characterize the territory in terms of vulnerability at local or national level. The use of data at such a high spatial resolution allows highlighting particular situations on which the health authorities can promptly intervene to control the disease spread.
Our approach provides decision-makers with useful geographically detailed metrics to evaluate those areas at major risk for infection spreading and for which restrictions of human mobility would give the greatest benefits, not only at the beginning of the epidemic but also in the last phase, when the risks deriving from the gradual lockdown exit strategies must be carefully evaluated.
Gait asymmetry, and bilateral coordination of gait during a six-minute walk test in persons with multiple sclerosis
Authors: Plotnik Meir , Wagner Joanne M. , Adusumilli Gautam , Gottlieb Amihai , Naismith Robert T.
Published: May 2020

Gait impairments in persons with multiple sclerosis (pwMS) underlying reduced walking endurance are still poorly understood. Thus, our objective was to assessed gait asymmetry (GA) and bilateral coordination of gait (BCG), among pwMS during the six-minute walk test (6MWT) and their association with disease severity. For this aim, we recruited ninety-two pwMS (age: 46.6 ± 7.9; 83% females) with a broad range of clinical disability who completed the 6MWT wearing gait analysis system. GA was assessed by comparing left and right swing times, and BCG by using the phase coordination index (PCI). Several functional and subjective gait assessments were performed. Results show that gait is more asymmetric and less coordinated as the disease progresses (p<.0001). Participants with mild MS showed significant better BCG as reflected by lower PCI values in comparison to the other two MS severity groups (severe: p =.001, moderate: p=.02). GA and PCI also deteriorated significantly with time during the 6MWT (p<.0001). GA and PCI (i.e., BCG) show somewhat weaker associations with clinical MS status than associations observed between functional and subjective gait assessments and MS status. Similar to other neurological cohorts, GA and PCI are important parameters to assess and to target in interventions among pwMS.
Connecting coil-to-globule transitions to full phase diagrams for intrinsically disordered proteins
Authors: Zeng X. , Holehouse A. S. , Mittag T. , Chilkoti A. , Pappu R. V.
Published: May 2020

Phase separation is thought to underlie spatial and temporal organization that is required for controlling biochemical reactions in cells. Multivalence of interaction motifs also known as stickers is a defining feature of proteins that drive phase separation. Intrinsically disordered proteins with stickers uniformly distributed along the linear sequence can serve as scaffold molecules that drive phase separation. The sequence-intrinsic contributions of disordered proteins to phase separation can be discerned by computing or measuring sequence-specific phase diagrams. These help to delineate the combinations of protein concentration and a suitable control parameter such as temperature that support phase separation. Here, we present an approach that combines detailed simulations with a numerical adaptation of an analytical Gaussian cluster theory to enable the calculation of sequence-specific phase diagrams. Our approach leverages the known equivalence between the driving forces for single chain collapse in dilute solutions and the driving forces for phase separation in concentrated solutions. We demonstrate the application of the theory-aided computations through calculation of phase diagrams for a set of archetypal intrinsically disordered low complexity domains.

STATEMENT OF SIGNIFICANCE

Intrinsically disordered proteins that have the requisite valence of adhesive linear motifs can drive phase separation and give rise to membraneless biomolecular condensates. Knowledge of how phase diagrams vary with amino acid sequence and changes to solution conditions is essential for understanding how proteins contribute to condensate assembly and dissolution. In this work, we introduce a new two-pronged computational approach to predict sequence-specific phase diagrams. This approach starts by extracting key parameters from simulations of single-chain coil-to-globule transitions. We use these parameters in our numerical implementation of the Gaussian cluster theory (GCT) for polymer solutions to construct sequences-specific phase diagrams. The method is efficient and demonstrably accurate and should pave the way for high-throughput assessments of phase behavior.
The impact of opening dedicated clinics on disease transmission during an influenza pandemic
Authors: Swann Julie L , Shi Pengyi , Yan Jia , Keskinocak Pinar L , Shane Andi L
Published: May 2020

