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Castonguay FM, Barnes A, Jeon S, Fornoff J, Adhikari BB, Fischer LS, Greening B, Hassan AO, Kahn EB, Kang GJ, Kauerauf J, Patrick S, Vohra S, Meltzer MI. Estimated public health impact of concurrent mask mandate and vaccinate-or-test requirement in Illinois, October to December 2021. BMC Public Health 2024; 24:1013. [PMID: 38609903 PMCID: PMC11010411 DOI: 10.1186/s12889-024-18203-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 02/24/2024] [Indexed: 04/14/2024] Open
Abstract
BACKGROUND Facing a surge of COVID-19 cases in late August 2021, the U.S. state of Illinois re-enacted its COVID-19 mask mandate for the general public and issued a requirement for workers in certain professions to be vaccinated against COVID-19 or undergo weekly testing. The mask mandate required any individual, regardless of their vaccination status, to wear a well-fitting mask in an indoor setting. METHODS We used Illinois Department of Public Health's COVID-19 confirmed case and vaccination data and investigated scenarios where masking and vaccination would have been reduced to mimic what would have happened had the mask mandate or vaccine requirement not been put in place. The study examined a range of potential reductions in masking and vaccination mimicking potential scenarios had the mask mandate or vaccine requirement not been enacted. We estimated COVID-19 cases and hospitalizations averted by changes in masking and vaccination during the period covering October 20 to December 20, 2021. RESULTS We find that the announcement and implementation of a mask mandate are likely to correlate with a strong protective effect at reducing COVID-19 burden and the announcement of a vaccinate-or-test requirement among frontline professionals is likely to correlate with a more modest protective effect at reducing COVID-19 burden. In our most conservative scenario, we estimated that from the period of October 20 to December 20, 2021, the mask mandate likely prevented approximately 58,000 cases and 1,175 hospitalizations, while the vaccinate-or-test requirement may have prevented at most approximately 24,000 cases and 475 hospitalizations. CONCLUSION Our results indicate that mask mandates and vaccine-or-test requirements are vital in mitigating the burden of COVID-19 during surges of the virus.
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Affiliation(s)
- François M Castonguay
- National Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Centers for Disease Control and Prevention, Health Economics and Modeling Unit, U.S. Department of Health and Human Services, 7101 Avenue du Parc, Local 3180, QC H3N 1X9, Atlanta, Georgia.
- Contact Tracing and Innovation Section (CTIS), State Tribal Local and Territorial (STLT) Task Force, CDC COVID-19 Response; Centers for Disease Control and Prevention, Modeling Support Team, U.S. Department of Health and Human Services, Atlanta, Georgia.
- Department of Health Management, Evaluation and Policy, University of Montreal School of Public Health, and Centre for Public Health Research - CReSP, 7101 Av du Parc, 3E Étage, Montréal, QC, H3N 1X9, Canada.
