Decentralization of viral load testing to improve HIV care and treatment cascade in rural Tanzania: Data from the Kilombero and Ulanga Antiretroviral Cohort

Decentralization of viral load testing to improve HIV care and treatment cascade in rural Tanzania: Data from the Kilombero and Ulanga Antiretroviral Cohort | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Decentralization of viral load testing to improve HIV care and treatment cascade in rural Tanzania: Data from the Kilombero and Ulanga Antiretroviral Cohort Dorcas Mnzava, James Okuma, Robert Ndege, Namvua Kimera, Alex Ntamatungiro, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2123101/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Apr, 2023 Read the published version in BMC Infectious Diseases → Version 1 posted 3 You are reading this latest preprint version Abstract Introduction: Monitoring HIV viral load (VL) in people living with HIV (PLHIV) on antiretroviral therapy (ART) is recommended by the World Health Organization. Implementation of VL testing programs have been affected by logistic and organizational challenges. Here we describe the VL monitoring cascade in a rural setting in Tanzania and compare turnaround times (TAT) between an on-site and a referral laboratory. Methods In a nested study of the prospective Kilombero and Ulanga Antiretroviral Cohort (KIULARCO) we included PLHIV aged ≥ 15 years, on ART for ≥ 6 months after implementation of routine VL monitoring in 2017. We assessed proportions of PLHIV with a blood sample taken for VL, whose results came back, and who were virally suppressed (VL < 1000 copies/mL) or unsuppressed (VL ≥ 1000 copies/mL). We described the proportion of PLHIV with unsuppressed VL and adequate measures taken as per national guidelines and outcomes among those with low-level viremia (LLV; 100–999 copies/mL). We compare TAT between on-site and referral laboratories by Wilcoxon rank sum tests. Results From 2017 to 2020, among 4,454 PLHIV, 4,238 (95%) had a blood sample taken and 4,177 99 %) of those had a result. Of those, 3,683 (88%) were virally suppressed. In the 494 (12%) unsuppressed PLHIV, 425 (86%) had a follow-up VL (102 (24%) within 4 months and 158 (37%) had virologic failure. Of these, 103 (65%) were already on second-line ART and 32/55 (58%) switched from first- to second-line ART after a median of 7.7 months (IQR 4.7–12.7). In the 371 (9%) PLHIV with LLV, 327 (88%) had a follow-up VL. Of these, 267 (82%) resuppressed to < 100 copies/ml, 41 (13%) had persistent LLV and 19 (6%) had unsuppressed VL. The median TAT for return of VL results was 21 days (IQR 13–39) at the on-site versus 59 days (IQR 27–99) at the referral laboratory (p < 0.001) with PLHIV receiving the VL results after a median of 91 days (IQR 36–94; similar for both laboratories). Conclusion Robust VL monitoring is achievable in remote resource-limited settings. More focus is needed on care models for PLHIV with high viral loads to timely address results from routine VL monitoring. HIV Cascade Viral load Testing Viral suppression failure low level viremia Figures Figure 1 Figure 2 Introduction The number of people living with HIV (PLHIV) on antiretroviral therapy (ART) globally and in Tanzania has been increasing over time with 82% accessing ART in 2020 ( 1 ). HIV viral load (VL) testing in PLHIV – the preferred monitoring approach by the World Health Organization (WHO) ( 2 ) – allows early detection of treatment failure and guides treatment decisions, for example adherence counselling or regimen change. In sub–Saharan Africa, VL monitoring has been scaled up in recent years with investments strengthening VL processing hubs and sample transportation systems, to overcome challenges of transport and result transmission especially in remote settings ( 3 ). In Tanzania, the government scaled up routine VL testing in 2017 through establishment of VL processing centres (hubs) and policies enabling all PLHIV to receive VL testing ( 4 , 5 ). For remote health facilities, the long distances to referral VL processing hubs, poor road infrastructures (especially during the rainy season), unreliable transport systems, and the danger of blood sample degradation due to failure of cold chains remain a challenge ( 6 , 7 ). For successful VL monitoring, a reliable testing process with a rapid turnaround time (TAT) is key and affects all stages of the testing cascade including blood withdrawal, sample transport and processing, generation of results, feedback to clinicians and PLHIV, and timely subsequent action. Samples for VL testing are recommended to be processed and results made available to the clinicians within 14 days for management of treatment ( 8 ). According to the Tanzania National AIDS Control Program guidelines, the first VL test is done at 6 months after initiation of ART and a second at 12 months. If both viral load results are < 1000 copies/mL, VL is then monitored yearly. PLHIV with unsuppressed VL receive enhanced adherence counselling for three months followed by a follow-up VL test in the fourth month - if reported adherence is > 95%. If the follow-up VL result is below 1000copies/ml, the patient will continue with the same drug regimen, otherwise the recommendation is to switch to a second-line ART regimen( 8 ). Gaps in the VL cascade, such as long TAT, delay in timely initiation of adherence counselling and/or switch to second-line ART in PLHIV with virologic failure (VF), lead to an increased risk of accumulation of drug resistance mutations, development of clinical failure and mortality as well as onwards HIV transmission ( 9 – 11 ). We hypothesised that with decentralization of VL testing from a referral laboratory to an on-site molecular laboratory capable of conducting VL testing, hence avoiding sample transport to a central referral laboratory, will reduce TAT of VL results. Therefore, we aimed at describing the VL monitoring cascade, compare turnaround times of viral load results when viral load testing was done at an on-site laboratory versus a referral laboratory and assess management and outcome among those with high- and low-level viremia following the national rollout of routine VL monitoring in a cohort of PLHIV in rural Tanzania. Methods Study setting This is an observational study in the prospective Kilombero and Ulanga Antiretroviral Cohort (KIULARCO). Kilombero and Ulanga are rural districts in the Morogoro region in South-western Tanzania, with St. Francis Referral Hospital (SFRH) being the largest health facility providing HIV care and treatment in the region. Morogoro Regional Referral Hospital (MRRH) – used for referral of laboratory services – is located 229 kilometres (km) away from SFRH. KIULARCO has existed since 2005 as collaboration between the SFRH, the Ifakara Health Institute (IHI), the Swiss Tropical and Public Health Institute, and the University Hospital of Basel, Switzerland. PLHIV attending the Chronic Diseases Clinic of Ifakara (CDCI) of the SFRH are invited to participate in KIULARCO. Almost 11,000 PLHIV have been enrolled in KIULARCO as of January 2021, with information collected prospectively in an electronic patient records database (openMRS), including demographics, clinical and laboratory data, medication history, drug toxicities, diagnoses and outcomes. Details of the cohort have been described elsewhere ( 12 , 13 ). Routine VL testing at SFRH was implemented in August 2017. Plasma samples from PLHIV were transported to the referral laboratory at MRRH for analysis. Additionally, a point of care system (GeneXpert ®) for VL testing was operating at the on-site laboratory with a 2-hour TAT for urgent cases. With the aim to decentralize VL testing, from August 2018 onwards, VL testing was started at the on-site laboratory at IHI in close collaboration with the National AIDS Control Program and the implementing partner USAID Boresha Afya. On-site laboratory at IHI offered VL testing for SFRH patients and was referral laboratory for VL testing for other peripheral health facilities. Referral of samples to MRRH was then only done in case of stock outs of reagents or machine breakdown. Study population For this study, we included all PLHIV with an informed consent enrolled in KIULARCO, who were at least 15 years old and on ART for at least 6 months with a clinical visit from August 2017 to July 2020, with follow-up through January 2021. VL testing and reporting procedures During routine visits, venous blood samples were collected in BD vacutainer EDTA tubes® by the phlebotomist at the clinics and brought to the on-site laboratory the same day. In the first year of roll out of VL testing (August 2017 to July 2018), blood samples were immediately centrifuged at the on-site laboratory and plasma was stored at -80°C freezer until transport to MRRH for VL testing. Transportation of the frozen plasma happened mostly twice a week. Upon arrival of the samples at MRRH, data clerks registered the patient-related information from the VL request forms and, depending on the work load, the samples were processed immediately or stored in -20°C freezers until they could be processed. VL testing was done using COBAS® AmpliPrep/COBAS® TaqMan® system, according to manufacturers’ instructions with lowest detection limit of 20 copies/ml. Paper forms with the VL results were brought from the MRRH to the SFRH by staff who carried the samples from SFRH to the MRRH or by local arrangements with office cars whenever possible. Data clerks entered the results in the openMRS database and filed paper copies in the patient files. From August 2018 to July 2020, VL testing happened at IHI, at the on-site laboratory on an Abbott m2000 System as per manufacturer’s instructions with lowest detection limit of 40copies/ml or 150copies/ml depending on the manufacturer’s protocol used. Depending on the work load, samples were processed immediately or stored in -80°C freezers until processed. VL results were then entered in the openMRS database. PLHIV were scheduled for routine VL testing or follow-up of unsuppressed VL following national guidelines( 8 ). In addition to VL control according guidelines, we controlled VL in PLHIV with LLV at their next scheduled visit. Objectives and definitions The main objective of the study was the description of the VL monitoring cascade and comparison of TAT between the on-site and the referral laboratory. The secondary objective was the outcome in PLHIV with LLV. We defined as baseline the first clinical visit of eligible patients. The VL measurement at this time is referred to as the first VL. We considered a VL ≥ 1000copies/mL as ‘unsuppressed’ and a VL < 1000copies/mL as ‘suppressed’. Virological failure (VF) was defined as two consecutives unsuppressed VL results despite adherence counselling. Due to having different VL measuring platforms with different lowest detection limits, we considered a VL of 100 copies/ml as the lower limit for VL detection. Hence LLV was defined as VL 100–999 copies/mL, and persistent LLV as two consecutive LLV. The analytical TAT was defined as the number of days elapsed between the date a sample was collected until the date the VL result was entered in the OpenMRS database and thus available to the clinician. Between these time points is the transport to the laboratory, the processing of the sample, result generation, result return to the on-site laboratory (if sent to the referral laboratory) and entry into the openMRS database. The overall TAT was defined as the number of days elapsed between the date a sample was collected until the date the patient received the results (among those who returned) and therapeutic measures could be taken (first clinical visit after the result was entered into OpenMRS). Additionally, for PLHIV with unsuppressed VL and a follow-up VL, the follow-up TAT was defined as the number of days elapsed between the date of unsuppressed VL result entry in the openMRS database to the date follow up