137 national hiv treatment cascades compared by region, hiv...
TRANSCRIPT
Abstract
Background: In 2014, UNAIDS and partners set the three 90-90-90 targets.
Reaching these targets may be more difficult in countries with lower HIV
prevalence, or with ongoing military conflict, high levels of corruption or resource
constraints. We assessed how close countries and regions are to reaching these
targets, and analysed outcome predictors.
Methods: Country level HIV treatment cascade data from 2010-2016 were
extracted from national reports, published papers and the www.AIDSinfoOnline
database and analysed. Weighted least squares regression was used to assess
predictors of cascade achievement (diagnosis, ART coverage and viral suppression)
by: region, HIV prevalence, Gross Domestic Product (GDP/capita), the 2016
Corruption Perceptions Index and the 2016 Global Peace Index (GPI, which ranks
all countries based on 3 main categories; societal safety, militarization and conflicts).
Results: Of the countries with national cascade data, there were 84 countries with
data on diagnosis, 137 with ART coverage and 94 with viral suppression data. HIV
diagnosis rates ranged from 92% (Romania & Khazakstan) to 3% (Madagascar). ART
coverage rates ranged from 86% (Denmark) to 2% (Madagascar) and viral
suppression ranged from 80% (Denmark) to 4% (Pakistan & Afghanistan). Figure 1
shows that SE Asia & Pacific and Sub-Saharan Africa had varying diagnosis rates
(64% and 46% respectively) but both achieved ART coverage of (42%). The regions
with the lowest ART coverage were Eastern Europe & Central Asia (17%) and
Middle East & North Africa (13%). In Sub-saharan Africa, providing ART to those
diagnosed has improved, but diagnosis rates are poor. Fig. 2a, 2b and 2c illustrate the
areas that are performing poorly (darker red) for the three UNAIDS targets.
Figure 3 shows the relationship between ART coverage and HIV Prevalence which
was calculated using least squares regression weighted by epidemic size and
controlling for GDP. Within Africa, countries with higher HIV prevalence had higher
rates of ART coverage (p<0.001) and viral suppression (p=0.00722), and higher
rates of diagnosis (p=0.0261) when controlling for GDP (p<0.001). Outside Africa,
countries with higher HIV prevalence had higher diagnosis rates, ART coverage and
viral suppression (all p<0.001). Countries with higher GDP/capita had higher ART
coverage (all p<0.001). Countries with a higher level of conflict (therefore a high
GPI score) had lower ART coverage (p<0.001). Countries with lower levels of
corruption also had higher ART coverage (p=0.03394).
Conclusions:
• Higher ART coverage was associated with higher GDP/capita, higher
HIV prevalence, lower corruption levels and lower conflict levels
• Many countries with a low prevalence of HIV need to increase rates of
HIV diagnosis and treatment.
• Some countries are not reaching targets for ART coverage due to
conflict or low GDP, while others may be struggling due to corruption,
but these factors are interrelated.
137 National HIV treatment cascades compared by region,
HIV prevalence, Conflict, Corruption and GDPAuthors: J. Levi1, A. Pozniak2, K. Heath3, A. Hill2
Institution(s): 1Imperial College London, london, UK2Chelsea & Westminster Hospital, London, UK,
3Oxford University, Oxford, UK
PRESENTED AT THE 9TH IAS CONFERENCE ON HIV SCIENCE - PARIS, FRANCE
WEPED1433 Abstract category: D38 Monitoring and evaluation of HIV cascade