| | - Arti Barnes
- Illinois Department of Public Health, Springfield, IL, USA
| | - Seonghye Jeon
- National Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Centers for Disease Control and Prevention, Health Economics and Modeling Unit, U.S. Department of Health and Human Services, 7101 Avenue du Parc, Local 3180, QC H3N 1X9, Atlanta, Georgia
- Contact Tracing and Innovation Section (CTIS), State Tribal Local and Territorial (STLT) Task Force, CDC COVID-19 Response; Centers for Disease Control and Prevention, Modeling Support Team, U.S. Department of Health and Human Services, Atlanta, Georgia
| | - Jane Fornoff
- Illinois Department of Public Health, Springfield, IL, USA
| | - Bishwa B Adhikari
- National Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Centers for Disease Control and Prevention, Health Economics and Modeling Unit, U.S. Department of Health and Human Services, 7101 Avenue du Parc, Local 3180, QC H3N 1X9, Atlanta, Georgia
- Contact Tracing and Innovation Section (CTIS), State Tribal Local and Territorial (STLT) Task Force, CDC COVID-19 Response; Centers for Disease Control and Prevention, Modeling Support Team, U.S. Department of Health and Human Services, Atlanta, Georgia
| | - Leah S Fischer
- National Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Centers for Disease Control and Prevention, Health Economics and Modeling Unit, U.S. Department of Health and Human Services, 7101 Avenue du Parc, Local 3180, QC H3N 1X9, Atlanta, Georgia
- Contact Tracing and Innovation Section (CTIS), State Tribal Local and Territorial (STLT) Task Force, CDC COVID-19 Response; Centers for Disease Control and Prevention, Modeling Support Team, U.S. Department of Health and Human Services, Atlanta, Georgia
| | - Bradford Greening
- National Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Centers for Disease Control and Prevention, Health Economics and Modeling Unit, U.S. Department of Health and Human Services, 7101 Avenue du Parc, Local 3180, QC H3N 1X9, Atlanta, Georgia
- Contact Tracing and Innovation Section (CTIS), State Tribal Local and Territorial (STLT) Task Force, CDC COVID-19 Response; Centers for Disease Control and Prevention, Modeling Support Team, U.S. Department of Health and Human Services, Atlanta, Georgia
| | | | - Emily B Kahn
- National Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Centers for Disease Control and Prevention, Health Economics and Modeling Unit, U.S. Department of Health and Human Services, 7101 Avenue du Parc, Local 3180, QC H3N 1X9, Atlanta, Georgia
- Contact Tracing and Innovation Section (CTIS), State Tribal Local and Territorial (STLT) Task Force, CDC COVID-19 Response; Centers for Disease Control and Prevention, Modeling Support Team, U.S. Department of Health and Human Services, Atlanta, Georgia
| | - Gloria J Kang
- National Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Centers for Disease Control and Prevention, Health Economics and Modeling Unit, U.S. Department of Health and Human Services, 7101 Avenue du Parc, Local 3180, QC H3N 1X9, Atlanta, Georgia
- Contact Tracing and Innovation Section (CTIS), State Tribal Local and Territorial (STLT) Task Force, CDC COVID-19 Response; Centers for Disease Control and Prevention, Modeling Support Team, U.S. Department of Health and Human Services, Atlanta, Georgia
| | - Judy Kauerauf
- Illinois Department of Public Health, Springfield, IL, USA
| | - Sarah Patrick
- Illinois Department of Public Health, Springfield, IL, USA
| | - Sameer Vohra
- Illinois Department of Public Health, Springfield, IL, USA
| | - Martin I Meltzer
- National Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Centers for Disease Control and Prevention, Health Economics and Modeling Unit, U.S. Department of Health and Human Services, 7101 Avenue du Parc, Local 3180, QC H3N 1X9, Atlanta, Georgia
- Contact Tracing and Innovation Section (CTIS), State Tribal Local and Territorial (STLT) Task Force, CDC COVID-19 Response; Centers for Disease Control and Prevention, Modeling Support Team, U.S. Department of Health and Human Services, Atlanta, Georgia
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He K, Foerster S, Vora NM, Blaney K, Keeley C, Hendricks L, Varma JK, Long T, Shaman J, Pei S. Evaluating completion rates of COVID-19 contact tracing surveys in New York City. BMC Public Health 2024; 24:414. [PMID: 38331772 PMCID: PMC10854191 DOI: 10.1186/s12889-024-17920-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 01/29/2024] [Indexed: 02/10/2024] Open
