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. 2026 Mar 13;7:78. doi: 10.1186/s43058-026-00896-0

Commonality and co-occurrence of discrete strategies within implementation strategy bundles: findings from the Living Database of HIV Implementation Science systematic review, 2014–2021

Sita Lujintanon 1,✉, Ingrid Eshun-Wilson 2, Noelle Le Tourneau 2, Laura K Beres 3, Sheree Schwartz 1, Stefan Baral 1, Ryan Thompson 1, Ashley Underwood 2, Branson Fox 2, Elvin H Geng 2, Christopher G Kemp 3
PMCID: PMC13097648  PMID: 41827047

Abstract

Background

HIV services and innovations are delivered through implementation strategy bundles that are often complex, comprising numerous discrete strategies. Systematically characterizing the use patterns of discrete strategies may inform strategy prioritization and selection to optimize service delivery. We used the Living Database of HIV Implementation Science (LIVE) to describe the commonality and co-occurrence of discrete strategies within multi-component strategy bundles in published HIV implementation studies from low- and middle-income countries.

Methods

The LIVE systematic review identified studies from PubMed, Embase, and CINAHL, and included HIV implementation studies that reported ≥ 1 HIV care cascade outcome, were conducted in low- and middle-income countries, and were published between January 1, 2014, and August 27, 2021. Discrete strategies were inductively specified (e.g., actor, action, action target) and classified into 5 categories consolidated from 2 strategy taxonomies, Effective Practice and Organisation of Care and Expert Recommendations for Implementing Change. Network analysis was conducted to describe the co-occurrence of discrete strategies within study arm strategy bundles.

Results

A total of 4,253 discrete implementation strategies were identified from 868 study arms across 485 individual studies, with a median of four reported strategies per study arm (range: 1–21). The most common strategies used were ‘providing education on a health innovation, service, or behavior’ (60%; 520/868) and ‘training to learn a new skill’ (30%; 260/868) under the ‘Capacity Building and Support’ category. These were also the most commonly co-occurring strategies within strategy bundles (degree centrality: 4,894 and 3,488, respectively) and were most often present to allow other strategies to co-occur in bundles (betweenness centrality: 3,526.3 and 1,647.0, respectively). Several other ‘Capacity Building and Support’ or ‘Health Service Delivery’ categories were common and central. Strategies related to ‘Financial Arrangement,’ ‘Governance,’ and ‘Implementation Process’ were infrequently reported and/or underutilized.

Conclusions

Capacity building approaches and changes to health service delivery are common in published HIV implementation strategy bundles. Future implementation studies should evaluate bundles of a more diverse range of strategies that target barriers at organization and health system levels.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43058-026-00896-0.

Keywords: HIV, Implementation strategies, Systematic review, Low- and middle-income countries, Network analysis

Contributions to the literature.

  • Network analysis can be used to describe how discrete implementation strategies co-occur within complex multi-component strategy bundles.

  • In published HIV implementation studies from low- and middle-income countries, discrete ‘Capacity Building and Support’ and ‘Health Service Delivery’ strategies are common and central to the enactment of other strategies in bundles to address the barriers faced by people living with HIV in receiving and healthcare providers in delivering care.

  • Discrete strategy centrality may explain how strategies interact and inform further investigation of strategy mechanisms, or the ways in which different strategies work together to produce implementation and health outcomes.

Introduction

Implementation strategies are “methods or techniques used to enhance the adoption, implementation, and sustainability of a clinical program or practice” [1].

When chosen appropriately, implementation strategies can improve implementation outcomes, leading to better service delivery and health outcomes [1]. Although discrete implementation strategies can be used in isolation [2–4], they are often bundled in implementation research [5, 6] and practice [7–11] to target multi-level contextual barriers. In fact, a systematic review of tested strategies across health and human service settings reported up to twenty strategies were used in a single strategy bundle [11]. However, the relative benefit of multi-component bundles of strategies compared to discrete strategies remains unclear [12, 13], partly due to the difficulty in assessing the effectiveness of diverse bundled strategies [11]. Additionally, the cost of implementing multi-component strategies must be considered [14], especially in resource-limited settings where the research-to-practice gap is often wider.

