Lessons Learned From COVID-19 Contact Tracing During a Public Health Emergency: A Prospective Implementation Study

Background: Contact tracing is a core element of the public health response to emerging infectious diseases including COVID-19. Better understanding the implementation context of contact tracing for pandemics, including individual- and systems-level predictors of success, is critical to preparing fo...

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Main Authors: Tyler Shelby, Christopher Schenck, Brian Weeks, Justin Goodwin, Rachel Hennein, Xin Zhou, Donna Spiegelman, Lauretta E. Grau, Linda Niccolai, Maritza Bond, J. Lucian Davis
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-08-01
Series:Frontiers in Public Health
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2021.721952/full
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language English
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author Tyler Shelby
Tyler Shelby
Christopher Schenck
Brian Weeks
Justin Goodwin
Justin Goodwin
Rachel Hennein
Rachel Hennein
Xin Zhou
Xin Zhou
Donna Spiegelman
Donna Spiegelman
Lauretta E. Grau
Linda Niccolai
Maritza Bond
J. Lucian Davis
J. Lucian Davis
J. Lucian Davis
spellingShingle Tyler Shelby
Tyler Shelby
Christopher Schenck
Brian Weeks
Justin Goodwin
Justin Goodwin
Rachel Hennein
Rachel Hennein
Xin Zhou
Xin Zhou
Donna Spiegelman
Donna Spiegelman
Lauretta E. Grau
Linda Niccolai
Maritza Bond
J. Lucian Davis
J. Lucian Davis
J. Lucian Davis
Lessons Learned From COVID-19 Contact Tracing During a Public Health Emergency: A Prospective Implementation Study
Frontiers in Public Health
COVID-19
contact tracing
implementation science
health equity
infectious disease outbreak
author_facet Tyler Shelby
Tyler Shelby
Christopher Schenck
Brian Weeks
Justin Goodwin
Justin Goodwin
Rachel Hennein
Rachel Hennein
Xin Zhou
Xin Zhou
Donna Spiegelman
Donna Spiegelman
Lauretta E. Grau
Linda Niccolai
Maritza Bond
J. Lucian Davis
J. Lucian Davis
J. Lucian Davis
author_sort Tyler Shelby
title Lessons Learned From COVID-19 Contact Tracing During a Public Health Emergency: A Prospective Implementation Study
title_short Lessons Learned From COVID-19 Contact Tracing During a Public Health Emergency: A Prospective Implementation Study
title_full Lessons Learned From COVID-19 Contact Tracing During a Public Health Emergency: A Prospective Implementation Study
title_fullStr Lessons Learned From COVID-19 Contact Tracing During a Public Health Emergency: A Prospective Implementation Study
title_full_unstemmed Lessons Learned From COVID-19 Contact Tracing During a Public Health Emergency: A Prospective Implementation Study
title_sort lessons learned from covid-19 contact tracing during a public health emergency: a prospective implementation study
publisher Frontiers Media S.A.
series Frontiers in Public Health
issn 2296-2565
publishDate 2021-08-01
description Background: Contact tracing is a core element of the public health response to emerging infectious diseases including COVID-19. Better understanding the implementation context of contact tracing for pandemics, including individual- and systems-level predictors of success, is critical to preparing for future epidemics.Methods: We carried out a prospective implementation study of an emergency volunteer contact tracing program established in New Haven, Connecticut between April 4 and May 19, 2020. We assessed the yield and timeliness of case and contact outreach in reference to CDC benchmarks, and identified individual and programmatic predictors of successful implementation using multivariable regression models. We synthesized our findings using the RE-AIM implementation framework.Results: Case investigators interviewed only 826 (48%) of 1,705 cases and were unable to reach 545 (32%) because of incomplete information and 334 (20%) who missed or declined repeated outreach calls. Contact notifiers reached just 687 (28%) of 2,437 reported contacts, and were unable to reach 1,597 (66%) with incomplete information and 153 (6%) who missed or declined repeated outreach calls. The median time-to-case-interview was 5 days and time-to-contact-notification 8 days. However, among notified contacts with complete time data, 457 (71%) were reached within 6 days of exposure. The least likely groups to be interviewed were elderly (adjusted relative risk, aRR 0.74, 95% CI 0.61–0.89, p = 0.012, vs. young adult) and Black/African-American cases (aRR 0.88, 95% CI 0.80–0.97, pairwise p = 0.01, vs. Hispanic/Latinx). However, ties between cases and their contacts strongly influenced contact notification success (Intraclass Correlation Coefficient (ICC) 0.60). Surging caseloads and high volunteer turnover (case investigator n = 144, median time from sign-up to retirement from program was 4 weeks) required the program to supplement the volunteer workforce with paid public health nurses.Conclusions: An emergency volunteer-run contact tracing program fell short of CDC benchmarks for time and yield, largely due to difficulty collecting the information required for outreach to cases and contacts. To improve uptake, contact tracing programs must professionalize the workforce; better integrate testing and tracing services; capitalize on positive social influences between cases and contacts; and address racial and age-related disparities through enhanced community engagement.
