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http://hdl.handle.net/10397/90815
| Title: | Author correction : An extended weight kernel density estimation model forecasts COVID-19 onset risk and identifies spatiotemporal variations of lockdown effects in China | Authors: | Shi, W Tong, C Zhang, A Wang, B Shi, Z Yao, Y Jia, P |
Issue Date: | 2021 | Source: | Communications biology, 2021, v. 4, no. 1, 418 | Publisher: | Nature Publishing Group | Journal: | Communications biology | EISSN: | 2399-3642 | DOI: | 10.1038/s42003-021-01924-6 | Rights: | © The Author(s) 2021 This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The following publication Shi, W., Tong, C., Zhang, A., Wang, B., Shi, Z., Yao, Y., & Jia, P. (2021). Author Correction: An extended Weight Kernel Density Estimation model forecasts COVID-19 onset risk and identifies spatiotemporal variations of lockdown effects in China. Communications Biology, 4(1), 1-8 is available at https://doi.org/10.1038/s42003-021-01924-6 |
| Appears in Collections: | Journal/Magazine Article |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| s42003-021-01924-6.pdf | 4.75 MB | Adobe PDF | View/Open |
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