The advent of highly active antiretroviral therapy (ART) has changed the course of the 40 + years of the HIV epidemic; however, implementation science is needed to identify strategies that optimize the delivery of ART and other HIV interventions in order to improve the health outcomes of people living with HIV, reduce new HIV infections, and end the HIV epidemic. Implementation strategies are particularly critical tools in low- and middle-income countries (LMICs) that must make use of insufficient resources to address high HIV burdens. A systematic review reported the use of various strategies related to management, infrastructure, technology, demand creation, and socio-behavioral changes for improving HIV care in LMICs [15]. The differentiated service delivery (DSD) framework, which has been adopted widely in LMICs, serves as a multi-component strategy bundle to tailor HIV service delivery to people’s preferences and clinical needs by changing the service type, provider, location, and time [16–18]. Many DSD strategies have been evaluated, including service integration [19], task shifting [20], decentralization [21, 22], and visit frequency spacing [23]. Several sequential multiple assignment randomized and factorial trials are underway to identify specific multi-component strategy bundles for optimized HIV treatment and prevention outcomes [24–29]. However, few HIV implementation studies have been replicated across diverse settings, which may limit the generalizability and applicability of findings more broadly. A systematic approach to study multi-component strategy bundles across settings may identify core strategies that should be recommended for inclusion in future bundling as well as underused and/or underreported strategies that should be further investigated in bundles.

The objective of this study was to systematically describe the commonality and co-occurrence of discrete implementation strategies within multi-component implementation strategy bundles in published HIV implementation research in LMICs from 2014 to 2021. We used network analysis to characterize and visualize the complex relationships inherent in strategy bundles. Although network analysis is more commonly used to study social connection/network to understand the spread of disease or information in the health field, it has been applied for text analysis in the linguistics field, which makes it appropriate for studying strategies extracted from published manuscripts in this systematic review. For each specified strategy, we reported two network statistics, which represent its use in bundles with other strategies (degree centrality) and its necessary role to support other strategies to co-occur in bundles (betweenness centrality) [30, 31].

Methods

Study design

The Living Database of HIV Implementation Science (LIVE) project conducted a living systematic review from 2014 to 2021 to support timely evidence syntheses on the effects of implementation strategies in improving HIV care cascade outcomes in LMICs [32]. The systematic review methods and results have been previously reported [33]. Briefly, this review included English language studies that were identified from PubMed, Embase, and CINAHL, conducted in LMICs, and published between January 1, 2014, and August 27, 2021. Eligible studies described the implementation of HIV interventions and reported ≥ 1 HIV care cascade outcome (i.e., HIV testing, HIV diagnosis, linkage to care, ART initiation, ART adherence, retention in care, re-engagement in care, or viral suppression). All researchers involved in the systematic review process underwent study protocol training and met weekly during the screening and data extraction processes. At least 2 researchers screened each abstract and at least 2 researchers screened the full text for inclusion. One researcher extracted data elements, including study characteristics and strategy specification; another researcher conducted an independent quality control check of data extracts. Any disagreements or inconsistencies arising during the systematic review process were resolved through discussions.

Here, we further conducted analyses to describe commonality and co-occurrence of discrete implementation strategies within bundles. We reported the findings following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines [34] (see Additional file 1).

Strategy specification and classification

During the data extraction process, all discrete strategies from eligible studies were extracted separately for each study arm (e.g., treatment arm, control arm). Each discrete strategy was inductively specified according to the Proctor et al.’s strategy specification framework (e.g., actor(s), action, action target(s), delivery mode(s), location(s)) [1] based on descriptions in the published manuscripts.

