Debbie Humphries

Background: The Ending the HIV Epidemic (EHE) initiative remains a national priority in the United States, aiming to reduce new HIV infections by 90% by 2030. As we cross the initiative’s midpoint, there is renewed commitment to strengthening the HIV workforce’s capacity to plan, implement, and sustain effective HIV prevention, treatment, and care interventions. Despite substantial improvement in HIV outcomes, uneven implementation of evidence-based interventions reflects persistent gaps between available evidence and its translation into locally actionable practice. Achieving EHE goals requires tailoring implementation to the diverse sociostructural conditions shaping HIV outcomes across jurisdictions. Research increasingly highlights the value of integrated, contextual data to strengthen public health decision-making. Linking indicators spanning multiple conceptual domains across various geographic levels can support a robust understanding of the distinct drivers of HIV outcomes, yet existing data systems remain fragmented. A harmonized, multisource, multilevel database is therefore essential to support targeted, needs-based, and data-driven implementation under the EHE initiative. We present a reproducible protocol detailing the transferable methodology of building and maintaining such a resource. Objective: This project aims to (1) build a high-quality contextual database integrating multiple data sources using transparent, replicable, and updatable methods and (2) develop and document systematic workflows for ongoing updates and quality assurance (QA) and support future use aligned with open-science frameworks and standard data practices. Methods: This project will follow best practices in data architecture, acquisition, standardization, and QA. For objective 1, we will integrate data across multiple geographic levels (eg, ZIP code, county) for 2020-2025, with measures categorized into conceptual domains (eg, epidemiologic and sociodemographic) guided by established theoretical frameworks. For objective 2, we will develop a tiered data structure using a GitHub repository to store documentation, processing scripts, and QA logs aligning with open science practices. Construction and QA methods were informed by targeted PubMed literature reviews. Data sources include existing data repositories, literature-identified datasets, and gray literature with consistent formatting and permissive terms of use suitable for web scraping. Stakeholder engagement will span all phases of database development, informing variable selection, usability, and validation to enable iterative refinement and revision. Results: Funding was obtained in August 2025. Literature reviews from October to November 2025 informed the database construction methods, source identification, and protocol development. Data acquisition, standardization, and QA began in May 2026, with acquisition remaining iterative. Cross-source integration, final QA checks, and dashboard development are expected to conclude in October 2026. Study results are anticipated for publication in summer 2027. Conclusions: This protocol will provide a reproducible, transferable model for building and maintaining a contextual data resource that could support public health planning and advance implementation science through more context-responsive decision-making under the EHE initiative.

Background: Worldwide, 451 million people and up to 156 million children are infected with hookworm, causing an estimated 3.2 million disability-adjusted life-years annually. We conducted a two-year longitudinal cohort study of hookworm infection with a random selection of 274 school-age children (4–16 yrs) in rural Ghana to identify nutritional and environmental exposures impacting hookworm infection and response to treatment. Methods: Every six months (baseline Jan 2013) we collected anthropometric measurements, pre- and post-treatment fecal samples, and blood samples. Household surveys and multiple-pass twenty-four-hour recalls were conducted at baseline and 18 months. Results: Seventy-eight participants (28.5%) were absent from at least 1 time point. Of the 196 that were screened at all five time points, 87 (44.4%) were hookworm-infected>1 time. Assessment of albendazole treatment response was conducted on 83 participants. Sixty (72.3%) were cleared of hookworm infections while 23 (27.5%) remained infected post-treatment (ERR: 0–99%). Treatment efficacy was more likely among children aged over 9.66 years (HR: 1.55; 95% CI: 1.18, 2.04) and those from food-insecure households (HR: 2.26; 95% CI: 1.06, 4.81). Hookworm infection status and albendazole treatment outcome at baseline and 18 months were the dominant influences on infections at 6 and 24 months, respectively. Future risk of infection at both 6 and 24 months had significant environmental and nutritional predictors, although the variables differed. Conclusions: Global school-based deworming has been associated with reduced rates of hookworm infection among schoolchildren in Africa; however, additional strategies will be necessary for long-term, sustainable control. This study reports on an innovative two-year longitudinal study of school age children with repeated cycles of testing and treatment. We modelled hookworm infection as a function of predictors that were measured six months prior, thereby strengthening the assessment of causal relationships between environmental, infection and nutritional risk factors.