Abstract
IMPORTANCE Contact tracing is the process of identifying people who have recently been in contact with someone diagnosed with an infectious disease. During an outbreak, data collected from contact tracing can inform interventions to reduce the spread of infectious diseases. Understanding factors associated with completion rates of contact tracing surveys can help design improved interview protocols for ongoing and future programs. OBJECTIVE To identify factors associated with completion rates of COVID-19 contact tracing surveys in New York City (NYC) and evaluate the utility of a predictive model to improve completion rates, we analyze laboratory-confirmed and probable COVID-19 cases and their self-reported contacts in NYC from October 1st 2020 to May 10th 2021. METHODS We analyzed 742,807 case investigation calls made during the study period. Using a log-binomial regression model, we examined the impact of age, time of day of phone call, and zip code-level demographic and socioeconomic factors on interview completion rates. We further developed a random forest model to predict the best phone call time and performed a counterfactual analysis to evaluate the change of completion rates if the predicative model were used. RESULTS The percentage of contact tracing surveys that were completed was 79.4%, with substantial variations across ZIP code areas. Using a log-binomial regression model, we found that the age of index case (an individual who has tested positive through PCR or antigen testing and is thus subjected to a case investigation) had a significant effect on the completion of case investigation - compared with young adults (the reference group,24 years old < age < = 65 years old), the completion rate for seniors (age > 65 years old) were lower by 12.1% (95%CI: 11.1% - 13.3%), and the completion rate for youth group (age < = 24 years old) were lower by 1.6% (95%CI: 0.6% -2.6%). In addition, phone calls made from 6 to 9 pm had a 4.1% (95% CI: 1.8% - 6.3%) higher completion rate compared with the reference group of phone calls attempted from 12 and 3 pm. We further used a random forest algorithm to assess its potential utility for selecting the time of day of phone call. In counterfactual simulations, the overall completion rate in NYC was marginally improved by 1.2%; however, certain ZIP code areas had improvements up to 7.8%. CONCLUSION These findings suggest that age and time of day of phone call were associated with completion rates of case investigations. It is possible to develop predictive models to estimate better phone call time for improving completion rates in certain communities.
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Affiliation(s)
- Kaiyu He
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, 10032, USA
| | - Steffen Foerster
- New York City Department of Health and Mental Hygiene (DOHMH), Long Island City, NY, 11001, USA
| | - Neil M Vora
- New York City Department of Health and Mental Hygiene (DOHMH), Long Island City, NY, 11001, USA
| | - Kathleen Blaney
- New York City Department of Health and Mental Hygiene (DOHMH), Long Island City, NY, 11001, USA
| | | | | | - Jay K Varma
- Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, 10065, USA
| | - Theodore Long
- NYC Health + Hospitals, New York, NY, USA
- Department of Population Health, New York University, New York, NY, 10016, USA
| | - Jeffrey Shaman
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, 10032, USA
- Columbia Climate School, Columbia University, New York, NY, 10025, USA
| | - Sen Pei
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, 10032, USA.
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Jeon S, Watson-Lewis L, Rainisch G, Chiu CC, Castonguay FM, Fischer LS, Moonan PK, Oeltmann JE, Adhikari BB, Lawman H, Meltzer MI. Adapting COVID-19 Contact Tracing Protocols to Accommodate Resource Constraints, Philadelphia, Pennsylvania, USA, 2021. Emerg Infect Dis 2024; 30:333-336. [PMID: 38181801 PMCID: PMC10826771 DOI: 10.3201/eid3002.230988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2024] Open
Abstract
Because of constrained personnel time, the Philadelphia Department of Public Health (Philadelphia, PA, USA) adjusted its COVID-19 contact tracing protocol in summer 2021 by prioritizing recent cases and limiting staff time per case. This action reduced required staff hours to prevent each case from 21-30 to 8-11 hours, while maintaining program effectiveness.
