Quasi-experimental study reveals divergent bug-resolution resilience across software governance models after aid freezes, highlighting structural vulnerabilities in digital health infrastructure.
Open-source digital public goods play a growing role in point-of-care health service delivery in low- and middle-income countries (LMICs). Many of these systems are developed and maintained by organizations that rely heavily on donor funding, making their long-term sustainability vulnerable to funding instability. The January 2025 U.S. Agency for International Development (USAID) funding freeze created a rare natural experiment to observe how different organizations maintaining these systems respond under external funding shocks. Using 7,922 issues from eight repositories created between June 2023 and June 2025, a DistilBERT model was fine-tuned to classify bug severity. Organizations were categorized into three funding-based models: donor-driven (primarily grant-funded), revenue-driven (sustained through commercial or internal investment), and hybrid (combining grants and revenue). Interrupted time series (ITS) and Cox proportional hazards models were then applied to evaluate changes in bug-resolution efficiency. Revenue-driven organizations did not exhibit a statistically significant immediate level change but experienced significant deterioration in the post-intervention period. Donor-driven organizations exhibited no substantial changes following the intervention, maintaining stable baseline levels. Hybrid organizations showed resilience to the immediate funding shock, with a gradual decline in bug resolution as time went on after the shock. These findings suggest that the funding shocks function as a stress test for digital public goods and highlight the resilience advantages of various governance models.
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Sheng et al. (2026) studied this question.
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