Estimates and Projections of National HIV/AIDS...
Transcript of Estimates and Projections of National HIV/AIDS...
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Spectrum 2009Estimates and Projections of
National HIV/AIDS Epidemics
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National Estimates
EPPSpectrumDemographic DataEpidemic Patterns
Treatment EffectivenessART and
PMTCT Coverage
Incidence
Number HIV+New InfectionsAIDS Deaths
Need for TreatmentOn Treatment
Orphans
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Modifications to Spectrum Methods• Adults
– Prevalence/incidence• Receive incidence from EPP
– Progression to need for treatment and AIDS death for adults• Patterns for eligibility at CD4<200 and CD4<350
– Survival on ART• First year survival can vary with time
– Effect of HIV infection on fertility• Children
– PMTCT– Progression patterns for children
• Separate by time of infection: intrapartum/post-partum– Child treatment
• % tested with PCR is time variant• Cotrimoxazole effects separated for with ART and without ART
– New equation for double AIDS orphans
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Age Patterns of Incidence
• Estimate age pattern of incidence from DHS data using Tim Hallett’s model– Hallett et al. Estimating Incidence from Prevalence in
Generalized Epidemics: Methods and Validation PLoS Med 5(4): e80. doi:10.1371/journal.pmed.0050080
• Compare patterns across countries
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Proportion of New Infections by Age for Females: Prevalence > 4%
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Proportion of New Infections by Age for Males: Prevalence > 4%
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Proportion of New Infections by Age: Females
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Proportion of New Infections by Age: Males
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Ratio of Female to Male Incidence 15-49
For SSAAverage = 1.37Median = 1.38
Outside SSA = 0.84IDU-driven = 0.42
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Prevalence by Age: Zambia
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Prevalence by Age: Malawi and Swaziland
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EPP and Spectrum Prevalence: Malawi
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Adult Progression Patterns
• Adult progression patterns based on analyses by ALPHA network and e-ART LINC Collaboration– Adult progression from infection to need for
treatment• CD4<200 and CD4<350
– Adult progression from need for treatment to AIDS death without treatment
• CD4<200 and CD4<350
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Progression Pattern: Males, Slow
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Progression Pattern: Females, Slow
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Progression Pattern: Males, Fast
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Progression Pattern: Females, Fast
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Survival on First Year of ART
First Year Subsequent Years
Mortality on Treatment 6% 2%Lost to Follow-up 17% 17%Mortality among LTFU 47% 47%Annual Survival 86% 90%
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Survival on First Year of ART
• First year is low because many patients start very late, median CD4 count ~ 100
• Higher coverage should mean higher CD4 count at initiation
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ART Coverage and Median CD4 Count at Initiation
Namibia
Botswana
Sub-Saharan Africa
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First Year Survival and Baseline CD4 Count
First year survival = %<50 x 0.16 + (1-%<50)*0.06 + 0.08
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Fertility Effects of HIV Infection
0.5
11.
52
2.5
33.
54
Age
-spe
cific
ferti
lity
rate
ratio
15-19 20-24 25-29 30-34 35-39 40-44 45-49Age groups (yr)
0.5
11.
52
2.5
33.
54
Age
-spe
cific
ferti
lity
rate
ratio
15-19 20-24 25-29 30-34 35-39 40-44 45-49Age groups (yr)
Box Plots of Ratio of Age-Specific Fertility Rates for HIV+ to HIV- Women for 20 Countries with a DHS
Analysis by Wei-ju Chen and Neff Walker
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Fertility Effects of HIV Infection
0.5
11.
52
2.5
33.
54
Age
-spe
cific
ferti
lity
rate
ratio
15-19 20-24 25-29 30-34 35-39 40-44 45-49Age groups (yr)
0.5
11.
52
2.5
33.
54
Age
-spe
cific
ferti
lity
rate
ratio
15-19 20-24 25-29 30-34 35-39 40-44 45-49Age groups (yr)
Box Plots of Ratio of Age-Specific Fertility Rates for HIV+ to HIV- Women for 20 Countries with a DHS
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Fertility Effects of HIV InfectionAge-specific fertility rate ratio and proportion of women aged 15-19 in Sub-Saharan Africa who are sexually active
0.5
11.
