Moshiri Niema
Department of Computer Science & Engineering, University of California, San Diego, CA, USA.
Methods Mol Biol. 2025;2927:173-193. doi: 10.1007/978-1-0716-4546-8_10.
The ability to simulate social contact networks, transmission networks, pathogen phylogenies, and pathogen genome sequences that capture a wide range of scenarios can enhance molecular epidemiology. However, the utility of such simulations depends entirely on their ability to capture important properties of the real-world epidemics they are used to study, which in turn depends on the appropriateness of the model assumptions behind the simulations. In this chapter, I introduce the FAVITES-Lite framework and discuss how one can use it to design and execute realistic epidemic simulations that appropriately model real-world epidemics of interest.
模拟社会接触网络、传播网络、病原体系统发育以及能够涵盖广泛场景的病原体基因组序列的能力，可以增强分子流行病学。然而，此类模拟的效用完全取决于它们捕捉其所用于研究的现实世界疫情重要特征的能力，而这又取决于模拟背后模型假设的恰当性。在本章中，我将介绍FAVITES-Lite框架，并讨论如何使用它来设计和执行能够恰当地模拟感兴趣的现实世界疫情的逼真疫情模拟。
