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Quantitative Methods in Demography: Methods and Related Applications in the Covid-19 Era 1st ed. 2022 [Hardback]

  • Formāts: Hardback, 504 pages, height x width: 235x155 mm, weight: 945 g, 1 Illustrations, black and white; XIV, 504 p. 1 illus., 1 Hardback
  • Sērija : The Springer Series on Demographic Methods and Population Analysis 52
  • Izdošanas datums: 01-Jun-2022
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030930041
  • ISBN-13: 9783030930042
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  • Formāts: Hardback, 504 pages, height x width: 235x155 mm, weight: 945 g, 1 Illustrations, black and white; XIV, 504 p. 1 illus., 1 Hardback
  • Sērija : The Springer Series on Demographic Methods and Population Analysis 52
  • Izdošanas datums: 01-Jun-2022
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030930041
  • ISBN-13: 9783030930042

This book provides quantitative and applied methodologies in the Covid-19 era exploring important issues in demography, population studies, and health. It provides insight into health and health measures as to the healthy life years lost and the healthy life expectancy related to Covid-19 pandemic. It also describes mortality and survival and focuses on data analysis in demography and population studies. Special methods and applications in demography and society are also described, thereby including applications in society, pension and insurance. As such, this book is a valuable guide for researchers, theoreticians and practitioners from various scientific fields.

Part I: Covid - 19 Studies.
Chapter
1. Reaction to COVID-19 Pandemic:
An Evaluation of Pandemic Management Around the World.
Chapter
2. Effects of
the Covid-19 pandemic in the area of tension between the economy and climate
change: A case study at rural and city district level in Southern Germany.-
Chapter
3. Predicting the second wave of COVID-19 pandemic through the
Dynamic Evolving Neuro Fuzzy Inference System.
Chapter
4. Losses in life
expectancy at birth from 2020: the impact of COVID-19 on the structure of
mortality by sex and age in Brazil.
Chapter
5. Stochastic Comparison between
the Original SARS-CoV 2 Genetic Structure and SARS-CoV2 - P.1 Variant.-
Chapter
6. Epidemic Management in the Emergency.  Protection Measures, Cost
and Compliance with Safety Protocols of the Employees of the Health Units.
The Case of the General University Hospital of Heraklion Venizeleio, The
Management and Pandemic of  SARS-CoV-2.- Part II: Global Health-Longevity.-
Chapter
7. How to estimate of the Healthy Life Expectancy (HLE) in the far
past: Switzerland (1876-2016) and forecasts to 2060 with comparisons with
HALE.
Chapter
8. Global health and longevity: an analysis of post-World War
II data.
Chapter
9. Health Care Need Adjusted Prospective Old-age Dependency
Ratio in Selected European Countries.
Chapter
10. Spreading disease modeling
using Markov random fields.- Part III: Mortality-Survival.
Chapter
11.
Mortality in Greece before and during the recent economic recession:
Short-terms effects of the economic austerity.
Chapter
12. Age exaggeration
ruses: infrequent age overstatement distorts the mortality curve at old age.-
Chapter
13. Completeness assessment of neonatal deaths in a region of Brazil:
linkage and imputing missing data.
Chapter
14. A Decomposition Analysis of
Differences in Length of life in the Czech Republic.
Chapter
15. Modelling
Nigerian Female Mortality: An Application of Four Stochastic Mortality
Models.
Chapter
16. Gender, health and socio-demographic influences on
updating subjective survival probabilities.
Chapter
17. Estimating
alcohol-attributable mortality in Czechia.
Chapter
18. Alcohol consumption
and marital status in the Czech Republic.
Chapter
19. Drug Addiction
Mortality among young Muscovites: official rates and actual scale.
Chapter
20. Factors reducing child mortality from congenital heart defects in
Russia.- Part IV: Special Methods.
Chapter
21. America's Zika virus and its
Similarities with African and Asian Lineages.
Chapter
22. A relative entropy
measure of divergences in labour market outcomes by educational attainment.-
Chapter
23. Assessing the intergenerational educational mobility in European
countries based on ESS data: 2002 2016.
Chapter
24. A different approach
to current developments in the 21st century - Grouping European countries in
terms of Mortality.- Part V: Various Applications.
Chapter
25. Examining
items suitability as the marker indicator in testing measurement
invariance.
Chapter
26. Real estate pension schemes: modeling and
perspectives.
Chapter
27. Insurance incentives to pursue social well-being.-
Chapter
28. Improved Insurers Capital Adequacy of reserve risk using copula
approach and hypothesis tests.
Chapter
29. Assessing the Performance of the
European Socio-economic Classification (ESeC) in Eight European Countries for
2018.
Chapter
30. A multisite-multivariate AQI and the determination of new
threshold values for health risk categories.
Chapter
31. Two indicators for
the social sciences.
Chapter
32. Life Expectancy and Different Parameter
Identification in Chinese Retirement Plan.
Chapter
33. Population loss due
to mental disorders caused by deviant behavior in the 2000s in Russia.
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 18 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.