Using publicly available, interactive epidemiological dashboards: an innovative approach to sharing data from the Rakai Community Cohort Study

July 23, 2024 by
Using publicly available, interactive epidemiological dashboards: an innovative approach to sharing data from the Rakai Community Cohort Study
Aber Maurine
Kevin Footer1; Camille M. Lake1; Joshua R. Porter1; Grace K. Ha1; Tanvir Ahmed1; Alex Glogowski1; Anthony Ndyanabo2; M. Kate Grabowski3; Larry W. Chang4,5; Joseph Ssekasanvu4; Joseph Kagaayi2; David M. Serwadda2; Jackie Mckina2; Christopher Whalen1; Lloyd Ssentongo1; Ivan Nsimbi1; Benedicto Kakeeto1; Godfrey Kigozi2; Robert Ssekubugu2; Tom Lutalo2; Maria J. Wawer4; Ronald H. Gray4; Steven J. Reynolds2,5,6; Alex Rosenthal1*; Thomas C. Quinn4,6; Michael Tartakovsky1

Affiliations:

1Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA
2Rakai Health Sciences Program, Kalisizo, Uganda
3Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA
4Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
5Johns Hopkins School of Medicine, Baltimore, MD, USA
6Laboratory of Immunoregulation, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA

*Corresponding author: Alex Rosenthal, MS, MBA, Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, 5601 Fishers Lane, Rockville, MD, USA. alexr@niaid.nih.gov

Equal Contribution: Thomas C. Quinn and Michael Tartakovsky contributed equally to this work.

Abstract

Objectives: Public sharing of de-identified biomedical data promotes collaboration between researchers and accelerates the development of disease prevention and treatment strategies. However, open-access data sharing presents challenges to researchers who need to protect the privacy of study participants, ensure that data are used appropriately, and acknowledge the inputs of all involved researchers. This article presents an approach to data sharing which addresses the above challenges by using a publicly available dashboard with de-identified, aggregated participant data from a large HIV surveillance cohort.

Materials and Methods: Data in this study originated from the Rakai Community Cohort Study (RCCS), which was integrated into a centralized data mart as part of a larger data management strategy for the Rakai Health Sciences Program in Uganda. These data were used to build a publicly available, protected health information (PHI)-secured visualization dashboard for general research use.

Results: Using two unique case studies, we demonstrate the capability of the dashboard to generate the following hypotheses: firstly, that HIV prevention strategies ART and circumcision have differing levels of impact depending on the marital status of investigated communities; secondly, that ART is very successful in comparison to circumcision as an interventional strategy in certain communities.

Discussion: The democratization of large-scale anonymized epidemiological data using public-facing dashboards has multiple benefits, including facilitated exploration of research data and increased reproducibility of research findings.

Conclusion: By allowing the public to explore data in depth and form new hypotheses, public-facing dashboard platforms have significant potential to generate new relationships and collaborations and further scientific discovery and reproducibility.

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