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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Frontiers Media S.A.
2021-08-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2021.721952/full |
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Article |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
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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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 |