VL result was entered in openMRS, Fig. 1 . Analytical TAT defined as the number of days elapsed between date of a sample was collected to date of VL result entry into OpenMRS with immediate availability to the clinician. Overall, TAT defined as the number of days elapsed between date a sample was collected to date the patient received results (corresponding to the next clinical visit among those who returned) and therapeutical consequences could take place. For patients with unsuppressed VL and a follow-up VL, follow up TAT defined as the number of days elapsed between date of unsuppressed VL result entry into openMRS database and date follow up VL is entered in openMRS Statistical methods Medians, interquartile (IQ) ranges, frequencies and proportions were used to describe PLHIV’ baseline characteristics, the VL monitoring cascade and TAT. TATs between the on-site and referral laboratories were compared using Wilcoxon rank sum tests. Analyses were performed using Stata version 15 ( 14 ). Covariates Baseline covariates were age, gender, marital status, highest education level, occupation, distance in km of residence from the clinic, daily alcohol consumption, body mass index (BMI), HIV WHO stage, CD4 cell count, ART regimen line, years since ART initiation, and calendar year. BMI, CD4 cell count and HIV WHO stage were those measurements closest to baseline, provided within 18 months before and up to 3 months after. Results Baseline characteristics From August 2017 to July 2020, 5,561 PLHIV visited the clinic. Of these, 1,107 were excluded from the analysis due to age < 15 years (N = 425), not being on ART (N = 89) or on ART for less than 6 months (N = 593 Among the 4,454 PLHIV included, 3,082 (69%) were female and median age was 42 years (IQR 35–51; Table 1 ). More than half of PLHIV (N = 2,528; 57%) were married, 3,709 (84%) had primary school education, 3,666 (83%) were farmers and 2,074 (48%) lived within a distance of less than 1 km from the clinic. The majority of PLHIV had a normal body mass index of 18.5–25 kg/m 2 (2,582; 60%). A WHO stage III/IV was diagnosed in 1,998 (45%) and the CD4 cell count was < 350 cells/ml in 1,205 (27%). The majority of PLHIV (2,798 (63%)) had been on ART for more than 2 years. Table 1 PLHIV’ characteristics at baseline a Characteristics All PLHIV n = 4454 Socio-demographics Age categories (years), n (%) 15–24 25–34 35–44 ≥45 281 (7%) 769 (17%) 1546 (35%) 1858 (42%) Gender, n (%) Male Female 1372 (31%) 3082 (69%) Married Status, n (%) Married/Cohabiting (%) Never married Separated/divorced/widowed Missing 2528 (57%) 474 (11%) 1451 (33%) 1 (< 0.1%) Education, n (%) None Primary Secondary and above/other Missing 363 (8%) 3709 (84%) 371 (8%) 11 (0.3%) Occupation, n (%) Farmer Non farmer Missing 3666 (83%) 777 (18%) 11 (0.3%) Distance of residence from clinic, n (%) ≤1 km 2 – <50 km ≥50 km Missing 2074 (48%) 1451 (33%) 835 (19%) 94 (2%) Daily alcohol consumption, n (%) No Yes 4403 (98%) 101 (2%) Clinical Body Mass Index, Kg/m 2 , n (%) b Underweight, < 18.5 Normal, 18.5 - <25 Overweight, 25 - <30 Obese, ≥ 30 Missing 365 (8%) 2582 (60%) 922 (21%) 464 (11%) 121 (3%) WHO Stage, n (%) b I II III IV Missing 1463 (33%) 986 (22%) 1378 (31%) 620 (14%) 7 (0.2%) CD4 cell count (cells/µl) b , n (%) <100 100–349 ≥350 Missing 157 (4%) 1048 (24%) 3192 (73%) 57 (1%) On Second line ART, n (%) No Yes 3976 (89%) 478 (11%) Baseline a calendar year, n (%) 2017 2018 2019 2020 3045 (68%) 813 (18%) 465 (11%) 131 (3%) Years since ART initiation, n (%) <2 years 2 – <5 years ≥5 years 1656 (37%) 1100 (25%) 1698 (38%) The characteristics analyzed are in number and percent of those with non-missing data, missing data rows are in number and column %. a at the first clinical visit aged ≥ 15 years old with at least 6 months on ART between August 2017 to July 2020. b nearest recorded measurement of BMI, CD4 cell count, WHO stage 18 months before to 3 months after baseline Viral load testing Cascade Among the 4,454 PLHIV, 4,238 (95%) had a blood sample taken for VL measurement. Of those, 4,177 (99%) had a VL result reported in the openMRS database (Fig. 2 and Table 2 ). Viral suppression was documented in 3,683/4,177 (88%) PLHIV, whereby 3,312 (79%) had a VL < 100 copies/ml, 371 (9%) had LLV and 494 (12%) were unsuppressed. Table 2 HIV Viral load monitoring cascade and outcomes Description N (%) or Median (IQR) 1. Cascade of viral load testing a. Number of PLHIV b. PLHIV with blood sample taken for VL testing c. PLHIV with a VL result reported in the medical records i. Overall number of VL test results ii. VL tests per person, median (IQR) 4,454 4,238/4,454 (95%) 4,177/4,238 (99%) 12,512 3 (2–4) 2. Results of first VL measurement a. VL < 1000 copies/mL (suppressed VL) i. VL 100–999 copies/mL (Low-level viremia (LLV)) ii. VL < 100 copies/mL b. VL ≥ 1000 copies/mL (unsuppressed VL) 3,683/4,177 (88%) 371/4,177 (9%) 3,312/4,177 (79%) 494/4,177 (12%) 3. Cascade of care for PLHIV with VL < 100 copies/mL, n = 3,312 a. Number with follow-up VL b. Median time to follow-up VL, n = 2,876 c. VL < 100 copies/mL d. LLV e. Unsuppressed VL 2,876/3,312 (87%) 12.0 months (11.8–13.2) 2,653/2,876 (92%) 132/2,876 (5%) 91/2,876 (3%) 4. Cascade of care for PLHIV with LLV, n = 371 a. Number with follow-up VL b. Median time to follow-up VL, n = 327 c. VL < 100 copies/mL d. Persistent LLV e. Unsuppressed VL 327/371 (88%) 9.0 months (6.0-12.2) 267/327 (82%) 41/327 (13%) 19/327 (6%) 5. Cascade of care for PLHIV with unsuppressed VL, n = 494 a. No follow-up VL b. Virologic failure (VF) c. Suppressed VL i. VL < 100 copies/mL ii. LLV d. Months from date of unsuppressed VL to date of follow-up VL, median (IQR), n = 425 i. ≤ 4 months ii. 5–6 months iii. 7–9 months iv. 10–12 months v. ≥ 13 months e. Switched to second line ART among suppressed follow up VL, n = 267 i. Already on second line ART at unsuppressed VL ii. Switched to second line ART by follow-up VL f. Outcomes for those with VF, n = 158 i. Already on second line ART at follow-up VL ii. Of those still on first-line, switched to second line ART - Months from date of follow-up VL to date of second line ART switch, n = 32 iii. No switch to second line despite VF -Had a third VL i. Unsuppressed VL ii. Suppressed VL - Months from date of follow-up VL to date of status (database censor date/LTFU/death), n = 23 - ≤ 4 months since follow-up VL - Active in care - LTFU - Died - Transfer out 69/494 (14%) 158/425 (37%) 267/425 (63%) 216/425 (51%) 51/425 (12%) 6.4 months (5.1–9.0) 102 (24%) 136 (32%) 114 (27%) 40 (9%) 33 (8%) 109/267 (41%) 11/267 (4%) 103/158 (65%) 32/55 (58%) 7.7 months (4.7–12.7) 23/55 (42%) 16/23 (26%) 3/16 (19%) 13/16 (81%) 16.4 months (9.1–25.8) 5/23 (22%) 14/23 (61%) 6/23 (26%) 2/23 (9%) 1/23 (4%) VL: HIV viral load, LTFU: lost to Follow-up HIV viral load monitoring cascade of KIULARCO PLHIV (percentages are of the numbers in the preceding bar). Bars show number of patients at different stages of the VL monitoring cascade. Cascade after unsuppressed VL Among the 494 (12%) PLHIV with unsuppressed VL, 425 (86%) had a follow up VL done after a median of 6.4 months (IQR 5.1–9.1). Of those, 267 (63%) were virally suppressed, whereby 216 (51%) had a VL < 100 copies/ml, 51 (12%) had LLV and 158 (37%) had VF (Fig. 2 and Table 2 ). Among 69 PLHIV with no follow-up VL, 10 (15%) were in active care, 41 (59%) had been lost to follow-up (LTFU), 6 (9%) had died and 12 (17%) were transferred to another clinic. Within study duration, the median follow-up time of unsuppressed VL (among those active-in-care), LTFU, death or transfer to another clinic was 6.1 months (IQR 3.0 -9.8). Of the 158 PLHIV with VF, 103 (65%) were already on second-line ART at the time of follow-up VL. Among the 55 PLHIV on first-line ART, 32 (58%) were switched from first- to second-line ART after a median of 7.7 months (IQR 4.7–12.7). Of the 23 PLHIV not switched, 14 (61%) were in active care, 6 (26%) were LTFU, 2 (9%) had died and 1 (4%) had transferred to another clinic. Of the 267 PLHIV who had a first unsuppressed VL and a suppressed follow-up VL, 109 (40%) were already on second-line ART at the first unsuppressed VL measurement and 11 (4%) were switched following the first unsuppressed VL (Fig. 2 and Table 2 ). Cascade after LLV Among 371 (9%) PLHIV who had LLV, 327 (88%) had a follow up VL done after a median of 9.0 months (IQR 6.0-12.1). Of these, 267 (82%) had follow-up a VL < 100 copies/ml, 41 (13%) had persistent LLV and 19 (6%) were unsuppressed (Fig. 2 and Table 2 ). Cascade after suppressed VL Among 3,312 (79%) PLHIV with a VL < 100 copies/ml, 2,876 (87%) had a follow-up VL done after a median of 12.0 months (IQR 11.8–13.2). Of those, 2,653 (92%) still had VL < 100 copies/ml, while 132 (5%) had LLV and 91 (3%) were unsuppressed Turn-around time (TAT) Among 4,454 PLHIV, 12,512 VL test results were received, with a median number of VL tests per person of 3 (IQR 2–3). Only 3,342 (27%) VL tests were processed within ≤ 14 days as per national guidelines recommendation. The median analytical TAT was 27 days (IQR 14–61), whereby at the on-site laboratory it was 21 days (IQR 13–39) versus 59 days (IQR 27–99) at the referral laboratory (p < 0.001; Table 3 ). The overall TAT– including result provision to the patient – was similar irrespective of the site of testing or unsuppressed VL results, with a median of 91 days (36–94) and 88 days (28–96) respectively. For those with unsuppressed VL, only 93 (19%) of follow-up VL samples were processed in ≤ 14 days and the median analytical TAT was 17 days (IQR 8–31) at the on-site versus 71 days (IQR 35–103) at the referral laboratory (p < 0.001). The median TAT until a patient received a result was 4.8 months (IQR 3.2–6.8) and only 102 (24%) had a follow-up VL within 4 months as per national guidelines. Table 3: Time around time for all PLHIV and those with unsuppressed VL Description Median (IQR) 1. TAT for all VL tests Analytical TAT (date sample taken to date result entered into openMRS database), n=12,512 Processed in ≤14 days Overall, median (IQR) Sample processed at on-site laboratory, median (IQR) Sample processed at referral laboratory, median (IQR) Overall TAT (date sample was taken to date participant received results (next clinical visit)), n=8,385 Overall, median (IQR) Sample processed at on-site laboratory, median (IQR) Sample processed at referral laboratory, median (IQR) 3,342 (27%) 27 days (14-61) 21 days (13-39) 59 days (27-99) 91 days (36-94) 91 days (33-93) 91 days (76-123) 2. TAT for PLHIV with unsuppressed VL Analytical TAT, n=494 Processed in ≤14 days Overall, median (IQR) Sample processed at on-site laboratory, median (IQR) Sample processed at referral laboratory, median (IQR) Overall TAT, n=485 Overall, median (IQR) Sample processed at on-site laboratory, median (IQR) Sample processed at referral laboratory, median (IQR) Follow-up VL TAT (date from unsuppressed VL result entry into openMRS database to date of follow up VL, n=425 Overall, median (IQR) Sample processed at on-site laboratory, median (IQR), n=272 Sample processed at referral laboratory, median (IQR), n=153 93 (19%) 49 days (20-88) 17 days (8-31) 71 days (35-103) 88 days (28-96) 85 days (30-95) 91 days (74-118) 4.8 months (3.2-6.8) 5.2 months (3.4-8.2) 3.9 months (3.2-5.8) TAT: Turnaround time, VL: Viral load, Discussion In this study nested within the KIULARCO cohort we have shown, that in the first three years after implementation of VL monitoring in our rural site, testing coverage among PLHIV on ART was high with 95% and 88% viral suppression. The median analytical TAT of samples processed at the on-site laboratory was one third of the time compared to samples sent to the referral laboratory. However, the time until clinical management remained long with 90 days irrespective of the testing site, indicating the challenge of getting unsuppressed PLHIV to return to care earlier than scheduled despite tracking activities. Among PLHIV with an unsuppressed