Autor: |
Jiahui Meng, Justina Yat Wa Liu, Lin Yang, Man Sing Wong, Hilda Tsang, Boyu Yu, Jincheng Yu, Freddy Man-Hin Lam, Daihai He, Lei Yang, Yan Li, Gilman Kit-Hang Siu, Stefanos Tyrovolas, Yao Jie Xie, David Man, David H.K. Shum |
Jazyk: |
angličtina |
Rok vydání: |
2024 |
Předmět: |
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Zdroj: |
Infectious Disease Modelling, Vol 9, Iss 2, Pp 474-482 (2024) |
Druh dokumentu: |
article |
ISSN: |
2468-0427 |
DOI: |
10.1016/j.idm.2024.02.002 |
Popis: |
An AI-empowered indoor digital contact-tracing system was developed using a centralized architecture and advanced low-energy Bluetooth technologies for indoor positioning, with careful preservation of privacy and data security. We analyzed the contact pattern data from two RCHs and investigated a COVID-19 outbreak in one study site. To evaluate the effectiveness of the system in containing outbreaks with minimal contacts under quarantine, a simulation study was conducted to compare the impact of different quarantine strategies on outbreak containment within RCHs. The significant difference in contact hours between weekdays and weekends was observed for some pairs of RCH residents and staff during the two-week data collection period. No significant difference between secondary cases and uninfected contacts was observed in a COVID-19 outbreak in terms of their demographics and contact patterns. Simulation results based on the collected contact data indicated that a threshold of accumulative contact hours one or two days prior to diagnosis of the index case could dramatically increase the efficiency of outbreak containment within RCHs by targeted isolation of the close contacts. This study demonstrated the feasibility and efficiency of employing an AI-empowered system in indoor digital contact tracing of outbreaks in RCHs in the post-pandemic era. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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