Study on the collection of disaggregated subnational data on HIVAIDS prevalence in 10 African countr

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Study on the collection of disaggregated
sub-national data on HIV/AIDS prevalence in 10
African countries (Preliminary findings)
Sives Govender Executive Director Vilde
Ulset Project co-coordinator EIS-AFRICA
CODIST 1, Addis Ababa, Ethiopia, 30 April 2009
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Presentation Outline

• Project Background
• T.O.R
• Methodology
• Outputs
• Definitions
• Southern African SALB
• Outputs Produced
• Country reports
• Lessons learnt
• Conclusions

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Project Background

• Planning and implementing accelerated treatment
  programmes require the information about the
  prevalence of sufferers and patients to be
  targeted by remedial action.
• This requires locational data.
• Specific actions require specific locations.
• With intranational variance in disease, finer
  resolution data is required to formulate
  geographically targeted interventions at
  sub-national level.
• HIV/AIDS exhibits this intranational variance and
  treatment programmes need geovisualisation tools.
• HIV/AIDS responses also require statistics and
  analytics at a sufficiently disaggregated
  geographic unit.
• Therefore ECA and EIS-AFRICA are working together
  to develop disaggregated sub-national data on
  HIV/AIDS according to SALB boundary
  specifications and protocols.

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T.O.R of study

• UN-ECA contracted EIS-AFRICA in February 2009 to
  undertake a study to support the collection and
  processing of sub-national boundary data,
  presented in GIS along with disaggregated
  HIV/AIDS data for priority countries.
• Countries
• Angola
• Botswana
• Lesotho
• Malawi
• Mozambique
• Namibia
• Tanzania
• Swaziland
• Zambia
• Zimbabwe
• Production of a GIS-based HIV/AIDS database (data
  inventory, docs studies etc.)

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Methodology

• Conduct a data inventory of SALB and HIV data at
  district level for 10 priority countries.
• Identify key national partners
• NMAs
• National Ministries /HIV/AIDS Health councils
• Identify key international partners
• WHO (SALB), ECA (SALB) USAID, UNAIDS, Macro
  International (field survey for Demographic
  Health Survey (DHS) with is done nationally but
  sponsored internationally)
• HIVspatialdata.net (DHS repository spatial, shp
  files, metadata) etc.
• Identify regional partners
• SAHIMS, SARDC, Southern African HIV AIDS
  dissemination service (SAfAIDS) etc.
• Contracted relevant partners
• Desktop study (telephonic interviews, web-based
  research etc.)

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Outputs

• Process, integrate, harmonise, validate and
  geocode data received
• Create Maps using ArcView 9.2
• Develop a thesaurus of metadata indicating the
  source, location, format, storage mode, status,
  quality, nature of use etc.
• Present interim report at CODIST 1.
• Update information (NMA and NHM)
• Prepare a comprehensive report of study (identity
  data gaps).

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HIV/AIDS in Southern Africa

• Southern Africa remains the global epicentre of
  the HIV/AIDS pandemic.
• In 2007, the region accounted for 35 percent of
  all people living with HIV worldwide and 32
  percent of the worlds new HIV infections and
  AIDS deaths.
• According to UNAIDS, in 2005, eight countries in
  southern Africa (Botswana, Lesotho, Mozambique,
  Namibia, South Africa, Swaziland, Zambia, and
  Zimbabwe) had a national adult HIV prevalence
  higher than 15 percent.
• Prevalence rates in the region have for the most
  part levelled off. Although Swaziland, Zambia,
  and Zimbabwe appear to have had significant
  declines in prevalence, UNAIDS cautions that the
  extent of these declines is not clear due to
  inconsistencies in the data.

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Second Admin Level Boundary (SALB)

• The Second Administrative Level Boundaries data
  set project (SALB) has been launched in 2001 in
  the context of the activities of the UN
  Geographic Information Working Group (UNGIWG) and
  has for objective to provide free access
  (non-commercial use) to a working platform for
  the collection, management, visualization and
  sharing of sub national data and information.
• Its original objective, was to provide the
  international community with a global
  standardized GIS layer containing the
  delimitation of the administrative boundaries
  down to the 2nd sub national level.