topic COVID-19
contact tracing
implementation science
health equity
infectious disease outbreak
url https://www.frontiersin.org/articles/10.3389/fpubh.2021.721952/full
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spelling doaj-a8a3193e0bf4443183fca6e1d3d18fbf2021-08-20T12:45:57ZengFrontiers Media S.A.Frontiers in Public Health2296-25652021-08-01910.3389/fpubh.2021.721952721952Lessons Learned From COVID-19 Contact Tracing During a Public Health Emergency: A Prospective Implementation StudyTyler Shelby0Tyler Shelby1Christopher Schenck2Brian Weeks3Justin Goodwin4Justin Goodwin5Rachel Hennein6Rachel Hennein7Xin Zhou8Xin Zhou9Donna Spiegelman10Donna Spiegelman11Lauretta E. Grau12Linda Niccolai13Maritza Bond14J. Lucian Davis15J. Lucian Davis16J. Lucian Davis17Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, United StatesYale School of Medicine, New Haven, CT, United StatesYale School of Medicine, New Haven, CT, United StatesNew Haven Health Department, New Haven, CT, United StatesDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, United StatesYale School of Medicine, New Haven, CT, United StatesDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, United StatesYale School of Medicine, New Haven, CT, United StatesDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, United StatesCenter for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, United StatesDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, United StatesCenter for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, United StatesDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, United StatesDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, United StatesNew Haven Health Department, New Haven, CT, United StatesDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, United StatesCenter for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, United StatesPulmonary, Critical Care and Sleep Medicine Section, Yale School of Medicine, New Haven, CT, United StatesBackground: Contact tracing is a core element of the public health response to emerging infectious diseases including COVID-19. Better understanding the implementation context of contact tracing for pandemics, including individual- and systems-level predictors of success, is critical to preparing for future epidemics.Methods: We carried out a prospective implementation study of an emergency volunteer contact tracing program established in New Haven, Connecticut between April 4 and May 19, 2020. We assessed the yield and timeliness of case and contact outreach in reference to CDC benchmarks, and identified individual and programmatic predictors of successful implementation using multivariable regression models. We synthesized our findings using the RE-AIM implementation framework.Results: Case investigators interviewed only 826 (48%) of 1,705 cases and were unable to reach 545 (32%) because of incomplete information and 334 (20%) who missed or declined repeated outreach calls. Contact notifiers reached just 687 (28%) of 2,437 reported contacts, and were unable to reach 1,597 (66%) with incomplete information and 153 (6%) who missed or declined repeated outreach calls. The median time-to-case-interview was 5 days and time-to-contact-notification 8 days. However, among notified contacts with complete time data, 457 (71%) were reached within 6 days of exposure. The least likely groups to be interviewed were elderly (adjusted relative risk, aRR 0.74, 95% CI 0.61–0.89, p = 0.012, vs. young adult) and Black/African-American cases (aRR 0.88, 95% CI 0.80–0.97, pairwise p = 0.01, vs. Hispanic/Latinx). However, ties between cases and their contacts strongly influenced contact notification success (Intraclass Correlation Coefficient (ICC) 0.60). Surging caseloads and high volunteer turnover (case investigator n = 144, median time from sign-up to retirement from program was 4 weeks) required the program to supplement the volunteer workforce with paid public health nurses.Conclusions: An emergency volunteer-run contact tracing program fell short of CDC benchmarks for time and yield, largely due to difficulty collecting the information required for outreach to cases and contacts. To improve uptake, contact tracing programs must professionalize the workforce; better integrate testing and tracing services; capitalize on positive social influences between cases and contacts; and address racial and age-related disparities through enhanced community engagement.https://www.frontiersin.org/articles/10.3389/fpubh.2021.721952/fullCOVID-19contact tracingimplementation sciencehealth equityinfectious disease outbreak