1. From universal access to universal coverage
How does health insurance mechanisms and
HIV interact: Overview of country experience
Erik Lamontagne, Ole Doetinchem, Robert Greener
Systems Integration, UNAIDS
Geneva
Bridging the Divide: Interdisciplinary Partnerships for HIV and Health Systems
Vienna, Austria, 16-17 July 2010
3. Different types of mechanisms
private health insurance social health insurance public tax-funded provision
4. The review of country experiences
•Questionnaire on country situation: how is the
overall health insurance and how HIV is eventually
integrated
•Excellent response rate (65/71) countries
•Country analysed in terms of their vulnerability
•Vulnerability level: incorporates proxy measures of
– Poverty rate
– Extend of the informal economy
(see World Social Security Report 2010)
5. Country characteristics
Government health expenditure
Classification using vulnerability
index is coherent with usual
characteristics
No clear trend of HIV prevalence
Among vulnerability groups of
countries
6. Health insurance coverage
Blue: % country including health insurance
Green: proportion of providing ART coverage
Orange: proportion of SHI providing PMTCT
9. Lessons to draw (1)
• Introducing health insurance is not an automatic
recipe for increasing revenue collection for health
or HIV
• Integrating HIV services in SHI: more challenging
for low income countries ( f(prevalence) )
• Not a fatality: Ghana, South Africa and Rwanda
• Countries that choose to include HIV services in
SHI are mainly those already having a functioning
health insurance system in place.
10. Lessons to draw (2)
• The review shows that including HIV = essentially
a political decision
• Possibility to progressively increase coverage
(pop, cost, services)
• External aid, incl. HIV financing can support (and
subsidise) progressive integration of HIV in SHI
11. Thank you
contact: Erik Lamontagne: lamontagnee@unaids.org
Geneva, UNAIDS
12. Annexe
50%
Economic share of government
Zimbabwe
Lesotho
40% Congo Swaziland
Government revenue as % of GNI
Botswana
South Africa
30%
Namibia R2 = 0.1757
Ghana
Malawi Mauritius
20% Djibouti
Gambia Kenya Senegal
Côte d'Ivoire
Zambia Cameroon
Burundi Togo Benin
Mali
Mauritania
Niger Rwanda
DR Congo Mozambique
Burkina Faso
Uganda
Guinea-Bissau LeoneTanzania
Ethiopia Sierra Madagascar Comoros
10% Gabon
Guinea
Central African Republic
Nigeria Angola
Chad
0%
$100 $1,000 $10,000
GNI per capita $US
13. Health expenditures and GDP
9
9
8
8
Log Health Expenditures/capita
Log Health Expenditures/capita 7
7
6
6
5
5
4
4
3
3
2
(most of ) Sub
2
Saharan Africa
1
1
4
4 5
5 6
6 7
7 8
8 9
9 10
10 11
11 12
12
Log GDP/capita
Log GDP/capita
Van der Gaag et al, Economics Reference Group, Dec 2009
14. Projection of health funding
•GDP per capita is an almost perfect predictor of health expenditure per
capita
•The estimated income elasticity is higher than zero and close to or
even higher than one.
•This implies that health is regarded more as a “luxury good” than as a
necessity (by the aggregate populations of most countries)
•Based on projections of health funding to 2030, Van der Gaag et al
(2009) concludes that:
– over time (relatively fast growing) middle income countries may have
sufficient funding…
– …but (relatively slow growing) low income countries will need significant
financial support for years to come.