VL only 24% had a follow up VL within the 4 months as recommended by the National HIV treatment guidelines. Of those with an LLV, 6% became unsuppressed within a year. Studies from different rural sub-Saharan African sites showed VL monitoring coverage rates ranging from 64–90% ( 15 , 16 ). In our study testing coverage of those in care reached 95% following VL monitoring roll out by the National AIDS Control Program and the implementing partner USAID Boresha Afya after starting with 22% in 2017 ( 17 ). The viral suppression rate during the study period was 88% - comparable to the 91% found in a previous study from our site( 18 ) and to the national level of 87% (84% of males and 89% of females) assessed during the Tanzania HIV Impact Survey (THIS) 2016-17 ( 19 , 20 ). While these numbers are close to the third 90% of the 2020 UNAIDS goals ( 21 ), a gap remains to reach the 2030 UNAIDS goals of 95% viral suppression of those on ART ( 22 ). This might be facilitated by the introduction of integrase inhibitors as first line treatment at the beginning of 2019 in Tanzania ( 8 , 22 ) – which was not yet implemented during the study period. The overall analytical TAT in this real-life rural sub-Saharan African setting was 27% and still notably longer than the 14 days recommended by Tanzanian’s National AIDS Control Programme guidelines ( 8 ). Other studies from sub-Saharan Africa using similar definitions showed median TATs ranging from 15–67 days ( 23 , 24 ). The improvement of the analytical TAT by performing the VL in an on-site laboratory compared to a referral laboratory has previously been reported by others. A study from Malawi could show a substantial impact of distance from the laboratory to the clinic on the TAT, suggesting inefficiency of specimen transfer as a factor driving longer turnaround times ( 25 ). This was confirmed by a reduction of the median analytical TAT for VL results of about 3 times after implementation of testing at the on-site laboratory in our study (from 59 to 21 days). Major reasons are inconsistent transport availabilities, weather conditions affecting road conditions, reagent stockouts, equipment and electricity shutdowns and administrative delays ( 23 – 25 ). Thus, there is a clear benefit of a molecular laboratory capable of conducting VL testing located in remote areas with high patient numbers. Additionally, point of care platforms such as GeneXpert can reduce the TAT of the results ( 26 ) and thus benefit clinically unstable PLHIV with a same day result for VL targeted monitoring and clinical decision making. On the other hand, the analytical TAT unfortunately did not affect the time until the patient received the results (overall TAT). The most important challenge was to track patients and convince them to come to an earlier than planned appointment. Reasons for not coming early indicated by PLHIV were socioeconomic constraints – mostly small-scale farmers and fishermen – with inability to come up for transport costs. A considerable number of PLHIV in our study (835 (19%)) live ≥ 50 kms away from the clinic with poor road infrastructure and are usually prescribed drugs for three months. In addition, the procedures in place to track PLHIV with an unsuppressed VL as per National HIV treatment guidelines were only partially successful as, even if PLHIV have phones, they frequently are not reachable due to network and electricity shortages. Innovative methods of VL results feedback to PLHIV such as use of mobile short message services might help in overcoming this challenge ( 27 , 28 ). The majority of PLHIV with an unsuppressed VL had re-suppressed at the follow-up testing (63%), which is an indicator for non-adherence rather than resistance and supports the strategy of enhanced adherence counselling. Etoori et al showed a re-suppression rate in Swaziland of 62% ( 9 ) while Glass et al reported a lower re-suppression rate of 45% in Lesotho ( 29 ). In our study, interestingly, 65% of PLHIV were already on second line at the time first VL measurement, indicating previous persistent treatment adherence problems. We reported a similar finding from a study of PLHIV switched to second line treatment in whom 13.1% had VF and no resistance could be documented at the time of switch nor after 6–12 months on second line treatment ( 30 ). Until recently, the WHO guidelines defined an unsuppressed VL using a threshold of ≥ 1000copies/mL( 2 ). Discussion on the implications of VL results between 100 and 999copies/mL was ongoing after increasing evidence of poor outcome in patients with LLV ( 31 – 33 ). Our study reports 9% frequency of LLV. Data from other sites are quite diverse with some reporting high rates of LLV of 23% − 38% frequency ( 34 , 35 ), while others show similar figures around 2–9% ( 30 , 36 , 37 ). Only in mid of this year, the WHO has updated its guidelines and newly defines virologic suppression as a VL 50copies/ml( 2 ). In our study, 6% of those with LLV progressed to unsuppressed VL in a median time of 9 months hence these PLHIV may benefit from closer monitoring. High-level resistance to at least two drugs has also been documented among PLHIV with LLV of 84–94%. PLHIV having high-level resistance to at least two drugs of NNRTI-based first-line ART regimen in studies from Lesotho ( 31 , 32 ). The strength of our study is the prospective real-life setting large cohort of PLHIV. The limitations of our study were: first, no resistance testing was done to identify the reasons for high VL in particular, among those with unsuppressed VL who switched to second line ART before having follow up VL and thus we could not determine if the decision to switch to second-line ART was justified or not. Second, we could not assess the impact of adherence counselling among those with unsuppressed VL. Similarly, we could not verify if all who had treatment switch to second line had treatment adherence counselling as per the national’s HIV treatment guidelines. Third, analytical TAT at both on-site and referral laboratories may have been affected by stock out of reagents, breakdown of machines, which may result to huge backlog of samples affecting TAT results. Conclusion Robust VL monitoring is achievable in rural remote resource limited settings and with reduced turnaround time of viral load results. The majority of PLHIV with VF were already on second-line ART indicating persistent adherence problems, meaning that it is crucial enhanced treatment adherence counselling is done timely and early enough to prevent HIV drug resistance development. Abbreviations VL; HIV viral load PLHIV; people living with HIV ART; antiretroviral therapy KIULARCO; Kilombero and Ulanga Antiretroviral Cohort SFRH; St. Francis Referral Hospital MRRH; Morogoro Regional Referral Hospital IHI; Ifakara Health Institute CDCI; Chronic Diseases Clinic of Ifakara LLV; low-level viremia WHO; World Health Organization VF; virologic failure TAT; turnaround time IQR; interquartile range BMI; body mass index OpenMRS; Open medical record system THIS; Tanzania HIV Impact Survey Declarations Ethics statement All PLHIV sign an informed consent before being enrolled into KIULARCO. For participants below 18years of age, informed consent was obtained from the parents or legal guardian. Ethical approval was obtained from the Ifakara Health Institute review board (IHI/IRB/No16-2006), the National Health Research Committee of the National Institute of Medical Research of Tanzania (NIMR/HQ/R.8a/Vol.IX/620) with yearly renewal, and the Ethikkomission Nordwest- und Zentralschweiz (EKNZ; Switzerland). All methods were performed within the respective ethical frameworks and in accordance with the National HIV/AIDS control guidelines and regulations. Consent for publication Participants also consented to data being published. Availability of data and materials All data generated and analysed during this study are included in this published article Competing interests All authors declare that they have no competing interests Funding The Chronic Disease Clinic in Ifakara receives funding from the Ministry of Health and Social Welfare of the government of Tanzania; the government of the Canton of Basel Stadt, Switzerland; the Swiss Tropical and Public Health Institute (Basel, Switzerland); the Ifakara Health Institute (Ifakara, Tanzania); and USAID Boresha Afya (service and medication support, with funding provided by the US Agency for International Development through the President’s Emergency Plan for AIDS Relief). Authors’ contributions: DM contributed to the study design and drafted the analytical plan, supervised all viral load testing at the laboratory and wrote the manuscript; JO collaborated in drafting the analytical plan and did the statistical analysis. TK, RN, NK, AN, TB, FA, PM, ET, TF provided diagnostic and clinical expertise, coordination and operational support and reviewed the manuscript. TG and FV supervised the statistical analysis MW designed the study and supervised the study implementation, statistical analytical plan and manuscript writing. MW also provided diagnostic and clinical expertise. All authors reviewed and approved the final manuscript. Acknowledgment: We thank all the collaborators at all levels, the staff of the Chronic Disease Clinic in Ifakara at St. Francis Referral Hospital (Ifakara, Tanzania) and participants of the KIULARCO cohort. Members of the KIULARCO Study Group: Aschola Asantiel, Farida Bani, Manuel Battegay, Theonestina Byakuzana, Adolphina Chale, Anna Eichenberger, , Gideon Francis, Hansjakob Furrer, , Tracy R. Glass, Speciosa Hwaya, Aneth V. Kalinjuma, , Bryson Kasuga, Andrew Katende, Namvua Kimera, Yassin Kisunga, Olivia Kitau, Thomas Klimkait, , Ezekiel Luoga, , Herry Mapesi, Mengi Mkulila, Margareth Mkusa, Slyakus Mlembe, Dorcas K. Mnzava, Gertrud J. Mollel, Lilian Moshi, Germana Mossad, Dolores Mpundunga, Athumani Mtandanguo, Selerine Myeya, Sanula Nahota, Regina Ndaki, Robert C. Ndege, Agatha Ngulukila, Alex John Ntamatungiro, Amina Nyuri, James Okuma, Daniel H. Paris, Leila Samson, Elizabeth Senkoro, Jenifa Tarimo, Yvan Temba, Juerg Utzinger, Fiona Vanobberghen, Maja Weisser, John Wigayi, And Herieth Wilson, Bernard Kivuma, George Sigalla, Ivana Di Salvo, Michael Kasmiri, Suzan Ngahyoma, Victor Urio, Aloyce Sambuta, Francisca Chuwa , Swalehe Masoud, Yvonne R Haridas, Jackline Nkouabi. References UNAIDS. United Republic of Tanzania | UNAIDS [Internet]. [cited 2021 May 9]. Available from: https://www.unaids.org/en/regionscountries/countries/unitedrepublicoftanzania . World Health Organization. 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Optimizing viral load testing access for the last mile: Geospatial cost model for point of care instrument placement. PLoS One. 2019. Health MF, Development C, Gender, Elderly AC. National Aids Control Programme. National Guidelines for The Management Of HIV And AIDS [Internet]. 2019. Available from: https://www.differentiatedservicedelivery.org/Portals/0/adam/Content/NqQGryocrU2RTj58iR37uA/File/NATIONAL_GUIDELINES_FOR_THE_MANAGEMENT_OF_HIV_AND_AIDS_2019.pdf . Etoori D, Ciglenecki I, Ndlangamandla M, Edwards CG, Jobanputra K, Pasipamire M, et al. Successes and challenges in optimizing the viral load cascade to improve antiretroviral therapy adherence and rationalize second-line switches in Swaziland. J Int AIDS Soc [Internet]. 2018 Oct 1 [cited 2021 Apr 19];21(10). Available from: /pmc/articles/PMC6198167/ . Olivia Keiser H, Tweya P, Braitstein F, Dabis P, MacPhail, et al. Mortality after failure of antiretroviral therapy in sub-Saharan Africa. Trop Med Int Heal [Internet]. 2010;volume 15:pp 251–258. Available from: chrome- extension://dagcmkpagjlhakfdhnbomgmjdpkdklff/enhanced-reader.html?openApp&pdf = https%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2Fpdfdirect%2F 10.1111%2Fj.1365-3156.2009.02445.x. Olivia Keiser BH, Chi T, Gsponer A, Boulle C, Orrell S, Phiri, et al. Outcomes of Antiretroviral Treatment in Programmes with and without Routine Viral Load Monitoring in Southern Africa. AIDS [Internet]. 