Washington D.C., USA, 22-27 July 2012 Sources of data: estimates of the size of key population...
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Washington D.C., USA, 22-27 July 2012www.aids2012.org
Sources of data: estimates of the size of key population groups –
mortality data
Peter Ghys, UNAIDS
Txema Calleja, WHO
Paloma Cuchi, UNITAID
John Stover, Futures Institute
Washington D.C., USA, 22-27 July 2012www.aids2012.org
Second Generation Surveillance framework
STISurveillance Second
GenerationSurveillance
HIV andAIDS case &
mortalityreporting
Behavioural or Bio-Behavioural
SurveysSentinel
Surveillance
SizeEstimation
of Risk Groups1
Washington D.C., USA, 22-27 July 2012www.aids2012.org
Size matters
Contribution of a subpopulation to the HIV epidemic is determined
by HIV prevalence + risk behaviors + size of subpopulation:– Small population + high HIV incidence + efficient bridge/interactions =
important role to the epidemic– Big population + low prevalence = main contributor HIV epidemic
Use of the SE data:– National estimates: policy, response planning, resource allocation,
advocacy, Understanding HIV surveillance– Local estimates: program planning and management (assessing
commodity, coverage, HIV program evaluation)
Washington D.C., USA, 22-27 July 2012www.aids2012.org
Size estimation issues
Few countries with good size estimation of sub-pops at risk • No regular, scientific SE studies & trends• Subpopulation "hidden" and poorly characterized• Not triangulated & validated w/multiple sources• Ad hoc assumptions often made in projection• Point estimates instead of time-varying trends (size change over
time)• Pressure to use “official” estimates & politics
• Low accuracy, large uncertainty of SE estimates and HIV Estimates
Washington D.C., USA, 22-27 July 2012www.aids2012.org
Methods
Methods based on data collected from at-risk population:• Census/Enumeration, Capture-
recapture, Multiplier
Methods based on data collected from general population:• Population survey • Network scale-up
Limitations:• Stigmatized populations need to
disclose behaviors (e.g. illegal)
• Geographically limited (1 city, 1 neighborhood) = not nationally representative
• Collect data on 1 population at a time = multiple studies for a full picture
Washington D.C., USA, 22-27 July 2012www.aids2012.org
Network Scale Up
• Ideal but not feasible: ask respondents directly about their behaviors (national survey)
• Challenges: stigma, embarrassment, fear
• Ask respondents about acquaintances: national survey, behaviors of others
• Individual’s behaviors are not disclosed
• Each respondent’s personal network contributes to sample
8 countries: Moldova, Ukraine, Kazakhstan, Japan, China, Brazil, Rwanda
Conclusions• On the radar (stigmatized
situations)• Feasible in diverse circumstances
& survey methods • Not for every occasions, needs to
be used appropriately and have data available
• Pending issues
Washington D.C., USA, 22-27 July 2012www.aids2012.org
2007 en
Data sources for the size of populations
• Often multiple data sources are available:– Sizes of at-risk populations
• Studies from any of the methods (i.e. Capture-recapture)• Mappings of higher risk sites• Estimates from NGOs (service statistics)• Police arrest records• Security office estimates
Washington D.C., USA, 22-27 July 2012www.aids2012.org
Regardless of the method
• National ownership
• Build consensus and agreed on a single estimate
• Use the results
• No harm
• Determine use of SE
• Know what you know
• Use multiple methods to get a better estimate
• Deal with conflicting results
• Repeat study every 2-3 years
Washington D.C., USA, 22-27 July 2012www.aids2012.org
Second Generation Surveillance framework
STISurveillance Second
GenerationSurveillance
HIV andAIDS case &
mortalityreporting
Behavioural or Bio-Behavioural
Surveys
SentinelSurveillance
SizeEstimation
of Risk Groups
2
Washington D.C., USA, 22-27 July 2012www.aids2012.org
1. Incidence of HIV Infection
3. Mortality from AIDS2. Prevalence of HIV Infection
Underreporting, delays and misclassification to other causes of death in death registration systems
HIV epidemiology
