Medicine and Health

Generating synthetic population for simulating the spatiotemporal dynamics of epidemics

K. Zhu, L. Yin, et al.

This research conducted by Kemin Zhu, Ling Yin, Kang Liu, Junli Liu, Yepeng Shi, Xuan Li, Hongyang Zou, and Huibin Du reveals a groundbreaking approach to generating synthetic populations for epidemic modeling. With over 17 million agents representing Shenzhen, China, it shows how realistic population data can dramatically influence epidemic projections, including peak incidence rates. Discover how innovative techniques can enhance our understanding of infectious disease spread!

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Playback language: English

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