2011; Available from: https://pubmed.ncbi.nlm.nih.gov/21681057/ . Letang E, Kalinjuma AV, Glass TR, Gamell A, Mapesi H, Sikalengo G, et al. Cohort profile: The Kilombero and Ulanga Antiretroviral Cohort (KIULARCO) - A prospective HIV cohort in rural Tanzania. Swiss Med Wkly. 2017. Vanobberghen F, Letang E, Gamell A, Mnzava DK, Faini D, Luwanda LB, et al. A decade of HIV care in rural Tanzania: Trends in clinical outcomes and impact of clinic optimisation in an open, prospective cohort. PLoS One [Internet]. 2017 Jul 1 [cited 2021 May 9];12(7):e0180983. Available from: https://doi.org/10.1371/journal.pone.0180983 . StataCorp. Stata Statistical Software: Release 15. College Station, TX: StataCorp LLC. [Internet]. 2017. Available from: https://www.stata.com/ . Nakalega R, Mukiza N, Kiwanuka G, Makanga-Kakumba R, Menge R, Kataike H, et al. Non-uptake of viral load testing among people receiving HIV treatment in Gomba district, rural Uganda. BMC Infect Dis. 2020 Oct 6;20(1). Lecher S, Williams J, Fonjungo PN, Kim AA, Ellenberger D, Zhang G, et al. Progress with scale-up of HIV viral load monitoring — seven Sub-Saharan African countries, January 2015–June 2016. Morbidity and Mortality Weekly Report; 2016. Antelman G, van de Ven R, Mukaminega M, Haule D, van ‘t Pad Bosch J SG. Title: Who does HIV viral load testing reach first? Lessons from Tanzania’s first year of scaling up HIV viral load accessibility. 2018. Ntamatungiro AJ, Muri L, Glass TR, Erb S, Battegay M, Furrer H, et al. Strengthening HIV therapy and care in rural Tanzania affects rates of viral suppression. J Antimicrob Chemother. 2017. Statistics NB. of. National Bureau of Statistics - The Tanzania HIV Impact Survey 2016–2017 (THIS) - Final Report [Internet]. [cited 2021 Apr 19]. Available from: https://www.nbs.go.tz/index.php/en/census-surveys/health-statistics/hiv-and-malaria-survey/382-the-tanzania-hiv-impact-survey-2016-2017-this-final-report . UNAIDS. United Republic of Tanzania | UNAIDS [Internet]. [cited 2021 Apr 19]. Available from: https://www.unaids.org/en/keywords/united-republic-tanzania . UNAIDS. 90-90-90: treatment for all | UNAIDS [Internet]. [cited 2021 Aug 4]. Available from: https://www.unaids.org/en/resources/909090 . UNAIDS. UNAIDS Issues New Fast-Track. Strategy to End AIDS by 2030 - EGPAF [Internet]. [cited 2021 Apr 16]. Available from: https://www.pedaids.org/2014/11/20/unaids-issues-new-fast-track-strategy-to-end-aids-by-2030/ . Mbiva F, Tweya H, Satyanarayana S, Takarinda K, Timire C, Dzangare J, et al. Long turnaround times in viral load monitoring of people living with HIV in resource-limited settings. J Glob Infect Dis [Internet]. 2021 [cited 2021 Jun 9];13(2):85. Available from: https://www.jgid.org/article.asp?issn=0974-777X ;year=2021;volume=13;issue=2;spage=85;epage=90;aulast=Mbiva. Shiferaw MB, Yismaw G. Magnitude of delayed turnaround time of laboratory results in Amhara Public Health Institute, Bahir Dar, Ethiopia. BMC Health Serv Res [Internet]. 2019 Apr 24 [cited 2021 Jun 9];19(1):1–6. Available from: https://link.springer.com/articles/ 10.1186/s12913-019-4077-2 . Minchella PA, Chipungu G, Kim AA, Sarr A, Ali H, Mwenda R, et al. Specimen origin, type and testing laboratory are linked to longer turnaround times for HIV viral load testing in Malawi. PLoS One [Internet]. 2017 Feb 1 [cited 2021 Apr 21];12(2). Available from: https://pubmed.ncbi.nlm.nih.gov/28235013/ . Nicholas S, Poulet E, Wolters L, Wapling J, Rakesh A, Amoros I, et al. Point-of-care viral load monitoring: outcomes from a decentralized HIV programme in Malawi. J Int AIDS Soc. 2019. Lester RT, Ritvo P, Mills EJ, Kariri A, Karanja S, Chung MH, et al. Effects of a mobile phone short message service on antiretroviral treatment adherence in Kenya (WelTel Kenya1): A randomised trial. Lancet. 2010 Nov 27;376(9755):1838–45. Da Costa TM, Barbosa BJP, Costa E, Sigulem DAG, De Fátima Marin D, Filho H. AC, et al. Results of a randomized controlled trial to assess the effects of a mobile SMS-based intervention on treatment adherence in HIV/AIDS-infected Brazilian women and impressions and satisfaction with respect to incoming messages. Int J Med Inform [Internet]. 2012 Apr [cited 2021 Nov 22];81(4):257–69. Available from: https://pubmed.ncbi.nlm.nih.gov/22296762/ . Glass TR, Motaboli L, Nsakala B, Lerotholi M, Vanobberghen F, Amstutz A, et al. The viral load monitoring cascade in a resource-limited setting: A prospective multicentre cohort study after introduction of routine viral load monitoring in rural Lesotho. PLoS One. 2019 Aug 1;14(8). Bircher RE, Ntamatungiro AJ, Glass TR, Mnzava D, Nyuri A, Mapesi H, et al. High failure rates of protease inhibitor-based antiretroviral treatment in rural Tanzania – A prospective cohort study. PLoS One [Internet]. 2020 Jan 1 [cited 2021 Apr 20];15(1). Available from: https://pubmed.ncbi.nlm.nih.gov/31929566/ . Labhardt ND, Bader J, Lejone TI, Ringera I, Hobbins MA, Fritz C, et al. Should viral load thresholds be lowered? Revisiting the WHO definition for virologic failure in patients on antiretroviral therapy in resource-limited settings. Med (United States) [Internet]. 2016 Jul 1 [cited 2021 Jun 16];95(28). Available from: https://journals.lww.com/md-journal/Fulltext/2016/07120/Should_viral_load_thresholds_be_lowered__.11.aspx . Brown JA, Amstutz A, Nsakala BL, Seeburg U, Vanobberghen F, Vanobberghen, et al. Extensive drug resistance during low-level HIV viraemia while taking NNRTI-based ART supports lowering the viral load threshold for regimen switch in resource-limited settings: a pre-planned analysis from the SESOTHO trial. J Antimicrob Chemother [Internet]. 2021 Apr 13 [cited 2021 Jun 16];76(5):1294–8. Available from: https://pubmed.ncbi.nlm.nih.gov/33599270/ . Amstutz A, Nsakala BL, Vanobberghen F, Muhairwe J, Glass TR, Achieng B, et al. SESOTHO trial (“Switch Either near Suppression Or THOusand”) - switch to second-line versus WHO-guided standard of care for unsuppressed patients on first-line ART with viremia below 1000 copies/mL: Protocol of a multicenter, parallel-group, open-label, r. BMC Infect Dis. 2018 Feb 12;18(1). Brown JA, Amstutz A, Nsakala BL, Seeburg U, Vanobberghen F, Vanobberghen, et al. Extensive drug resistance during low-level HIV viraemia while taking NNRTI-based ART supports lowering the viral load threshold for regimen switch in resource-limited settings: a pre-planned analysis from the SESOTHO trial. J Antimicrob Chemother [Internet]. 2021 Apr 13 [cited 2021 Nov 22];76(5):1294–8. Available from: https://pubmed.ncbi.nlm.nih.gov/33599270/ . Zhang T, Ding H, An M, Wang X, Tian W, Zhao B, et al. Factors associated with high-risk low-level viremia leading to virologic failure: 16-year retrospective study of a Chinese antiretroviral therapy cohort. BMC Infect Dis [Internet]. 2020 Feb 17 [cited 2021 Apr 22];20(1):147. Available from: https://bmcinfectdis.biomedcentral.com/articles/ 10.1186/s12879-020-4837-y . Delaugerre C, Gallien S, Flandre P, Mathez D, Amarsy R, Ferret S, et al. Impact of low-level-viremia on HIV-1 drug-resistance evolution among antiretroviral treated-patients. PLoS One. 2012. Fleming J, Mathews WC, Rutstein RM, Aberg J, Somboonwit C, Cheever LW, et al. Low-level viremia and virologic failure in persons with HIV infection treated with antiretroviral therapy. AIDS [Internet]. 2019 Nov 1 [cited 2021 Jun 16];33(13):2005–12. Available from: https://pubmed.ncbi.nlm.nih.gov/31306175/ . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 07 Apr, 2023 Read the published version in BMC Infectious Diseases → Version 1 posted Editor invited by journal 14 Oct, 2022 Submission checks completed at journal 14 Oct, 2022 First submitted to journal 01 Oct, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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09:59:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2123101/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2123101/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-023-08155-6","type":"published","date":"2023-04-07T20:24:31+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":27937268,"identity":"baf589a4-1d29-47f4-b53f-dcae18641160","added_by":"auto","created_at":"2022-10-18 15:10:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":24792,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram for analytical, overall and follow-up TAT.\u003c/p\u003e","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2123101/v1/d03626d61352af48b2dcab4c.png"},{"id":27937267,"identity":"e7a5ae15-cfb3-4fdc-8ab5-10109bf7c426","added_by":"auto","created_at":"2022-10-18 15:10:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":26609,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHIV viral load cascade\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-2123101/v1/7a29102e3aa01ba48044fd0c.png"},{"id":44724491,"identity":"409b3e94-8aab-41c3-8c48-d0c8a38327e2","added_by":"auto","created_at":"2023-10-16 20:31:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":515568,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2123101/v1/9d10519e-89d4-436e-b793-34a5b3a7bfc4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Decentralization of viral load testing to improve HIV care and treatment cascade in rural Tanzania: Data from the Kilombero and Ulanga Antiretroviral Cohort","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe number of people living with HIV (PLHIV) on antiretroviral therapy (ART) globally and in Tanzania has been increasing over time with 82% accessing ART in 2020 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). HIV viral load (VL) testing in PLHIV \u0026ndash; the preferred monitoring approach by the World Health Organization (WHO) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) \u0026ndash; allows early detection of treatment failure and guides treatment decisions, for example adherence counselling or regimen change. In sub\u0026ndash;Saharan Africa, VL monitoring has been scaled up in recent years with investments strengthening VL processing hubs and sample transportation systems, to overcome challenges of transport and result transmission especially in remote settings (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In Tanzania, the government scaled up routine VL testing in 2017 through establishment of VL processing centres (hubs) and policies enabling all PLHIV to receive VL testing (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). For remote health facilities, the long distances to referral VL processing hubs, poor road infrastructures (especially during the rainy season), unreliable transport systems, and the danger of blood sample degradation due to failure of cold chains remain a challenge (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor successful VL monitoring, a reliable testing process with a rapid turnaround time (TAT) is key and affects all stages of the testing cascade including blood withdrawal, sample transport and processing, generation of results, feedback to clinicians and PLHIV, and timely subsequent action. Samples for VL testing are recommended to be processed and results made available to the clinicians within 14 days for management of treatment (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). According to the Tanzania National AIDS Control Program guidelines, the first VL test is done at 6 months after initiation of ART and a second at 12 months. If both viral load results are \u0026lt;\u0026thinsp;1000 copies/mL, VL is then monitored yearly. PLHIV with unsuppressed VL receive enhanced adherence counselling for three months followed by a follow-up VL test in the fourth month - if reported adherence is \u0026gt;\u0026thinsp;95%. If the follow-up VL result is below 1000copies/ml, the patient will continue with the same drug regimen, otherwise the recommendation is to switch to a second-line ART regimen(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGaps in the VL cascade, such as long TAT, delay in timely initiation of adherence counselling and/or switch to second-line ART in PLHIV with virologic failure (VF), lead to an increased risk of accumulation of drug resistance mutations, development of clinical failure and mortality as well as onwards HIV transmission (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe hypothesised that with decentralization of VL testing from a referral laboratory to an on-site molecular laboratory capable of conducting VL testing, hence avoiding sample transport to a central referral laboratory, will reduce TAT of VL results. Therefore, we aimed at describing the VL monitoring cascade, compare turnaround times of viral load results when viral load testing was done at an on-site laboratory versus a referral laboratory and assess management and outcome among those with high- and low-level viremia following the national rollout of routine VL monitoring in a cohort of PLHIV in rural Tanzania.