Washington D.C., USA, 22-27 July 2012www.aids2012.org
South Africa - overall mortality levels
0
10000
20000
30000
40000
50000
60000
70000
Age0
Age1-4
Age5-9
Age10-14
Age15-19
Age20-24
Age25-29
Age30-34
Age35-39
Age40-44
Age45-49
Age50-54
Age55-59
Age60-64
Age65-69
Age70-74
Age75-79
Age80-84
Age85+
no
of
dea
ths 1993
1995
1996
1998
2000
2005
name South Africa Diseases All Causes
Data
Year
Analyses of the overall mortality can gauge the level of HIV mortality
Analyses for miscoding of AIDS deaths in vital registration data for S Africa, R Fed, Belarus, Ukraine and Thailand (Source and slides “HIV deaths in vital registration data” from Doris Ma Fat, Mortality and Burden of Disease Unit, Department of Health Statistics and Informatics, Dec 2010)
Washington D.C., USA, 22-27 July 2012www.aids2012.org
South Africa 2004: Further analyses of trends and patterns are necessary to identify potentially misclassified HIV deaths
ALRI - M
0500
10001500
2000250030003500
A0M
A51
0M
A15
19M
A25
29M
A35
39M
A45
49M
A55
59M
A65
69M
A75
79M
A85
00M
199319962004
Meningitis - M
0
100
200
300
400
500
600
700
A0
M
A5
10
M
A1
51
9M
A2
52
9M
A3
53
9M
A4
54
9M
A5
55
9M
A6
56
9M
A7
57
9M
A8
50
0M
1993
1996
2004
other infectious - F
0
500
1000
1500
2000
2500
A0M
A51
0M
A15
19M
A25
29M
A35
39M
A45
49M
A55
59M
A65
69M
A75
79M
A85
00M
1993
1996
2004
ENDOCRINE - F
0
500
1000
1500
2000
2500
A0M
A51
0M
A15
19M
A25
29M
A35
39M
A45
49M
A55
59M
A65
69M
A75
79M
A85
00M
1993
1996
2004
Diarhoea - F
0500
1000150020002500300035004000
A0M
A51
0M
A15
19M
A25
29M
A35
39M
A45
49M
A55
59M
A65
69M
A75
79M
A85
00M
1993
1996
2004
Ill defined - M
0500
10001500
2000250030003500
A0M
A10
14M
A25
29M
A40
44M
A55
59M
A70
74M
A85
00M
199319962004
Acute lower resp. inf -male Other infectious dis - maleMeningitis - male
Diarrhoea - female Endocrine disorders - female Ill-defined injuries - male
Washington D.C., USA, 22-27 July 2012www.aids2012.org
AIDS-related mortality
• HIV has a significant impact on mortality• Measuring HIV mortality to evaluate the impact of NAP’s
efforts • One of the clearest indicators of success is a decrease
in HIV mortality • Two of the 10 MDG require mortality data• Provide evidence of equity in distribution of health
services
In many cases this information is not available
Washington D.C., USA, 22-27 July 2012www.aids2012.org
Data sources HIV-related mortality
•Civil registration systems - gold standard
• Verbal autopsy – most common
– Nationally representative sample vital registration with
verbal autopsy (SAVVY)
• Facility-based mortality surveillance (e.g., HIV treatment
and care facilities, hospitals, prisons, drug treatment
facilities, morgues)
Washington D.C., USA, 22-27 July 2012www.aids2012.org
Data sources HIV-related mortality
• Burial systems with verbal autopsy (cadaver autopsy,)
• Surveys & research
– Population-based surveys with verbal autopsy (VA)
(e.g., DHS and post-census mortality surveys) -
retrospective
– Prospective Demographic Surveillance Systems
(DSS) with verbal autopsy (ALPHA Analyzing
Longitudinal Population-based HIV/AIDS data on Africa)
linkages between DSS participants and HIV prevention,
treatment and care services
Washington D.C., USA, 22-27 July 2012www.aids2012.org
5 data considerations
1. Data identification: multiple data sources need to
identify all. Organization, creativity, ongoing
2. Data quality and completeness: evaluate all potential
sources (strengths, weaknesses). Underestimation,
quality (cause, date, sex, age…. )
3. Data management: different sources & ways to
collect data, duplications, use
4. Data Analysis: limitations in the analysis of mortality
data
Washington D.C., USA, 22-27 July 2012www.aids2012.org
5 data considerations
5. Future data issues: strengthening current systems, data collection, sharing systems and collaboration
• Short-term goals: obtaining measures of HIV mortality
• Longer-term goals: identify opportunities and advocacy strategies for health systems strengthening and creating strong civil registration systems
Washington D.C., USA, 22-27 July 2012www.aids2012.org
GUIDELINES
Guidelines available on UNAIDS and WHO website
WWW.UNAIDS.ORG WWW.WHO.INT