Figure2a:HIV Diagnosis Rates by country
Figure 2b:ART Coverage by country
Figure 2c: Viral Suppression Rates by country
Figure 4:ART Coverage vs Global Peace Index (2016)
Figure 3:ART coverage vs Adult HIV prevalence, weighted by epidemic size
Figure 1 – Regional Cascades, weighted by epidemic size
UNAIDSTargets
OceaniaWesternEurope
SouthAmerica
CaribbeanCentralAmerica
South EastAsia &Pacific
EasternEurope andCentral Asia
SubSaharan
Africa
Middle Eastand North
Africa
% Diagnosed 90% 85% 84% 75% 72% 64% 64% 57% 46% 26%
% On ART 81% 72% 75% 49% 50% 46% 42% 18% 42% 13%
% Virally Suppressed 73% 62% 66% 40% 28% 31% 39% 14% 29% 6%
90%
81%
73%
0%
20%
40%
60%
80%
100%
% Diagnosed % On ART % Virally Suppressed
Afghanistan
Algeria
Angola
Argentina
Armenia
Australia
Bangladesh
Belarus
Benin
Bolivia
Botswana
Brazil
Burkina Faso
Burundi
Cambodia
Cameroon
Central African Republic
Chad
Chile
Colombia
Costa Rica
Côte d'Ivoire
Cuba
DR Congo
Djibouti
Dominican Republic
Ecuador
Egypt
Eritrea
Georgia
Greece
Guatemala
Guyana
Haiti
Honduras India
Indonesia Iran
Italy
Jamaica
Kazakhstan
Kenya
KyrgyzstanLatvia
Lebanon
Lesotho
Liberia
Madagascar
Malawi
Malaysia Mali
Mauritania
Mauritius
Mexico
Mongolia
Morocco
Mozambique
Myanmar
Namibia
Nepal
Nicaragua
Niger
Nigeria
Pakistan
Panama
Papua New Guinea
Paraguay
Peru
Philippines
Rwanda
Senegal
Sierra Leone
Somalia
South Africa
South Sudan
Spain
Sri Lanka
Sudan
Swaziland
Tajikistan
Thailand
Togo
Trinidad and Tobago
Tunisia
Uganda
Ukraine
UR of Tanzania
Uruguay
Uzbekistan
Yemen
Venezuela
Vietnam
Zambia
Zimbabwe
Russian Federation
Denmark
New Zealand
Switzerland
Sweden
Germany
UK
China
France
Albania
Bhutan
Belgium
El Salvador
Equ Guinea
Estonia
Ethiopia
Gabon
Gambia
Ghana
Guinea-Bissau
Japan
Laos PDR
Lithuania
Netherlands
Romania
Serbia
0%
20%
40%
60%
80%
1 1.5 2 2.5 3 3.5 4
AR
T co
vera
ge
Global Peace Index Score (2016)
Bubble colour:Red = GPI 2.88- 4.00
Orange = GPI 2.83 - 2.38Yellow = GPI 2.37 - 1.92Green= GPI 1.91 - 1.43Blue = GPI 1.43 - 1.19
Ref 1: GPI 2016 - Quantifying peace and its benefits. Sydney, Australia: Institute for Economics and Peace. 2016. http://visionofhumanity.org/app/uploads/2017/02/GPI-2016-Report_2.pdf
Ref 2: CPI 2016 – Corruption Perceptions Index 2016. Transparency International. https://www.transparency.org/whatwedo/publication/corruption_perceptions_index_2016
Afghanistan
Algeria
Angola
Argentina
Armenia
Australia
Bangladesh
Belarus
Belize
Benin
Bolivia
Botswana
Brazil
Burkina Faso
Burundi
Cambodia
Cameroon
Central African Republic
Chad
Chile
Colombia
Costa Rica
Côte d'Ivoire
Cuba
DR Congo
Djibouti
Dominican Republic
Ecuador
Egypt
Eritrea
Georgia
Greece
Guatemala
Guyana
Haiti
Honduras
Indonesia
Iran
Italy
Jamaica
Kazakhstan
Kenya
KyrgyzstanLatvia
Lebanon
Lesotho
Liberia
Madagascar
Malawi
Malaysia Mali
Mauritania
Mauritius
Mexico
Mongolia
Morocco
Mozambique
Myanmar
Namibia
Nepal
Nicaragua
Niger
Nigeria
Pakistan
Panama
Papua New Guinea
Paraguay
Peru
Philippines
Republic of Moldova
Rwanda
Senegal
Sierra Leone
Somalia
South Africa
South Sudan
Spain
Sri Lanka
Sudan
Suriname
Swaziland
Tajikistan
Thailand
Togo
Trinidad and Tobago
Tunisia
Uganda
Ukraine
UR of Tanzania
Uruguay
Uzbekistan
Yemen
Venezuela
Vietnam
Zambia
Zimbabwe
El SalvadorEqu Guinea
Gabon
Gambia
Ghana
0%
20%
40%
60%
80%
0 5 10 15 20 25
Pe
rce
nta
ge o
n A
RT
HIV Prevalence (2015 UNAIDS)
Bubble colour:Red = GPI 2.88- 4.00
Orange = GPI 2.83 - 2.38Yellow = GPI 2.37 - 1.92
Green= GPI 1.91 - 1.43Blue = GPI 1.43 - 1.19