To prepare for analysis, three researchers (SL, IE, and CK) independently and retroactively mapped the inductively-specified, discrete strategies to existing and complementing strategy taxonomies, Effective Practice and Organisation of Care (EPOC) [4] and Expert Recommendations for Implementing Change (ERIC) [2, 3], when possible. Any discrepancies in mapping were resolved via discussions. Due to the gaps in the existing taxonomies, we expanded the taxonomies by introducing new strategy terminologies, particularly for patient-level strategies – also known as ‘adjunctive interventions’ [33, 35]. We classified these discrete strategies into five categories formed by consolidating categories of EPOC and ERIC strategy taxonomies: ‘Capacity Building and Support’ (from combining ERIC categories), ‘Financial Arrangement’ (from both EPOC and ERIC), ‘Governance’ (from EPOC), ‘Health Service Delivery’ (from EPOC), and ‘Implementation Process’ (from EPOC) [33].

Analysis

Data were analyzed at the level of individual study arms within published manuscripts. That is, the combination of implementation strategies used within an individual study arm was treated as a distinct multi-component strategy bundle. Within each study arm bundle, we defined a discrete strategy as a unique inductively coded action.

We assessed the commonality of discrete strategies by ranking them by the number of study arms using each strategy. We applied network analysis methods to describe co-occurrence of discrete strategies within study arm bundles [30, 31]. We visualized co-occurrence using an undirected network graph, with nodes representing discrete strategies and paths (also known formally as edges) representing their co-occurrence within study arms. The sizes of the nodes and the paths were proportional to their occurrence and co-occurrence, respectively. Additionally, we calculated two network statistics: degree centrality and betweenness centrality to provide insight into the relative importance of a strategy within a network of strategy bundles [30, 31]. Degree centrality measures the number of direct connections each node has. In our context, this indicates the total number of co-occurrences between the strategy of interest and other strategies within the strategy bundles. However, degree centrality captures only direct co-occurrences. It does not account for a strategy's influence on the broader network structure. In contrast, betweenness centrality reflects a strategy's role as a connector; it measures how often a strategy acts as a bridge along the shortest paths between other strategies. A node with high betweenness centrality lies on many paths between other nodes and thus mediates the network flow. When multiple shortest paths exist between two nodes, the betweenness centrality is equally distributed among the nodes on these paths. In our context, betweenness centrality indicates which strategies are crucial for connecting other strategies. Adding or removing a strategy with high betweenness centrality could potentially alter the functioning of other strategies in a bundle, especially if there is a causal relationship between them [31]. Stratified analyses by World Health Organization (WHO) geographic region [36], study population, and HIV care cascade target were conducted to explore result heterogeneity.

Further network analyses were conducted to understand the mechanistic paths between discrete strategies in the bundle and HIV care cascade outcomes by changing the behavior of the targeted individuals involved (i.e., action targets). Two network analyses were performed in which we redefined a strategy as a combination of actions and action targets. Because single strategies often addressed multiple targets, this redefinition resulted in a change in total count of strategy-target pairs. In the first analysis, we treated actions as discrete strategies to maintain granularity, resulting in a higher total count of strategy-target pairs (n = 4,760). In the second analysis, we grouped the actions into mid-level strategy categories [33, 37], resulting in a lower total count of strategy-target pairs (n = 3,919). We classified the action targets based on the 7 P’s Framework to identify key partners in patient-centered outcomes research [38].

The analysis was conducted using R version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria). We used igraph, ggraph, and tidygraph packages to conduct the network analysis [30].

Results

From the 485 studies and 868 individual study arms included in this analysis, there were a total of 4,253 discrete strategies identified, with a median of 4 (range: 1–21) strategies per arm. A total of 122 unique discrete strategies were identified. Of the total sample of strategies identified, 1,968 (46%) were in the ‘Health Service Delivery’ category, 1,645 (39%) in the ‘Capacity Building and Support’ category, 398 (9%) in the ‘Implementation Process’ category, 235 (6%) in the ‘Financial Arrangement’ category, and 7 (< 1%) in the ‘Governance’ category.

