scholarly journals On Topological Properties of COVID-19: Predicting and Controling Pandemic Risk with Network Statistics

Author(s):  
Mike K.P. So ◽  
Amanda M.Y. Chu ◽  
Agnes Tiwari ◽  
Jacky N.L. Chan

The spread of coronavirus disease 2019 (COVID-19) has caused more than 24 million confirmed infected cases and more than 800,000 people died as of 28 August 2020. While it is essential to quantify risk and characterize transmission dynamics in closed populations using Susceptible-Infection-Recovered modeling, the investigation of the effect from worldwide pandemic cannot be neglected. This study proposes a network analysis to assess global pandemic risk by linking 164 countries in pandemic networks, where links between countries were specified by the level of 'co-movement' of newly confirmed COVID-19 cases. More countries showing increase in the COVID-19 cases simultaneously will signal the pandemic prevalent over the world. The network density, clustering coefficients, and assortativity in the pandemic networks provide early warning signals of the pandemic in late February 2020. We propose a preparedness pandemic risk score for prediction and a severity risk score for pandemic control. The preparedness risk score contributed by countries in Asia is between 25% to 50% most of the time after February and America contributes close to 50% recently. The high preparedness risk contribution implies the importance of travel restrictions between those countries. The severity risk score of America is greater than 50% after May and even exceeds 75% in July, signifying that the control of COVID-19 is still worrying in America. We can keep track of the pandemic situation in each country using an online dashboard to update the pandemic risk scores and contributions.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mike K. P. So ◽  
Amanda M. Y. Chu ◽  
Agnes Tiwari ◽  
Jacky N. L. Chan

AbstractThe spread of coronavirus disease 2019 (COVID-19) has caused more than 80 million confirmed infected cases and more than 1.8 million people died as of 31 December 2020. While it is essential to quantify risk and characterize transmission dynamics in closed populations using Susceptible-Infection-Recovered modeling, the investigation of the effect from worldwide pandemic cannot be neglected. This study proposes a network analysis to assess global pandemic risk by linking 164 countries in pandemic networks, where links between countries were specified by the level of ‘co-movement’ of newly confirmed COVID-19 cases. More countries showing increase in the COVID-19 cases simultaneously will signal the pandemic prevalent over the world. The network density, clustering coefficients, and assortativity in the pandemic networks provide early warning signals of the pandemic in late February 2020. We propose a preparedness pandemic risk score for prediction and a severity risk score for pandemic control. The preparedness risk score contributed by countries in Asia is between 25% and 50% most of the time after February and America contributes around 40% in July 2020. The high preparedness risk contribution implies the importance of travel restrictions between those countries. The severity risk score of America and Europe contribute around 90% in December 2020, signifying that the control of COVID-19 is still worrying in America and Europe. We can keep track of the pandemic situation in each country using an online dashboard to update the pandemic risk scores and contributions.


2014 ◽  
Vol 17 (3) ◽  
pp. 17-22 ◽  
Author(s):  
Svetlana Vladimirovna Mustafina ◽  
Galina Il'inichna Simonova ◽  
Oksana Dmitrievna Rymar

The worldwide prevalence of diabetes among adults (aged 20?79 years) was 8.35% in 2013, and this is expected to increase by 55% (592 million adults) by 2035. To avoid the increase in the prevalence of diabetes, primary prevention and early diagnosis of prediabetes are required. It is important to identify individuals at a high risk of hyperglycaemia using inexpensive and available methods. At present, risk score is an alternative to identify the risk of developing diabetes. There are approximately 10 types of risk scores in the world, and further research for the development and adaptation of risk scores for various populations are being conducted. The use of risk score methods for prediction allows the setting of the level of total risk, identification of high-risk patients and prescription of necessary preventive measures. Actual validation of existing diabetes risk score for the Russian population is being conducted. Assessment of the risk of diabetes is simple, fast, inexpensive, non-invasive and reliable.


2020 ◽  
Vol 11 (SPL1) ◽  
pp. 748-752
Author(s):  
Swapnali Khabade ◽  
Bharat Rathi ◽  
Renu Rathi

A novel, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causes severe acute respiratory syndrome and spread globally from Wuhan, China. In March 2020 the World Health Organization declared the SARS-Cov-2 virus as a COVID- 19, a global pandemic. This pandemic happened to be followed by some restrictions, and specially lockdown playing the leading role for the people to get disassociated with their personal and social schedules. And now the food is the most necessary thing to take care of. It seems the new challenge for the individual is self-isolation to maintain themselves on the health basis and fight against the pandemic situation by boosting their immunity. Food organised by proper diet may maintain the physical and mental health of the individual. Ayurveda aims to promote and preserve the health, strength and the longevity of the healthy person and to cure the disease by properly channelling with and without Ahara. In Ayurveda, diet (Ahara) is considered as one of the critical pillars of life, and Langhana plays an important role too. This article will review the relevance of dietetic approach described in Ayurveda with and without food (Asthavidhi visheshaytana & Lanhgan) during COVID-19 like a pandemic.