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Affiliation(s)
| | | | - Gabriel Rainisch
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA (S. Jeon, G. Rainisch, F.M. Castonguay, L.S. Fischer, P.K. Moonan, J.E. Oeltmann, B.B. Adhikari, M.I. Meltzer)
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania, USA (L. Watson-Lewis, C.-C. Chiu, H. Lawman)
- University of Montreal School of Public Health, Montreal, Quebec, Canada (F.M. Castonguay)
| | - Chu-Chuan Chiu
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA (S. Jeon, G. Rainisch, F.M. Castonguay, L.S. Fischer, P.K. Moonan, J.E. Oeltmann, B.B. Adhikari, M.I. Meltzer)
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania, USA (L. Watson-Lewis, C.-C. Chiu, H. Lawman)
- University of Montreal School of Public Health, Montreal, Quebec, Canada (F.M. Castonguay)
| | - François M. Castonguay
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA (S. Jeon, G. Rainisch, F.M. Castonguay, L.S. Fischer, P.K. Moonan, J.E. Oeltmann, B.B. Adhikari, M.I. Meltzer)
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania, USA (L. Watson-Lewis, C.-C. Chiu, H. Lawman)
- University of Montreal School of Public Health, Montreal, Quebec, Canada (F.M. Castonguay)
| | - Leah S. Fischer
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA (S. Jeon, G. Rainisch, F.M. Castonguay, L.S. Fischer, P.K. Moonan, J.E. Oeltmann, B.B. Adhikari, M.I. Meltzer)
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania, USA (L. Watson-Lewis, C.-C. Chiu, H. Lawman)
- University of Montreal School of Public Health, Montreal, Quebec, Canada (F.M. Castonguay)
| | - Patrick K. Moonan
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA (S. Jeon, G. Rainisch, F.M. Castonguay, L.S. Fischer, P.K. Moonan, J.E. Oeltmann, B.B. Adhikari, M.I. Meltzer)
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania, USA (L. Watson-Lewis, C.-C. Chiu, H. Lawman)
- University of Montreal School of Public Health, Montreal, Quebec, Canada (F.M. Castonguay)
| | - John E. Oeltmann
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA (S. Jeon, G. Rainisch, F.M. Castonguay, L.S. Fischer, P.K. Moonan, J.E. Oeltmann, B.B. Adhikari, M.I. Meltzer)
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania, USA (L. Watson-Lewis, C.-C. Chiu, H. Lawman)
- University of Montreal School of Public Health, Montreal, Quebec, Canada (F.M. Castonguay)
| | - Bishwa B. Adhikari
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA (S. Jeon, G. Rainisch, F.M. Castonguay, L.S. Fischer, P.K. Moonan, J.E. Oeltmann, B.B. Adhikari, M.I. Meltzer)
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania, USA (L. Watson-Lewis, C.-C. Chiu, H. Lawman)
- University of Montreal School of Public Health, Montreal, Quebec, Canada (F.M. Castonguay)
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Castonguay FM, Chesson HW, Jeon S, Rainisch G, Fischer LS, Adhikari BB, Kahn EB, Greening B, Gift TL, Meltzer MI. Building a Simple Model to Assess the Impact of Case Investigation and Contact Tracing for Sexually Transmitted Diseases: Lessons From COVID-19. AJPM FOCUS 2024; 3:100147. [PMID: 38149077 PMCID: PMC10749878 DOI: 10.1016/j.focus.2023.100147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/28/2023]
Abstract
Introduction During the COVID-19 pandemic, the U.S. Centers for Disease Control and Prevention developed a simple spreadsheet-based tool to help state and local public health officials assess the performance and impact of COVID-19 case investigation and contact tracing in their jurisdiction. The applicability and feasibility of building such a tool for sexually transmitted diseases were assessed. Methods The key epidemiologic differences between sexually transmitted diseases and respiratory diseases (e.g., mixing patterns, incubation period, duration of infection, and the availability of treatment) were identified, and their implications for modeling case investigation and contact tracing impact with a simple spreadsheet tool were remarked on. Existing features of the COVID-19 tool that are applicable for evaluating the impact of case investigation and contact tracing for sexually transmitted diseases were also identified. Results Our findings offer recommendations for the future development of a spreadsheet-based modeling tool for evaluating the impact of sexually transmitted disease case investigation and contact tracing efforts. Generally, we advocate for simplifying sexually transmitted disease-specific complexities and performing sensitivity analyses to assess uncertainty. The authors also acknowledge that more complex modeling approaches might be required but note that it is possible that a sexually transmitted disease case investigation and contact tracing tool could incorporate features from more complex models while maintaining a user-friendly interface. Conclusions A sexually transmitted disease case investigation and contact tracing tool could benefit from the incorporation of key features of the COVID-19 model, namely its user-friendly interface. The inherent differences between sexually transmitted diseases and respiratory viruses should not be seen as a limitation to the development of such tool.
