Abstract

Case investigation and contact tracing (CICT) are public health measures that aim to break the chain of pathogen transmission. Changes in viral characteristics of COVID-19 variants have likely affected the effectiveness of CICT programs. We estimated and compared the cases averted in Vermont when the original COVID-19 strain circulated (Nov. 25, 2020–Jan. 19, 2021) with two periods when the Delta strain dominated (Aug. 1–Sept. 25, 2021, and Sept. 26–Nov. 20, 2021). When the original strain circulated, we estimated that CICT prevented 7180 cases (55% reduction in disease burden), compared to 1437 (15% reduction) and 9970 cases (40% reduction) when the Delta strain circulated. Despite the Delta variant being more infectious and having a shorter latency period, CICT remained an effective tool to slow spread of COVID-19; while these viral characteristics did diminish CICT effectiveness, non-viral characteristics had a much greater impact on CICT effectiveness.

Details

Title
The public health impact of COVID-19 variants of concern on the effectiveness of contact tracing in Vermont, United States
Author
Castonguay, François M. 1 ; Borah, Brian F. 2 ; Jeon, Seonghye 3 ; Rainisch, Gabriel 3 ; Kelso, Patsy 4 ; Adhikari, Bishwa B. 3 ; Daltry, Daniel J. 4 ; Fischer, Leah S. 3 ; Greening, Bradford 3 ; Kahn, Emily B. 3 ; Kang, Gloria J. 3 ; Meltzer, Martin I. 3 

 U.S. Department of Health and Human Services, National Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Health Economics and Modeling Unit, Centers for Disease Control and Prevention, Atlanta, USA (GRID:grid.27235.31); Department of Health and Human Services, Modeling Support Team, Contact Tracing and Innovation Section (CTIS), State Local Tribal and Territorial (STLT) Task Force, CDC COVID-19 Response; Centers for Disease Control and Prevention, Atlanta, USA (GRID:grid.27235.31); University of Montreal School of Public Health, and Centre for Public Health Research – CReSP, Department of Health Management, Evaluation and Policy, Montréal, Canada (GRID:grid.14848.31) (ISNI:0000 0001 2104 2136) 
 Vermont Department of Health, Burlington, USA (GRID:grid.422196.a) (ISNI:0000 0004 0382 6238); U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Epidemic Intelligence Service, Atlanta, USA (GRID:grid.416738.f) (ISNI:0000 0001 2163 0069) 
 U.S. Department of Health and Human Services, National Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Health Economics and Modeling Unit, Centers for Disease Control and Prevention, Atlanta, USA (GRID:grid.27235.31); Department of Health and Human Services, Modeling Support Team, Contact Tracing and Innovation Section (CTIS), State Local Tribal and Territorial (STLT) Task Force, CDC COVID-19 Response; Centers for Disease Control and Prevention, Atlanta, USA (GRID:grid.27235.31) 
 Vermont Department of Health, Burlington, USA (GRID:grid.422196.a) (ISNI:0000 0004 0382 6238) 
Pages
17848
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3087040953
Copyright
© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.