HIV-1 Transmission Patterns Within and Between Risk Groups in Coastal Kenya

Abstract

HIV-1 transmission patterns within and between populations at different risk of HIV-1 acquisition in Kenya are not well understood. We investigated HIV-1 transmission networks in men who have sex with men (MSM), injecting drug users (IDU), female sex workers (FSW) and heterosexuals (HET) in coastal Kenya. We used maximum-likelihood and Bayesian phylogenetics to analyse new (N = 163) and previously published (N = 495) HIV-1 polymerase sequences collected during 2005-2019. Of the 658 sequences, 131 (20%) were from MSM, 58 (9%) IDU, 109 (17%) FSW, and 360 (55%) HET. Overall, 206 (31%) sequences formed 61 clusters. Most clusters (85%) consisted of sequences from the same risk group, suggesting frequent within-group transmission. The remaining clusters were mixed between HET/MSM (7%), HET/FSW (5%), and MSM/FSW (3%) sequences. One large IDU-exclusive cluster was found, indicating an independent sub-epidemic among this group. Phylodynamic analysis of this cluster revealed a steady increase in HIV-1 infections among IDU since the estimated origin of the cluster in 1987. Our results suggest mixing between high-risk groups and heterosexual populations and could be relevant for the development of targeted HIV-1 prevention programmes in coastal Kenya. Approximately 5.6% in the population in Kenya are infected by HIV-1, with a more than threefold higher HIV-1 prevalence among so-called high-risk groups-including men who have sex with men (MSM), injecting drug users (IDU) and female sex workers 1-4. Modelling data on modes of HIV-1 transmission in Kenya have shown that at least one-third of all new infections occur among high-risk groups 5. However, little is known about local HIV-1 networks and transmission within and between high-risk groups and the heterosexual (HET) population in African settings 6. Molecular epidemiology studies in coastal Kenya have described a dynamic HIV-1 epidemic characterised by subtypes A, C, D, and different circulating recombinant forms (CRFs) 6-15. These studies have indicated high proportions of recombinants within HET, but this was not evident among MSM in a recent study 8 , alluding to separate epidemics. One study in coastal Kenya observed similar HIV-1 recombination patterns among HIV-1 strains in MSM and FSW, suggesting reinfections within mixed networks 13. HIV-1 transmission dynamics can be assessed by linking socio-demographic, clinical and behavioural data with HIV-1 sequence data by phylogenetics 16,17. With few exceptions, most phylogenetic studies of the HIV-1 epidemic in sub-Saharan Africa have focused on understanding HIV-1 subtype diversity and prevalence of antiretroviral resistance mutations 18-24. Phylogenetic studies highlighting the dynamics of HIV-1 transmission and contribution of high-risk groups to onward viral transmission are common in North America and Europe, where largescale HIV-1 sequence data are available 25-32. Due to the limited availability of HIV-1 sequences from sub-Saharan Africa, only a few phylogenetic studies have assessed the dynamics of the HIV-1 epide...

From general to specific: moving past the general population in the HIV response across sub‐Saharan Africa

“…Among young women in Tanzania, for instance, having an older partner and engaging in transactional sex are each associated with double the HIV prevalence of not having an older partner and not having transactional sex respectively [39,40]. In addition, there is substantial contact between groups [41,42]. Past epidemiological studies among men who have sex with men in Botswana, Namibia, Malawi, South Africa, Kenya, Senegal and Nigeria suggest that sex with women is relatively common among men who have sex with men.…”

“…These may be defined by age, gender, labour migration, or geography at different scales. By tracing transmission clusters, phylodynamic modelling promises to aid our understanding of HIV transmission risk both within and across these populations [41‐42,56]. In the absence of detailed sexual‐ or genetic‐network data, the determinants of sexual networks (e.g.…”

The Role of Phylogenetics in Discerning HIV-1 Mixing among Vulnerable Populations and Geographic Regions in Sub-Saharan Africa: A Systematic Review

“…The HIV-1 epidemic in Kenya is diverse and has had multiple and separate introductions [10,43,44]. Hue and colleagues performed a phylogeographic analysis based on 153 sequences collected in Kilifi county in 2008-2009 together with published Kenyan sequences to investigate how HIV-1 transmission in rural Coastal Kenya related to the region [43].…”

“…As a consequence, individuals in these populations often withhold risk information, which results in limited HIV-1 research involving key populations [27]. Additionally, there is evidence of overlapping sexual networks and phylogenetic linkages between HIV-1 key populations and HET, which may have implications for the dynamics of HIV-1 spread [44,65]. Figure 3 summarises HIV-1 prevalence estimates among HIV-1 key and vulnerable populations relative to HET in different regions of sSA.…”

A more responsive, multi‐pronged strategy is needed to strengthen HIV healthcare for men who have sex with men in a decentralized health system: qualitative insights of a case study in the Kenyan coast

“…HIV incidence, however, has remained high in coastal Kenya despite programmatic pre‐exposure prophylaxis (PrEP) offered to MSM since 2017 [4]. While HIV transmission patterns within and between risk groups in Kenya are not well understood, recent HIV phylogeny research showed that 85% of transmission clusters was within risk groups, whereas 15% was shared between risk groups [5], suggesting that the HIV epidemic among MSM require targeted interventions.…”