Implementation of an interactive mobile application to pilot a rapid assay to detect HIV drug resistance mutations in Kenya

Development and Optimization of Oligonucleotide Ligation Assay (OLA) Probes for Detection of HIV-1 Resistance to Dolutegravir

The WHO currently recommends dolutegravir (DTG)-based ART for persons living with HIV infection in resource-limited-settings (RLS). To expand access to testing for HIV drug resistance (DR) to DTG in RLS, we developed probes for use in the oligonucleotide ligation assay (OLA)-Simple, a near-point of care HIV DR kit. Genotypic data from clinical trials and case reports were used to determine the mutations in HIV-1 integrase critical to identifying individuals with DTG-resistance at virologic failure of DTG-based ART. Probes to detect G118R, Q148H/K/R, N155H and R263K in HIV-1 subtypes A, B, C, D and CRF01_AE were designed using sequence alignments from the Los Alamos database and validated using 61 clinical samples of HIV-1 subtypes A, B, C, D, CRF01_AE genotyped by PacBio (n = 15) or Sanger (n = 46). Initial OLA probes failed to ligate for 16/244 (6.5%) codons (9 at G118R and 7 at Q148H/K/R). Probes revised to accommodate polymorphisms interfering with ligation at codons G118R and Q148R reduced indeterminates to 3.7% (5 at G118R and 4 at Q148H/K/R) and detected DTG-mutations with a sensitivity of 96.5% and 100% specificity. These OLA DTG resistance probes appear highly sensitive and specific across HIV-1 subtypes common in RLS with high burden of HIV infection.

Optimising HIV drug resistance testing laboratory networks in Kenya: insights from systems engineering modelling

BACKGROUND

HIV drug resistance (DR) is a growing threat to the durability of current and future HIV treatment success. DR testing (DRT) technologies are very expensive and specialised, relying on centralised laboratories in most low and middle-income countries. Modelling for laboratory network with point-of-care (POC) DRT assays to minimise turnaround time (TAT), is urgently needed to meet the growing demand.

METHODS

We developed a model with user-friendly interface using integer programming and queueing theory to improve the DRT system in Kisumu County, Kenya. We estimated DRT demand based on both current and idealised scenarios and evaluated a centralised laboratory-only network and an optimised POC DRT network. A one-way sensitivity analysis of key user inputs was conducted.

RESULTS

In a centralised laboratory-only network, the mean TAT ranged from 8.52 to 8.55 working days, and the system could not handle a demand proportion exceeding 1.6%. In contrast, the mean TAT for POC DRT network ranged from 1.13 to 2.11 working days, with demand proportion up to 4.8%. Sensitivity analyses showed that expanding DRT hubs reduces mean TAT substantially while increasing the processing rate at national labs had minimal effect. For instance, doubling the current service rate at national labs reduced the mean TAT by only 0.0%-1.9% in various tested scenarios, whereas doubling the current service rate at DRT hubs reduced the mean TAT by 37.5%-49.8%. In addition, faster batching modes and transportation were important factors influencing the mean TAT.

CONCLUSIONS

Our model offers decision-makers an informed framework for improving the DRT system using POC in Kenya. POC DRT networks substantially reduce mean TAT and can handle a higher demand proportion than a centralised laboratory-only network, especially for children and pregnant women living with HIV, where there is an immediate push to use DRT results for patient case management.