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy setting\u003c/h2\u003e \u003cp\u003eThis is an observational study in the prospective Kilombero and Ulanga Antiretroviral Cohort (KIULARCO). Kilombero and Ulanga are rural districts in the Morogoro region in South-western Tanzania, with St. Francis Referral Hospital (SFRH) being the largest health facility providing HIV care and treatment in the region. Morogoro Regional Referral Hospital (MRRH) \u0026ndash; used for referral of laboratory services \u0026ndash; is located 229 kilometres (km) away from SFRH. KIULARCO has existed since 2005 as collaboration between the SFRH, the Ifakara Health Institute (IHI), the Swiss Tropical and Public Health Institute, and the University Hospital of Basel, Switzerland. PLHIV attending the Chronic Diseases Clinic of Ifakara (CDCI) of the SFRH are invited to participate in KIULARCO. Almost 11,000 PLHIV have been enrolled in KIULARCO as of January 2021, with information collected prospectively in an electronic patient records database (openMRS), including demographics, clinical and laboratory data, medication history, drug toxicities, diagnoses and outcomes. Details of the cohort have been described elsewhere (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRoutine VL testing at SFRH was implemented in August 2017. Plasma samples from PLHIV were transported to the referral laboratory at MRRH for analysis. Additionally, a point of care system (GeneXpert \u0026reg;) for VL testing was operating at the on-site laboratory with a 2-hour TAT for urgent cases. With the aim to decentralize VL testing, from August 2018 onwards, VL testing was started at the on-site laboratory at IHI in close collaboration with the National AIDS Control Program and the implementing partner USAID Boresha Afya. On-site laboratory at IHI offered VL testing for SFRH patients and was referral laboratory for VL testing for other peripheral health facilities. Referral of samples to MRRH was then only done in case of stock outs of reagents or machine breakdown.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003e For this study, we included all PLHIV with an informed consent enrolled in KIULARCO, who were at least 15 years old and on ART for at least 6 months with a clinical visit from August 2017 to July 2020, with follow-up through January 2021.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eVL testing and reporting procedures\u003c/h2\u003e \u003cp\u003eDuring routine visits, venous blood samples were collected in BD vacutainer EDTA tubes\u0026reg; by the phlebotomist at the clinics and brought to the on-site laboratory the same day. In the first year of roll out of VL testing (August 2017 to July 2018), blood samples were immediately centrifuged at the on-site laboratory and plasma was stored at -80\u0026deg;C freezer until transport to MRRH for VL testing. Transportation of the frozen plasma happened mostly twice a week. Upon arrival of the samples at MRRH, data clerks registered the patient-related information from the VL request forms and, depending on the work load, the samples were processed immediately or stored in -20\u0026deg;C freezers until they could be processed. VL testing was done using COBAS\u0026reg; AmpliPrep/COBAS\u0026reg; TaqMan\u0026reg; system, according to manufacturers\u0026rsquo; instructions with lowest detection limit of 20 copies/ml. Paper forms with the VL results were brought from the MRRH to the SFRH by staff who carried the samples from SFRH to the MRRH or by local arrangements with office cars whenever possible. Data clerks entered the results in the openMRS database and filed paper copies in the patient files.\u003c/p\u003e \u003cp\u003eFrom August 2018 to July 2020, VL testing happened at IHI, at the on-site laboratory on an Abbott m2000 System as per manufacturer\u0026rsquo;s instructions with lowest detection limit of 40copies/ml or 150copies/ml depending on the manufacturer\u0026rsquo;s protocol used. Depending on the work load, samples were processed immediately or stored in -80\u0026deg;C freezers until processed. VL results were then entered in the openMRS database. PLHIV were scheduled for routine VL testing or follow-up of unsuppressed VL following national guidelines(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In addition to VL control according guidelines, we controlled VL in PLHIV with LLV at their next scheduled visit.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eObjectives and definitions\u003c/h2\u003e \u003cp\u003eThe main objective of the study was the description of the VL monitoring cascade and comparison of TAT between the on-site and the referral laboratory. The secondary objective was the outcome in PLHIV with LLV.\u003c/p\u003e \u003cp\u003eWe defined as baseline the first clinical visit of eligible patients. The VL measurement at this time is referred to as the first VL. We considered a VL\u0026thinsp;\u0026ge;\u0026thinsp;1000copies/mL as \u0026lsquo;unsuppressed\u0026rsquo; and a VL\u0026thinsp;\u0026lt;\u0026thinsp;1000copies/mL as \u0026lsquo;suppressed\u0026rsquo;. Virological failure (VF) was defined as two consecutives unsuppressed VL results despite adherence counselling. Due to having different VL measuring platforms with different lowest detection limits, we considered a VL of 100 copies/ml as the lower limit for VL detection. Hence LLV was defined as VL 100\u0026ndash;999 copies/mL, and persistent LLV as two consecutive LLV.\u003c/p\u003e \u003cp\u003eThe analytical TAT was defined as the number of days elapsed between the date a sample was collected until the date the VL result was entered in the OpenMRS database and thus available to the clinician. Between these time points is the transport to the laboratory, the processing of the sample, result generation, result return to the on-site laboratory (if sent to the referral laboratory) and entry into the openMRS database. The overall TAT was defined as the number of days elapsed between the date a sample was collected until the date the patient received the results (among those who returned) and therapeutic measures could be taken (first clinical visit after the result was entered into OpenMRS). Additionally, for PLHIV with unsuppressed VL and a follow-up VL, the follow-up TAT was defined as the number of days elapsed between the date of unsuppressed VL result entry in the openMRS database to the date follow up VL result was entered in openMRS, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnalytical TAT defined as the number of days elapsed between date of a sample was collected to date of VL result entry into OpenMRS with immediate availability to the clinician. Overall, TAT defined as the number of days elapsed between date a sample was collected to date the patient received results (corresponding to the next clinical visit among those who returned) and therapeutical consequences could take place. For patients with unsuppressed VL and a follow-up VL, follow up TAT defined as the number of days elapsed between date of unsuppressed VL result entry into openMRS database and date follow up VL is entered in openMRS\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical methods\u003c/h2\u003e \u003cp\u003eMedians, interquartile (IQ) ranges, frequencies and proportions were used to describe PLHIV\u0026rsquo; baseline characteristics, the VL monitoring cascade and TAT. TATs between the on-site and referral laboratories were compared using Wilcoxon rank sum tests. Analyses were performed using Stata version 15 (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eBaseline covariates were age, gender, marital status, highest education level, occupation, distance in km of residence from the clinic, daily alcohol consumption, body mass index (BMI), HIV WHO stage, CD4 cell count, ART regimen line, years since ART initiation, and calendar year. BMI, CD4 cell count and HIV WHO stage were those measurements closest to baseline, provided within 18 months before and up to 3 months after.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003eBaseline characteristics\u003c/h2\u003e\n \u003cp\u003eFrom August 2017 to July 2020, 5,561 PLHIV visited the clinic. Of these, 1,107 were excluded from the analysis due to age\u0026thinsp;\u0026lt;\u0026thinsp;15 years (N\u0026thinsp;=\u0026thinsp;425), not being on ART (N\u0026thinsp;=\u0026thinsp;89) or on ART for less than 6 months (N\u0026thinsp;=\u0026thinsp;593 Among the 4,454 PLHIV included, 3,082 (69%) were female and median age was 42 years (IQR 35\u0026ndash;51; Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). More than half of PLHIV (N\u0026thinsp;=\u0026thinsp;2,528; 57%) were married, 3,709 (84%) had primary school education, 3,666 (83%) were farmers and 2,074 (48%) lived within a distance of less than 1 km from the clinic. The majority of PLHIV had a normal body mass index of 18.5\u0026ndash;25 kg/m\u003csup\u003e2\u003c/sup\u003e (2,582; 60%). A WHO stage III/IV was diagnosed in 1,998 (45%) and the CD4 cell count was \u0026lt;\u0026thinsp;350 cells/ml in 1,205 (27%). The majority of PLHIV (2,798 (63%)) had been on ART for more than 2 years.