Dedicated clinics can be established in an influenza pandemic to isolate people and potentially reduce opportunities for influenza transmission. However, their operation requires resources and their existence may attract the worried-well. In this study, we quantify the impact of opening dedicated influenza clinics during a pandemic based on an agent-based simulation model across a time-varying social network of households, workplaces, schools, community locations, and health facilities in the state of Georgia. We calculate performance measures, including peak prevalence and total attack rate, while accounting for clinic operations, including timing and location. We find that opening clinics can reduce disease spread and hospitalizations even when visited by the worried-well, open for limited weeks, or open in limited locations, and especially when the clinics are in operation during times of highest prevalence. Specifically, peak prevalence, total attack rate, and hospitalization reduced 0.07-0.32%, 0.40-1.51%, 0.02-0.09%, respectively, by operating clinics for the pandemic duration.
Keywords: Pandemics; Human Influenza; Theoretical Models; Prevalence; Masks; Health Facilities
Adjusted fatality rates of COVID19 pandemic: a comparison across countries
Authors: Canelo-Aybar Carlos , Beltran Jessica , Santero Marilina , Alonso-Coello Pablo
Published: May 2020

Background: A key impact measure of COVID-19 pandemic is the case fatality rate (CFR), but estimating it during an epidemic is challenging as the true number of cases may remain elusive.
Objective: To estimate the CFR applying a delay-adjusted method across countries, exploring differences to simple methods and potential correlation to country level variables.
Methods: Secondary analysis of publicly available data from countries with ≥500 cases by April 30th. We calculated CFR adjusting for delay time from diagnosis to death and using simple methods for comparison. We performed a random effects meta-analysis to pooling CFRs for all countries and for those with high testing coverage and low positivity rate. We explored correlation of adjusted CFR with age structure and health care resources at country level.
Results: We included 107 countries and the Diamond Princess cruise-ship. The overall delay adjusted CFR was 2.8% (95%CI: 2.1 to 3.1) while naive CFR was 5.1% (95%CI: 4.1 to 6.2). In countries with high testing coverage/low positivity rate the pooled adjusted CFR was 2.1% (95%CI: 1.5 to 3.0), there was a correlation with age over 65 years (β = 0.12; 95%CI: 0.06 to 0.18), but not with number of physician or critical care beds. Naive method underestimated the CFR of the CFR with a median of 1.3% across countries.
Conclusion: Our best estimation of CFR across countries is 2% and varies according to the aged population size. Modelers and policy makers may consider these results to assess the impact of lockdowns or other mitigation policies.
A Sparse Gaussian Network Model for Prediction the Growth Trend of COVID-19 Overseas Import Case: When can Hong Kong Lift the International Traffic Blockad?
Authors: Rui Miao , Qi Dang , Yong Liang
Published: May 2020

The COVID-19 virus was first discovered from China. It has been widely spread internationally.
Currently, compare with the rising trend of the overall international epidemic situation, China's
domestic epidemic situation has been contained and shows a steady and upward trend. In this
situation, overseas imports have become the main channel for china to increase the number of
infected people. Therefore, how to track the spread channel of international epidemics and predict
the growth of overseas case imports is become an open research question. This study proposes a
Gaussian sparse network model based on lasso and uses Hong Kong as an example. To explore
the COVID-19 virus from a network perspective and analyzes 75 consecutive days of COV-19
data in 188 countries and regions around the world. This article establishes an epidemic spread
relationship network between Hong Kong and various countries and regions around the world
and build a regression model based on network information to fit Hong Kong's COV-19 epidemic growth data. The results show that the regression model based on the relationship network can better fit the existing cumulative number growth curve. After combining the SEIJR model, we predict the future development trend of cumulative cases in Hong Kong (without blocking international traffic). Based on the prediction results, we suggest that Hong Kong can lift the international traffic blockade from early to mid-June
Deposition distribution of the new coronavirus (SARS-CoV-2) in the human airways upon exposure to cough-generated aerosol
Authors: Madas Balázs G. , Füri Péter , Farkas Árpád , Nagy Attila , Czitrovszky Aladár , Balásházy Imre , Schay Gusztáv G. , Horváth Alpár
Published: May 2020