BACKGROUND The Ending the HIV Epidemic (EHE) initiative remains a national priority in the United States (U.S.), aiming to reduce new HIV infections by 90% by 2030. As we cross the initiative’s midpoint, there has been a renewed commitment to strengthening the HIV workforce’s capacity to plan, implement, and sustain effective HIV prevention, treatment, and care interventions. Despite substantial improvements in HIV outcomes, uneven implementation of evidence-based interventions reflects persistent gaps between available evidence and its translation into locally actionable practice. Achieving EHE goals requires tailoring implementation to the diverse epidemiological, social, and structural conditions shaping HIV outcomes across jurisdictions. Research increasingly highlights the value of integrated, contextual data to strengthen public health decision-making. Linking indicators spanning multiple conceptual domains across regional, local and individual levels can support a more robust understanding of the distinct drivers of HIV outcomes, yet existing data systems remain fragmented across domains and scales. A harmonized, multisource, multilevel database is therefore essential to support targeted, needs-based and data-driven implementation under the EHE initiative. OBJECTIVE This project has two objectives: (1) to build a high-quality contextual database integrating multiple sources of public data using transparent, replicable, and updateable methods, and (2) to develop and document systematic workflows for ongoing database updates, quality assurance, and to support future use aligned with open-science frameworks and standard data practices. METHODS This project will follow best practices in data architecture, acquisition, standardization, and quality assurance. For Objective 1, we will integrate data across multiple geographic levels (e.g., ZIP code, county) for the years 2020-2025, with measures categorized into conceptual domains (e.g., epidemiologic, sociodemographic) guided by established theoretical frameworks to facilitate future analyses. For Objective 2, we will develop a tiered data structure to enable transparent and reproducible data management, using a GitHub repository to store all documentation, processing scripts, and quality assurance logs to align with open science practices. Database construction and quality assurance methods were informed by targeted literature reviews in PubMed. Data sources will be identified from three inputs: existing data repositories, datasets identified through targeted literature reviews, and reports or grey-literature with consistent formatting and permissive terms of use suitable for web scraping. Stakeholder engagement will be integrated through all phases of database development, informing variable selection, usability, and validation to enable iterative refinement and revision. RESULTS Literature reviews were conducted from October to November of 2025, to inform database construction methods, source identification, and protocol development. Data acquisition will begin in May 2026. CONCLUSIONS This contextual database will provide a reproducible and scalable data resource to support public health planning and advance implementation science by enabling more context-responsive decision-making under the EHE initiative.

Implementation science (IS) plays a critical role in translating research into real-world health outcomes. Few studies have evaluated models that provide technical assistance and other resources to build IS capacity. The Coordinating and Capacity-Building Hubs to Enhance the Science of HIV Implementation Research (CHESHIRE) network supports US-based HIV research awardees participating in the Ending the HIV Epidemic in the US (EHE) initiative. The objective of this study is to describe the evaluation protocol for CHESHIRE and assess the effect of the implementation of hub technical assistance activities on EHE-funded research team outcomes, including IS competencies, scientific collaboration, and research productivity. This protocol describes a mixed methods evaluation using qualitative interviews with EHE project leads (n=36); social network analysis of CHESHIRE-affiliated researchers and hub members (n=265); and secondary data analysis of National Institutes of Health (NIH) RePORTER, PubMed, and NIH Implementation Science Coordination Initiative EHE Project Final Progress Report Survey data (n=248). We will use descriptive analyses, network metrics, and thematic coding to describe outcomes following CHESHIRE implementation, including IS competencies, interinstitutional partnerships, and research productivity. CHESHIRE coordinating center and hub activities were funded through NIH Center for AIDS Research and AIDS Research Center supplements beginning in 2019, with hubs funded between 2019 and 2024. Available survey data include EHE projects that completed the EHE Project Final Progress Report Survey between August 2021 and February 2025. As of January 2026, we have completed enrollment, with 265 network members in the final recruiting list. Data abstraction and analysis of the evaluation components are ongoing. Publication of findings is anticipated for December 2026. Evaluation findings will be disseminated after completion of data analysis. The findings will provide insights on whether structured IS support through CHESHIRE increases researchers' IS competencies, interinstitutional partnerships, and research productivity. This evaluation will provide empirical evidence to guide the development and optimization of technical assistance hubs in public health research and inform their future evaluation of hub-based IS capacity-building models. Findings will inform strategies to optimize IS capacity building and accelerate the translation of evidence-based interventions into practice, especially in HIV prevention and treatment. DERR1-10.2196/91374.

