Viral and Host Characteristics of Recent and Established HIV-1 Infections in Kisumu based on a Multiassay Approach

Abstract

Integrated approaches provide better understanding of HIV/AIDS epidemics. We optimised a multiassay algorithm (MAA) and assessed HIV incidence, correlates of recent infections, viral diversity, plus transmission clusters among participants screened for Kisumu Incidence Cohort Study (KICoS1) (2007–2009). We performed BED-CEIA, Limiting antigen (LAg) avidity, Biorad avidity, and viral load (VL) tests on HIV-positive samples. Genotypic analyses focused on HIV-1 pol gene. Correlates of testing recent by MAA were assessed using logistic regression model. Overall, 133 (12%, 95% CI: 10.2–14.1) participants were HIV-positive, of whom 11 tested recent by MAA (BED-CEIA OD-n < 0.8 + LAg avidity OD-n < 1.5 + VL > 1000 copies/mL), giving an incidence of 1.46% (95% CI: 0.58–2.35) per year. This MAA-based incidence was similar to longitudinal KICoS1 incidence. Correlates of testing recent included sexually transmitted infection (STI) treatment history (OR = 3.94, 95% CI: 1.03–15.07) and syphilis seropositivity (OR = 10.15, 95% CI: 1.51–68.22). Overall, HIV-1 subtype A (63%), D (15%), C (3%), G (1%) and recombinants (18%), two monophyletic dyads and intrinsic viral mutations (V81I, V81I/V, V108I/V and K101Q) were observed. Viral diversity mirrored known patterns in this region, while resistance mutations reflected likely non-exposure to antiretroviral drugs. Management of STIs may help address ongoing HIV transmission in this region.

HIV-1 subtype diversity, transmission networks and transmitted drug resistance amongst acute and early infected MSM populations from Coastal Kenya

“…Overall, our data also confirm that the HIV-1 MSM epidemic from Coastal Kenya is largely characterized by a predominance of sub-subtype A1 infections, which is consistent with subtype diversity literature from Kenya [13–18]. However, and while some studies have also reported high and/or increasing circulating or complex recombinant forms amongst the general heterosexual population [19–22], this was not evident in our study population.…”

“…In Kenya, several studies have described HIV-1 subtype distribution in the general heterosexual population, and reported a predominance of HIV-1 sub-subtype A1 [13–18], with increasing inter-subtype recombinants [19–22]. In addition, a study amongst the heterosexual population from Coastal Kenya reported minimum clustering and high genetic variability between the study-volunteers’ pol sequences [21].…”

Identifying major drivers of incident HIV infection using recent infection testing algorithms (RITAs) to precisely inform targeted prevention

“…When clinical information is combined with the recency assay to classify recent HIV infection, FRR has been shown to be reduced. According to WHO guidelines, we used CD4+ T cell count <200 cells/ml, and VL <1000 copies/mL as reclassification criteria for recent infection to reduce misclassification (Aghaizu et al, 2014;Laeyendecker et al, 2018;Otecko et al, 2016;Shah et al, 2017). A previous study showed that FRR was reduced from 4.9% to 0.4% when VL was incorporated into an algorithm initially consisting of the recency assay and CD4+ T cell count.…”

Human immunodeficiency virus (HIV) type 1 genetic diversity in HIV positive individuals on antiretroviral therapy in a cross sectional study conducted in Teso, Western Kenya

“…Another study done on the gag and env regions of HIV-1 in 74 samples revealed A1, C, D, G, A1/C, A1/D, C/A1, D/A1, A1/A2 and A2/C [ 21 ]. In Kisumu, analysis of 100 samples identified the following subtypes; A, D, C, G, AD, AC, AG [ 22 ]. In Nairobi A1, D, C, G, AD, AC, AG and A2D were identified in analysis of 140 samples [ 23 ].…”