The new coronavirus disease 2019 (COVID-19) has been emerged as a rapidly spreading pandemic. The disease is thought to spread mainly from person-to-person through respiratory droplets produced when an infected person coughs, sneezes, or talks. The pathogen of COVID-19 is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It infects the cells binding to the angiotensin-converting enzyme 2 receptor (ACE2) which is expressed by cells throughout the airways as targets for cellular entry. Although the majority of persons infected with SARS-CoV-2 experience symptoms of mild upper respiratory tract infection, in some people infections of the peripheral airways result in severe, potentially fatal pneumonia. However, the induction of COVID-19 pneumonia requires that SARS-CoV-2 reaches the peripheral airways. While huge efforts have been made to understand the spread of the disease as well as the pathogenesis following cellular entry, much less attention is paid how SARS-CoV-2 from the environment reach the receptors of the target cells. The aim of the present study is to characterize the deposition distribution of SARS-CoV-2 in the airways upon exposure to cough-generated aerosol. For this purpose, the Stochastic Lung Deposition Model has been applied. Aerosol size distribution and breathing parameters were taken from the literature supposing normal breathing through the nose. We found that the probability of direct infection of the peripheral airways due to inhalation of aerosol generated by a bystander cough is very low. As the number of pathogens deposited in the extrathoracic airways is ~10 times higher than in the peripheral airways, we concluded that in most cases COVID-19 pneumonia must be preceded by SARS-CoV-2 infection of the upper airways. Our results suggest that without the enhancement of viral load in the upper airways, COVID-19 would be much less dangerous. The period between the onset of initial symptoms and the potential clinical deterioration could provide an opportunity for prevention of pneumonia by blocking or significantly reducing the transport of viruses towards the peripheral airways. Coughing into a tissue or cloth even at home in order to absorb the emitted aerosol is highly recommended to avoid the continuous re-inhalation of own cough.
Fast and accurate diagnostics from highly multiplexed sequencing assays
Authors: Booeshaghi A. Sina , Lubock Nathan B. , Cooper Aaron R. , Simpkins Scott W. , Bloom Joshua S. , Gehring Jase , Luebbert Laura , Kosuri Sriram , Pachter Lior
Published: May 2020

Scalable, inexpensive, accurate, and secure testing for SARS-CoV-2 infection is crucial for control of the novel coronavirus pandemic. Recently developed highly multiplexed sequencing assays that rely on high-throughput sequencing (HMSAs) can, in principle, meet these demands, and present promising alternatives to currently used RT-qPCR-based tests. However, the analysis and interpretation of HMSAs requires overcoming several computational and statistical challenges. Using recently acquired experimental data, we present and validate an accurate and fast computational testing workflow based on kallisto and bustools, that utilize robust statistical methods and fast, memory efficient algorithms for processing high-throughput sequencing data. We show that our workflow is effective at processing data from all recently proposed SARS-CoV-2 sequencing based diagnostic tests, and is generally applicable to any diagnostic HMSAs.
A new method for exploring gene-gene and gene-environment interactions in GWAS with tree ensemble methods and SHAP values
Authors: Johnsen Pål Vegard , Riemer-Sørensen Signe , DeWan Andrew Thomas , Cahill Megan E. , Langaas Mette
Published: May 2020

Background

The identification of gene-gene and gene-environment interactions in genome-wide association studies is challenging due to the unknown nature of the interactions and the overwhelmingly large number of possible combinations. Classical logistic regression models are suitable to look for pre-defined interactions while more complex models, such as tree ensemble models, with the ability to detect any interactions have previously been difficult to interpret. However, with the development of methods for model explainability, it is now possible to interpret tree ensemble models with a strong theoretical ground and efficiently.

Results

We propose a tree ensemble- and SHAP-based method for identifying as well as interpreting both gene-gene and gene-environment interactions on large-scale biobank data. A set of independent cross-validation runs are used to implicitly investigate the whole genome. We apply and evaluate the method using data from the UK Biobank with obesity as the phenotype. The results are in line with previous research on obesity as we identify top SNPs previously associated with obesity. We further demonstrate how to interpret and visualize interactions. The analysis suggests that the new method finds interactions between features that logistic regression models have difficulties in detecting.