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Affiliation(s)
- François M. Castonguay
- Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
- Department of Health Management, Evaluation and Policy, School of Public Health, University of Montréal, Montréal, Québec, Canada
- Centre for Public Health Research (CReSP), Montréal, Québec, Canada
| | - Harrell W. Chesson
- National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Division of STD Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Seonghye Jeon
- Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Gabriel Rainisch
- Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Leah S. Fischer
- Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Biswha B. Adhikari
- Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Emily B. Kahn
- Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Bradford Greening
- Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Thomas L. Gift
- National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Division of STD Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Martin I. Meltzer
- Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
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Hijano DR, Dennis SR, Hoffman JM, Tang L, Hayden RT, Gaur AH, Hakim H. Employee investigation and contact tracing program in a pediatric cancer hospital to mitigate the spread of COVID-19 among the workforce, patients, and caregivers. Front Public Health 2024; 11:1304072. [PMID: 38259752 PMCID: PMC10801179 DOI: 10.3389/fpubh.2023.1304072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Background Case investigations and contact tracing are essential disease control measures used by health departments. Early in the pandemic, they were seen as a key strategy to stop COVID-19 spread. The CDC urged rapid action to scale up and train a large workforce and collaborate across public and private agencies to halt COVID-19 transmission. Methods We developed a program for case investigation and contact tracing that followed CDC and local health guidelines, compliant with the Occupational Safety and Health Administration (OSHA) regulations and tailored to the needs and resources of our institution. Program staff were trained and assessed for competency before joining the program. Results From March 2020 to May 2021, we performed 838 COVID-19 case investigations, which led to 136 contacts. Most employees reported a known SARS-CoV-2 exposure from the community (n = 435) or household (n = 343). Only seven (5.1%) employees were determined as more likely than not to have SARS-CoV-2 infection related to workplace exposure, and when so, lapses in following the masking recommendations were identified. Between June 2021-February 2022, our program adjusted to the demand of the different waves, particularly omicron, by significantly reducing the amount of data collected. No transmission from employees to patients or caregivers was observed during this period. Conclusion Prompt implementation of case investigation and contact tracing is possible, and it effectively reduces workplace exposures. This approach can be adapted to suit the specific needs and requirements of various healthcare settings, particularly those serving the most vulnerable patient populations.
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Affiliation(s)
- Diego R. Hijano
- Departments of Infectious Diseases, St. Jude Children’s Research Hospital, Memphis, TN, United States
- Department of Pediatrics, University of Tennessee Health Sciences Center, Memphis, TN, United States
| | - Sandra R. Dennis
- Department of Human Resources, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - James M. Hoffman
- Department of Human Resources, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Li Tang
- Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Randall T. Hayden
- Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | | | - Aditya H. Gaur
- Departments of Infectious Diseases, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Hana Hakim
- Office of Quality and Patient Safety, St. Jude Children’s Research Hospital, Memphis, TN, United States
- Department of Preventive Medicine, University of Tennessee Health Sciences Center, Memphis, TN, United States
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Woodward A, Rivers C. Building Case Investigation and Contact Tracing Programs in US State and Local Health Departments: A Conceptual Framework. Disaster Med Public Health Prep 2023; 17:e540. [PMID: 38031272 DOI: 10.1017/dmp.2023.205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
OBJECTIVE At the onset of the COVID-19 pandemic, and to this day, US state, tribal, local, and territorial health departments lacked comprehensive case investigation and contact tracing (CI/CT) guidelines that clearly define the capabilities and capacities of CI/CT programs and how to scale up these programs to respond to outbreaks. This research aims to identify the capabilities and capacities of CI/CT programs and to develop a conceptual framework that represents the relationships between these program components. METHODS This study conducted a narrative literature review and qualitative interviews with 10 US state and local health departments and 4 public health experts to identify and characterize the capacities and capabilities of CI/CT programs. RESULTS This research resulted in the first comprehensive analysis of the capabilities and capacities of CI/CT programs and a conceptual framework that illustrates the interrelationships between the capacities, capabilities, outcomes, and impacts of CI/CT programs. CONCLUSIONS Our findings highlight the need for further guidance to assist jurisdictional health departments in shifting CI/CT program goals as outbreaks evolve. Training the public health workforce on making decisions around CI/CT program implementation during outbreaks is critical to ensure readiness for a variety of outbreak scenarios.
