COVID Transmission Modeling

This book will explore and formulate new mathematical/statistical and epidemiological modelling based on the research findings. It covers all the aspects of mitigation, estimation of transmission rate, control measures, economic impact assessment, genetic complexity of COVID and herd immunity.

Auteur

Basavarajaiah D M is an Associate Professor and Head of Department of Statistics and Computer Science, Karnataka Veterinary Animal and Fisheries Sciences University (B), Hebbal, Bangalore. He obtained his Ph.D from the National Institute of Epidemiology (NIE), ICMR, Chennai; (affiliated with the University of Madras). His research focuses on Statistical Theory, Statistical modeling on high-dimensional data sets in Agriculture, Medicine, Veterinary and Animal Sciences. He has written hundreds of research articles and published seven academic books in various national journals and Springer nature group (HIV transmission Statistical modeling and Design of Experiments and advanced statistical techniques in Clinical research). He is serving as an Editorial Board Member and Scientific Board advisor of various International indexed journals. He is also an Academic editor of Plos One, TJPRC,Science Publication, a Life Member of numerous academic organizations and has received several accolades for his academic and research Excellence (Chartered Scientist award stalwart by Science Council, the United Kingdom in Collaboration with Royal Statistical Society, International Scientist award honored by VDGOOD organization, Best Reviewer award-2016 'TRANSSTELLAR'Journal Publications and Research Consultancy,TJPRCLtd., (NAAS rated Journals), Bharathshikshratana and Indo-Dubai Achiever's Pacific award honored by Global Society of health and educational growth new Delhi, Best reviewer -2015, Best Scientific Board advisor- 2016 and Best editorial and researcher award bestowed by International Academy of Engineering Science and Technology, USA). He is a Fellow of Royal Statistical Society, UK (London) & Mathematical Society, UK (London). He is an active member of the Board of Studies and Academic Council of various Universities.

B Narasimha Murthy is a well -known academician and researcher, former Scientist 'G' (Director Grade cadre), National Institute of Epidemiology of ICMR, Chennai. Presently, he is a National Level Monitor, National Health Mission, MOH&FW, Government of India. He has obtained his Ph.D from International Institute of Population Science (IIPS), affiliated by Bombay University (1985). His area of research heeds Mathematical Statistics, Operational research, Clinical research, Public health, Demography and Vital Statistics, Mathematical modeling with respect to Medical Science and Public health. He has penned more than 100 research articles published in the reputed National and International Journals two books published in Springer Nature. He is Serving as an editorial Board Member and Scientific Board advisor of various International indexed MCI and UGC recognized Journals. He is also an Academic editor of Plos OneJournals, Science Publication, and a Life Member of various academic organizations. He has been honored with several accolades for his academic and research excellence viz.,Prof. R. N. Srivastava Gold medal award, 'Bharat Jyothi Award', 'Best Citizens of India etc. He served as a member of the Board of Studies of various National Universities (University of Madras, AcharyaNagarjunaUniversity &the University of Kerala). He is a visiting emeritus Professor of Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland, North Carolina University, USA etc. Reviewer of National and International Journals.

Texte du rabat

COVID Transmission Modelling: An Insight into Infectious Diseases Mechanism provides an interdisciplinary overview of Covid-19 pandemic crisis worldwide and covers various aspects of newer modelling techniques and practical solutions for health emergencies. The book aims to formulate various innovative and pragmatic mathematical, statistical and epidemiological models on Covid 19 real data sets. It emphasizes interdisciplinary theoretical postulates derived from practical insight and knowledge of public health. The book contains 12 chapters - each chapter provides invaluable and exploratory tools to enable explicit assumptions and highlight key health indicators , also determine geometric progression , control measures of diseases. The present developed models will allow us to extrapolate the exact reason for the outbreak and pave the way for recent scientific information on vaccine trail, socio-economic, psychological and disease burden worldwide. These advanced techniques of modelling and their applications are in greater need than ever for effective connection/association between mathematicians, statisticians, epidemiologists, researchers, clinicians and policy makers for taking appropriate decisions at right time. With advent of emerging health science, all models were demonstrated with real-life data sets, provided with more illustrations, eye-catching graphs and diagrams so that the readers can easily understand the concept of Covid 19 pandemic intervention, control measures and the impact.

Features

. Covers all the aspects of mitigation/control measures, estimation of transmission rate, control measures, economic impact assessment, genetic complexity of COVID, herd immunity and various methods including newer mathematical, statistical and epidemiological models in the analysis of COVID 19 pandemic outbreak

. All chapters cover application of innovative advanced statistical and epidemiological models and try to demonstrate possible solutions towards supportive treatment aspects of COVID 19 and their control measures

. All models can easily be followed in formulating the mathematical derivations and key points

. All chapters are supplemented with ample number of illustrations, images, diagrams and figures

This book is aimed at postgraduate students in medical, mathematics and statistical information. Researchers will also find this book helpful.

Contenu

1. Mathematical Modelling Approach to Covid19: Vetted Real Data. 1.1 Introduction. 1.2 Anatomical Structure of Covid19 virus. 1.3 Virus incubation period. 1.4 Epidemiological aspects of nCov2019 (SARS-Cov-19). 1.5 Economic impact of novel Corona virus. 1.6 Mathematical model for prediction of novel corona virus (n Cov 2019). 1.7 Model discussion. 1.8 Epidemiological model for estimation of hazard rate and geometric progression of nCov 2019. 1.9 Epidemiological Model approach of new diseases. 1.10 Susceptible -Infected - Recovered (SIR) epidemiological model of Covid. EP Model with varying population. 1.11 EP Model with varying population. 1.12 Machine learning model SARS-Cov-19. 1.13 Models of Machine Learning. 1.14 Covid Mathematical model approach to Indian Scenario. 1.15 Recommendations. 1.16 Study limitations. 1.17 Conflict of interest. 2. Time Series Stochastic Projection Models for estimation of Covid Trend. 2.1 Introduction. 2.2 Time series stochastic models. 2.3 ARIMA forecasting model approach to Covid progression estimation. 2.4 Model discussion. 2.5 Conclusion. 2.6 Random Walk Markov chain Stochastic Transient Model (RMCST). 2.7 Optimization of Covid cases from transition matrix. 2.8 Model diagnostic test. 2.9 Discussion. 2.10 Conclusion. 3. Study of anxiety and fear of Covid. 3.1 Introduction. 3.2 Methods. 3.3 Results. 3.4 Discussion. 3.5 Conclusion. 4. Covid19Gene sequencing Modeling. 4.2 Introduction. 4.3 Maxam and Gilbert Method. 4.4 Long read sequencing methods. 4.5 Cauchy distribution. 4.6 Exponential distribution. 4.7 Gamma distribution. 4.8 Log normal distribution. 4.9 Logistic distribution. 4.10 Poisson distribution. 4.11 Weibull distribution model. 4.12 Next generation sequencing. 4.13 Illumina Solexa Sequencing. 4.14 Model formulation 4.15 Pyro…