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Jilei Tai

As seen in: PLOS, medRxiv
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Articles

Behavior-driven forecasts of neighborhood-level COVID-19 spread in New York City

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By Renquan Zhang, Jilei Tai, Qing Feng Yao, Kai Ruggeri
| PLOS
Discussion Population contacts driven by human activities can facilitate the transmission of SARS-CoV-2. In this study, we analyzed aggregated foot traffic data in different place categories in NYC. Our study resulted in several findings that can inform improved neighborhood-level forecasting of disease outbreaks.
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Behavior-driven forecasts of neighborhood-level COVID-19 spread in New York City

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By Renquan Zhang, Jilei Tai, Qing Feng Yao, Kai Ruggeri
| medRxiv
JS and Columbia University disclose partial ownership of SK Analytics. JS discloses consulting for BNI. All other authors declare they have no competing interests. This study was supported by funding from National Science Foundation DMS-2229605, Centers for Disease Control and Prevention 75D30122C14289 and U01CK000592, and Council of State and Territorial Epidemiologists NU38OT00297.
Open in Who Shared View Duplicates (109) Issue with article?

Ensemble inference of unobserved infections in networks using partial observations

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By Sen Pei, Renquan Zhang, Jilei Tai
| PLOS
Experiments in simulated networks We first validated the ensemble inference algorithm using synthetic outbreaks on simulated networks. We compared the performance of the ensemble inference with several alternative methods to locate unobserved infections.
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