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优化全校范围的COVID-19测试通知,使用可解释的废水时间序列功能,使用机器学习模型

Tuo Lin1, Smruthi Karthikeyan2, Alysson Satterlund3

  • 1Department of Biostatistics, University of Florida, Gainesville, FL, 32608, USA.

Scientific reports
|November 24, 2023
PubMed
概括

对SARS-CoV-2的废水监测有效地预测了住宅中的COVID-19感染. 在过去7天中至少3天的污水样本呈阳性是个体感染的最佳指标.

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In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
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