2020 ◽  
Vol 11 (SPL1) ◽  
pp. 758-762
Author(s):  
Amit Biswas ◽  
KunalChandankhede

Wuhan originated Covid-19 disease is caused by SARC-COV 2 virus. It is a contagious disease it spread all over the world. World health organization declared a global pandemic disease. In Covid-19 immunity plays an important role. In old age people or having other co-morbid conditions the mortality rate is more. Ayurveda has a big role in improved immunity or to intact immunity. The principle of Ayurveda is to keep individual swastha (diseases free). To maintain individual disease-free Ritucharya is one of the important subjects of Ayurveda. Aimed of study is to find out Ritucharya literature from the Ayurveda and modern research specifically Varsha and Sharad ritu. Ritucharya contains dietary regimen, living modification, common medicine, and contraindicated things those changing according to environmental change. Upcoming season in India is Varsha and Sharad ritu. Environmental changes are huge in this season and it directly affected human beings. So this study reveals property of ritu, dietary regimen, living modification, common medicine and contraindicated things in upcoming varsha and sharad ritu.


2020 ◽  
Author(s):  
Arathy Puthillam

That American and European participants are overrepresented in psychological studies has been previously established. In addition, researchers also often tend to be similarly homogenous. This continues to be alarming, especially given that this research is being used to inform policies across the world. In the face of a global pandemic where behavioral scientists propose solutions, we ask who is conducting research and on what samples. Forty papers on COVID-19 published in PsyArxiV were analyzed; the nationalities of the authors and the samples they recruited were assessed. Findings suggest that an overwhelming majority of the samples recruited were from the US and the authors were based in US and German institutions. Next, men constituted a large proportion of primary and sole authors. The implications of these findings are discussed.


Author(s):  
Ekta Shirbhate ◽  
Preeti Patel ◽  
Vijay K Patel ◽  
Ravichandran Veerasamy ◽  
Prabodh C Sharma ◽  
...  

: The novel coronavirus disease-19 (COVID-19), a global pandemic that emerged from Wuhan, China has today travelled all around the world, so far 216 countries or territories with 21,732,472 people infected and 770,866 deaths globally (as per WHO COVID-19 update dated August 18, 2020). Continuous efforts are being made to repurpose the existing drugs and develop vaccines for combating this infection. Despite, to date, no certified antiviral treatment or vaccine prevails. Although, few candidates have displayed their efficacy in in vitro studies and are being repurposed for COVID-19 treatment. This article summarizes synthetic and semi-synthetic compounds displaying potent activity in their clinical experiences or studies against COVID-19 and also focuses on mode of action of drugs being repositioned against COVID-19.


2021 ◽  
Vol 10 (5) ◽  
pp. 955
Author(s):  
Ovidiu Mitu ◽  
Adrian Crisan ◽  
Simon Redwood ◽  
Ioan-Elian Cazacu-Davidescu ◽  
Ivona Mitu ◽  
...  

Background: The current cardiovascular disease (CVD) primary prevention guidelines prioritize risk stratification by using clinical risk scores. However, subclinical atherosclerosis may rest long term undetected. This study aimed to evaluate multiple subclinical atherosclerosis parameters in relation to several CV risk scores in asymptomatic individuals. Methods: A cross-sectional, single-center study included 120 asymptomatic CVD subjects. Four CVD risk scores were computed: SCORE, Framingham, QRISK, and PROCAM. Subclinical atherosclerosis has been determined by carotid intima-media thickness (cIMT), pulse wave velocity (PWV), aortic and brachial augmentation indexes (AIXAo, respectively AIXbr), aortic systolic blood pressure (SBPao), and ankle-brachial index (ABI). Results: The mean age was 52.01 ± 10.73 years. For cIMT—SCORE was more sensitive; for PWV—Framingham score was more sensitive; for AIXbr—QRISK and PROCAM were more sensitive while for AIXao—QRISK presented better results. As for SBPao—SCORE presented more sensitive results. However, ABI did not correlate with any CVD risk score. Conclusions: All four CV risk scores are associated with markers of subclinical atherosclerosis in asymptomatic population, except for ABI, with specific particularities for each CVD risk score. Moreover, we propose specific cut-off values of CV risk scores that may indicate the need for subclinical atherosclerosis assessment.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hirak Shah ◽  
Thomas Murray ◽  
Jessica Schultz ◽  
Ranjit John ◽  
Cindy M. Martin ◽  
...  

AbstractThe EUROMACS Right-Sided Heart Failure Risk Score was developed to predict right ventricular failure (RVF) after left ventricular assist device (LVAD) placement. The predictive ability of the EUROMACS score has not been tested in other cohorts. We performed a single center analysis of a continuous-flow (CF) LVAD cohort (n = 254) where we calculated EUROMACS risk scores and assessed for right ventricular heart failure after LVAD implantation. Thirty-nine percent of patients (100/254) had post-operative RVF, of which 9% (23/254) required prolonged inotropic support and 5% (12/254) required RVAD placement. For patients who developed RVF after LVAD implantation, there was a 45% increase in the hazards of death on LVAD support (HR 1.45, 95% CI 0.98–2.2, p = 0.066). Two variables in the EUROMACS score (Hemoglobin and Right Atrial Pressure to Pulmonary Capillary Wedge Pressure ratio) were not predictive of RVF in our cohort. Overall, the EUROMACS score had poor external discrimination in our cohort with area under the curve of 58% (95% CI 52–66%). Further work is necessary to enhance our ability to predict RVF after LVAD implantation.