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Affiliation(s)
- Alexandra Woodward
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Johns Hopkins Center for Health Security, Baltimore, MD, USA
| | - Caitlin Rivers
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Johns Hopkins Center for Health Security, Baltimore, MD, USA
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Dorabawila V, Maduka D, Barnes V, Ramesh N, Hoefer D. Contact tracing: Characteristics of COVID-19 cases that provided contacts. PLoS One 2023; 18:e0293208. [PMID: 37917769 PMCID: PMC10621982 DOI: 10.1371/journal.pone.0293208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 10/08/2023] [Indexed: 11/04/2023] Open
Abstract
This cross-sectional study evaluated COVID-19 contact tracing efforts to identify variations in contact tracing outcomes in different population subgroups. Contact tracing was a critical tool to slow the COVID-19 epidemic. A literature gap evaluating contact tracing elicitation exits, particularly on prioritized groups. We analyzed data from COVID-19 cases linking statewide case management, immunization, laboratory testing, and hospitalization databases in New York State (NYS) outside of New York City from February 1 to November 30, 2021. Focus was cases in home-based residential settings (excluding congregate care) and prioritized groups (educational institutions, large households, close quarters, higher-risk persons, hospitalized). The primary outcome was completed interviews that provided a contact. Of the 550,850 cases interviewed during the study period, 316,645 (57.5%) provided at least one contact. Adults aged 18 to 49 years were most likely to provide contacts than those aged 65 years and older (adjusted odds ratio [aOR], 1.42; 95% confidence interval [CI], 1.39-1.45). Compared to unvaccinated cases, boosted individuals (aOR, 1.61; 95% CI, 1.50-1.73) were most likely to provide contacts, followed by persons with only a primary vaccine series (aOR, 1.3; 95%CI, 1.28-1.33) and partially vaccinated (aOR, 1.21; 95%CI, 1.18-1.24). Repeat cases (aOR, 1.07; 95%CI, 1.01-1.14), pregnant persons (aOR, 1.26; 95% CI, 1,19-1.34), those with underlying conditions (aOR 1.22; 95%CI, 1.20-1.23), and those in K-12 settings (aOR 1.55; 95%CI, 1.50-1.61) were more likely to provide contacts. There was no clear association between hospitalized, while zip code level income may (aOR, 1.006; 95%CI, 1.003, 1.009). Persons from larger households were more likely to provide contacts: aOR for two or more persons vs. one person households ranged from 2.49 to 4.7 (95%CI, 2.20-4.78). Our findings indicate success in eliciting contacts from prioritized groups and identify variable contact elicitation outcomes from different population groups. These results may serve as a tool for future contact tracing efforts.
