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arXiv · 2307.02616

Federated Epidemic Surveillance

Ruiqi Lyu·Roni Rosenfeld·Bryan Wilder
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Abstract

Epidemic surveillance is a challenging task, especially when crucial data is fragmented across institutions and data custodians are unable or unwilling to share it. This study aims to explore the feasibility of a simple federated surveillance approach. The idea is to conduct hypothesis tests for a rise in counts behind each custodian's firewall and then combine p-values from these tests using techniques from meta-analysis. We propose a hypothesis testing framework to identify surges in epidemic-related data streams and conduct experiments on real and semi-synthetic data to assess the power of different p-value combination methods to detect surges without needing to combine the underlying counts. Our findings show that relatively simple combination methods achieve a high degree of fidelity and suggest that infectious disease outbreaks can be detected without needing to share even aggregate data across institutions.

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Ruiqi Lyu, Roni Rosenfeld, Bryan Wilder. 2023-07-05. Federated Epidemic Surveillance. https://arxiv.org/abs/2307.02616

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