New temporal prior model enhances disease transmission reconstruction

Researchers have developed a novel temporal prior model for reconstructing disease transmission, demonstrating its effectiveness on an Andes virus benchmark. This model achieved significantly higher accuracy and mean reciprocal rank compared to traditional methods. An audit of NYC mpox data revealed substantial uncertainty in genomic resolution, and incorporating this uncertainty into transmission graphs altered prioritization for intervention strategies. AI

IMPACT This research could lead to more accurate public health interventions by improving disease transmission modeling.

RANK_REASON The cluster contains a research paper published on arXiv detailing a new model and its evaluation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

• alphaXiv
• Andes virus
• arXiv
• CatalyzeX
• DagsHub
• Gotit.pub
• Guangdong Delta
• Hugging Face
• IArxiv
• Influence Flower
• NYC mpox
• ScienceCast

• paper
• model release

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