Publication

Title: Effect of population viral load on prospective HIV incidence in a hyperendemic rural African community
Authors: Tanser F, Vandormael A, Cuadros D, Phillips AN, de Oliveira T, Tomita A, Barnighausen T, Pillay D.
Journal: Science Translational Medicine,9:eaam8012 (2017)

Journal Impact Factor (I.F.): 19.5
Number of citations (Google Scholar): 10

Abstract

Monitoring HIV population viral load (PVL) has been advocated as an important means of inferring HIV transmission potential and predicting the future rate of new HIV infections (HIV incidence) in a particular community. However, the relationship between PVL measures and directly measured HIV incidence has not been quantified in any setting and, most importantly, in a hyperendemic sub-Saharan African setting.

We assessed this relationship using one of Africa?s largest population-based prospective population cohorts in rural KwaZulu-Natal, South Africa in which we followed 8732 HIV-uninfected participants between 2011 and 2015. Despite clear evidence of spatial clustering of high viral loads in some communities, our results demonstrate that PVL metrics derived from aggregation of viral load data only from the HIV-positive members of a particular community did not predict HIV incidence in this typical hyperendemic, rural African population. Only once we used modified PVL measures, which combined viral load information with the underlying spatial variation in the proportion of the population infected (HIV prevalence), did we find a consistently strong relationship with future risk of HIV acquisition. For example, every 1% increase in the overall proportion of a population having detectable virus (PDVP) was independently associated with a 6.3% increase in an individual?s risk of HIV acquisition (P = 0.001).

In hyperendemic African populations, these modified PVL indices could play a key role in targeting and monitoring interventions in the most vulnerable communities where the future rate of new HIV infections is likely to be highest.

Download: Full text paper

Citation: Tanser F, Vandormael A, Cuadros D, Phillips AN, de Oliveira T, Tomita A, Barnighausen T, Pillay D. Effect of population viral load on prospective HIV incidence in a hyperendemic rural African community Science Translational Medicine,9:eaam8012 (2017).

Printed and Online Media Coverage

Scientists develop new prediction methods for HIV infection rates - 2017-12-14

The Mercury, 14 December 2017, KwaZulu-Natal-based medical research organisations have developed an improved method to accurately predict where the highest rate of new HIV infections will likely occur in a community. Press coverage of our KRISP paper by Tanser et al. (Science TM 2017)


KRISP Papers

Science TM Editorial: Status is not everythingKRISP Papers - 2017-12-15

Many parameters are examined to try to understand HIV transmission in endemic areas. Tanser et al. (Science TM 2017) use longitudinal population-based data from rural South Africa to show that population viral load indices incorporating geographical location and local HIV prevalence can be used to infer HIV transmission potential.