Pop opulation D Dyn ynamics Stron ongly y Influence H e HIV E - - PowerPoint PPT Presentation

Pop

• pulation D

Dyn ynamics Stron

• ngly

y Influence H e HIV E V Estimates es: A A Descri escriptive Study

Athena Pantazis U.S. Census Bureau Population Division Annual Meeting of the Population Association of America April 10-13, 2019, Austin, TX

The presentation is released to inform interested parties of ongoing research and to encourage discussion of work in progress. Any views expressed are those

• f the authors and not necessarily those of the U. S. Census Bureau

1

Global HIV Estimates

• Software from Avenir Health (avenirhealth.org)
• Models developed and revised by the UNAIDS Reference Group on

Estimates, Modelling and Projections (http://www.epidem.org/)

• Different methods for obtaining HIV incidence and prevalence

estimates from available data

• Cohort-component population projection starting in 1970 for
• btaining HIV indicators, etc.

2

Objectives

Descriptive analysis to explore how population dynamics shape HIV projections using the Spectrum model

3

Methods

• Project a stationary population from 1970 to 2035 in Spectrum with 2

HIV curves: one with no antiretroviral (ART) interventions and another with Fast Track (95-95-95) targets attained by 2030

• Compare with a stable, growing population projection and a stable,

declining population projection

• Compare with projections for 4 fertility levels based on observed total

fertility rate (TFR) trends in countries with high HIV burden

• Compare with projections where timing for fertility decline is varied

4

Stationary, Growing, Shrinking Populations

5

Very High, High, Medium and Low Fertility: PLHIV Population

6

Very High, High, Medium and Low Fertility: New HIV Infections

7

Very High, High, Medium and Low Fertility: PMTCT Need

8

Timing of Fertility Decline: New HIV Infections

9

Timing of Fertility Decline: PMTCT Need

10

Conclusions

• Identical HIV curves produce different estimates of key HIV indicators

under different population dynamics.

• These differences are generally within the estimated uncertainty,

though they can still be quite large.

• The differences are large enough to likely impact decision-making.
• Analyzing trends obtained from these different estimates would lead

to different conclusions about the success of interventions and the general trends of the HIV epidemic. Underlying population dynamics need to be considered when using estimated HIV indicators

11

Thank you!

12

Extra Slides

13

Structure

Demographic Data Program Statistics Epidemic Patterns

Surveillance, Survey and Routine Testing Data

Demographic and Epidemic Calculations

• Mother-to-child transmission
• Child model
• Adult model

Prevalence / incidence trend

Results

• Number HIV+
• New Infections
• AIDS deaths
• Need for ART
• Need for PMTCT

Tracking New Adult HIV Infections by CD4 Count

New Infections >500 350-499 250-349 200-249 100-199 50-99 <50

On ART

AIDS Death >500 350-499 250-349 200-249 100-199 50-99 <50 λ6 λ5 λ4 λ3 λ2 λ1 μ1 μ2 μ3 μ4 μ5 μ6 μ7

α1 α2 α3 α4 α5 α6 α7

c1 c2 c3 c4 c5 c6 c7

µ = non-AIDS mortality rate, λ = progression rate, c = rate

• f initiating ART, α = mortality rate on ART