Friday, May 18, 2018

The impact of HIV prevalence, conflict, corruption, and GDP/capita on treatment cascades: data from 137 countries

 2018 Apr 1;4(2):80-90.

The impact of HIV prevalence, conflict, corruption, and GDP/capita on treatment cascades: data from 137 countries.

Author information

1
Imperial College London, UK.
2
Chelsea and Westminster NHS Foundation Trust, London, UK.
3
Oxford University, UK.

Abstract

OBJECTIVE:

In 2014, UNAIDS and partners set the 90-90-90 targets for the HIV treatment cascade. Multiple social, political and structural factors might influence progress towards these targets. We assessed how close countries and regions are to reaching these targets, and compared cascade outcomes with HIV prevalence, gross domestic product (GDP)/capita, conflict and corruption.

METHODS:

Country-level HIV cascade data on diagnosis, ART coverage and viral suppression, from 2010 to 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: region, HIV prevalence, GDP/capita, the 2016 Corruption Perceptions Index (CPI), which is an international ranking system, and the 2016 Global Peace Index (GPI), which ranks all countries based on three main categories: societal safety, militarisation and conflict.

RESULTS:

Data were available for diagnosis for 84 countries, ART coverage for 137 countries, and viral suppression for 94 countries. Regions with the lowest ART coverage were South-east Asia and Pacific (36%), Eastern Europe and Central Asia (17%), and Middle East and North Africa (13%). Lower HIV prevalence was associated with poorer cascade results. Countries with higher GDP/capita achieved higher ART coverage (P<0.001). Furthermore, countries with lower levels of peace and higher corruption had lower ART coverage (P<0.001). Countries with a GPI >2.5 all had ART coverage of <40%.

CONCLUSION:

Only one country has reached the UNAIDS 90-90-90 targets. International comparison remains difficult due to heterogeneous data reporting. Difficulty meeting UNAIDS targets is associated with lower GDP/capita, lower HIV prevalence, higher corruption and conflict levels.

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