Effect of population viral load on prospective HIV incidence in a hyperendemic rural African community
Status is not everything - Many parameters are examined to try to understand HIV transmission in endemic areas. Tanser et al. 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...
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| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
13 December 2017
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| In: |
Science translational medicine
Year: 2017, Jahrgang: 9, Heft: 420 |
| ISSN: | 1946-6242 |
| DOI: | 10.1126/scitranslmed.aam8012 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.1126/scitranslmed.aam8012 Verlag, Volltext: http://stm.sciencemag.org/content/9/420/eaam8012 
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| Verfasserangaben: | Frank Tanser, Alain Vandormael, Diego Cuadros, Andrew N. Phillips, Tulio de Oliveira, Andrew Tomita, Till Bärnighausen, Deenan Pillay |
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| 520 | |a Status is not everything - Many parameters are examined to try to understand HIV transmission in endemic areas. Tanser et al. 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. Their data demonstrate that accounting for HIV-negative individuals in calculations and transmission models is important for appropriate interpretations. Their findings could be helpful in guiding prevention intervention strategies in hyperendemic settings. - 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. - We propose HIV population viral load indices, which we demonstrate predict future risk of acquiring HIV in a rural South African population. - We propose HIV population viral load indices, which we demonstrate predict future risk of acquiring HIV in a rural South African population. | ||
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