Implementation science in resource-poor countries and communities is arguably more important than implementation science in resource-rich settings, because resource poverty requires novel solutions to ensure that research results are translated into routine practice and benefit the largest possible number of people. We reviewed the role of resources in the extant implementation science frameworks and literature. We analyzed opportunities for implementation science in resource-poor countries and communities, as well as threats to the realization of these opportunities. Many of the frameworks that provide theoretical guidance for implementation science view resources as contextual factors that are important to (i) predict the feasibility of implementation of research results in routine practice, (ii) explain implementation success and failure, (iii) adapt novel evidence-based practices to local constraints, and (iv) design the implementation process to account for local constraints. Implementation science for resource-poor settings shifts this view from “resources as context” to “resources as primary research object.” We find a growing body of implementation research aiming to discover and test novel approaches to generate resources for the delivery of evidence-based practice in routine care, including approaches to create higher-skilled health workers—through tele-education and telemedicine, freeing up higher-skilled health workers—through task-shifting and new technologies and models of care, and increasing laboratory capacity through new technologies and the availability of medicines through supply chain innovations. In contrast, only few studies have investigated approaches to change the behavior and utilization of healthcare resources in resource-poor settings. We identify three specific opportunities for implementation science in resource-poor settings. First, intervention and methods innovations thrive under constraints. Second, reverse innovation transferring novel approaches from resource-poor to research-rich settings will gain in importance. Third, policy makers in resource-poor countries tend to be open for close collaboration with scientists in implementation research projects aimed at informing national and local policy. Implementation science in resource-poor countries and communities offers important opportunities for future discoveries and reverse innovation. To harness this potential, funders need to strongly support research projects in resource-poor settings, as well as the training of the next generation of implementation scientists working on new ways to create healthcare resources where they lack most and to ensure that those resources are utilized to deliver care that is based on the latest research results.

Introduction: The uptake of HIV testing and linkage to care remains low among men, contributing to high HIV incidence in women in South Africa. We conducted the “Home‐Based Intervention to Test and Start” (HITS) in a 2x2 factorial cluster randomized controlled trial in one of the World’s largest ongoing HIV cohorts in rural South Africa aimed at enhancing both intrinsic and extrinsic motivations for HIV testing.Methods: Between February and December 2018, in the uMkhanyakude district of KwaZulu‐Natal, we randomly assigned 45 communities (clusters) (n = 13,838 residents) to one of the four arms: (i) financial incentives for home‐based HIV testing and linkage to care (R50 [$3] food voucher each); (ii) male‐targeted HIV‐specific decision support application, called EPIC‐HIV; (iii) both financial incentives and male‐targeted HIV‐specific decision support application and (iv) standard of care (SoC). EPIC‐HIV was developed to encourage and serve as an intrinsic motivator for HIV testing and linkage to care, and individually offered to men via a tablet device. Financial incentives were offered to both men and women. Here we report the effect of the interventions on uptake of home‐based HIV testing among men. Intention‐to‐treat (ITT) analysis was performed using modified Poisson regression with adjustment for clustering of standard errors at the cluster levels.Results: Among all 13,838 men ≥ 15 years living in the 45 communities, the overall population coverage during a single round of home‐based HIV testing was 20.7%. The uptake of HIV testing was 27.5% (683/2481) in the financial incentives arm, 17.1% (433/2534) in the EPIC‐HIV arm, 26.8% (568/2120) in the arm receiving both interventions and 17.8% in the SoC arm. The probability of HIV testing increased substantially by 55% in the financial incentives arm (risk ratio (RR)=1.55, 95% CI: 1.31 to 1.82, p < 0.001) and 51% in the arm receiving both interventions (RR = 1.51, 95% CI: 1.21 to 1.87 p < 0.001), compared to men in the SoC arm. The probability of HIV testing did not significantly differ in the EPIC‐HIV arm (RR = 0.96, 95% CI: 0.76 to 1.20, p = 0.70).Conclusions: The provision of a small financial incentive acted as a powerful extrinsic motivator substantially increasing the uptake of home‐based HIV testing among men in rural South Africa. In contrast, the counselling and testing application which was designed to encourage and serve as an intrinsic motivator to test for HIV did not increase the uptake of home‐based testing.

Evidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects of CQI on quality of antenatal HIV care in primary care clinics in rural South Africa. We conducted a stepped-wedge cluster-randomised controlled trial (RCT) comparing CQI to usual standard of antenatal care (ANC) in 7 nurse-led, public-sector primary care clinics—combined into 6 clusters—over 8 steps and 19 months. Clusters randomly switched from comparator to intervention on pre-specified dates until all had rolled over to the CQI intervention. Investigators and clusters were blinded to randomisation until 2 weeks prior to each step. The intervention was delivered by trained CQI mentors and included standard CQI tools (process maps, fishbone diagrams, run charts, Plan-Do-Study-Act [PDSA] cycles, and action learning sessions). CQI mentors worked with health workers, including nurses and HIV lay counsellors. The mentors used the standard CQI tools flexibly, tailored to local clinic needs. Health workers were the direct recipients of the intervention, whereas the ultimate beneficiaries were pregnant women attending ANC. Our 2 registered primary endpoints were viral load (VL) monitoring (which is critical for elimination of mother-to-child transmission of HIV [eMTCT] and the health of pregnant women living with HIV) and repeat HIV testing (which is necessary to identify and treat women who seroconvert during pregnancy). All pregnant women who attended their first antenatal visit at one of the 7 study clinics and were ≥18 years old at delivery were eligible for endpoint assessment. We performed intention-to-treat (ITT) analyses using modified Poisson generalised linear mixed effects models. We estimated effect sizes with time-step fixed effects and clinic random effects (Model 1). In separate models, we added a nested random clinic–time step interaction term (Model 2) or individual random effects (Model 3). Between 15 July 2015 and 30 January 2017, 2,160 participants with 13,212 ANC visits (intervention n = 6,877, control n = 6,335) were eligible for ITT analysis. No adverse events were reported. Median age at first booking was 25 years (interquartile range [IQR] 21 to 30), and median parity was 1 (IQR 0 to 2). HIV prevalence was 47% (95% CI 42% to 53%). In Model 1, CQI significantly increased VL monitoring (relative risk [RR] 1.38, 95% CI 1.21 to 1.57, p < 0.001) but did not improve repeat HIV testing (RR 1.00, 95% CI 0.88 to 1.13, p = 0.958). These results remained essentially the same in both Model 2 and Model 3. Limitations of our study include that we did not establish impact beyond the duration of the relatively short study period of 19 months, and that transition steps may have been too short to achieve the full potential impact of the CQI intervention. We found that CQI can be effective at increasing quality of primary care in rural Africa. Policy makers should consider CQI as a routine intervention to boost quality of primary care in rural African communities. Implementation research should accompany future CQI use to elucidate mechanisms of action and to identify factors supporting long-term success. This trial is registered at ClinicalTrials.gov under registration number NCT02626351.

