Technical Case Study of Privacy-Enhancing Technologies (PETs) for Public Health

Computer Science > Cryptography and Security [Submitted on 13 Mar 2026] Technical Case Study of Privacy-Enhancing Technologies (PETs) for Public Health Avinash Laddha, Danil Mikhailov, Uyi Stewart We present a technical case study on the Privacy-Enhancing Technologies (PETs) for Public Health Challenge, a collaborative effort to safely leverage sensitive private sector data for social impact, specifically pandemic management. The project utilized Differential Privacy (DP) to create realistic, privacy-preserved synthetic financial transaction data, which was then combined with public health and mobility datasets. This approach successfully addressed the critical hurdle of sharing sensitive financial information for research and policy. The analysis demonstrated that this synthetic, DP-protected data possesses significant spatial-temporal and predictive power for public health. Key outcomes include the development of six reusable tools and frameworks supporting diagnostic nowcasting (e.g., Hotspot Detection, Pandemic Adherence Monitoring) and predictive forecasting (e.g., Mobility Analysis, Contact Matrix Estimation) for epidemiological decision-making. The study provides best practices for advancing data sharing in a privacy-compliant manner. Comments: Estimated 20 pages, 0 figures. The work is a technical case study of the PETs for Public Health Challenge. Author Avinash Laddha contributed to this final report and interpreted insights. For more information on the organizing non-profit, see this http URL Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI) MSC classes: 92C60 (Primary) 62P10, 68P25 (Secondary) ACM classes: J.3; E.3 Cite as: arXiv:2603.13444 [cs.CR]   (or arXiv:2603.13444v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2603.13444 Focus to learn more Submission history From: Avinash Laddha Mr [view email] [v1] Fri, 13 Mar 2026 13:04:59 UTC (3,058 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-03 Change to browse by: cs cs.AI References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)