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Here we provide you with news articles, blogs and tweets on the key aspects of our bioinformatics and drug resistance work.

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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)

The Africa Health Research Institute (AHRI) said in a statement that this innovative set of measurements would help to target treatment and prevention resources and interventions where they are most needed.

'In the paper, published in the scientific journal Science Translational Medicine, the researchers show that Population Viral Load (PVL) measures, which have previously been used to try to predict the intensity of new HIV infections in a particular area, do not accurately predict HIV incidence in a rural South African setting.'

They proposed and rigorously tested a set of modified indices, which considered variations in viral load patterns as well as the proportion of the population already infected with HIV, and found this gave a strong prediction of high incidence.

The manuscript is a collaboration between AHRI, KRISP, UKZN and UCL researchers and it is entitled:Effect of population viral load on prospective HIV incidence in a hyperendemic rural African community.

Links:

https://www.iol.co.za/mercury/scientists-develop-new-prediction-methods-for-hiv-infection-rates-12417449

Publication cited

Highlights of the second ISCB Student Council Symposium in Africa, 2017. Rafael CN, Ashano E, Moosa Y, Shome S, DeBlasio D, F1000 Research (2017), 6(ISCB Comm J):2183 (doi: 10.12688/f1000research.13463.1).

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