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DHS, MapLibrary and SALB

• The Map Library is a source of public domain
  basic map data concerning administrative
  boundaries in developing countries. The data is
  broken down into manageable chunks to make it
  easier to download for those with poor internet
  connections. www.maplibrary.org
• http//www.hivspatialdata.net metadata available

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Southern African SALB (MAP)
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Countries at a glance

• Paste image of all countries stats at provincial
  level.

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Countries at a glance

• Paste image of all countries stats at provincial
  level.

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Countries at a glance

• Paste image of all countries stats at provincial
  level.

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Southern African SALB
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Countries at a glance

• Paste image of all countries stats at provincial
  level.

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Countries at a glance

• Paste image of all countries stats at provincial
  level.

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Countries at a glance

• Paste image of all countries stats at provincial
  level.

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Countries at a glance

• Paste image of all countries stats at provincial
  level.

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Countries at a glance

• Paste image of all countries stats at provincial
  level.

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Countries at a glance

• Paste image of all countries stats at provincial
  level.

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Country issues 1

• Mozambique Don't have HIV data for all
  Districts. Have SALB from NMA. HIV that we have
  is not stratified by Gender Age.
• Botswana Have all HIV data at District level.
  Need data by Age at District level at the moment
  only available nationally by Age. Need national
  SALB for NMA. We got the data now!
• Angola no SALB from NMA! No HIV data at
  district level.
• Lesotho received SALB from NMA but no HIV data
  at district (constituency) level! They have it
  but we havent received it. We can provide
  analysis by age and gender at provincial (Lesotho
  district level)
• Malawi DHS survey, National sentinel survey
  (National AIDS commission), SALB boundaries, no
  national source of district boundaries.

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Country issues 2

• Namibia Reports at Health District level which
  doesn't correspond to NMA admin 2 boundaries or
  SALB. Reporting only by total population and
  pregnant women. HDL shape files not available.
  SALB (Admin 2) and NMA boundaries don't match.
• Swaziland Admin2 boundaries from MapLibrary.
  Provincial boundaries from DHS and NMA. NMA will
  be sending official boundaries. HIV data only at
  provincial level both by Age and Gender.
• Tanzania Provincial HIV Data for gender and
  Age. Have Admin2 boundaries from Ministry of
  Lands and Map Library. Boundaries don't
  correspond.
• Zambia Boundaries for admin2 from SALB. No NMA
  boundaries. HIV prevalence at District level
  from UNAIDS only in total population. Also have
  DHS at provincial level. (WHO has done study).
• Zimbabwe DHS at Provincial level. SALB
  boundaries. No HIV statistics at Admin2 level.

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Lesson learnt

• HIV reports are at provincial level
• Health departments rely on international agencies
  to undertake surveys.
• By of total population (males/females etc.)
• By Pregnant women (antenatal centres)
• No communication between NMAs and Health
  Departments
• No national health facilities surveys.
• Few countries have health facilities geo-coded.
• Census data is required.
• Barriers from health department reporting (stigma
  etc.)

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Lessons Learnt continued

• Boundaries are questionable.
• National ministries have different boundaries
  (health, lands etc.)
• HIV districts don't match SALB place names.
• Terminology District Province etc.
• NSDI non existent (issues driven SDI).
• Metadata at from national agencies are non
  existent.
• Central repository of HIV at District level and
  national DHIS (HIV, TB etc.) is needed.
• Health networks (NHD, HIV NGOs, MNAs)
• An integrated Disease Surveillance System is
  needed for all infectious diseases.
• NMAs send me your SALB!!!!! (You must support the
  SALB initiative)

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Conclusion

• Geographic information and their related systems
  and infrastructure are essential components in
  ME Health issues.
• However, constraints to mapping health
  information include
• Spatial Data (collection, availability, acquiring
  and sharing)
• Resources (Overall personal, finances etc.)
• Awareness (collaboration and cooperation)
• HIV data (facilities level, spatialised,
  availability, shared and accessible)
• Standards (metadata)

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Geospatial technologies can integrate data and
gives us strength for deeper analysis.... It
gives a common perspective.... It can transform
the way we look at issues.... because its
visual its helps people to see.....gives people
access to knowledge that dont have formal
education. (Prof. Lidia Brito, CODIST 1, 2009)
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Contact Information
THANKS! Sives Govender Executive
Director EIS-AFRICA sgovender_at_eis-africa.org Sive
s.govender_at_gmail.com Vilde Ulset vulset_at_eis-afric
a.org www.eis-africa.org www.africagis2009.org