학술논문

Evaluating the impact of test-trace-isolate for COVID-19 management and alternative strategies.
Document Type
Article
Source
PLoS Computational Biology. 9/1/2023, Vol. 19 Issue 9, p1-20. 20p. 1 Diagram, 6 Graphs.
Subject
*COVID-19
*CONTACT tracing
*INFECTIOUS disease transmission
*COMMUNICABLE diseases
*SARS-CoV-2
Language
ISSN
1553-734X
Abstract
There are many contrasting results concerning the effectiveness of Test-Trace-Isolate (TTI) strategies in mitigating SARS-CoV-2 spread. To shed light on this debate, we developed a novel static-temporal multiplex network characterizing both the regular (static) and random (temporal) contact patterns of individuals and a SARS-CoV-2 transmission model calibrated with historical COVID-19 epidemiological data. We estimated that the TTI strategy alone could not control the disease spread: assuming R0 = 2.5, the infection attack rate would be reduced by 24.5%. Increased test capacity and improved contact trace efficiency only slightly improved the effectiveness of the TTI. We thus investigated the effectiveness of the TTI strategy when coupled with reactive social distancing policies. Limiting contacts on the temporal contact layer would be insufficient to control an epidemic and contacts on both layers would need to be limited simultaneously. For example, the infection attack rate would be reduced by 68.1% when the reactive distancing policy disconnects 30% and 50% of contacts on static and temporal layers, respectively. Our findings highlight that, to reduce the overall transmission, it is important to limit contacts regardless of their types in addition to identifying infected individuals through contact tracing, given the substantial proportion of asymptomatic and pre-symptomatic SARS-CoV-2 transmission. Author summary: Among the various targeted NPIs, the Test-Trace-Isolate (TTI) strategies have been commonly adopted to mitigate and control the spread of infectious diseases. Previous studies evaluating the effectiveness of TTI strategy on SARS-CoV-2 spreading have presented contrasting results, which could be due to the nature of observation studies and imperfect reflection of characteristics of the disease and interventions including TTI in the analyses. To properly account for the contact patterns, here we propose a novel static-temporal multiplex network model describing the static contacts and temporal contacts encountered in different settings (like households, schools, workplaces or general community), which captures the essential nature of social behavior relevant to transmission risk and enables us to assess the effectiveness of the TTI strategy. Our proposed model suggests that TTI strategy solely could not control the spread of SARS-CoV-2 and it should be combined with other social distancing policy to reduce the overall transmission of SARS-CoV-2. [ABSTRACT FROM AUTHOR]