Surveillance Testing for Rapid Detection of Outbreaks in Facilities

Autor:	Ding, Yanyue, Agrawal, Sudesh K., Cao, Jincheng, Meyers, Lauren, Hasenbein, John J.
Rok vydání:	2021
Předmět:	Quantitative Biology - Populations and Evolution Statistics - Computation
Druh dokumentu:	Working Paper
Popis:	This paper develops an agent-based disease spread model on a contact network in an effort to guide efforts at surveillance testing in small to moderate facilities such as nursing homes and meat-packing plants. The model employs Monte Carlo simulations of viral spread sample paths in the contact network. The original motivation was to detect COVID-19 outbreaks quickly in such facilities, but the model can be applied to any communicable disease. In particular, the model provides guidance on how many test to administer each day and on the importance of the testing order among staff or workers. Comment: 21 pages, 14 figures and 3 tables. Submitted to Health Care Management Science
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2110.00170 Zobrazit plný text záznamu View this record from Arxiv