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePLHIV\u0026rsquo; characteristics at baseline\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll PLHIV\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;4454\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocio-demographics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge categories (years), n (%)\u003c/p\u003e\n \u003cp\u003e15\u0026ndash;24\u003c/p\u003e\n \u003cp\u003e25\u0026ndash;34\u003c/p\u003e\n \u003cp\u003e35\u0026ndash;44\u003c/p\u003e\n \u003cp\u003e\u0026ge;45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e281 (7%)\u003c/p\u003e\n \u003cp\u003e769 (17%)\u003c/p\u003e\n \u003cp\u003e1546 (35%)\u003c/p\u003e\n \u003cp\u003e1858 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender, n (%)\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1372 (31%)\u003c/p\u003e\n \u003cp\u003e3082 (69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried Status, n (%)\u003c/p\u003e\n \u003cp\u003eMarried/Cohabiting (%)\u003c/p\u003e\n \u003cp\u003eNever married\u003c/p\u003e\n \u003cp\u003eSeparated/divorced/widowed\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2528 (57%)\u003c/p\u003e\n \u003cp\u003e474 (11%)\u003c/p\u003e\n \u003cp\u003e1451 (33%)\u003c/p\u003e\n \u003cp\u003e1 (\u0026lt;\u0026thinsp;0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducation, n (%)\u003c/p\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003cp\u003eSecondary and above/other\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e363 (8%)\u003c/p\u003e\n \u003cp\u003e3709 (84%)\u003c/p\u003e\n \u003cp\u003e371 (8%)\u003c/p\u003e\n \u003cp\u003e11 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOccupation, n (%)\u003c/p\u003e\n \u003cp\u003eFarmer\u003c/p\u003e\n \u003cp\u003eNon farmer\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3666 (83%)\u003c/p\u003e\n \u003cp\u003e777 (18%)\u003c/p\u003e\n \u003cp\u003e11 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDistance of residence from clinic, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026le;1 km\u003c/p\u003e\n \u003cp\u003e2 \u0026ndash; \u0026lt;50 km\u003c/p\u003e\n \u003cp\u003e\u0026ge;50 km\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2074 (48%)\u003c/p\u003e\n \u003cp\u003e1451 (33%)\u003c/p\u003e\n \u003cp\u003e835 (19%)\u003c/p\u003e\n \u003cp\u003e94 (2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDaily alcohol consumption, n (%)\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4403 (98%)\u003c/p\u003e\n \u003cp\u003e101 (2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody Mass Index, Kg/m\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e, n (%) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eUnderweight, \u0026lt;\u0026thinsp;18.5\u003c/p\u003e\n \u003cp\u003eNormal, 18.5 - \u0026lt;25\u003c/p\u003e\n \u003cp\u003eOverweight, 25 - \u0026lt;30\u003c/p\u003e\n \u003cp\u003eObese, \u0026ge;\u0026thinsp;30\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e365 (8%)\u003c/p\u003e\n \u003cp\u003e2582 (60%)\u003c/p\u003e\n \u003cp\u003e922 (21%)\u003c/p\u003e\n \u003cp\u003e464 (11%)\u003c/p\u003e\n \u003cp\u003e121 (3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWHO Stage, n (%) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1463 (33%)\u003c/p\u003e\n \u003cp\u003e986 (22%)\u003c/p\u003e\n \u003cp\u003e1378 (31%)\u003c/p\u003e\n \u003cp\u003e620 (14%)\u003c/p\u003e\n \u003cp\u003e7 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD4 cell count (cells/\u0026micro;l) \u003csup\u003eb\u003c/sup\u003e, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026lt;100\u003c/p\u003e\n \u003cp\u003e100\u0026ndash;349\u003c/p\u003e\n \u003cp\u003e\u0026ge;350\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e157 (4%)\u003c/p\u003e\n \u003cp\u003e1048 (24%)\u003c/p\u003e\n \u003cp\u003e3192 (73%)\u003c/p\u003e\n \u003cp\u003e57 (1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOn Second line ART, n (%)\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3976 (89%)\u003c/p\u003e\n \u003cp\u003e478 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBaseline\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e calendar year, n (%)\u003c/p\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3045 (68%)\u003c/p\u003e\n \u003cp\u003e813 (18%)\u003c/p\u003e\n \u003cp\u003e465 (11%)\u003c/p\u003e\n \u003cp\u003e131 (3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYears since ART initiation, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026lt;2 years\u003c/p\u003e\n \u003cp\u003e2 \u0026ndash; \u0026lt;5 years\u003c/p\u003e\n \u003cp\u003e\u0026ge;5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1656 (37%)\u003c/p\u003e\n \u003cp\u003e1100 (25%)\u003c/p\u003e\n \u003cp\u003e1698 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe characteristics analyzed are in number and percent of those with non-missing data, missing data rows are in number and column %. \u003csup\u003ea\u003c/sup\u003e at the first clinical visit aged\u0026thinsp;\u0026ge;\u0026thinsp;15 years old with at least 6 months on ART between August 2017 to July 2020.\u0026nbsp;\u003csup\u003eb\u003c/sup\u003e nearest recorded measurement of BMI, CD4 cell count, WHO stage 18 months before to 3 months after baseline\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003eViral load testing Cascade\u003c/h2\u003e\n \u003cp\u003eAmong the 4,454 PLHIV, 4,238 (95%) had a blood sample taken for VL measurement. Of those, 4,177 (99%) had a VL result reported in the openMRS database (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Viral suppression was documented in 3,683/4,177 (88%) PLHIV, whereby 3,312 (79%) had a VL\u0026thinsp;\u0026lt;\u0026thinsp;100 copies/ml, 371 (9%) had LLV and 494 (12%) were unsuppressed.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eHIV Viral load monitoring cascade and outcomes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN (%) or Median (IQR)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1. Cascade of viral load testing\u003c/p\u003e\n \u003cp\u003ea. Number of PLHIV\u003c/p\u003e\n \u003cp\u003eb. PLHIV with blood sample taken for VL testing\u003c/p\u003e\n \u003cp\u003ec. PLHIV with a VL result reported in the medical records\u003c/p\u003e\n \u003cp\u003ei. Overall number of VL test results\u003c/p\u003e\n \u003cp\u003eii. VL tests per person, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,454\u003c/p\u003e\n \u003cp\u003e4,238/4,454 (95%)\u003c/p\u003e\n \u003cp\u003e4,177/4,238 (99%)\u003c/p\u003e\n \u003cp\u003e12,512\u003c/p\u003e\n \u003cp\u003e3 (2\u0026ndash;4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2. Results of first VL measurement\u003c/p\u003e\n \u003cp\u003ea. VL\u0026thinsp;\u0026lt;\u0026thinsp;1000 copies/mL (suppressed VL)\u003c/p\u003e\n \u003cp\u003ei. VL 100\u0026ndash;999 copies/mL (Low-level viremia (LLV))\u003c/p\u003e\n \u003cp\u003eii. VL\u0026thinsp;\u0026lt;\u0026thinsp;100 copies/mL\u003c/p\u003e\n \u003cp\u003eb. VL\u0026thinsp;\u0026ge;\u0026thinsp;1000 copies/mL (unsuppressed VL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,683/4,177 (88%)\u003c/p\u003e\n \u003cp\u003e371/4,177 (9%)\u003c/p\u003e\n \u003cp\u003e3,312/4,177 (79%)\u003c/p\u003e\n \u003cp\u003e494/4,177 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3. Cascade of care for PLHIV with VL\u0026thinsp;\u0026lt;\u0026thinsp;100 copies/mL, n\u0026thinsp;=\u0026thinsp;3,312\u003c/p\u003e\n \u003cp\u003ea. Number with follow-up VL\u003c/p\u003e\n \u003cp\u003eb. Median time to follow-up VL, n\u0026thinsp;=\u0026thinsp;2,876\u003c/p\u003e\n \u003cp\u003ec. VL\u0026thinsp;\u0026lt;\u0026thinsp;100 copies/mL\u003c/p\u003e\n \u003cp\u003ed. LLV\u003c/p\u003e\n \u003cp\u003ee. Unsuppressed VL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,876/3,312 (87%)\u003c/p\u003e\n \u003cp\u003e12.0 months (11.8\u0026ndash;13.2)\u003c/p\u003e\n \u003cp\u003e2,653/2,876 (92%)\u003c/p\u003e\n \u003cp\u003e132/2,876 (5%)\u003c/p\u003e\n \u003cp\u003e91/2,876 (3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4. Cascade of care for PLHIV with LLV, n\u0026thinsp;=\u0026thinsp;371\u003c/p\u003e\n \u003cp\u003ea. Number with follow-up VL\u003c/p\u003e\n \u003cp\u003eb. Median time to follow-up VL, n\u0026thinsp;=\u0026thinsp;327\u003c/p\u003e\n \u003cp\u003ec. VL\u0026thinsp;\u0026lt;\u0026thinsp;100 copies/mL\u003c/p\u003e\n \u003cp\u003ed. Persistent LLV\u003c/p\u003e\n \u003cp\u003ee. Unsuppressed VL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e327/371 (88%)\u003c/p\u003e\n \u003cp\u003e9.0 months (6.0-12.2)\u003c/p\u003e\n \u003cp\u003e267/327 (82%)\u003c/p\u003e\n \u003cp\u003e41/327 (13%)\u003c/p\u003e\n \u003cp\u003e19/327 (6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5. Cascade of care for PLHIV with unsuppressed VL, n\u0026thinsp;=\u0026thinsp;494\u003c/p\u003e\n \u003cp\u003ea. No follow-up VL\u003c/p\u003e\n \u003cp\u003eb. Virologic failure (VF)\u003c/p\u003e\n \u003cp\u003ec. Suppressed VL\u003c/p\u003e\n \u003cp\u003ei. VL\u0026thinsp;\u0026lt;\u0026thinsp;100 copies/mL\u003c/p\u003e\n \u003cp\u003eii. LLV\u003c/p\u003e\n \u003cp\u003ed. Months from date of unsuppressed VL to date of follow-up VL, median (IQR), n\u0026thinsp;=\u0026thinsp;425\u003c/p\u003e\n \u003cp\u003ei. \u0026le;\u0026thinsp;4 months\u003c/p\u003e\n \u003cp\u003eii. 5\u0026ndash;6 months\u003c/p\u003e\n \u003cp\u003eiii. 7\u0026ndash;9 months\u003c/p\u003e\n \u003cp\u003eiv. 10\u0026ndash;12 months\u003c/p\u003e\n \u003cp\u003ev. \u0026ge;\u0026thinsp;13 months\u003c/p\u003e\n \u003cp\u003ee. Switched to second line ART among suppressed follow up VL, n\u0026thinsp;=\u0026thinsp;267\u003c/p\u003e\n \u003cp\u003ei. Already on second line ART at unsuppressed VL\u003c/p\u003e\n \u003cp\u003eii. Switched to second line ART by follow-up VL\u003c/p\u003e\n \u003cp\u003ef. Outcomes for those with VF, n\u0026thinsp;=\u0026thinsp;158\u003c/p\u003e\n \u003cp\u003ei. Already on second line ART at follow-up VL\u003c/p\u003e\n \u003cp\u003eii. Of those still on first-line, switched to second line ART\u003c/p\u003e\n \u003cp\u003e- Months from date of follow-up VL to date of second line ART switch, n\u0026thinsp;=\u0026thinsp;32\u003c/p\u003e\n \u003cp\u003eiii. No switch to second line despite VF\u003c/p\u003e\n \u003cp\u003e-Had a third VL\u003c/p\u003e\n \u003cp\u003ei. Unsuppressed VL\u003c/p\u003e\n \u003cp\u003eii. Suppressed VL\u003c/p\u003e\n \u003cp\u003e- Months from date of follow-up VL to date of status (database censor date/LTFU/death), n\u0026thinsp;=\u0026thinsp;23\u003c/p\u003e\n \u003cp\u003e- \u0026le; 4 months since follow-up VL\u003c/p\u003e\n \u003cp\u003e- Active in care\u003c/p\u003e\n \u003cp\u003e- LTFU\u003c/p\u003e\n \u003cp\u003e- Died\u003c/p\u003e\n \u003cp\u003e- Transfer out\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69/494 (14%)\u003c/p\u003e\n \u003cp\u003e158/425 (37%)\u003c/p\u003e\n \u003cp\u003e267/425 (63%)\u003c/p\u003e\n \u003cp\u003e216/425 (51%)\u003c/p\u003e\n \u003cp\u003e51/425 (12%)\u003c/p\u003e\n \u003cp\u003e6.4 months (5.1\u0026ndash;9.0)\u003c/p\u003e\n \u003cp\u003e102 (24%)\u003c/p\u003e\n \u003cp\u003e136 (32%)\u003c/p\u003e\n \u003cp\u003e114 (27%)\u003c/p\u003e\n \u003cp\u003e40 (9%)\u003c/p\u003e\n \u003cp\u003e33 (8%)\u003c/p\u003e\n \u003cp\u003e109/267 (41%)\u003c/p\u003e\n \u003cp\u003e11/267 (4%)\u003c/p\u003e\n \u003cp\u003e103/158 (65%)\u003c/p\u003e\n \u003cp\u003e32/55 (58%)\u003c/p\u003e\n \u003cp\u003e7.7 months (4.7\u0026ndash;12.7)\u003c/p\u003e\n \u003cp\u003e23/55 (42%)\u003c/p\u003e\n \u003cp\u003e16/23 (26%)\u003c/p\u003e\n \u003cp\u003e3/16 (19%)\u003c/p\u003e\n \u003cp\u003e13/16 (81%)\u003c/p\u003e\n \u003cp\u003e16.4 months (9.1\u0026ndash;25.8)\u003c/p\u003e\n \u003cp\u003e5/23 (22%)\u003c/p\u003e\n \u003cp\u003e14/23 (61%)\u003c/p\u003e\n \u003cp\u003e6/23 (26%)\u003c/p\u003e\n \u003cp\u003e2/23 (9%)\u003c/p\u003e\n \u003cp\u003e1/23 (4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003eVL: HIV viral load, LTFU: lost to Follow-up\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eHIV viral load monitoring cascade of KIULARCO PLHIV (percentages are of the numbers in \u003cstrong\u003ethe\u003c/strong\u003e preceding bar). Bars show number of patients at different stages of the VL monitoring cascade.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003ch2\u003eCascade after unsuppressed VL\u003c/h2\u003e\n \u003cp\u003eAmong the 494 (12%) PLHIV with unsuppressed VL, 425 (86%) had a follow up VL done after a median of 6.4 months (IQR 5.1\u0026ndash;9.1). Of those, 267 (63%) were virally suppressed, whereby 216 (51%) had a VL\u0026thinsp;\u0026lt;\u0026thinsp;100 copies/ml, 51 (12%) had LLV and 158 (37%) had VF (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Among 69 PLHIV with no follow-up VL, 10 (15%) were in active care, 41 (59%) had been lost to follow-up (LTFU), 6 (9%) had died and 12 (17%) were transferred to another clinic. Within study duration, the median follow-up time of unsuppressed VL (among those active-in-care), LTFU, death or transfer to another clinic was 6.1 months (IQR 3.0 -9.8).