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.
Part I: Healthy Life Expectancy Estimates.
Chapter
1. The Direct
Healthy Life Expectancy Estimates from Life Tables to Support HALE Measures
done by the World Health Organization. A New Tool for a Standard Measure.-
Chapter
2. Expanding the Life Tables for Companion Dogs in UK and Japan to
include the Healthy Life Expectancy.
Chapter
3. Direct Healthy Life
Expectancy Estimates from Life Tables with a Sullivan Extension: The case of
Brazil 2003.
Chapter
4. Assessment of the CASP-12 scale among people aged
50+ in Europe: An analysis using SHARE data.
Chapter
5. Possibilities of
creating new health indicators.
Chapter
6. Expanding the Life Tables to
Include the Healthy Life Expectancy.- Part II: Health Covid-19.
Chapter
7.
Reaction to COVID-19 Pandemic: An Evaluation of Pandemic Management Around
the World.
Chapter
8. A Stochastic Characterization of Omicron Variant of
SARS-COV 2 Virus.
Chapter
9. Factors associated with direct and indirect
aspects of loneliness among Europeansaged 50 or higher.
Chapter
10.
Neuropsychological Normed Measures for the Tinker Toy Test (TTT). Exploring
Latent Structures.
Chapter
11. A Tool for Measuring Alcohol Policy Scoring
in Czechia and EU: The Innovative Alcohol Policy Indicator.- Part III:
Mortality.
Chapter
12. Epidemic models with several levels of immunity.-
Chapter
13. Preventable deaths and maternal and newborn factors in a region
of Brazil: panel data modeling.
Chapter
14. Comparing the mortality regimes
in the once called western world..
Chapter
15. Kane Tanakas 119 birthday
and the Supercentenarians age estimation. Further remarks on the oldest old
record of 122 years by Jeanne Calment.
Chapter
16. Recent changes in Human
mortality: The case study of Greece.- Part IV: Data Analysis.
Chapter
17.
Exploring cross-national comparability of unidimensional constructs.
Chapter
18. Measuring transition smoothness into European labour market(s).
Chapter
19. Could the idea of equitable normal pension age stabilize the pension
system?.
Chapter
20. The use of Artificial Intelligence in medical imaging.
Scientific Research and opinions of doctors and radiologists towards the use
of artificial intelligence in radiology.- Part V: Demography And Society.-
Chapter
21. Semantic integration of data: from theory to social research
practice.
Chapter
22. To read on not to read? Examining the relation between
students well-being and their attitude towards reading.
Chapter
23. The
demographic, social and regional profile of peoples perceptions of their
social class: Evidence from the 7th wave of the World Values Survey,
2017-2020.
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.
