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