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Affiliation(s)
- Vajeera Dorabawila
- Bureau of Surveillance and Data Systems, New York State Department of Health, Albany, New York, United States of America
| | - Doris Maduka
- Bureau of Surveillance and Data Systems, New York State Department of Health, Albany, New York, United States of America
| | - Virgile Barnes
- Bureau of Surveillance and Data Systems, New York State Department of Health, Albany, New York, United States of America
| | - Nirmala Ramesh
- Bureau of Surveillance and Data Systems, New York State Department of Health, Albany, New York, United States of America
| | - Dina Hoefer
- Bureau of Surveillance and Data Systems, New York State Department of Health, Albany, New York, United States of America
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Udeagu CCN, Gbedemah M, Pitiranggon M, Feldman S, Cordoba E, Goldenberg S, Keeley C, Blaney K, Vora NM, Long T. Integrating Contact Tracers Into Point-of-Care Testing Workflow to Accelerate the Tracing of People With Exposure to COVID-19, August-December 2020, New York City. JOURNAL OF PUBLIC HEALTH MANAGEMENT AND PRACTICE 2023; 29:708-717. [PMID: 37290128 PMCID: PMC10373849 DOI: 10.1097/phh.0000000000001748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
OBJECTIVES We assessed the timeliness of contact tracing following rapid-positive COVID-19 test result at point-of-care testing (POCT) sites in New York City (NYC). DESIGN Interviewed case-patients to elicit exposed contacts and conducted COVID-19 exposure notifications. SETTINGS Twenty-two COVID-19 POCT sites in NYC, the 2 NYC international airports, and 1 ferry terminal. PARTICIPANTS Case-patients with rapid-positive COVID-19 test results and their named contacts. MAIN OUTCOME MEASURES We quantified the proportions of interviewed individuals with COVID-19 and notified contacts and assessed the timeliness between the dates of the rapid-positive COVID-19 test results and the interviews or notifications. RESULTS In total, 11 683 individuals with rapid-positive COVID-19 test results were referred for contact tracing on the day of their diagnosis; 8878 (76) of whom were interviewed within 1 day of diagnosis, of whom 5499 (62%) named 11 486 contacts. A median of 1.24 contacts were identified from each interview. The odds of eliciting contacts were significantly higher among individuals reporting COVID-19 symptoms than among persons with no symptoms (51% vs 36%; adjusted odds ratio [aOR] = 1.37; 95% confidence interval [CI], 1.11-1.70) or living with 1 or more persons than living alone (89% vs 38%; aOR = 12.11; 95% CI, 10.73-13.68). Among the 8878 interviewed case-patients, 8317 (94%) were interviewed within 1 day of their rapid-positive COVID-19 test results and 91% of contact notifications were completed within 1 day of contact identification. The median interval from test result to interview date and from case investigation interview to contact notification were both 0 days (IQR = 0). CONCLUSIONS The integration of contact tracers into COVID-19 POCT workflow achieved timely case investigation and contact notification. Accelerated contact tracing can be used to curb COVID-19 transmission during local outbreaks.
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Affiliation(s)
- Chi-Chi N. Udeagu
- New York City Department of Health and Mental Hygiene, Queens, New York (Mss Udeagu, Pitiranggon, and Blaney and Dr Vora); New York City Test & Trace Corps, New York City, New York (Mss Udeagu, Gbedemah, Pitiranggon, Feldman, Goldenberg, Keeley, and Blaney and Drs Cordoba, Vora, and Long); and New York City Health + Hospitals Corporation, New York City, New York (Mss Gbedemah, Feldman, Goldenberg, and Keeley and Drs Cordoba and Long)
| | - Misato Gbedemah
- New York City Department of Health and Mental Hygiene, Queens, New York (Mss Udeagu, Pitiranggon, and Blaney and Dr Vora); New York City Test & Trace Corps, New York City, New York (Mss Udeagu, Gbedemah, Pitiranggon, Feldman, Goldenberg, Keeley, and Blaney and Drs Cordoba, Vora, and Long); and New York City Health + Hospitals Corporation, New York City, New York (Mss Gbedemah, Feldman, Goldenberg, and Keeley and Drs Cordoba and Long)
