Browsing by Author "Nichols B"

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Patterns of engagement in care during clients' first 12 months after HIV treatment initiation in Zambia: a retrospective cohort analysis using routinely collected data.
(2025-Aug-11) Benade M; Maskew M; Chilembo P; Wa Mwansa M; Savory T; Nichols B; Bolton C; Mulenga LB; Sivile S; Zyambo KD; Rosen S
BACKGROUND: The first year after HIV treatment initiation or re-initiation is the period of highest risk of a treatment interruption or disengagement, yet little is known about the timing, patterns and effects of interruptions in the early treatment period. METHODS: Using routinely collected electronic medical record data from 543 Zambian facilities from 2018 to 2023, we described patterns of engagement during the first year of HIV treatment. We defined engagement patterns for months 0-6 and months 7-12 after initiation or reinitiation as (1) continuous (attended all scheduled clinic and medication pickup visits as planned; (2) cyclical (attended ≥1 visits late >28 days but returned to and remained in care) or (3) disengaged (missed a scheduled visit by >28 days and had no evidence of return). RESULTS: Our sample population comprised 159 429 adult participants (61% female, median age 33). Of the 513 322 interactions observed ≤12 months after initiation, 53% occurred as planned, 22% were late ≤28 days late, 9% were >28 days late, and 17% were scheduled but never attended. In 0-6 months after initiation, 51% clients were continuously engaged, 12% cyclically engaged and 33% disengaged. Two-thirds of disengagers (21% of cohort) did not return after the initiation visit. During months 7-12, most clients who had been continuously engaged in months 0-6 (54%) remained continuous, while 18% moved to cyclical engagement. Among cyclical engagers in months 0-6, nearly half (47%) moved to being continuously engaged by month 12. Only 34% of the study population remained engaged continuously by the end of the 12-month period. CONCLUSIONS: Fewer than 60% of clients initiating antiretroviral therapy care between 2018 and 2022 at Zambian facilities remained continuously engaged at month 6 and 34% at month 12. Cyclical engagement and frequent interruptions should be accepted as the norm and models of service delivery designed to accommodate them.
Sustainable HIV treatment in Africa through viral-load-informed differentiated care.
(2015-Dec-03) Phillips A; Shroufi A; Vojnov L; Cohn J; Roberts T; Ellman T; Bonner K; Rousseau C; Garnett G; Cambiano V; Nakagawa F; Ford D; Bansi-Matharu L; Miners A; Lundgren JD; Eaton JW; Parkes-Ratanshi R; Katz Z; Maman D; Ford N; Vitoria M; Doherty M; Dowdy D; Nichols B; Murtagh M; Wareham M; Palamountain KM; Chakanyuka Musanhu C; Stevens W; Katzenstein D; Ciaranello A; Barnabas R; Braithwaite RS; Bendavid E; Nathoo KJ; van de Vijver D; Wilson DP; Holmes C; Bershteyn A; Walker S; Raizes E; Jani I; Nelson LJ; Peeling R; Terris-Prestholt F; Murungu J; Mutasa-Apollo T; Hallett TB; Revill P
There are inefficiencies in current approaches to monitoring patients on antiretroviral therapy in sub-Saharan Africa. Patients typically attend clinics every 1 to 3 months for clinical assessment. The clinic costs are comparable with the costs of the drugs themselves and CD4 counts are measured every 6 months, but patients are rarely switched to second-line therapies. To ensure sustainability of treatment programmes, a transition to more cost-effective delivery of antiretroviral therapy is needed. In contrast to the CD4 count, measurement of the level of HIV RNA in plasma (the viral load) provides a direct measure of the current treatment effect. Viral-load-informed differentiated care is a means of tailoring care so that those with suppressed viral load visit the clinic less frequently and attention is focussed on those with unsuppressed viral load to promote adherence and timely switching to a second-line regimen. The most feasible approach to measuring viral load in many countries is to collect dried blood spot samples for testing in regional laboratories; however, there have been concerns over the sensitivity and specificity of this approach to define treatment failure and the delay in returning results to the clinic. We use modelling to synthesize evidence and evaluate the cost-effectiveness of viral-load-informed differentiated care, accounting for limitations of dried blood sample testing. We find that viral-load-informed differentiated care using dried blood sample testing is cost-effective and is a recommended strategy for patient monitoring, although further empirical evidence as the approach is rolled out would be of value. We also explore the potential benefits of point-of-care viral load tests that may become available in the future.
The integration of tuberculosis and HIV testing on GeneXpert can substantially improve access and same-day diagnosis and benefit tuberculosis programmes: A diagnostic network optimization analysis in Zambia.
(2023) Girdwood S; Pandey M; Machila T; Warrier R; Gautam J; Mukumbwa-Mwenechanya M; Benade M; Nichols K; Shibemba L; Mwewa J; Mzyece J; Lungu P; Albert H; Nichols B; Choonga P
Diagnostic network optimization (DNO), a geospatial optimization technique, can improve access to diagnostics and reduce costs through informing policy-makers' decisions on diagnostic network changes. In Zambia, viral load (VL) testing and early infant diagnosis (EID) for HIV has been performed at centralized laboratories, whilst the TB-programme utilizes a decentralized network of GeneXpert platforms. Recently, the World Health Organization (WHO) has recommended point-of-care (POC) EID/VL to increase timely diagnosis. This analysis modelled the impact of integrating EID/VL testing for children and pregnant/breastfeeding-women (priority-HIV) with TB on GeneXpert in Zambia. Using OptiDx, we established the baseline diagnostic network using inputs for testing demand (October 2019-September 2020), referrals, testing sites, testing platforms, and costs for HIV/TB testing (transport, test, device) respectively in Zambia. Next, we integrated priority-HIV testing on GeneXpert platforms, historically only utilized by the TB-programme. 228,265 TB tests were conducted on GeneXpert devices and 167,458 (99%) of priority-HIV tests on centralized devices at baseline, of which 10% were tested onsite at the site of sample collection. With integration, the average distance travelled by priority-HIV tests decreased 10-fold (98km to 10km) and the proportion tested onsite increased (10% to 48%). 52% of EID tests are likely to be processed within the same-day from a baseline of zero. There were also benefits to the TB-programme: the average distance travelled/specimen decreased (11km to 7km), alongside potential savings in GeneXpert device-operating costs (30%) through cost-sharing with the HIV-programme. The total cost of the combined testing programmes reduced marginally by 1% through integration/optimization. DNO can be used to strategically leverage existing capacity to achieve the WHO's recommendation regarding POC VL/EID testing. Through DNO of the Zambian network, we have shown that TB/HIV testing integration can improve the performance of the diagnostic network and increase the proportion of specimens tested closer to the patient whilst not increasing costs.