Search

IntroductionTruenat MTB-RIF assay (Truenat), a nucleic acid amplification test (NAAT), is a real-time polymerase chain reaction (RT-PCR) chip-based assay that can detect Mycobacterium tuberculosis (Mtb) and rifampicin (RIF) drug resistance using portable, battery-operated devices. The National TB Elimination Program (NTEP) in India introduced this novel tool at the district and subdistrict level in 2020. This study aimed to assess the level and causes of inconclusive results (invalid results, errors, and indeterminate results) in MTB and RIF testing at NTEP sites and the root causes of these in the programmatic setting.MethodsTruenat testing data from 1,690 functional Truenat sites under the NTEP from April to June 2021 were analyzed to assess the rates of errors, invalid MTB results, and indeterminate RIF results. Following this analysis, 12 Truenat sites were selected based on site performance in Truenat testing, diversity of climatic conditions, and geographical terrain. These sites were visited to assess the root causes of their high and low rates of inconclusive results using a structured checklist.ResultsA total of 327,649 Truenat tests performed for MTB and RIF testing were analyzed. The rate of invalid MTB results was 5.2% [95% confidence interval (CI): 5.11–5.26; n = 16,998] and the rate of errors was 2.5% (95% CI: 2.46–2.57; n = 8,240) in Truenat MTB chip testing. For Mtb-positive samples tested using the Truenat RIF chip for detection of RIF resistance (n = 40,926), the rate of indeterminate results was 15.3% (95% CI: 14.97–15.67; n = 6,267) and the rate of errors was 1.6% (95% CI: 1.53–1.78; n = 675). There was a 40.1% retesting gap for Mtb testing and a 78.2% gap for inconclusive RR results. Among the inconclusive results retested, 27.9% (95% CI: 27.23–28.66; n = 4,222) were Mtb-positive, and 9.2% (95% CI: 7.84–10.76; n = 139) were detected as RR.ConclusionThe main causes affecting Truenat testing performance include suboptimal adherence to standard operating procedures (SOPs), inadequate training, improper storage of testing kits, inadequate sputum quality, lack of quality control, and delays in the rectification of machine issues. Root cause analysis identified that strengthening of training, external quality control, and supervision could improve the rate of inconclusive results. Ensuring hands-on training of technicians for Truenat testing and retesting of samples with inconclusive results are major recommendations while planning for Truenat scale-up. The recommendations from the study were consolidated into technical guidance documents and videos and disseminated to laboratory staff working at the tiered network of TB laboratories under the NTEP in order to improve Truenat MTB-RIF testing performance.

Abstract: Adolescent girls and young women (AGYW) are vulnerable populations to HIV/AIDS. We conducted a cross-sectional survey among 637 AGYW in Cameroon to study the feasibility and willingness to use mobile applications (apps) for HIV testing, prevention, and treatment. We found that phone ownership is high among AGYW, where 93.9% ( n = 598) of them (median age: 22 years, interquartile range: 21-24 years) had access to a smartphone, 49.5% ( n = 315) frequently searched for health information, and 48.9% ( n = 312) frequently used health-related apps. AGYW's willingness to use mobile apps for HIV testing, prevention, and treatment were 87.9% ( n = 560), 84.4% ( n = 538), and 84.9% ( n = 541), respectively. The high willingness to use apps was associated with older age, HIV testing, and searching for health information on a phone. Barriers to willingness included having no internet access, concerns about internet cost and privacy, and lack of consistent access to a smartphone., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of Association of Nurses in AIDS Care.)

To investigate the route of zoonotic transmission of HIV-1, we isolated three and seven HIV-1 strains from 449 Pygmy hunter gatherers and 169 neighboring Bantu, respectively, in southern Cameroon. Phylogenetic analysis based on pol-integrase and env-C2V3 sequences revealed that strains from Pygmies were 1CRF02_AG/CRF02_AG, 1 subtype G/CRF02 AG (pol/env), and 1 CRFll_cpx/CRF11_cpx, and that those from Bantu were 2 CRF02_AG/CRF02_AG, 1 CRF02_AG/CRF01_AE/A, 1 CRF02_AG/subtype A, 1 G/A, 1G/CRF02_AG, and 1 unclassified fH. CRF02_AG and CRF11_cpx have been identified in Cameroon. The results suggest that HIV-1 has been introduced into Pygmies through their neighboring Bantu rather than directly from nonhuman primates.