2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
D Radenkovic ◽  
S.C Chawla ◽  
G Botta ◽  
A Boli ◽  
M.B Banach ◽  
...  

Abstract   The two leading causes of mortality worldwide are cardiovascular disease (CVD) and cancer. The annual total cost of CVD and cancer is an estimated $844.4 billion in the US and is projected to double by 2030. Thus, there has been an increased shift to preventive medicine to improve health outcomes and development of risk scores, which allow early identification of individuals at risk to target personalised interventions and prevent disease. Our aim was to define a Risk Score R(x) which, given the baseline characteristics of a given individual, outputs the relative risk for composite CVD, cancer incidence and all-cause mortality. A non-linear model was used to calculate risk scores based on the participants of the UK Biobank (= 502548). The model used parameters including patient characteristics (age, sex, ethnicity), baseline conditions, lifestyle factors of diet and physical activity, blood pressure, metabolic markers and advanced lipid variables, including ApoA and ApoB and lipoprotein(a), as input. The risk score was defined by normalising the risk function by a fixed value, the average risk of the training set. To fit the non-linear model >400,000 participants were used as training set and >45,000 participants were used as test set for validation. The exponent of risk function was represented as a multilayer neural network. This allowed capturing interdependent behaviour of covariates, training a single model for all outcomes, and preserving heterogeneity of the groups, which is in contrast to CoxPH models which are traditionally used in risk scores and require homogeneous groups. The model was trained over 60 epochs and predictive performance was determined by the C-index with standard errors and confidence intervals estimated with bootstrap sampling. By inputing the variables described, one can obtain personalised hazard ratios for 3 major outcomes of CVD, cancer and all-cause mortality. Therefore, an individual with a risk Score of e.g. 1.5, at any time he/she has 50% more chances than average of experiencing the corresponding event. The proposed model showed the following discrimination, for risk of CVD (C-index = 0.8006), cancer incidence (C-index = 0.6907), and all-cause mortality (C-index = 0.7770) on the validation set. The CVD model is particularly strong (C-index >0.8) and is an improvement on a previous CVD risk prediction model also based on classical risk factors with total cholesterol and HDL-c on the UK Biobank data (C-index = 0.7444) published last year (Welsh et al. 2019). Unlike classically-used CoxPH models, our model considers correlation of variables as shown by the table of the values of correlation in Figure 1. This is an accurate model that is based on the most comprehensive set of patient characteristics and biomarkers, allowing clinicians to identify multiple targets for improvement and practice active preventive cardiology in the era of precision medicine. Figure 1. Correlation of variables in the R(x) Funding Acknowledgement Type of funding source: None


2021 ◽  
Vol 9 (5) ◽  
pp. e001942
Author(s):  
Xu Yang ◽  
Ying Hu ◽  
Keyan Yang ◽  
Dongxu Wang ◽  
Jianzhen Lin ◽  
...  

BackgroundThis study was designed to screen potential biomarkers in plasma cell-free DNA (cfDNA) for predicting the clinical outcome of immune checkpoint inhibitor (ICI)-based therapy in advanced hepatobiliary cancers.MethodsThree cohorts including 187 patients with hepatobiliary cancers were recruited from clinical trials at the Peking Union Medical College Hospital. Forty-three patients received combination therapy of programmed cell death protein 1 (PD-1) inhibitor with lenvatinib (ICI cohort 1), 108 patients received ICI-based therapy (ICI cohort 2) and 36 patients received non-ICI therapy (non-ICI cohort). The plasma cfDNA and blood cell DNA mutation profiles were assessed to identify efficacy biomarkers by a cancer gene-targeted next-generation sequencing panel.ResultsBased on the copy number variations (CNVs) in plasma cfDNA, the CNV risk score model was constructed to predict survival by using the least absolute shrinkage and selection operator Cox regression methods. The results of the two independent ICI-based therapy cohorts showed that patients with lower CNV risk scores had longer overall survival (OS) and progression-free survival (PFS) than those with high CNV risk scores (log-rank p<0.01). In the non-ICI cohort, the CNV risk score was not associated with PFS or OS. Furthermore, the results indicated that 53% of patients with low CNV risk scores achieved durable clinical benefit; in contrast, 88% of patients with high CNV risk scores could not benefit from combination therapy (p<0.05).ConclusionsThe CNVs in plasma cfDNA could predict the clinical outcome of the combination therapy of PD-1 inhibitor with lenvatinib and other ICI-based therapies in hepatobiliary cancers.


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