Conclusions

The new method robustly detects interesting interactions, and can be applied to large-scale biobanks with high-dimensional data.
COVID-19 In Shang Hai: It is Worth Learning from the Successful Experience in Preventing and Controlling the Overseas Epidemic Situation
Authors: Dang Qi , Rui Miao , Yong Liang
Published: May 2020

COVID-19 first appeared in Wuhan, Hubei Province,China in late December 2019 and spread rapidly in China. Currently, the spread of local epidemics has been basically blocked. The import of overseas epidemics has become the main form of growth in China's new epidemic. As an important international transportation hub in China, Shanghai is one of the regions with the highest risk of imported cases abroad. Due to imported of overseas cases are affected by the international epidemic trend. The traditional infectious disease model is difficult to accurately predict the cumulative trend of cumulative cases in the Shanghai areas. It is also difficult to accurately evaluate the effectiveness of the international traffic blockade. In this situation, this study takes Shanghai as an example to propose a new type of infectious disease prediction model. The model first uses the sparse graph model to analyze the international epidemic spread network to find countries and regions related to Shanghai. Next, multiple regression models were used to fit the existing COV-19 growth data in Shanghai. Finally, the model can predict the growth curve of Shanghai's epidemic without blocking traffic. The results show that the control measures taken by Shanghai are very effective. At present, more and more countries and regions will face the current situation in Shanghai. We recommend that other countries and regions learn from Shanghai's successful experience in preventing overseas imports in order to fully prepare for epidemic prevention and control.
Olfactory and Gustatory Dysfunction as An Early Identifier of COVID-19 in Adults and Children: An International Multicenter Study
Authors: Qiu Chenghao , Cui Chong , Hautefort Charlotte , Haehner Antje , Zhao Jun , Yao Qi , Zeng Hui , Nisenbaum Eric J. , Liu Li , Zhao Yu , Zhang Di , Levine Corinna G. , Cejas Ivette , Dai Qi , Zeng Mei , Herman Philippe , Jourdaine Clement , With Katja de , Draf Julia , Chen Bing , Jayaweera Dushyantha T. , Denneny James C. , Casiano Roy , Yu Hongmeng , Eshraghi Adrien A. , Hummel Thomas , Liu Xuezhong , Shu Yilai , Lu Hongzhou
Published: May 2020

Abstract
Objective: Evaluate the prevalence and characteristics of olfactory or gustatory dysfunction in COVID-19 patients
Study Design: Multicenter Case Series
Setting: 5 tertiary care hospitals (3 in China, 1 in France, 1 in Germany)
Subjects and Methods: 394 PCR confirmed COVID-19 positive patients were screened, and those with olfactory or gustatory dysfunction were included. Data including demographics, COVID-19 severity, patient outcome, and the incidence and degree of olfactory and/or gustatory dysfunction were collected and analyzed. The Questionnaire of Olfactory Disorders (QOD) and Visual Analogue Scale (VAS) were used to quantify olfactory and gustatory dysfunction respectively. All subjects at one hospital (Shanghai) without subjective olfactory complaints underwent objective testing.
Results: Of 394 screened subjects, 161 (41%) reported olfactory and/or gustatory dysfunction and were included. Incidence of olfactory and/or gustatory disorders in Chinese (n=239), German (n=39) and French (n=116) cohorts were 32%, 69%, and 49% 138 respectively. The median age of included subjects was 39 years old, 92/161 (57%) were male, and 10/161 (6%) were children. Of included subjects, 10% had only olfactory or gustatory symptoms, and 19% had olfactory and/or gustatory complaints prior to any other COVID-19 symptom. Of subjects with objective olfactory testing, 10/90 demonstrated abnormal chemosensory function despite reporting normal subjective olfaction. 43% (44/102) of subjects with follow-up showed symptomatic improvement in olfaction or gustation.
Conclusions: Olfactory and/or gustatory disorders may represent early or isolated symptoms of SARS-CoV-2 infection. They may serve as a useful additional screening criterion, particularly for the identification of patients in the early stages of infection.