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Estimating the impact of HIV and AIDS in Zimbabwe

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CDC Zimbabwe. Overview for Generalised Epidemics. Surveillance ... Process for Zimbabwe Estimates ... Reasons for Differences in Zimbabwe and UNAIDS Estimates ... – PowerPoint PPT presentation

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Title: Estimating the impact of HIV and AIDS in Zimbabwe


1
Estimating the impact of HIV and AIDS in Zimbabwe
  • A.D. McNaghten
  • CDC Zimbabwe

2
Overview for Generalised Epidemics
Surveillance data from ANC
EPP
Adult HIV Prevalence
UN Population Divisions Population estimates
Spectrum
  • PLWHA
  • New Infections
  • AIDS Deaths

Epidemiology assumptions
3
Process for Zimbabwe Estimates
  • WHO/UNAIDS training in estimation methods and
    software (Harare, April 2003)
  • Ministry of Health and Child Welfare (MOHCW) 2002
    Antenatal Clinic (ANC) Report and National
    Prevalence Estimate Workshop (Harare, May 2003)
  • Estimate Working Group
  • MOHCW, National Microbiology Reference
    Laboratory, Central Statistical Office,
    University of Zimbabwe, Futures Group, UNAIDS,
    Imperial College, CDC Zimbabwe
  • Classification of ANC sites as Urban, Rural and
    Other
  • EPP curve fits
  • based on sentinel surveillance data collected
    from women attending antenatal clinics
  • Estimates and ranges from Spectrum

4
EPP
  • ANC sites classified by location as
  • urban
  • rural (communal lands, resettlements, small-scale
    commercial farms)
  • other (large scale commercial farms,
    administrative centres, growth points, other
    urban e.g., mines, state land e.g., national
    parks, special e.g., army camp)
  • 6 rural sites were adjusted down 30
  • Women lived in or near commercial centre

5
EPP
  • Adjustments for unreliability of ANC surveillance
    estimates
  • Implausibly high results at 2 sites additional
    test results used
  • Inconsistent data points for 2 sites removed
  • Representativeness of ANC data of the prevalence
    among women and men 15-49 in the general
    population
  • EPP curve fits

6
EPP curve fits for Urban, Rural and Other census
strata
Percent
7
Adult (15-49) HIV prevalence by census strata,
2003
  • Urban 28.1
  • Rural1 20.9
  • Other2 34.9
  • Overall 24.6

1 Communal land, small scale commercial farms,
resettlements 2 Large scale commercial farms, adm
inistrative centres, growth points, other urban
(e.g., mines), state land (e.g., national parks),
special (e.g., army camp)
8
Overview for Generalised Epidemics
Surveillance data from ANC
EPP
Adult HIV Prevalence
UN Population Divisions Population estimates
Spectrum
  • PLWHA
  • New Infections
  • AIDS Deaths

Epidemiology assumptions
9
Spectrum
  • To create a national HIV estimate Spectrum makes
    a demographic and an epidemiologic projection
  • Demographic and epidemiologic assumptions can be
    accepted or revised
  • Local and national data can be used

10
Spectrum Demographic Assumptions
  • UN Population Division figures
  • Total fertility and age-specific fertility rates
    estimates from 1988, 1994 and 1999 Demographic
    Health Survey
  • Life expectancy at birth (in the theoretical
    absence of HIV) set using UN Population Division
    estimates

11
Spectrum Epidemiologic Assumptions
  • Adult HIV prevalence was read from EPP file
  • Perinatal transmission rate 32 through 1999 30
    2000-2003
  • Total fertility rate reduction based on
    Manicaland Study data

12
Spectrum Epidemiologic Assumptions
  • UNAIDS ratio of female to male HIV prevalence
    (sub-Saharan Africa) through 1999 1.35
    2000-2003
  • Ratio of prevalence by age group to prevalence in
    25-29 year age group from Young Adult Survey
    (15-29) and Manicaland project 1998-2000

13
Spectrum Outputs
  • Estimates of prevalence
  • males and females
  • children and adults
  • Estimates of incidence
  • Mortality for adults and children
  • AIDS orphans

14
Adult HIV prevalence estimate and range, 2003
Percent
2003 estimate 24.6, range 20-28
15
Estimated number of people living with HIV, 2003
  • Estimate Range
  • Adult (15-49) prevalence 24.6 (20 - 28)
  • Adults and Children 1,820,000 (1,473,000 -
    2,020,000)
  • Adults (15-49) 1,540,000 (1,250,000
    1,710,000)
  • Women (15-49) 870,000 (700,000 960,000)
  • Children (0-14) 165,000 (131,000 186,000)

16
AIDS Deaths During 2003
  • Estimate Range
  • Adults (15-49) 135,000 (107,000
    151,000)
  • Women (15-49) 77,000 (61,000 86,000)
  • Children (0-14) 36,000 (29,000 41,000)

17
New AIDS Cases During 2003
  • Estimate Range
  • Adults (15-49) 138,000 (110,000
    154,000)
  • Women (15-49) 78,000 (62,000 87,000)
  • Children (0-14) 36,000 (29,000 41,000)

18
New HIV Infections During 2003
  • Estimate Range
  • Adults (15-49) 166,000 (137,000
    184,000)
  • Women (15-49) 88,000 (73,000 97,000)
  • Children (0-14) 40,000 (32,000 45,000)

19
Adult HIV prevalence comparison of Zimbabwe and
UNAIDS estimates
Percent
UNAIDS Report on the Global HIV/AIDS Epidemic,
2002
20
Estimated number of people living with HIV a
comparison of 2001 estimates
  • New Estimates UNAIDS Estimates
  • Adult (15-49) prevalence 24.9 33.7
  • Adults and children 1,800,000 2,300,000
  • Adults (15-49) 1,520,000 2,000,000
  • Women (15-49) 860,000 1,200,000
  • Children (0-14) 160,000 240,000

21
Reasons for Differences in Zimbabwe and UNAIDS
Estimates
  • Updated and more accurate ANC data entered into
    EPP
  • Stratification of areas as urban, rural or
    other (e.g., growth points, mines) more
    accurately reflects prevalence in rural and
    other areas
  • Updated United Nations population figures reflect
    population declines since the last estimates

22
Changes for 2004 Estimates
  • The process and methods are constantly evolving
    and improving
  • Recent UNAIDS Working Group changes
  • Mother to child transmission
  • Orphan definition

23
Concluding Remarks
  • Methodological changes were the reason for a
    decrease in prevalence
  • More data are needed to say the epidemic is
    declining or leveling
  • Estimates are best represented by a range

24
Role of the ME Officer
  • Be familiar with sources of data available
  • Identification of individuals and organizations
    who can contribute to the estimate process
  • Understand how estimates are derived (in general
    and country-specific)
  • Be able to explain country estimates to others
  • Data and methods
  • Relationship to other country-level data
  • Changes over time
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