An extended Weight Kernel Density Estimation model forecasts COVID-19 onset risk and identifies spatiotemporal variations of lockdown effects in China

Wenzhong Shi et al. propose an extended Weight Kernel Density Estimation model to predict the COVID-19 onset risk, with and without the Wuhan lockdown, and corresponding symptom onset and spatial heterogeneity in 347 Chinese cities. The authors find that the lockdown delayed COVID-19 peak onset by 1...

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Autores principales: Wenzhong Shi, Chengzhuo Tong, Anshu Zhang, Bin Wang, Zhicheng Shi, Yepeng Yao, Peng Jia
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/ad2ac98641494ad49b5bb3bf054219d6
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