Year: 2024
Type: conference-paper
Abstract: Early detection of an emerging VOC (Variant-Of-Concern) is essential for effective preparedness for a disease like COVID-19. The spreading of an emerging VOC not only depends on the disease dynamics of itself but also depends on the state of the circulating variants and the susceptibility of the population. Resources for testing are typically quite limited, and a number of strategies have been considered for deploying them. However, it has been difficult to evaluate the performance of such strategies, especially higher order effects, and inequities, while incorporating constraints on these resources. Here, we develop an agent-based surveillance framework, Networkdetect, to understand the early warning system of an emerging VOC. Our framework allows us to incorporate various population heterogeneities and resource constraints.
Source: Winter Simulation Conference
Institution: University of Virginia
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Awards: G1026679911, G1645119126, G166562317, G203625172, III: Medium: Collaborative Research: Detecting and Controlling Network-based Spread of Hospital Acquired Infections, G2411683797, G2584197162, G2988778103, G313676650, G3641276455, G3828073557, G5260964573, BIGDATA: Collaborative Research: F: Efficient Distributed Computation of Large-Scale Graph Problems in Epidemiology and Contagion Dynamics, G5726405315, G6490865898, Collaborative Research: Framework: Software: CINES: A Scalable Cyberinfrastructure for Sustained Innovation in Network Engineering and Science, Detection and characterization of critical under-immunized hotspots, Expeditions: Collaborative Research: Global Pervasive Computational Epidemiology, G8906985441, G8943143067
OpenAlex ID: W4406611533