As shown in Fig. 1A, the most common strategy was ‘providing education on a health innovation, service, or behavior,’ which was used in 60% (520/868) of study arms. This was followed by 30% (260/868) of study arms using ‘training to learn a new skill’ strategy, 26% (223/868) of study arms using ‘providing community-based services’ strategy, 22% (194/868) of study arms using ‘providing psychosocial support counselling’ strategy, and 172 (20%) arms using ‘instituting new or altered discharge and/or referral systems’ strategy. A full list of discrete strategies ranked by commonality is shown in Additional file 2.

Fig. 1.

Fig. 1

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Discrete implementation strategies with high commonality, degree centrality, and betweenness centrality. Top 20 discrete strategies ranked by commonality (A), degree centrality (B), and betweenness centrality (C) from 868 intervention arms within HIV implementation studies conducted in low- and middle-income countries and published between 2014 and 2021. The strategies highlighted in green are highly ranked in all three aspects. The strategies highlighted in yellow are commonly used and have high degree centrality. The strategies highlighted in red are commonly used and have high betweenness centrality. The strategies highlighted in blue have high degree centrality and betweenness centrality

The network statistics identified a variety of ‘Health Service Delivery’ and ‘Capacity Building and Support’ strategies used, but the ‘Capacity Building and Support’ strategies were more central to the enactment of other strategies within the network (Fig. 1B and C). Visualized in Fig. 2, ‘Capacity Building and Support’ strategies appear as network hubs, characterized by larger nodes and thicker connecting paths. The discrete strategy ‘providing education on a health innovation, service, or behavior’ had the highest degree centrality (4,894), meaning that there were 4,894 instances in which it co-occurred with other discrete strategies across all strategy bundles, and the highest betweenness centrality (3,526.3), meaning that it was most often present on the shortest co-occurrence path between other two discrete strategies within the greater network of all strategies. This strategy belonged to the ‘Capacity Building and Support’ category and co-occurred frequently with other ‘Capacity Building and Support’ strategies, such as ‘training to learn a new skill’ and ‘providing psychosocial support counselling,’ as well as ‘Health Service Delivery’ strategies, such as ‘instituting new or altered discharge and/or referral systems,’ ‘providing community-based services,’ ‘changing physical structure and equipment,’ ‘tracing lost or late patients,’ and ‘sending messages about a service, innovation, or behavior.’ Additionally, the discrete strategy ‘training to learn a new skill’ (degree centrality: 3,488 and betweenness centrality: 1,647.0) co-occurred frequently with ‘supervising, mentoring, coaching, or facilitating,’ ‘providing psychosocial support counselling,’ ‘providing community-based services,’ and ‘changing physical structure and equipment.’ Other central strategies mostly fell under the ‘Capacity Building and Support’ or ‘Health Service Delivery’ categories, which are represented by a variety of red and blue nodes in the network graph. Few strategies under ‘Implementation Process’ and ‘Financial Arrangement’ categories had high degree centrality (i.e., ‘involving stakeholder(s) in strategy design’ (1,106) and ‘providing unconditional incentive’ (850)) and betweenness centrality (i.e., ‘involving stakeholder(s) in strategy design’ (171.4), ‘using leaders, champions, or influencers to mandate change’ (108.1), and ‘providing or altering external funding’ (105.0)). ‘Governance’ strategies were rare and barely visible on the network graph. A full list of discrete strategies ranked by centrality is shown in Additional file 2. The analyses stratified by geographic regions, study populations, and HIV cascade targets showed similar results (see Additional file 3).

Fig. 2.

Fig. 2

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Network graph of discrete strategies co-occurring within multi-component strategy bundles. Undirected network graph illustrating the co-occurrence of discrete implementation strategies from 868 intervention arms within HIV implementation studies conducted in low- and middle-income countries and published between 2014 and 2021. The nodes represent discrete strategies. Their colors represent the strategy categories: red for ‘Capacity Building and Support’ strategies, olive green for ‘Financial Arrangement’ strategies, forest green for ‘Governance’ strategies, blue for ‘Health Service Delivery’ strategies, and magenta for ‘Implementation Process’ strategies. The paths between the nodes represent co-occurrence. The sizes of the nodes and the paths are proportional to their occurrence and co-occurrence, respectively

The network analyses assessing the mechanistic paths found that the discrete strategies, including those with high centrality, primarily targeted the ‘Patients and the Public’ category (i.e., patients, their families, communities, and the public; 63%; 2,978/4,760), and the ‘Providers,’ including providers and other health workforce (37%; 1,755/4,760) when aiming to improve the HIV care cascade outcomes (see Additional file 4). Other targets, including ‘Policy Makers’ (< 1%; 17/4,760) and ‘Product Makers’ (< 1%; 1/4,760), were rare.