Background: Missouri is one of seven priority states identified by the Ending the HIV Epidemic Initiative, and St. Louis contains almost half of the people living with HIV (PLWH) in Missouri. As St. Louis has a marked history of structural racism and economic inequities, we utilized the Intersectionality Based Policy Analysis (IBPA) framework to guide a participatory needs assessment for planning and program development.Methods: The planning team included researchers, the lead implementer from our community partner, and two community representatives, and had biweekly 60–90 min meetings for 18 months. The planning team approved all research materials, reviewed and interpreted results, and made decisions about recruitment, conduct of the needs assessment, and development of the planned intervention. The needs assessment integrated information from existing data, (1) interviews with (a) PLWH (n = 12), (b) community leaders (n = 5), (c) clinical leaders (n = 4), and (d) community health workers (CHWs) (n = 3) and (e) CHW supervisors (n = 3) who participated in a Boston University-led project on CHWs in the context of HIV and (2) focus groups (2 FG, 12 participants) with front-line health workers such as peer specialists, health coaches and outreach workers. A rapid qualitative analysis approach was used for all interviews and focus groups.Results: The IBPA was used to guide team discussions of team values, definition and framing of the problem, questions and topics in the key informant interviews, development of the logic model of the problem, and all results. Applying the IBPA framework contributed to a focus on intersectional drivers of inequities in HIV. The effective management of HIV faces significant challenges from high provider turnover, insufficient integration of CHWs into care teams, and organizational limitations in tailoring treatment plans. Increasing use of CHWs for HIV treatment and prevention also faces challenges. People living with HIV (PLWH) encounter multiple barriers including stigma, lack of social support, co-morbidities, and difficulties in meeting basic needs.Conclusion: Addressing intersectional drivers of health inequities may require multi-level, structural approaches. We see the IBPA as a valuable tool for participatory planning that emphasizes equity and integrates community engagement principles in program and implementation design for improving HIV outcomes.

Background: Community–academic partnerships (C-APs) have been central to advancements in HIV research over the past 4 decades and were specifically called for in the national Ending the HIV Epidemic (EHE) initiative. Community engagement in research, particularly in HIV research, plays a critical role in prioritizing community needs in all stages of HIV research and intervention implementation. Methods: To address the known gaps in building strong C-APs, 2 EHE Implementation Science Consultation Hubs collaboratively facilitated 2 webinars with a panel of expert community leaders. The panel discussions explored (1) what researchers need to know to create equitable C-APs and (2) best practices for navigating power in C-APs. After the webinars, we conducted a quantitative analysis of the 131 EHE research projects partnered with community-based organizations or faith-based organizations between 2019 and 2023 to examine the community engagement in research relationships between EHE academic researchers and implementation partners. Results: Community panelists identified areas for academic researchers to prioritize, including building relationships with community partners, engaging equitably in partnership processes, sharing use of resources, and paying attention to community history. The quantitative analysis found 58% of EHE researchers are in new collaborations, lasting 2 years or less, with their implementation partner, and have not yet established robust partnerships. Conclusions: This study identifies strategies for strengthening community engagement in HIV research and sustaining equitable C-APs for existing EHE supplement recipients that can be integrated into future EHE research and implementation strategies to help end the HIV epidemic in the United States.

Background: Because implementation remains the biggest challenge to Ending the HIV Epidemic in the United States (EHE), since 2019, the National Institutes of Health (NIH) has funded 248 supplements to identify best practices for delivering evidence-based HIV interventions. NIH also funded a coordination center [Implementation Science (IS) Coordination Initiative “ISCI”] and 9 consultation hubs (“Hubs”) to provide technical assistance and cross-project information sharing, measure harmonization, and data synthesis. This article describes this unique capacity-building model, lessons learned from the first 5 years, and opportunities created by this infrastructure. Methods: Beginning in FY20, Hubs were assigned 7–9 funded supplement projects in EHE priority jurisdictions. Primary Hub services included direct coaching, multiproject meetings, communities of practice, and technical webinars. ISCI and the Hubs met monthly to reflect on project support, discuss ways to enhance HIV IS broadly, and assess projects' use of Hub services. Findings: Hub engagement strategies included grouping projects by HIV intervention type, setting data reporting expectations early, and tailoring engagement based on EHE team IS expertise. Support and coordination provided by the Hubs and ISCI have developed generalizable IS knowledge from local knowledge (e.g., publications and tools). The network of ISCI, the Hubs, and EHE projects have also led to infrastructure for conducting multisite HIV implementation research. Implications for D&I Science: The Hub model is a novel, systemwide approach for rapidly improving IS capacity in a field. Implementation of this model will continue to be refined through an ongoing evaluation and as the funding transitions to regular, nonsupplement NIH funding mechanisms.

: To identify potential sources of hookworm infections in a Ghanaian community of endemicity that could be targeted to interrupt transmission, we tracked the movements of infected and noninfected persons to their most frequented locations. Fifty-nine participants (29 hookworm positives and 30 negatives) wore GPS trackers for 10 consecutive days. Their movement data were captured in real time and overlaid on a community grid map. Soil samples were collected and divided into two parts: one for determining the physical and chemical properties and the other for culture of helminth larvae. Soil parameters were determined using standard methods, and the number of larvae recovered from Baermann cultures (expressed as larvae per gram of soil) was recorded. We found no significant difference in the larval counts between sites of infected and noninfected participants (P = 0.59). Sandy-loam soil, pH, and effective cation exchange capacity were associated with high larval recovery counts (P P Panagrolaimus superbus, Parastrongyloides trichosuri, Trichuris trichiura (human whipworm), and Ancylostoma caninum (dog hookworm). Despite Necator americanus being the predominant species in the community, no larvae of this species were identified. This study, however, demonstrates the feasibility of applying molecular tools for identifying environmental factors and places associated with exposure to human and zoonotic helminths, including areas that may be targeted to break transmission in communities where infection is endemic.

