Modeling age-specific mortality for countries with generalized HIV epidemics.
Identifieur interne : 000549 ( PubMed/Curation ); précédent : 000548; suivant : 000550Modeling age-specific mortality for countries with generalized HIV epidemics.
Auteurs : David J. Sharrow [États-Unis] ; Samuel J. Clark [Ghana] ; Adrian E. Raftery [États-Unis]Source :
- PloS one [ 1932-6203 ] ; 2014.
Descripteurs français
- KwdFr :
- MESH :
- mortalité : Infections à VIH.
- Facteurs de l'âge, Humains, Modèles théoriques, Prévalence, Tables de survie, Épidémies.
English descriptors
- KwdEn :
- MESH :
- mortality : HIV Infections.
- statistics & numerical data : Epidemics.
- Age Factors, Humans, Life Tables, Models, Theoretical, Prevalence.
Abstract
In a given population the age pattern of mortality is an important determinant of total number of deaths, age structure, and through effects on age structure, the number of births and thereby growth. Good mortality models exist for most populations except those experiencing generalized HIV epidemics and some developing country populations. The large number of deaths concentrated at very young and adult ages in HIV-affected populations produce a unique 'humped' age pattern of mortality that is not reproduced by any existing mortality models. Both burden of disease reporting and population projection methods require age-specific mortality rates to estimate numbers of deaths and produce plausible age structures. For countries with generalized HIV epidemics these estimates should take into account the future trajectory of HIV prevalence and its effects on age-specific mortality. In this paper we present a parsimonious model of age-specific mortality for countries with generalized HIV/AIDS epidemics.
DOI: 10.1371/journal.pone.0096447
PubMed: 24853081
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Clark</name><affiliation wicri:level="1"><nlm:affiliation>Department of Sociology, University of Washington, Seattle, Washington, United States of America; Institute of Behavioral Science (IBS), University of Colorado at Boulder, Boulder, Colorado, United States of America; MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; ALPHA Network, London School of Hygiene and Tropical Medicine, London, United Kingdom; INDEPTH Network, Accra, Ghana.</nlm:affiliation><country xml:lang="fr">Ghana</country><wicri:regionArea>Department of Sociology, University of Washington, Seattle, Washington, United States of America; Institute of Behavioral Science (IBS), University of Colorado at Boulder, Boulder, Colorado, United States of America; MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; ALPHA Network, London School of Hygiene and Tropical Medicine, London, United Kingdom; INDEPTH Network, Accra</wicri:regionArea></affiliation></author><author><name sortKey="Raftery, Adrian E" sort="Raftery, Adrian E" uniqKey="Raftery A" first="Adrian E" last="Raftery">Adrian E. Raftery</name><affiliation wicri:level="1"><nlm:affiliation>Department of Statistics, University of Washington, Seattle, Washington, United States of America; Department of Sociology, University of Washington, Seattle, Washington, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Statistics, University of Washington, Seattle, Washington, United States of America; Department of Sociology, University of Washington, Seattle, Washington</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2014">2014</date><idno type="RBID">pubmed:24853081</idno><idno type="pmid">24853081</idno><idno type="doi">10.1371/journal.pone.0096447</idno><idno type="wicri:Area/PubMed/Corpus">000549</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000549</idno><idno type="wicri:Area/PubMed/Curation">000549</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000549</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Modeling age-specific mortality for countries with generalized HIV epidemics.</title><author><name sortKey="Sharrow, David J" sort="Sharrow, David J" uniqKey="Sharrow D" first="David J" last="Sharrow">David J. Sharrow</name><affiliation wicri:level="1"><nlm:affiliation>Department of Sociology, University of Washington, Seattle, Washington, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Sociology, University of Washington, Seattle, Washington</wicri:regionArea></affiliation></author><author><name sortKey="Clark, Samuel J" sort="Clark, Samuel J" uniqKey="Clark S" first="Samuel J" last="Clark">Samuel J. Clark</name><affiliation wicri:level="1"><nlm:affiliation>Department of Sociology, University of Washington, Seattle, Washington, United States of America; Institute of Behavioral Science (IBS), University of Colorado at Boulder, Boulder, Colorado, United States of America; MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; ALPHA Network, London School of Hygiene and Tropical Medicine, London, United Kingdom; INDEPTH Network, Accra, Ghana.</nlm:affiliation><country xml:lang="fr">Ghana</country><wicri:regionArea>Department of Sociology, University of Washington, Seattle, Washington, United States of America; Institute of Behavioral Science (IBS), University of Colorado at Boulder, Boulder, Colorado, United States of America; MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; ALPHA Network, London School of Hygiene and Tropical Medicine, London, United Kingdom; INDEPTH Network, Accra</wicri:regionArea></affiliation></author><author><name sortKey="Raftery, Adrian E" sort="Raftery, Adrian E" uniqKey="Raftery A" first="Adrian E" last="Raftery">Adrian E. Raftery</name><affiliation wicri:level="1"><nlm:affiliation>Department of Statistics, University of Washington, Seattle, Washington, United States of America; Department of Sociology, University of Washington, Seattle, Washington, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Statistics, University of Washington, Seattle, Washington, United States of America; Department of Sociology, University of Washington, Seattle, Washington</wicri:regionArea></affiliation></author></analytic><series><title level="j">PloS one</title><idno type="eISSN">1932-6203</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Age Factors</term><term>Epidemics (statistics & numerical data)</term><term>HIV Infections (mortality)</term><term>Humans</term><term>Life Tables</term><term>Models, Theoretical</term><term>Prevalence</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Facteurs