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Principal Investigator: Michelle Birkett
Organization: NORTHWESTERN UNIVERSITY AT CHICAGO
Fiscal Year: 2024
Award: $659,491
Funding agency: National Institute on Drug Abuse
PROJECT SUMMARY
Over the last two decades, a growing literature has demonstrated that social factors drive both drug use and
infectious diseases such as HIV. Simultaneously, epidemic modeling has become vital for reducing the spread
of HIV, as it allows insight into mechanisms of spread, forecasts future incidence, and provides guidance on
effective intervention strategies. However, despite all their power and complexity, these epidemic models still
often lack realistic social data, as network and contextual data reflective of the most at-risk populations are
often deemed too methodologically challenging to capture. In line with the urgent need for data capture tools
which enable researchers to understand the social context around the most at-risk populations, our
interdisciplinary team has developed a free, open-source, NIH BD2K-funded software suite called Network
Canvas (R01DA042711). While Network Canvas has already substantially improved the ability of researchers
to quickly and accurately capture complex network and contextual data, to be useful for HIV elimination, our
existing tool requires optimization to further improve its timely and broad reach to the most at-risk populations,
as well as enhancements that will modernize the tool to better meet the needs of epidemic modelers. In
particular, we must transition Network Canvas to a Hybrid Cloud Model, developing a cloud-based software
platform that will enhance the ability of researchers to robustly capture data remotely and at scale, as well as
reach the most essential but hard-to-reach populations. Additionally, we propose user-engagement and
evaluation activities to inform the software's design and rigorously evaluate its value and impact on the
measurement of networks relevant to epidemic modeling and HIV. Through the work proposed within the
current project, we aim to: 1) Enhance data reproducibility, timeliness, and measurement for researchers; 2)
Enhance the availability and accessibility for study participants; 3) Rigorously evaluate the tool's impact on the
measurement of sexual and drug networks. This work will result in both an enhanced free and open-source
tool and an increased scientific understanding of the value and impact of the tool for capturing crucial data
relevant to HIV and drug use. Finally, just as we have done over the last five-year period, this project will
employ a strong plan for user engagement where we build partnerships with and actively employ iterative
feedback from relevant research communities to shape software features and functionality. Feedback would
be sought widely - from our highly accomplished Scientific Advisory Board (SAB); from our collaborative pilot
partnerships with researchers who hold strong NIH-funded drug use, HIV, and epidemic modeling research
portfolios; and from at-risk populations themselves. This development approach is key in ensuring community
buy-in, accelerated adoption, and long-term sustainability of our tools.
Terms: <AIDS Virus><AIDS prevention><Acceleration><Access to Care><Acquired Immune Deficiency Syndrome Virus><Acquired Immunodeficiency Syndrome Virus><Adoption><Application Context><Articulation><Automobile Driving><BD2K><Big Data to Knowledge><Collaborations><Collection><Communicable Diseases><Communities><Complement><Complement Proteins><Complex><Computer software><Country><Data><Designing computer software><Development><Disease><Disorder><Disparities><Disparity><Drug usage><Drugs><E-Mail><Electronic Mail><Email><Ensure><Epidemic><Evaluation><FAIR data><FAIR guiding principles><FAIR principles><Feedback><Findable, Accessible, Interoperable and Re-usable><Findable, Accessible, Interoperable, and Reusable><Funding><Future><Groups at risk><Guidelines><HIV><HIV Prevention><HIV/AIDS prevention><Health><Health Services Accessibility><Human Immunodeficiency Viruses><Hybrids><Impairment><Incidence><Individual><Infectious Disease Pathway><Infectious Diseases><Infectious Disorder><Internet><Intervention><Intervention Strategies><Interview><Investigators><LAV-HTLV-III><Language><Letters><Literature><Lymphadenopathy-Associated Virus><Measurement><Medication><Methodology><Modeling><Modernization><NIDA><NIH><National Institute of Drug Abuse><National Institute on Drug Abuse><National Institutes of Health><Network Analysis><Notification><Participant><Pathway Analysis><People at risk><Persons><Persons at risk><Pharmaceutical Preparations><Population><Population Dynamics><Populations at Risk><Position><Positioning Attribute><Protocol><Protocols documentation><Public Health><Reproducibility><Research><Research Personnel><Researchers><Risk><Schedule><Scientific Advances and Accomplishments><Self Administered><Self Administration><Shapes><Social Environment><Social Network><Software><Software Design><Speed><Survey Instrument><Surveys><System><Technology><Testing><Time><United States National Institutes of Health><Virus-HIV><WWW><Work><access to health services><access to services><access to treatment><accessibility to health services><availability of services><care access><cloud based><complementation><contextual factors><data quality><design><designing><developmental><driving><drug use><drug/agent><effective intervention><electronic communication><experience><health service access><health services availability><improved><innovate><innovation><innovative><insight><interventional strategy><marginalized group><marginalized individual><marginalized people><marginalized population><open source><open source tool><open source toolkit><scientific accomplishments><scientific advances><service availability><social><social climate><social context><social factors><socioenvironment><socioenvironmental><study population><substance use><substance using><success><tool><treatment access><uptake><usability><web><world wide web>