52
2.5
3
Age
-spe
cific
ferti
lity
rate
ratio
0 20 40 60 80
Proportion of sexually active women aged 15-19 years old (%)Correlation coefficient = -0.7923
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HIV in Children• New options for PMTCT• Separate progression by mode of
infection• New treatment guidelines
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Abortion Option for HIV+ Pregnant Women
• In some countries pregnant women identified as HIV+ either before pregnancy or early in the pregnancy may choose abortion
• Input will be percent or number of all pregnancies to HIV+ women terminated by abortion
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Probability of Mother to Child Transmission at Birth
Prophylaxis IntrapartumNone 20%SD NVP 11%Dual ARV 4%Triple ARV prophylaxis 2%Triple ARV treatment (Direct Input) 2%
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Monthly Probability of HIV Transmission through Breastfeeding
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Exposure to Transmission Through Breastfeeding
• Median duration of any breastfeeding
• Use input in year t for those in PMTCT program
• Use year before PMTCT program started for those not in the program
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Breastfeeding Patterns
Source: Bradley SE, Mishra V HIV and Nutrition Among Women in Sub-Saharan Africa, DHS Analytical Studies No. 16, Macro International, September 2008.
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Child Progression Patterns
• Child progression from infection to need for treatment and to AIDS death– Infected intrapartum or through breastfeeding– On-going work by Milly Marston and
colleagues to update Lancet 2004 paper and add Ditrame Plus
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Proportion of HIV+ Children Surviving by Time Since Infection
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Need for ART Among HIV+ Children
• All children on ART• Under 1 year of age = all HIV+ children
– Children infected intrapartum– Children infected through breastfeeding
• Over 1 year of age based on progression to need
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Early Infant Diagnosis• Percent of infants diagnosed with PCR
can now be varied by year• But ‘need for treatment’ will be based on
actual status not knowledge of status• Distribution of new ART patients by age
is on the basis need, for children under the age of one this is ‘identified’ need, which requires PCR
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Child Survival on ART
Age/Duration on ART Annual Probability of Survival
Under age 1 80%Over age 1First year on ART 85%Subsequent years on ART 93%
Source: Consultative Meeting on Data Collection and Estimation Methods Related to HIV Infection in Infants and Children, 8-10 July 2008, New York.
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Co-trimoxazole Prophylaxis
Year 1 Year 2 Year 3 Year 4 Year 5 Year 5+No ART 33% 33% 33% 33% 33% 0%With ART 33% 16% 8% 0% 0% 0%
Reduction in AIDS mortality due to co-trimoxazole prophylaxis
•Assume CTX coverage applies equally to all children in need•Need for CTX is:
•All exposed children < 18 months•All HIV+ children < 5 years of age•Children >= 5 who have progressed to need for treatment
•Assume that duration of use of CTX is the same as duration of ART use for those children on both ART and CTX
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Using Spectrum• Create a new file
– Use EasyProj to read demographic data– Read incidence and adult ART data from EPP – Specify type of epidemic for age patterns & orphans– Add data on PMTCT, child treatment, BF duration
• Read an existing file– Update EasyProj if necessary– Read incidence and ART from EPP– Select default progression and age patterns– Update program data, BF duration
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Create a New Projection
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Create a New Projection
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Create Your Own Demographic Projection?
• You will need– Population by age and sex in base year
• Census data need to be adjusted for undercount, age heaping, etc.
– Total fertility rate by year, historical and projected– Non-AIDS life expectancy by year– Model life table selection– Migration by age and sex by year
• Unless this has already been prepared by your Census Bureau or National Statistical Office it is better to use EasyProj
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Read Incidence from EPP
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Read Incidence from EPP
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Select Progression Patterns
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Set Fertility Adjustment
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Enter PMTCT Data: Prophylaxis
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Enter Child Feeding Data
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Enter Adult ART Data
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Enter Child Treatment Data
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Set Orphan Data
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Display Results• Display
– AIDS• Total population• Adults 15-49• Adults 15+• Children• Children under 1• Children 1-4• Regional table• AIDS impacts• Orphans• Treatment costs
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Display Multiple Projections• Up to 10 projections
can be open at on time
• To create alternate projections– Open the same
projection twice– Rename the second
projection– Edit the second
projection
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Uncertainty Analysis
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New Program Features
• Update demographic data with EasyProj• Format numbers in tables and editors
– Outline cells– Right click to change number of decimals
• Export Spectrum files– Packages together all files for one
projection in a zip file
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Acknowledgements• Spectrum is developed by Futures Institute in
collaboration with UNAIDS Reference Group on Estimates Models and Projections
• Special assistance from US Census Bureau, United Nations Population Division, University of Cape Town
• Financial support from USAID through the Health Policy Initiative implemented by the Futures Group International