de l'âge</term><term>Humains</term><term>Infections à VIH (mortalité)</term><term>Modèles théoriques</term><term>Prévalence</term><term>Tables de survie</term><term>Épidémies ()</term></keywords><keywords scheme="MESH" qualifier="mortality" xml:lang="en"><term>HIV Infections</term></keywords><keywords scheme="MESH" qualifier="mortalité" xml:lang="fr"><term>Infections à VIH</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Epidemics</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Age Factors</term><term>Humans</term><term>Life Tables</term><term>Models, Theoretical</term><term>Prevalence</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Facteurs de l'âge</term><term>Humains</term><term>Modèles théoriques</term><term>Prévalence</term><term>Tables de survie</term><term>Épidémies</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In a given population the age pattern of mortality is an important determinant of total number of deaths, age structure, and through effects on age structure, the number of births and thereby growth. Good mortality models exist for most populations except those experiencing generalized HIV epidemics and some developing country populations. The large number of deaths concentrated at very young and adult ages in HIV-affected populations produce a unique 'humped' age pattern of mortality that is not reproduced by any existing mortality models. Both burden of disease reporting and population projection methods require age-specific mortality rates to estimate numbers of deaths and produce plausible age structures. For countries with generalized HIV epidemics these estimates should take into account the future trajectory of HIV prevalence and its effects on age-specific mortality. In this paper we present a parsimonious model of age-specific mortality for countries with generalized HIV/AIDS epidemics.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">24853081</PMID><DateCreated><Year>2014</Year><Month>05</Month><Day>23</Day></DateCreated><DateCompleted><Year>2015</Year><Month>06</Month><Day>01</Day></DateCompleted><DateRevised><Year>2017</Year><Month>02</Month><Day>20</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>9</Volume><Issue>5</Issue><PubDate><Year>2014</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS ONE</ISOAbbreviation></Journal><ArticleTitle>Modeling age-specific mortality for countries with generalized HIV epidemics.</ArticleTitle><Pagination><MedlinePgn>e96447</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0096447</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">In a given population the age pattern of mortality is an important determinant of total number of deaths, age structure, and through effects on age structure, the number of births and thereby growth. Good mortality models exist for most populations except those experiencing generalized HIV epidemics and some developing country populations. The large number of deaths concentrated at very young and adult ages in HIV-affected populations produce a unique 'humped' age pattern of mortality that is not reproduced by any existing mortality models. Both burden of disease reporting and population projection methods require age-specific mortality rates to estimate numbers of deaths and produce plausible age structures. For countries with generalized HIV epidemics these estimates should take into account the future trajectory of HIV prevalence and its effects on age-specific mortality. In this paper we present a parsimonious model of age-specific mortality for countries with generalized HIV/AIDS epidemics.</AbstractText><AbstractText Label="METHODS AND FINDINGS" NlmCategory="RESULTS">The model represents a vector of age-specific mortality rates as the weighted sum of three independent age-varying components. We derive the age-varying components from a Singular Value Decomposition of the matrix of age-specific mortality rate schedules. The weights are modeled as a function of HIV prevalence and one of three possible sets of inputs: life expectancy at birth, a measure of child mortality, or child mortality with a measure of adult mortality. We calibrate the model with 320 five-year life tables for each sex from the World Population Prospects 2010 revision that come from the 40 countries of the world that have and are experiencing a generalized HIV epidemic. Cross validation shows that the model is able to outperform several existing model life table systems.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">We present a flexible, parsimonious model of age-specific mortality for countries with generalized HIV epidemics. Combined with the outputs of existing epidemiological and demographic models, this model makes it possible to project future age-specific mortality profiles and number of deaths for countries with generalized HIV epidemics.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Sharrow</LastName><ForeName>David J</ForeName><Initials>DJ</Initials><AffiliationInfo><Affiliation>Department of Sociology, University of Washington, Seattle, Washington, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Clark</LastName><ForeName>Samuel J</ForeName><Initials>SJ</Initials><AffiliationInfo><Affiliation>Department of Sociology, University of Washington, Seattle, Washington, United States of America; Institute of Behavioral Science (IBS), University of Colorado at Boulder, Boulder, Colorado, United States of America; MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; ALPHA Network, London School of Hygiene and Tropical Medicine, London, United Kingdom; INDEPTH Network, Accra, Ghana.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Raftery</LastName><ForeName>Adrian E</ForeName><Initials>AE</Initials><AffiliationInfo><Affiliation>Department of Statistics, University of Washington, Seattle, Washington, United States of America; Department of Sociology, University of Washington, Seattle, Washington, United States of America.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>K01 HD057246</GrantID><Acronym>HD</Acronym><Agency>NICHD NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>R01 HD054511</GrantID><Acronym>HD</Acronym><Agency>NICHD NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>R01 HD070936</GrantID><Acronym>HD</Acronym><Agency>NICHD 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