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Does the Spectrum model accurately predict trends in adult mortality? Evaluation of model estimates using empirical data from a rural HIV community cohort study in north-western Tanzania

Bibliographic Data

ID19530706
AuthorsDenna Michael (National Institute for Medical Research, corresponding author), Chifundo Kanjala (0000-0003-0540-8374, London School of Hygiene & Tropical Medicine), Clara Calvert (0000-0003-3272-1040, London School of Hygiene & Tropical Medicine), Carel Pretorius (0000-0002-7608-3995, Avenir Health), Alison Wringe (0000-0001-6939-3461, London School of Hygiene & Tropical Medicine), Jim Todd (0000-0001-5918-4914, London School of Hygiene & Tropical Medicine), Balthazar Mtenga (National Institute for Medical Research), Raphael Isingo (National Institute for Medical Research), Basia Zaba (0000-0003-2449-0983, London School of Hygiene & Tropical Medicine), Mark Urassa (0000-0003-0257-6938, London School of Hygiene & Tropical Medicine)
Year2014
Volume7
Issue1
Pages21783-21783
Publication date2014-12-01
Open AccessYes
TypeARTICLE
VenueGlobal Health Action (JOURNAL)
Journal identifiersISSN: 1654-9716 • E-ISSN: 1654-9880
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.3402/gha.v7.21783
PMID24438873
OpenAlexW2056901495
LanguageEN
Citations received4
References cited20

INTRODUCTION: Spectrum epidemiological models are used by UNAIDS to provide global, regional and national HIV estimates and projections, which are then used for evidence-based health planning for HIV services. However, there are no validations of the Spectrum model against empirical serological and mortality data from populations in sub-Saharan Africa. METHODS: Serologic, demographic and verbal autopsy data have been regularly collected among over 30,000 residents in north-western Tanzania since 1994. Five-year age-specific mortality rates (ASMRs) per 1,000 person years and the probability of dying between 15 and 60 years of age (45Q15,) were calculated and compared with the Spectrum model outputs. Mortality trends by HIV status are shown for periods before the introduction of antiretroviral therapy (1994-1999, 2000-2005) and the first 5 years afterwards (2005-2009). RESULTS: Among 30-34 year olds of both sexes, observed ASMRs per 1,000 person years were 13.33 (95% CI: 10.75-16.52) in the period 1994-1999, 11.03 (95% CI: 8.84-13.77) in 2000-2004, and 6.22 (95% CI; 4.75-8.15) in 2005-2009. Among the same age group, the ASMRs estimated by the Spectrum model were 10.55, 11.13 and 8.15 for the periods 1994-1999, 2000-2004 and 2005-2009, respectively. The cohort data, for both sexes combined, showed that the 45Q15 declined from 39% (95% CI: 27-55%) in 1994 to 22% (95% CI: 17-29%) in 2009, whereas the Spectrum model predicted a decline from 43% in 1994 to 37% in 2009. CONCLUSION: From 1994 to 2009, the observed decrease in ASMRs was steeper in younger age groups than that predicted by the Spectrum model, perhaps because the Spectrum model under-estimated the ASMRs in 30-34 year olds in 1994-99. However, the Spectrum model predicted greater 45Q15 mortality than observed in the cohort,although the reasons for this over-estimate are unclear [corrected]

Cause of death · Cohort · Cohort study · Disease · Geography · Mortality rate · Tanzania · Verbal autopsy · Demography · Global Maternal and Child Health · HIV/AIDS Impact and Responses · HIV/AIDS Research and Interventions · Medicine · Epidemiology · Immunology · Internal Medicine

  • Special Issue

    Open Access•Jim Todd•Global Health Action•2014

  • Measuring HIV-related mortality in the first decade of anti-retroviral therapy in sub-Saharan Africa

    Open Access•Jim Todd, Emma Slaymaker et al.•Global Health Action•2014

  • Using HIV-attributable mortality to assess the impact of antiretroviral therapy on adult mortality in rural Tanzania

    Open Access•Chifundo Kanjala, Denna Michael et al.•Global Health Action•2014

  • How have ART treatment programmes changed the patterns of excess mortality in people living with HIV? Estimates from four countries in East and Southern Africa

    Open Access•Emma Slaymaker, Jim Todd et al.•Global Health Action•2014

  • InterVA versus Spectrum

    Open Access•Samuel Oti, Samuel Oji Oti et al.•Global Health Action•2013

Citations per year0.33
Citation span2014 - 2014 (1)
Highly citedNo

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