The HIV epidemic remains a national priority in the United States, and the Ending the HIV Epidemic initiative has renewed the call for expanded prevention and treatment strategies capable of reducing new HIV infections by 90% by 2030. Achieving this goal requires robust, integrated data for understanding HIV-related needs, barriers to care, and the effectiveness of interventions. However, despite the existence of numerous publicly available datasets, few integrate multiple domains such as HIV outcomes, social determinants of health, and community-level factors. The lack of unified data and difficulty linking datasets hampers efforts for meaningful cross-domain analyses to tailor HIV management and treatment strategies. The resulting fragmentation constitutes a methodological gap: implementation teams lack replicable guidance for constructing unified HIV and contextual databases from public sources. In this viewpoint, we describe our experience building a unified compilation of publicly available HIV and community data to identify factors influencing HIV outcomes and interventions. The completed database comprises 242 variables drawn from 8 public sources mapped across clinic, zip code, county, and state levels of geography. Rather than simply reporting what we built, we position four core decisions as transferable methodological advances: (1) treating source identification as a bounded phase before construction begins, (2) adopting automated data engineering tools from the outset rather than manual entry, (3) establishing a shared data dictionary before the first variable is entered, and (4) integrating quality control throughout the workflow rather than as a final phase. The build required approximately 350 total project hours and revealed an initial spot-check error rate of approximately 33%, which we attribute primarily to manual data entry. By sharing the approach used to develop this database and making the final resource publicly accessible through the Yale Center for Methods in Implementation and Prevention Science, we aim to reduce barriers to data access and encourage similar data integration efforts. The methodological framework described in this paper is intentionally designed to be replicable with modest resources, and we present it as a practical model for research teams operating without specialized infrastructure. Consolidating HIV, social determinants of health, and contextual variables into a unified data source is a critical step toward enabling deeper, more comprehensive analysis and supporting ongoing efforts to end the HIV epidemic in the US.

BACKGROUND The HIV epidemic is a national focus within the United States (U.S.), Ending the HIV Epidemic (EHE) Initiative aiming to reduce new HIV infections by 90% by 2023 through scaling of prevention and treatment strategies. Data are crucial to understanding HIV-related needs, barriers to care, and the effectiveness of interventions. While several publicly available datasets exist, few integrate multiple topic domains such as HIV outcomes, social determinants of health (SDOH), and community-level factors. The lack of unified data and difficulty linking datasets across these domains hampers efforts to tailor HIV management and treatment strategies. Existing datasets are often siloed and difficult to analyze together, limiting potential for comprehensive research. Combining and integrating data across geographic and thematic strata offers significant potential to better understand the factors influencing HIV outcomes and to optimize intervention strategies. OBJECTIVE This study explores the feasibility of combining public HIV and community data to identify factors influencing HIV outcomes and interventions. We described the process of sourcing, extracting, and linking variables into a unified database to highlight key community factors and demonstrate the potential of this integrated approach for overcoming data access barriers in HIV research. METHODS A team of two researchers was integrated within a larger network to undergo this task. Approximately 350 hours were spent developing a single unified database. The build was conducted across three phases: 1) initial sourcing of datasets, 2) extracting and linking data, and 3) quality control/quality assurance. Experts were consulted to identify relevant data sources, and data was extracted and linked across multiple geographics levels. Quality control included manual spot checks and web scraping with Web Scraper, a third-party tool to verify accuracy of the extracted data. Data were uploaded to SAS for further analysis. RESULTS The resulting database comprises 242 variables sources from eight publicly available datasets. These variables were linked to 104 Ryan White-associated clinics across five U.S. states, covering geographic levels from state to individual clinic. All data were sourced and scraped between August 2022 and January 2023. Following data preparation, descriptive tables were generated, grouped into three domains: environmental variables, HIV-related variables, and implementation outcome variables. The final database and data dictionary are publicly accessible on the Yale Center for Implementation and Prevention Science (CMIPS) website for future research. CONCLUSIONS This integrated HIV and SDOH database overcomes key challenges in accessing fragmented data, offering valuable insights for addressing HIV outcomes. Despite barriers like technology learning curves and data availability, the project successfully created a resource that can inform EHE goals and guide future interventions. Expanding the database will enable deeper analysis and support ongoing effort to end the HIV epidemic.