Background: We evaluated continuous quality improvement (CQI) targeting antenatal HIV care quality in rural South Africa using a stepped-wedge cluster-randomised controlled trial (Management and Optimisation of Nutrition, Antenatal, Reproductive, Child health, MONARCH) and an embedded process evaluation. Here, we present results of the process evaluation examining determinants of CQI practice and ‘normalisation.’ Methods: A team of CQI mentors supported public-sector health workers in seven primary care clinics to (1) identify root causes of poor HIV viral load (VL) monitoring among pregnant women living with HIV and repeat HIV testing among pregnant women not living with HIV, and (2) design and iteratively test their own solutions. We used a mixed methods evaluation with field notes from CQI mentors (‘dose’ and ‘reach’ of CQI, causes of poor HIV care testing rates, implemented change ideas); patient medical records (HIV care testing by clinic and time step); and semi-structured interviews with available health workers. We analysed field notes andsemi-structured interviews for determinants of CQI implementation and ‘normalisation’ using Normalisation Process Theory (NPT) and Tailored Implementation of Chronic Diseases (TICD) frameworks. Results: All interviewed health workers found the CQI mentors and methodology helpful for quality improvement. Total administered ‘dose’ was higher than planned but ‘reach’ was limited by resource constraints, particularly staffing shortages. Simple workable improvements to identified root causes were implemented, such as a patient tracking notebook and results filing system. VL monitoring improved over time, but not repeat HIV testing. Besides resource constraints, gaps in knowledge of guidelines, lack of leadership, poor clinical documentation, and data quality gaps reduced CQI implementation fidelity and normalisation. Conclusion: While CQI holds promise, we identified several health system challenges. Priorities for policy makers include improving staffing and strategies to improve clinical documentation. Additional support with implementing clinical guidelines and improving routine data quality are needed. Normalising CQI may be challenging without concurrent health system improvements.

Background: South Africa implemented universal test and treat (UTT) in September 2016 in an effort to encourage earlier initiation of antiretroviral therapy (ART). Methods: We therefore conducted an interrupted time series (ITS) analysis to assess the impact of UTT on mean CD4 count at ART initiation among adults aged ≥16 years attending 17 public sector primary care clinics in rural South Africa, between July 2014 and March 2019. Results: Among 20 599 individuals (69% women), CD4 counts were available for 74%. Mean CD4 at ART initiation increased from 317.1 cells/μL (95% confidence interval [CI], 308.6 to 325.6) 1 to 8 months prior to UTT to 421.0 cells/μL (95% CI, 413.0 to 429.0) 1 to 12 months after UTT, including an immediate increase of 124.2 cells/μL (95% CI, 102.2 to 146.1). However, mean CD4 count subsequently fell to 389.5 cells/μL (95% CI, 381.8 to 397.1) 13 to 30 months after UTT but remained above pre-UTT levels. Men initiated ART at lower CD4 counts than women (–118.2 cells/μL, 95% CI, –125.5 to –111.0) throughout the study. Conclusions: Although UTT led to an immediate increase in CD4 count at ART initiation in this rural community, the long-term effects were modest. More efforts are needed to increase initiation of ART early in those living with human immunodeficiency virus, particularly men.

Since the advent of combination antiretroviral therapy to successfully treat HIV infection, drug–drug interactions (DDIs) have become a significant problem as many antiretrovirals (ARVs) are metabolized in the liver. Antituberculous therapy traditionally includes rifamycins, particularly rifampicin. Rifabutin (RBT) has shown similar efficacy as rifampicin but induces CYP3A4 to a lesser degree and is less likely to have DDIs with ARVs. We identified 14 DDI pharmacokinetic studies on HIV monoinfected and HIV–tuberculosis coinfected individuals, and the remaining studies were healthy volunteer studies. Although RBT may be coadministered with most nonnucleoside reverse transcriptase inhibitors, identifying the optimal dose with ritonavir-boosted or cobicistat-boosted protease inhibitors is challenging because of concern about adverse effects with increased RBT exposure. Limited healthy volunteer studies on other ARV drug classes and RBT suggest that dose modification may be unnecessary. The paucity of data assessing clinical tuberculosis endpoints concurrently with RBT and ARV pharmacokinetics limits evidence-based recommendations on the optimal dose of RBT within available ARV drug classes.