Dataset Information

Viral load monitoring of antiretroviral therapy, cohort viral load and HIV transmission in Southern Africa: a mathematical modelling analysis.

ABSTRACT: In low-income settings, treatment failure is often identified using CD4 cell count monitoring. Consequently, patients remain on a failing regimen, resulting in a higher risk of transmission. We investigated the benefit of routine viral load monitoring for reducing HIV transmission.Mathematical model.We developed a stochastic mathematical model representing the course of individual viral load, immunological response and survival in a cohort of 1000 HIV-infected patients receiving antiretroviral therapy (ART) in southern Africa. We calculated cohort viral load (CVL; sum of individual viral loads) and used a mathematical relationship between individual viral load values and transmission probability to estimate the number of new HIV infections. Our model was parameterized with data from the International epidemiologic Databases to Evaluate AIDS Southern African collaboration. Sensitivity analyses were performed to assess the validity of the results in a universal 'test and treat' scenario, wherein patients start ART earlier after HIV infection.If CD4 cell count alone was regularly monitored, the CVL was 2.6?×?10?copies/ml and the treated patients transmitted on average 6.3 infections each year. With routine viral load monitoring, both CVL and transmissions were reduced by 31% to 1.7?×?10?copies/ml and 4.3 transmissions, respectively. The relative reduction of 31% between monitoring strategies remained similar for different scenarios.Although routine viral load monitoring enhances the preventive effect of ART, the provision of ART to everyone in need should remain the highest priority.

SUBMITTER: Estill J

PROVIDER: S-EPMC3750130 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Viral load monitoring of antiretroviral therapy, cohort viral load and HIV transmission in Southern Africa: a mathematical modelling analysis.

Estill Janne J Aubrière Cindy C Egger Matthias M Johnson Leigh L Wood Robin R Garone Daniela D Gsponer Thomas T Wandeler Gilles G Boulle Andrew A Davies Mary-Ann MA Hallett Timothy B TB Keiser Olivia O

AIDS (London, England) 20120701 11

<h4>Objectives</h4>In low-income settings, treatment failure is often identified using CD4 cell count monitoring. Consequently, patients remain on a failing regimen, resulting in a higher risk of transmission. We investigated the benefit of routine viral load monitoring for reducing HIV transmission.<h4>Design</h4>Mathematical model.<h4>Methods</h4>We developed a stochastic mathematical model representing the course of individual viral load, immunological response and survival in a cohort of 100 ...[more]

PMID: 22421243

Similar Datasets

Project description:BackgroundThe proportion of heterosexual HIV transmission in sub-Saharan Africa that occurs within cohabiting partnerships, compared with that in single people or extra-couple relationships, is widely debated. We estimated the proportional contribution of different routes of transmission to new HIV infections. As plans to use antiretroviral drugs as a strategy for population-level prevention progress, understanding the importance of different transmission routes is crucial to target intervention efforts.MethodsWe built a mechanistic model of HIV transmission with data from Demographic and Health Surveys (DHS) for 2003-2011, of 27,201 cohabiting couples (men aged 15-59 years and women aged 15-49 years) from 18 sub-Saharan African countries with information about relationship duration, age at sexual debut, and HIV serostatus. We combined this model with estimates of HIV survival times and country-specific estimates of HIV prevalence and coverage of antiretroviral therapy (ART). We then estimated the proportion of recorded infections in surveyed cohabiting couples that occurred before couple formation, between couple members, and because of extra-couple intercourse.FindingsIn surveyed couples, we estimated that extra-couple transmission accounted for 27-61% of all HIV infections in men and 21-51% of all those in women, with ranges showing intercountry variation. We estimated that in 2011, extra-couple transmission accounted for 32-65% of new incident HIV infections in men in cohabiting couples, and 10-47% of new infections in women in such couples. Our findings suggest that transmission within couples occurs largely from men to women; however, the latter sex have a very high-risk period before couple formation.InterpretationBecause of the large contribution of extra-couple transmission to new HIV infections, interventions for HIV prevention should target the general sexually active population and not only serodiscordant couples.FundingUS National Institutes of Health, US National Science Foundation, and J S McDonnell Foundation.

Dataset Information

Viral load monitoring of antiretroviral therapy, cohort viral load and HIV transmission in Southern Africa: a mathematical modelling analysis.

Publications

Viral load monitoring of antiretroviral therapy, cohort viral load and HIV transmission in Southern Africa: a mathematical modelling analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets