Sensitivity and elasticity analysis of novel corona virus transmission model: A mathematical approach

Das, Kalyan; Kumar, G. Ranjith; Reddy, K. Madhusudhan; Lakshminarayan, Kamakshi

doi:10.1016/j.sintl.2021.100088

Cited by 12 publications

(3 citation statements)

References 19 publications

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“…This study used the sensitivity analysis approach to quantitatively quantify the proposed QSAR model􀆳s dependency on molecular descriptor variables to validate its performance [44] . We use the controlled variable approach in the sensitivity analysis, a case study of the compound #1, which requires us to modify only one molecular description at a time.…”

Section: Sensitivity Analysismentioning

confidence: 99%

Machine Learning-Based Quantitative Structure-Activity Relationship and ADMET Prediction Models for ERα Activity of Anti-Breast Cancer Drug Candidates

2023

Wuhan Univ. J. Nat. Sci.

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Breast cancer is presently one of the most common malignancies worldwide, with a higher fatality rate. In this study, a quantitative structure-activity relationship (QSAR) model of compound biological activity and ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) properties prediction model were performed using estrogen receptor alpha (ERα) antagonist information collected from compound samples. We first utilized grey relation analysis (GRA) in conjunction with the random forest (RF) algorithm to identify the top 20 molecular descriptor variables that have the greatest influence on biological activity, and then we used Spearman correlation analysis to identify 16 independent variables. Second, a QSAR model of the compound were developed based on BP neural network (BPNN), genetic algorithm optimized BP neural network (GA-BPNN), and support vector regression (SVR). The BPNN, the SVR, and the logistic regression (LR) models were then used to identify and predict the ADMET properties of substances, with the prediction impacts of each model compared and assessed. The results reveal that a SVR model was used in QSAR quantitative prediction, and in the classification prediction of ADMET properties: the SVR model predicts the Caco-2 and hERG(human Ether-a-go-go Related Gene) properties, the LR model predicts the cytochrome P450 enzyme 3A4 subtype (CYP3A4) and Micronucleus (MN) properties, and the BPNN model predicts the Human Oral Bioavailability (HOB) properties. Finally, information entropy theory is used to validate the rationality of variable screening, and sensitivity analysis of the model demonstrates that the constructed model has high accuracy and stability, which can be used as a reference for screening probable active compounds and drug discovery.

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Section: Sensitivity Analysismentioning

confidence: 99%

Machine Learning-Based Quantitative Structure-Activity Relationship and ADMET Prediction Models for ERα Activity of Anti-Breast Cancer Drug Candidates

2023

Wuhan Univ. J. Nat. Sci.

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“…The literature on epidemic models is extensive, with structure variables and vaccination elements. In our References, we have listed many of such works [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 …”

Section: Introductionmentioning

confidence: 99%

An Epidemic Model with Infection Age and Vaccination Age Structure

Webb,

Zhao

2024

Infectious Disease Reports

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A model of epidemic dynamics is developed that incorporates continuous variables for infection age and vaccination age. The model analyzes pre-symptomatic and symptomatic periods of an infected individual in terms of infection age. This property is shown to be of major importance in the severity of the epidemic, when the infectious period of an infected individual precedes the symptomatic period. The model also analyzes the efficacy of vaccination in terms of vaccination age. The immunity to infection of vaccinated individuals varies with vaccination age and is also of major significance in the severity of the epidemic. Application of the model to the 2003 SARS epidemic in Taiwan and the COVID-19 epidemic in New York provides insights into the dynamics of these diseases. It is shown that the SARS outbreak was effectively contained due to the complete overlap of infectious and symptomatic periods, allowing for the timely isolation of affected individuals. In contrast, the pre-symptomatic spread of COVID-19 in New York led to a rapid, uncontrolled epidemic. These findings underscore the critical importance of the pre-symptomatic infectious period and the vaccination strategies in influencing the dynamics of an epidemic.

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“…To gain understanding of the spread and preventive measures that could be applied to curtail the disease, researchers have presented varieties of mathematical models. Das et al (2021) established a mathematical model that described COVID-19 transmission dynamics with isolation class. The data acquired from an ongoing event in India was applied and their outcomes recommended how to control the spread of COVID-19, keeping in mind contact and recovery rate.…”

Section: Introductionmentioning

confidence: 99%

Dynamical Analysis and Control Strategies for Capturing the Spread of COVID-19

et al. 2022

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In this paper, a study of preventive measures capable of curbing the spread of COVID 19pandemic to avoid its second wave was carried out. The existence and uniqueness of theproposed mathematical model is assured, the basic reproduction number is established, thelocal and global stability of the disease free equilibrium are well obtained and the variationaliteration method is applied to solve the mathematical model. Numerical simulation of theincluded control parameters are carried out. The obtained results and outcomes are presentedgraphically. It was revealed that enlightenment to vaccination awareness should be encouragedas vaccination is a good strategy of capturing the spread of the disease. Keywords: Covid-19, Basic Reproduction Number, Local stability, Global Stability,variational Iteration Method

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Sensitivity and elasticity analysis of novel corona virus transmission model: A mathematical approach

Cited by 12 publications

References 19 publications

Machine Learning-Based Quantitative Structure-Activity Relationship and ADMET Prediction Models for ERα Activity of Anti-Breast Cancer Drug Candidates

Machine Learning-Based Quantitative Structure-Activity Relationship and ADMET Prediction Models for ERα Activity of Anti-Breast Cancer Drug Candidates

An Epidemic Model with Infection Age and Vaccination Age Structure

Dynamical Analysis and Control Strategies for Capturing the Spread of COVID-19

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