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Cities — try to predict superspreading hotspots for COVID-19

Author

Listed:
  • Roland Bouffanais
  • Sun Sun Lim

Abstract

Tracking how people move around urban areas can pinpoint where disease might transmit fastest and farthest.

Suggested Citation

  • Roland Bouffanais & Sun Sun Lim, 2020. "Cities — try to predict superspreading hotspots for COVID-19," Nature, Nature, vol. 583(7816), pages 352-355, July.
    • Handle: RePEc:nat:nature:v:583:y:2020:i:7816:d:10.1038_d41586-020-02072-3
    DOI: 10.1038/d41586-020-02072-3
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    Cited by:

    1. Loren March & Ute Lehrer, 2022. "Common Areas, Common Causes: Public Space in High-Rise Buildings During Covid-19," Urban Planning, Cogitatio Press, vol. 7(4), pages 352-363.
    2. Sui Zhang & Minghao Wang & Zhao Yang & Baolei Zhang, 2021. "A Novel Predictor for Micro-Scale COVID-19 Risk Modeling: An Empirical Study from a Spatiotemporal Perspective," IJERPH, MDPI, vol. 18(24), pages 1-16, December.

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