Article

Developing an Interpretable Hybrid AI Framework that Integrates Mobility Data, Genomic Surveillance, and Symptom Reporting for Early Outbreak Signal Detection

2026-07-30

Abstract excerpt

<h4>Background: </h4> Early detection of infectious disease outbreaks is critical for containing transmission and mitigating public health impacts. Traditional surveillance systems rely on clinical case reporting, which suffers from significant delays due to diagnostic confirmation and administrative lags. While machine learning has been applied to epidemic modeling, most existing approaches utilize single data st...

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Literature Corpus work: 1b1e2710-9ee4-5b18-ab17-ad1331a17e1a
DOI: 10.14293/pr2199.004179.v1

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