Discussion

A systematic review of published HIV implementation strategies in LMICs found that discrete strategies within the categories of 'Capacity Building and Support' and 'Health Service Delivery' are the most commonly reported in bundles. Specifically, discrete strategies such as 'providing education on a health innovation, service, or behavior' and 'training to learn a new skill' frequently co-occur and are central to the enactment of other strategies in bundles. However, these commonly reported and central strategies primarily address barriers faced by people living with HIV in receiving care and healthcare providers in delivering care. Strategies targeting organization- and health system-level barriers, such as financing, governance, and operations, may have been underused and/or underreported, despite their potential importance as components of an effective strategy bundle to target multi-level barriers and improve HIV care cascade outcomes.

The centrality of strategies under the 'Capacity Building and Support' category suggests that they play a fundamental role in improving HIV care cascade outcomes in published studies. 'Capacity Building and Support' strategies directed at people living with HIV, such as providing education and psychosocial support counseling, help individuals make informed decisions about their care and enhance engagement across the HIV care continuum. This includes activities like voluntary counseling and testing, as well as adherence counseling [39–42]. Training can also equip healthcare providers with the knowledge and skills needed to adopt and deliver HIV services with fidelity. However, 'Capacity Building and Support' strategies that target local implementers and key partners, which could strengthen and sustain the HIV service delivery system, were less emphasized in HIV implementation studies from LMICs. These strategies should be explored to make implementation in LMICs more sustainable, such as by building capacity of local implementers and key partners to identify and apply research evidence to practice, gain leadership and management skills [43], conduct and publish research to inform future HIV responses, and qualify for further financial investment [44], particularly in the time of declining support from high income countries.

The 'Capacity Building and Support' strategies often co-occurred and potentially interacted with similar strategies from the same category or with strategies from the 'Health Service Delivery' category. This interaction may improve the capacity of people living with HIV to use or adhere to HIV interventions [35]. A systematic review of tested implementation strategies across health and human service settings also found that educational and support strategies (distribute education material, conduct educational meetings, audit and feedback, and external facilitators) most commonly co-occurred with other strategies and suggested that these strategies may be necessary but not sufficient in successful strategy bundles [11]. Interpreted through the Behavior Change Wheel framework [45], most of the reported 'Capacity Building and Support' strategies only enhance the capability of people living with HIV and healthcare providers. Consequently, they often fail to address opportunity or motivation, which are distinct mechanisms required to receive or deliver HIV services. Bundling 'Capacity Building and Support' strategies with ‘Health Service Delivery’ strategies that target different individual change mechanisms might be done to enhance the effectiveness of strategy bundles. Future studies are needed to confirm the roles of these strategies in bundles and should consider using optimization study designs to evaluate small strategy bundles, or rigorous tracking of strategy usage over time in combination with advanced causal inference methods to evaluate complex strategy bundles.

