The United Nations publishes updated estimates and projections of the populations of all the world's countries, broken down by age and sex. These are widely used by international organizations, governments, the private sector and researchers, for example for climate modeling and for assessing progress towards the Millenium Development Goals. The UN's current projections are deterministic, but assessing uncertainty about population estimates and projections is important for policy-making and other purposes. We propose to develop a fully probabilistic population projection methodology. We will develop methods for probabilistic projection of fertility and mortality, taking account of within-country and between-country correlations. We will develop methods for probabilistic projection of international migration. We will develop methods for probabilistic population projections in countries with generalized sexually transmitted infectious disease epidemics, which require special methods because the demographic impact of such diseases is massive and different from most other diseases, being concentrated among the least vulnerable parts of the population, namely young sexually active adults. We will develop methods for reconstructing past populations with uncertainty from fragmentary data. We will produce publicly available software for implementing the new methods.

Public Health Relevance

Every two years, the United Nations produces projections of the populations of all countries, which are widely used by international organizations, governments, the private sector and researchers. The UN's current projections are deterministic, but assessing uncertainty about future population is important for policy-making and other purposes. We propose to develop a fully probabilistic population methodology which will be applicable to all countries, and will also be useful for assessing global concerns, such as climate change and progress towards the Millenium Development Goals.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
5R01HD070936-03
Application #
8624702
Study Section
Social Sciences and Population Studies Study Section (SSPS)
Program Officer
Newcomer, Susan
Project Start
2012-03-01
Project End
2017-02-28
Budget Start
2014-03-01
Budget End
2015-02-28
Support Year
3
Fiscal Year
2014
Total Cost
$297,661
Indirect Cost
$95,971
Name
University of Washington
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
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Scrucca, Luca; Fop, Michael; Murphy, T Brendan et al. (2016) mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models. R J 8:289-317
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Šev?íková, Hana; Raftery, Adrian E (2016) bayesPop: Probabilistic Population Projections. J Stat Softw 75:
Baraff, Aaron J; McCormick, Tyler H; Raftery, Adrian E (2016) Estimating uncertainty in respondent-driven sampling using a tree bootstrap method. Proc Natl Acad Sci U S A 113:14668-14673
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Azose, Jonathan J; Šev?íková, Hana; Raftery, Adrian E (2016) Probabilistic population projections with migration uncertainty. Proc Natl Acad Sci U S A 113:6460-5
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Scrucca, Luca; Raftery, Adrian E (2015) Improved initialisation of model-based clustering using Gaussian hierarchical partitions. Adv Data Anal Classif 9:447-460

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