\u003c/p\u003e\n \u003cp\u003eOf the 158 PLHIV with VF, 103 (65%) were already on second-line ART at the time of follow-up VL. Among the 55 PLHIV on first-line ART, 32 (58%) were switched from first- to second-line ART after a median of 7.7 months (IQR 4.7\u0026ndash;12.7). Of the 23 PLHIV not switched, 14 (61%) were in active care, 6 (26%) were LTFU, 2 (9%) had died and 1 (4%) had transferred to another clinic. Of the 267 PLHIV who had a first unsuppressed VL and a suppressed follow-up VL, 109 (40%) were already on second-line ART at the first unsuppressed VL measurement and 11 (4%) were switched following the first unsuppressed VL (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec13\"\u003e\n \u003ch2\u003eCascade after LLV\u003c/h2\u003e\n \u003cp\u003eAmong 371 (9%) PLHIV who had LLV, 327 (88%) had a follow up VL done after a median of 9.0 months (IQR 6.0-12.1). Of these, 267 (82%) had follow-up a VL\u0026thinsp;\u0026lt;\u0026thinsp;100 copies/ml, 41 (13%) had persistent LLV and 19 (6%) were unsuppressed (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec14\"\u003e\n \u003ch2\u003eCascade after suppressed VL\u003c/h2\u003e\n \u003cp\u003eAmong 3,312 (79%) PLHIV with a VL\u0026thinsp;\u0026lt;\u0026thinsp;100 copies/ml, 2,876 (87%) had a follow-up VL done after a median of 12.0 months (IQR 11.8\u0026ndash;13.2). Of those, 2,653 (92%) still had VL\u0026thinsp;\u0026lt;\u0026thinsp;100 copies/ml, while 132 (5%) had LLV and 91 (3%) were unsuppressed\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec15\"\u003e\n \u003ch2\u003eTurn-around time (TAT)\u003c/h2\u003e\n \u003cp\u003eAmong 4,454 PLHIV, 12,512 VL test results were received, with a median number of VL tests per person of 3 (IQR 2\u0026ndash;3). Only 3,342 (27%) VL tests were processed within \u0026le;\u0026thinsp;14 days as per national guidelines recommendation. The median analytical TAT was 27 days (IQR 14\u0026ndash;61), whereby at the on-site laboratory it was 21 days (IQR 13\u0026ndash;39) versus 59 days (IQR 27\u0026ndash;99) at the referral laboratory (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The overall TAT\u0026ndash; including result provision to the patient \u0026ndash; was similar irrespective of the site of testing or unsuppressed VL results, with a median of 91 days (36\u0026ndash;94) and 88 days (28\u0026ndash;96) respectively. For those with unsuppressed VL, only 93 (19%) of follow-up VL samples were processed in \u0026le;\u0026thinsp;14 days and the median analytical TAT was 17 days (IQR 8\u0026ndash;31) at the on-site versus 71 days (IQR 35\u0026ndash;103) at the referral laboratory (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The median TAT until a patient received a result was 4.8 months (IQR 3.2\u0026ndash;6.8) and only 102 (24%) had a follow-up VL within 4 months as per national guidelines.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3: Time around time for all PLHIV and those with unsuppressed VL\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"75.75757575757575%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.242424242424242%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"75.75757575757575%\"\u003e\n \u003cp\u003e1. TAT for all VL tests\u003c/p\u003e\n \u003col start=\"1\"\u003e\n \u003cli\u003eAnalytical TAT (date sample taken to date result entered into openMRS database), n=12,512\u003col\u003e\n \u003cli\u003eProcessed in \u0026le;14 days\u003c/li\u003e\n \u003cli\u003eOverall, median (IQR)\u003c/li\u003e\n \u003cli\u003eSample processed at on-site laboratory, median (IQR)\u003c/li\u003e\n \u003cli\u003eSample processed at referral laboratory, median (IQR)\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/li\u003e\n \u003cli\u003eOverall TAT (date sample was taken to date participant received results (next clinical visit)), n=8,385 \u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003col\u003e\n \u003cli\u003eOverall, median (IQR)\u003c/li\u003e\n \u003cli\u003eSample processed at on-site laboratory, median (IQR)\u003c/li\u003e\n \u003cli\u003eSample processed at referral laboratory, median (IQR)\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.242424242424242%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3,342 (27%)\u003c/p\u003e\n \u003cp\u003e27 days (14-61)\u003c/p\u003e\n \u003cp\u003e21 days (13-39)\u003c/p\u003e\n \u003cp\u003e59 days (27-99)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e91 days (36-94)\u003c/p\u003e\n \u003cp\u003e91 days (33-93)\u003c/p\u003e\n \u003cp\u003e91 days (76-123)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"75.75757575757575%\"\u003e\n \u003cp\u003e2. TAT for\u0026nbsp;PLHIV\u0026nbsp;with unsuppressed VL\u003c/p\u003e\n \u003col start=\"1\"\u003e\n \u003cli\u003e\u0026nbsp;Analytical TAT, n=494\u003c/li\u003e\n \u003c/ol\u003e\n \u003col\u003e\n \u003cli\u003eProcessed in \u0026le;14 days\u003c/li\u003e\n \u003cli\u003eOverall, median (IQR)\u003c/li\u003e\n \u003cli\u003eSample processed at on-site laboratory, median (IQR)\u003c/li\u003e\n \u003cli\u003eSample processed at referral laboratory, median (IQR)\u003c/li\u003e\n \u003c/ol\u003e\n \u003col start=\"2\"\u003e\n \u003cli\u003eOverall TAT, n=485 \u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003col\u003e\n \u003cli\u003eOverall, median (IQR)\u003c/li\u003e\n \u003cli\u003eSample processed at on-site laboratory, median (IQR)\u003c/li\u003e\n \u003cli\u003eSample processed at referral laboratory, median (IQR)\u003c/li\u003e\n \u003c/ol\u003e\n \u003col start=\"3\"\u003e\n \u003cli\u003eFollow-up VL TAT (date from unsuppressed VL result entry into openMRS database to date of follow up VL, n=425\u003c/li\u003e\n \u003c/ol\u003e\n \u003col\u003e\n \u003cli\u003eOverall, median (IQR)\u003c/li\u003e\n \u003cli\u003eSample processed at on-site laboratory, median (IQR), n=272\u003c/li\u003e\n \u003cli\u003eSample processed at referral laboratory, median (IQR), n=153\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.242424242424242%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e93 (19%)\u003c/p\u003e\n \u003cp\u003e49 days (20-88)\u003c/p\u003e\n \u003cp\u003e17 days (8-31)\u003c/p\u003e\n \u003cp\u003e71 days (35-103)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e88 days (28-96)\u003c/p\u003e\n \u003cp\u003e85 days (30-95)\u003c/p\u003e\n \u003cp\u003e91 days (74-118)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.8 months (3.2-6.8)\u003c/p\u003e\n \u003cp\u003e5.2 months (3.4-8.2)\u003c/p\u003e\n \u003cp\u003e3.9 months (3.2-5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eTAT: Turnaround time, VL: Viral load,\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study nested within the KIULARCO cohort we have shown, that in the first three years after implementation of VL monitoring in our rural site, testing coverage among PLHIV on ART was high with 95% and 88% viral suppression. The median analytical TAT of samples processed at the on-site laboratory was one third of the time compared to samples sent to the referral laboratory. However, the time until clinical management remained long with 90 days irrespective of the testing site, indicating the challenge of getting unsuppressed PLHIV to return to care earlier than scheduled despite tracking activities. Among PLHIV with an unsuppressed VL only 24% had a follow up VL within the 4 months as recommended by the National HIV treatment guidelines. Of those with an LLV, 6% became unsuppressed within a year.\u003c/p\u003e \u003cp\u003eStudies from different rural sub-Saharan African sites showed VL monitoring coverage rates ranging from 64\u0026ndash;90% (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In our study testing coverage of those in care reached 95% following VL monitoring roll out by the National AIDS Control Program and the implementing partner USAID Boresha Afya after starting with 22% in 2017 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The viral suppression rate during the study period was 88% - comparable to the 91% found in a previous study from our site(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) and to the national level of 87% (84% of males and 89% of females) assessed during the Tanzania HIV Impact Survey (THIS) 2016-17 (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). While these numbers are close to the third 90% of the 2020 UNAIDS goals (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), a gap remains to reach the 2030 UNAIDS goals of 95% viral suppression of those on ART (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). This might be facilitated by the introduction of integrase inhibitors as first line treatment at the beginning of 2019 in Tanzania (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) \u0026ndash; which was not yet implemented during the study period.\u003c/p\u003e \u003cp\u003eThe overall analytical TAT in this real-life rural sub-Saharan African setting was 27% and still notably longer than the 14 days recommended by Tanzanian\u0026rsquo;s National AIDS Control Programme guidelines (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Other studies from sub-Saharan Africa using similar definitions showed median TATs ranging from 15\u0026ndash;67 days (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). The improvement of the analytical TAT by performing the VL in an on-site laboratory compared to a referral laboratory has previously been reported by others. A study from Malawi could show a substantial impact of distance from the laboratory to the clinic on the TAT, suggesting inefficiency of specimen transfer as a factor driving longer turnaround times (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). This was confirmed by a reduction of the median analytical TAT for VL results of about 3 times after implementation of testing at the on-site laboratory in our study (from 59 to 21 days). Major reasons are inconsistent transport availabilities, weather conditions affecting road conditions, reagent stockouts, equipment and electricity shutdowns and administrative delays (\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Thus, there is a clear benefit of a molecular laboratory capable of conducting VL testing located in remote areas with high patient numbers. Additionally, point of care platforms such as GeneXpert can reduce the TAT of the results (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) and thus benefit clinically unstable PLHIV with a same day result for VL targeted monitoring and clinical decision making.\u003c/p\u003e \u003cp\u003eOn the other hand, the analytical TAT unfortunately did not affect the time until the patient received the results (overall TAT). The most important challenge was to track patients and convince them to come to an earlier than planned appointment. Reasons for not coming early indicated by PLHIV were socioeconomic constraints \u0026ndash; mostly small-scale farmers and fishermen \u0026ndash; with inability to come up for transport costs. A considerable number of PLHIV in our study (835 (19%)) live\u0026thinsp;\u0026ge;\u0026thinsp;50 kms away from the clinic with poor road infrastructure and are usually prescribed drugs for three months. In addition, the procedures in place to track PLHIV with an unsuppressed VL as per National HIV treatment guidelines were only partially successful as, even if PLHIV have phones, they frequently are not reachable due to network and electricity shortages. Innovative methods of VL results feedback to PLHIV such as use of mobile short message services might help in overcoming this challenge (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The majority of PLHIV with an unsuppressed VL had re-suppressed at the follow-up testing (63%), which is an indicator for non-adherence rather than resistance and supports the strategy of enhanced adherence counselling. Etoori et al showed a re-suppression rate in Swaziland of 62% (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) while Glass et al reported a lower re-suppression rate of 45% in Lesotho (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In our study, interestingly, 65% of PLHIV were already on second line at the time first VL measurement, indicating previous persistent treatment adherence problems. We reported a similar finding from a study of PLHIV switched to second line treatment in whom 13.1% had VF and no resistance could be documented at the time of switch nor after 6\u0026ndash;12 months on second line treatment (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUntil recently, the WHO guidelines