Medicine and HealthPLOS Computational Biology
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!
Related Publications
Explore these studies to deepen your understanding
Adjacent work that informs or extends this paper's methodology and findings.
Psychology
Spatiotemporal dynamics of hippocampal-cortical networks underlying the unique phenomenological properties of trauma-related intrusive memories
K. J. Clancy, Q. Devignes, et al.
Education
Not-for-profit or for-profit? Research on the high-quality development path of private universities in China based on system dynamics
S. Duan, H. Yang, et al.
Political Science
The language of crisis: spatiotemporal effects of COVID-19 pandemic dynamics on health crisis communications by political leaders
B. J. Mandl and B. Y. Reis
Chemistry
Simulating the ghost: quantum dynamics of the solvated electron
J. Lan, V. Kapil, et al.