The scarcity of 'Implementation Process,' 'Financial Arrangement,' and 'Governance' strategies identified in our systematic review raises an important question: are these strategies underused in practice and/or underreported in research? Few strategies from these categories were reported with high commonality or centrality in our analyses, despite some evidence in the literature suggesting that they could improve health outcomes. For instance, transitioning the implementation leadership of the Systems Analysis and Improvement Approach to the local Department of Health Services sustained the uptake of HIV testing and counseling services in Mombasa County, Kenya [46]. Building community ownership and leadership, working within the existing resources through adaptation to context, and developing infrastructures for intervention maintenance have shown to facilitate sustainability and effectiveness of various health interventions implemented in Sub-Saharan Africa [47]. These strategies likely impact health outcomes through indirect, diffuse effects on implementation outcomes such as adoption, acceptability, and feasibility [48]. However, a lack of clear understanding regarding these mechanisms may contribute to their under-reporting in research. Additionally, these strategies might occur informally but might not be considered as research activities and thus not reported. Our analyses also drew data from public health and medical journals that focused more on reporting clinical procedures rather than the implementation strategies used to facilitate those procedures. Nonetheless, previous systematic reviews also reported similar overemphasis of strategies targeting (HIV) intervention recipients and deliverers over organization- or health system-level barriers [11, 49]. Future implementation studies should evaluate bundles of a more diverse range of strategies, including 'Implementation Process,' 'Financial Arrangement,' and 'Governance' strategies, to understand their role in bundles for improved HIV-related health outcomes. A more systematic assessment of the characteristics and needs of other individuals involved (e.g., policymakers and product developers) and implementation domains (e.g., implementation processes, organizations, and health systems) might be necessary to inform future selection of diverse strategies in bundles.

Several limitations to our approach should be noted. First, the LIVE systematic review is subjected to possible publication bias, under-reporting of implementation strategies in manuscripts, under-specification of reported strategy components, and the exclusion of pertinent implementation studies that did not report HIV care cascade outcomes [33]. Grey literature, such as reports from programmatic efforts, might be a valuable source of real-world implementation strategy usage and should be considered in future efforts to improve the comprehensiveness of evidence synthesis on implementation strategies. Second, although we mapped extracted strategies against established taxonomies, we identified gaps in these taxonomies and therefore opted to create new categories for strategies that were not reflected in either. These new categories may require further application in other settings to determine their broader utility. Third, we used a data-driven analytic method (network analysis) to study complex strategy bundles when other study only analyzed pairwise bundles [11]. Although we believe that the centrality of strategies may inform the mechanisms of reported discrete capacity building and support, and health service delivery strategies, network statistics were difficult to interpret, and we caution against overinterpreting their importance, as we may overlook the role of underreported financial arrangement, governance, and implementation process strategies in intervention implementation. Fourth, our network analysis did not show directionality because we could not determine the chronological order in which the strategies co-occurred within published studies. This limitation inhibits us from making inferences about how discrete strategies in bundles affect each other and related health outcomes. We urge future research to comprehensively report strategy usage and investigate the mechanisms of strategies and their effects on implementation and health outcomes. Understanding the mechanisms can precisely inform which strategies should be used and prioritized for optimized, desired outcomes. Lastly, our analysis was conducted based on the HIV literature from LMICs, which have limited resources and varied health system capacity relative to high-income countries. Nonetheless, we believe our findings may provide insights for implementation scientists and implementers more broadly given that implementation strategies affect implementation outcomes common across disciplines [50].

Conclusions

Our findings from published HIV implementation studies from LMICs in 2014–2021 highlighted that the common and central strategies reported primarily addressed the barriers faced by people living with HIV in receiving and healthcare providers in delivering HIV care, mainly through improving ‘Capacity Building and Support’ and ‘Health Service Delivery.’ Although these strategies might be foundational to HIV service delivery, they may have limited change mechanisms and failed to address a wide range of contextual barriers in the implementation setting, including those at the organization and health system levels. Future implementation research and practice may consider systematically assessing the implementation context to inform a more comprehensive strategy bundle to improve HIV-related health outcomes.

Supplementary Information

43058_2026_896_MOESM1_ESM.docx (31.9KB, docx)

Additional file 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting check list.

43058_2026_896_MOESM2_ESM.xlsx (19.9KB, xlsx)

Additional file 2. The complete ranking of discrete strategies by commonality, degree centrality, and betweenness centrality from 868 intervention arms within HIV implementation studies conducted in low- and middle-income countries and published between 2014 and 2021.

