Quantitative Demography and Health Estimates - Healthy Life Expectancy, Templates for Direct Estimates from Life Tables and other Applications

This book provides new theoretic and applied material with focus on quantitative methods and data analysis techniques applied in demography, population studies, health issues and statistics. It discusses the quantitative techniques to estimate the healthy life expectancy by expanding the classical life tables to include the proportion with disability calculated from life tables, along with the Sullivan method. The provided templates apply immediately to the life tables from WHO, HMD, Eurostat and other life table providers. Furthermore, the book explores the possibility of creating new health indicators along with Covid-19 pandemic management, factors associated to loneliness and an alcohol indicator. Part of the book is devoted to mortality, epidemic models, and the supercentenarians age estimation. Data analysis and artificial intelligence methods are included to apply in demographic and socio-economic cases. By providing a methodology to cope with health problems in demography and society by quantifying important health parameters, this book is a valuable guide for researchers, theoreticians, and practitioners from various disciplines and especially health scientists, statisticians, economists, and sociologists.



Christos H. Skiadas, PhD, was the founder and director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete, Greece, 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 an associate 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 state modeling.