Identification and validation of a multi-assay algorithm for cross-sectional HIV incidence estimation in populations with subtype C infection.

Laeyendecker, Oliver.Konikoff, Jacob.Morrison, Douglas E.Brookmeyer, Ronald.Wang, Jing.Celum, Connie Locke.Morrison, Charles S.Abdool Karim, Quarraisha.Pettifor, Audrey E.Eshleman, Susan H.2019-12-152019-12-1520182018Laeyendecker, O., Konikoff, J., Morrison, D.E., Brookmeyer, R., Wang, J., Celum, C., Morrison, C.S., Abdool Karim, Q., Pettifor, A.E. and Eshleman, S.H. 2018. Identification and validation of a multi‐assay algorithm for cross‐sectional HIV incidence estimation in populations with subtype C infection. Journal of the International AIDS Society 21(2), e25082.http://dx.doi.org/10.1002/jia2.25082https://researchspace.ukzn.ac.za/handle/10413/16668CAPRISA, 2018.Abstract available in pdf.enCross-sectional incidence testing.Southern Africa.Subtype C.Women.Epidemiology.Identification and validation of a multi-assay algorithm for cross-sectional HIV incidence estimation in populations with subtype C infection.Article