defined an unsuppressed VL using a threshold of \u0026ge;\u0026thinsp;1000copies/mL(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Discussion on the implications of VL results between 100 and 999copies/mL was ongoing after increasing evidence of poor outcome in patients with LLV (\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Our study reports 9% frequency of LLV. Data from other sites are quite diverse with some reporting high rates of LLV of 23% \u0026minus;\u0026thinsp;38% frequency (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), while others show similar figures around 2\u0026ndash;9% (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOnly in mid of this year, the WHO has updated its guidelines and newly defines virologic suppression as a VL\u0026thinsp;\u0026lt;\u0026thinsp;50copies/ml. VF remains defined as two VL\u0026thinsp;\u0026ge;\u0026thinsp;1000copies/ml. The recommendation is to do adherence counselling and retest VL in all patients with VL values\u0026thinsp;\u0026gt;\u0026thinsp;50copies/ml(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our study, 6% of those with LLV progressed to unsuppressed VL in a median time of 9 months hence these PLHIV may benefit from closer monitoring. High-level resistance to at least two drugs has also been documented among PLHIV with LLV of 84\u0026ndash;94%. PLHIV having high-level resistance to at least two drugs of NNRTI-based first-line ART regimen in studies from Lesotho (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe strength of our study is the prospective real-life setting large cohort of PLHIV. The limitations of our study were: first, no resistance testing was done to identify the reasons for high VL in particular, among those with unsuppressed VL who switched to second line ART before having follow up VL and thus we could not determine if the decision to switch to second-line ART was justified or not. Second, we could not assess the impact of adherence counselling among those with unsuppressed VL. Similarly, we could not verify if all who had treatment switch to second line had treatment adherence counselling as per the national\u0026rsquo;s HIV treatment guidelines. Third, analytical TAT at both on-site and referral laboratories may have been affected by stock out of reagents, breakdown of machines, which may result to huge backlog of samples affecting TAT results.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eRobust VL monitoring is achievable in rural remote resource limited settings and with reduced turnaround time of viral load results. The majority of PLHIV with VF were already on second-line ART indicating persistent adherence problems, meaning that it is crucial enhanced treatment adherence counselling is done timely and early enough to prevent HIV drug resistance development.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eVL; HIV viral load\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePLHIV; people living with HIV\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eART; antiretroviral therapy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKIULARCO; Kilombero and Ulanga Antiretroviral Cohort\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSFRH; St. Francis Referral Hospital\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMRRH; Morogoro Regional Referral Hospital\u003c/p\u003e\n\u003cp\u003eIHI; Ifakara Health Institute\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCDCI; Chronic Diseases Clinic of Ifakara\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLLV; low-level viremia\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWHO; World Health Organization\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVF; virologic failure\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTAT; turnaround time\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIQR; interquartile range\u003c/p\u003e\n\u003cp\u003eBMI; body mass index\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOpenMRS; Open medical record system\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTHIS; Tanzania HIV Impact Survey\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll PLHIV sign an informed consent before being enrolled into KIULARCO.\u0026nbsp;For participants below 18years of age, informed consent was obtained from the parents or legal guardian.\u0026nbsp;Ethical approval was obtained from the Ifakara Health Institute review board (IHI/IRB/No16-2006), the National Health Research Committee of the National Institute of Medical Research of Tanzania (NIMR/HQ/R.8a/Vol.IX/620) with yearly renewal, and the Ethikkomission Nordwest- und Zentralschweiz (EKNZ; Switzerland).\u0026nbsp;\u0026nbsp;All methods were performed within the respective ethical frameworks and in accordance with the National HIV/AIDS control guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants also consented to data being published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated and analysed during this study are included in this published article\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Chronic Disease Clinic in Ifakara receives funding from the Ministry of Health and Social Welfare of the government of Tanzania; the government of the Canton of Basel Stadt, Switzerland; the Swiss Tropical and Public Health Institute (Basel, Switzerland); the Ifakara Health Institute (Ifakara, Tanzania); and USAID Boresha Afya (service and medication support, with funding provided by the US Agency for International Development through the President\u0026rsquo;s Emergency Plan for AIDS Relief).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u0026nbsp;\u003c/strong\u003eDM contributed to the study design and drafted the analytical plan, supervised all viral load testing at the laboratory and wrote the manuscript; JO collaborated in drafting the analytical plan and did the statistical analysis. TK, RN, NK, AN, TB, FA, PM, ET, TF provided diagnostic and clinical expertise, coordination and operational support and reviewed the manuscript. TG and FV supervised the statistical analysis MW designed the study and supervised the study implementation, statistical analytical plan and manuscript writing. MW also provided diagnostic and clinical expertise. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment:\u003c/strong\u003e We thank all the collaborators at all levels, the staff of the Chronic Disease Clinic in Ifakara at St. Francis Referral Hospital (Ifakara, Tanzania) and participants of the KIULARCO cohort.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMembers of the KIULARCO Study Group:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAschola Asantiel, Farida Bani, Manuel Battegay, Theonestina Byakuzana, Adolphina Chale, Anna Eichenberger, , Gideon Francis, Hansjakob Furrer, , Tracy R. Glass, Speciosa Hwaya, Aneth V. Kalinjuma, , Bryson Kasuga, Andrew Katende, Namvua Kimera, Yassin Kisunga, Olivia Kitau, Thomas Klimkait, , Ezekiel Luoga, , Herry Mapesi, Mengi Mkulila, Margareth Mkusa, Slyakus Mlembe, Dorcas K. Mnzava, Gertrud J. Mollel, Lilian Moshi, Germana Mossad, Dolores Mpundunga, Athumani Mtandanguo, Selerine Myeya, Sanula Nahota, Regina Ndaki, Robert C. Ndege, Agatha Ngulukila, Alex John Ntamatungiro, Amina Nyuri, James Okuma, Daniel H. Paris, Leila Samson, Elizabeth Senkoro, Jenifa Tarimo, Yvan Temba, Juerg Utzinger, Fiona Vanobberghen, Maja Weisser, John Wigayi, And Herieth Wilson, Bernard Kivuma, George Sigalla, Ivana Di Salvo, Michael Kasmiri, Suzan Ngahyoma, Victor Urio, Aloyce Sambuta, Francisca Chuwa , Swalehe Masoud, Yvonne R Haridas, Jackline Nkouabi.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eUNAIDS. United Republic of Tanzania | UNAIDS [Internet]. [cited 2021 May 9]. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/31306175/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/31306175/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HIV Cascade, Viral load Testing, Viral suppression, failure, low level viremia","lastPublishedDoi":"10.21203/rs.3.rs-2123101/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2123101/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eMonitoring HIV viral load (VL) in people living with HIV (PLHIV) on antiretroviral therapy (ART) is recommended by the World Health Organization. Implementation of VL testing programs have been affected by logistic and organizational challenges. Here we describe the VL monitoring cascade in a rural setting in Tanzania and compare turnaround times (TAT) between an on-site and a referral laboratory.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn a nested study of the prospective Kilombero and Ulanga Antiretroviral Cohort (KIULARCO) we included PLHIV aged\u0026thinsp;\u0026ge;\u0026thinsp;15 years, on ART for \u0026ge;\u0026thinsp;6 months after implementation of routine VL monitoring in 2017. We assessed proportions of PLHIV with a blood sample taken for VL, whose results came back, and who were virally suppressed (VL\u0026thinsp;\u0026lt;\u0026thinsp;1000 copies/mL) or unsuppressed (VL\u0026thinsp;\u0026ge;\u0026thinsp;1000 copies/mL). We described the proportion of PLHIV with unsuppressed VL and adequate measures taken as per national guidelines and outcomes among those with low-level viremia (LLV; 100\u0026ndash;999 copies/mL). We compare TAT between on-site and referral laboratories by Wilcoxon rank sum tests.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFrom 2017 to 2020, among 4,454 PLHIV, 4,238 (95%) had a blood sample taken and 4,177 99 %) of those had a result. Of those, 3,683 (88%) were virally suppressed. In the 494 (12%) unsuppressed PLHIV, 425 (86%) had a follow-up VL (102 (24%) within 4 months and 158 (37%) had virologic failure. Of these, 103 (65%) were already on second-line ART and 32/55 (58%) switched from first- to second-line ART after a median of 7.7 months (IQR 4.7\u0026ndash;12.7). In the 371 (9%) PLHIV with LLV, 327 (88%) had a follow-up VL. Of these, 267 (82%) resuppressed to \u0026lt;\u0026thinsp;100 copies/ml, 41 (13%) had persistent LLV and 19 (6%) had unsuppressed VL. The median TAT for return of VL results was 21 days (IQR 13\u0026ndash;39) at the on-site versus 59 days (IQR 27\u0026ndash;99) at the referral laboratory (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with PLHIV receiving the VL results after a median of 91 days (IQR 36\u0026ndash;94; similar for both laboratories).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eRobust VL monitoring is achievable in remote resource-limited settings. More focus is needed on care models for PLHIV with high viral loads to timely address results from routine VL monitoring.\u003c/p\u003e","manuscriptTitle":"Decentralization of viral load testing to improve HIV care and treatment cascade in rural Tanzania: Data from the Kilombero and Ulanga Antiretroviral Cohort","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-10-18 15:10:51","doi":"10.21203/rs.3.rs-2123101/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvited","content":"","date":"2022-10-14T11:03:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-10-14T10:58:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2022-10-01T09:44:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"026998b7-1403-4899-b6b0-daa55e54e304","owner":[],"postedDate":"October 18th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T20:28:38+00:00","versionOfRecord":{"articleIdentity":"rs-2123101","link":"https://doi.org/10.1186/s12879-023-08155-6","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2023-04-07 20:24:31","publishedOnDateReadable":"April 7th, 2023"},"versionCreatedAt":"2022-10-18 15:10:51","video":"","vorDoi":"10.1186/s12879-023-08155-6","vorDoiUrl":"https://doi.org/10.1186/s12879-023-08155-6","workflowStages":[]},"version":"v1","identity":"rs-2123101","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2123101","identity":"rs-2123101","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}