Generating synthetic population for simulating the spatiotemporal dynamics of epidemics.

ABSTRACT: Agent-based models have gained traction in exploring the intricate processes governing the spread of infectious diseases, particularly due to their proficiency in capturing nonlinear interaction dynamics. The fidelity of agent-based models in replicating real-world epidemic scenarios hinges on the accurate portrayal of both population-wide and individual-level interactions. In situations where comprehensive population data are lacking, synthetic populations serve as a vital input to agent-based models, approximating real-world demographic structures. While some current population synthesizers consider the structural relationships among agents from the same household, there remains room for refinement in this domain, which could potentially introduce biases in subsequent disease transmissio

SUBMITTER: Zhu K 

PROVIDER: S-EPMC10890746 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature