TEMPORAL TRENDS AND TRANSMISSION DYNAMICS OF PRE-TREATMENT HIV-1 DRUG RESISTANCE WITHIN AND BETWEEN RISK GROUPS IN KENYA, 1986-2020
Bibliographic record
Abstract
ABSTRACT Background Evidence on the distribution of pre-treatment HIV-1 drug resistance (HIVDR) by risk groups is limited in Africa. We assessed prevalence, trends, and transmission dynamics of pre-treatment HIVDR within-and-between men who have sex with men (MSM), people who inject drugs (PWID), female sex workers (FSW), heterosexuals (HET), and children infected perinatally in Kenya. Methods HIV-1 partial pol sequences from antiretroviral-naïve samples collected between 1986-2020 were used. Pre-treatment RTI, PI and INSTI mutations were assessed using the Stanford HIVDR database. Phylogenetics methods were used to determine and date transmission clusters. Results Of 3567 sequences analysed, 550 (15.4%, 95% CI: 14.2-16.6) had at least one pre-treatment HIVDR mutation, which was most prevalent amongst children (41.3%), followed by PWID (31.0%), MSM (19.9%), FSW (15.1%) and HET (13.9%). No INSTI resistance mutations were detected. Among HET, pre-treatment HIVDR increased from 6.6% in 1986-2005 to 20.2% in 2011-2015 but dropped to 6.5% in 2016-2020. Overall, 22 clusters with shared pre-treatment HIVDR mutations were identified. The largest was a K103N mutation cluster involving 16 MSM sequences sampled between 2010-2017, with an estimated tMRCA of 2005 (HPD, 2000-2008). This lineage had a growth rate=0.1/year and R 0 =1.1, indicating propagation over 12 years among ART-naïve MSM in Kenya. Conclusions Compared to HET, children and key populations had higher levels of pre-treatment HIVDR. Introduction of INSTIs after 2016 may have reversed the increase in pre-treatment RTI mutations in Kenya. Continued surveillance of HIVDR, with a particular focus on children and key populations, is warranted to inform treatment strategies in Kenya. Summary Compared to the heterosexual population, key populations had higher levels of pre-treatment HIV-1 drug resistance (HIVDR). Propagation of HIVDR was risk-group exclusive. Introduction of integrase inhibitors abrogated propagation of reverse transcriptase inhibitors mutations among the heterosexual, but not key populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".