43058_2026_896_MOESM3_ESM.xlsx (119.9KB, xlsx)

Additional file 3. The complete ranking of discrete strategies by commonality, degree centrality, and betweenness centrality from 868 intervention arms within HIV implementation studies conducted in low- and middle-income countries and published between 2014 and 2021, stratified by geographic region, study population, and HIV care cascade target.

43058_2026_896_MOESM4_ESM.xlsx (29.4KB, xlsx)

Additional file 4. The complete ranking of discrete strategies, defined as a unique combination of action and action target, by commonality, degree centrality, and betweenness centrality from 868 intervention arms within HIV implementation studies conducted in low- and middle-income countries and published between 2014 and 2021.

Acknowledgements

The LIVE project was made possible by a team of research assistants that reviewed studies for inclusion, abstracted the data, and conducted quality control check: Alec Aaron, Ashley Germann, Cynthia Li, Gauri Kore, Margaret Crampton, Siyu Wang, Sydney Rothman, and Umaima Tahir Banda. We are grateful for the support of Nathan Ford, the WHO collaborators, and the global HIV research community, along with the participants who contributed to this work.

Abbreviations

ART

Antiretroviral therapy

CFIR

Consolidated Framework for Implementation Research

DSD

Differentiated service delivery

EPOC

Effective Practice and Organization of Care

ERIC

Expert Recommendation for Implementing Change

LIVE

Living Database of HIV Implementation Science

LMICs

Low- and middle-income countries

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

WHO

World Health Organization

Authors’ contributions

IE, LB, SS, SB, EG, and CK led the design and implementation of the LIVE project. IE, NL, RT, and BF developed and maintained the database. NL and RT led the systematic review process. SL, NL, RT, and AU were part of a team of research assistants that conducted the systematic review. SL and CK conceptualized and conducted the analysis. SL wrote the first draft. All authors contributed to the review and revision of the manuscript, and approved the final manuscript.

Funding

The effort of JHU investigators (SL, LKB, SS, SB, RT, CGK) was supported by the National Institutes of Health through National Institutes of Allergy and Infectious Diseases (NIAID) (R24AI191865), the Implementation Science Core of the Johns Hopkins University Center for AIDS Research (P30AI094189) and the National Institutes of Mental Health (NIMH) through K01MH130244 and the Center for HIV and Mental Health Stigma Elimination Strategies (P30MH136919). The LIVE project was supported in part by the Bill & Melinda Gates Foundation [INV-009840_2020]. Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. EHG is supported by the Bill & Melinda Gates Foundation (OPP1215984) and the NIAID (K24AI134413).

Data availability

Data summary is available at https://idig.science/LIVE/. Individual study level data are available upon reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

EG is the Editor-in-Chief and CK is the associate editor of Implementation Science Communications. Other authors declare no competing interests related to this work.

Footnotes

Publisher’ Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

43058_2026_896_MOESM1_ESM.docx (31.9KB, docx)

Additional file 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting check list.

43058_2026_896_MOESM2_ESM.xlsx (19.9KB, xlsx)

Additional file 2. The complete ranking of discrete strategies by commonality, degree centrality, and betweenness centrality from 868 intervention arms within HIV implementation studies conducted in low- and middle-income countries and published between 2014 and 2021.

43058_2026_896_MOESM3_ESM.xlsx (119.9KB, xlsx)

Additional file 3. The complete ranking of discrete strategies by commonality, degree centrality, and betweenness centrality from 868 intervention arms within HIV implementation studies conducted in low- and middle-income countries and published between 2014 and 2021, stratified by geographic region, study population, and HIV care cascade target.

43058_2026_896_MOESM4_ESM.xlsx (29.4KB, xlsx)

Additional file 4. The complete ranking of discrete strategies, defined as a unique combination of action and action target, by commonality, degree centrality, and betweenness centrality from 868 intervention arms within HIV implementation studies conducted in low- and middle-income countries and published between 2014 and 2021.

Data Availability Statement

Data summary is available at https://idig.science/LIVE/. Individual study level data are available upon reasonable request.

Articles from Implementation Science Communications are provided here courtesy of BMC

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