This first volume of two provides quantitative techniques to estimate the healthy life years lost by expanding the classical life tables to include the proportion with disability calculated from life tables, along with a final part using the Sullivan method. The provided templates apply immediately to the life tables from the WHO, HMD, Eurostat and other life table providers. Furthermore, the possibility of creating new health indicators is explored along with Covid-19 pandemic management. A part of this book is devoted to mortality, epidemic models, and comparative studies in Czehia, Greece, and the EU. Data analysis and artificial intelligence methods are included to apply in demographic and Cox regression and gender differences and the gender gap in EU.

Mortality is tested with support methodology, while the gender gap is extensively analyzed and tested in several countries. The post covid-19 cases are tested, including mortality and economic implications for cases from China, Greece and Czechia. The stochastic behavior of Epstein-Barr Virus is explored and a case study on heterochronous Maltese SARS-CoV-2 genomic data is presented. Leonhard Euler’s research on the multiplication of the human race with models of population growth is also reviewed.

By providing a methodology to cope with health and mortality problems in demography and society in Volume 1 and quantifying important health parameters in Volume 2, the books are a valuable guide for researchers, theoreticians, and practitioners from various disciplines and especially applied demographers, health scientists, statisticians, economists, and sociologists.

Autorentext

Christos H. Skiadas, PhD, was the founder and director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete and former Vice-Rector of the University. He is chair of the Demographics Workshop series, the Applied Stochastic Models and Data Analysis Conference series and the Chaotic Modeling and Simulation Conference series. He has published more than 80 papers, three monographs, and 24 books, including probability, statistics, data analysis and forecasting. His research interests include innovation diffusion modeling and forecasting, life table data modeling, healthy life expectancy estimates, and deterministic, stochastic, and chaotic modeling.

Charilaos Skiadas, PhD, is professor in mathematics and computer science at Hanover College, Indiana, USA. His research interests encompass a wide array of mathematical and computing topics, ranging from algebraic geometry to statistics and programming languages to data science and health statemodeling.