| | - Masha Pitiranggon
- New York City Department of Health and Mental Hygiene, Queens, New York (Mss Udeagu, Pitiranggon, and Blaney and Dr Vora); New York City Test & Trace Corps, New York City, New York (Mss Udeagu, Gbedemah, Pitiranggon, Feldman, Goldenberg, Keeley, and Blaney and Drs Cordoba, Vora, and Long); and New York City Health + Hospitals Corporation, New York City, New York (Mss Gbedemah, Feldman, Goldenberg, and Keeley and Drs Cordoba and Long)
| | - Samantha Feldman
- New York City Department of Health and Mental Hygiene, Queens, New York (Mss Udeagu, Pitiranggon, and Blaney and Dr Vora); New York City Test & Trace Corps, New York City, New York (Mss Udeagu, Gbedemah, Pitiranggon, Feldman, Goldenberg, Keeley, and Blaney and Drs Cordoba, Vora, and Long); and New York City Health + Hospitals Corporation, New York City, New York (Mss Gbedemah, Feldman, Goldenberg, and Keeley and Drs Cordoba and Long)
| | - Evette Cordoba
- New York City Department of Health and Mental Hygiene, Queens, New York (Mss Udeagu, Pitiranggon, and Blaney and Dr Vora); New York City Test & Trace Corps, New York City, New York (Mss Udeagu, Gbedemah, Pitiranggon, Feldman, Goldenberg, Keeley, and Blaney and Drs Cordoba, Vora, and Long); and New York City Health + Hospitals Corporation, New York City, New York (Mss Gbedemah, Feldman, Goldenberg, and Keeley and Drs Cordoba and Long)
| | - Shifra Goldenberg
- New York City Department of Health and Mental Hygiene, Queens, New York (Mss Udeagu, Pitiranggon, and Blaney and Dr Vora); New York City Test & Trace Corps, New York City, New York (Mss Udeagu, Gbedemah, Pitiranggon, Feldman, Goldenberg, Keeley, and Blaney and Drs Cordoba, Vora, and Long); and New York City Health + Hospitals Corporation, New York City, New York (Mss Gbedemah, Feldman, Goldenberg, and Keeley and Drs Cordoba and Long)
| | - Chris Keeley
- New York City Department of Health and Mental Hygiene, Queens, New York (Mss Udeagu, Pitiranggon, and Blaney and Dr Vora); New York City Test & Trace Corps, New York City, New York (Mss Udeagu, Gbedemah, Pitiranggon, Feldman, Goldenberg, Keeley, and Blaney and Drs Cordoba, Vora, and Long); and New York City Health + Hospitals Corporation, New York City, New York (Mss Gbedemah, Feldman, Goldenberg, and Keeley and Drs Cordoba and Long)
| | - Kathleen Blaney
- New York City Department of Health and Mental Hygiene, Queens, New York (Mss Udeagu, Pitiranggon, and Blaney and Dr Vora); New York City Test & Trace Corps, New York City, New York (Mss Udeagu, Gbedemah, Pitiranggon, Feldman, Goldenberg, Keeley, and Blaney and Drs Cordoba, Vora, and Long); and New York City Health + Hospitals Corporation, New York City, New York (Mss Gbedemah, Feldman, Goldenberg, and Keeley and Drs Cordoba and Long)
| | - Neil M. Vora
- New York City Department of Health and Mental Hygiene, Queens, New York (Mss Udeagu, Pitiranggon, and Blaney and Dr Vora); New York City Test & Trace Corps, New York City, New York (Mss Udeagu, Gbedemah, Pitiranggon, Feldman, Goldenberg, Keeley, and Blaney and Drs Cordoba, Vora, and Long); and New York City Health + Hospitals Corporation, New York City, New York (Mss Gbedemah, Feldman, Goldenberg, and Keeley and Drs Cordoba and Long)
| | - Theodore Long
- New York City Department of Health and Mental Hygiene, Queens, New York (Mss Udeagu, Pitiranggon, and Blaney and Dr Vora); New York City Test & Trace Corps, New York City, New York (Mss Udeagu, Gbedemah, Pitiranggon, Feldman, Goldenberg, Keeley, and Blaney and Drs Cordoba, Vora, and Long); and New York City Health + Hospitals Corporation, New York City, New York (Mss Gbedemah, Feldman, Goldenberg, and Keeley and Drs Cordoba and Long)
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9
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Oeltmann JE, Vohra D, Matulewicz HH, DeLuca N, Smith JP, Couzens C, Lash RR, Harvey B, Boyette M, Edwards A, Talboy PM, Dubose O, Regan P, Loosier P, Caruso E, Katz DJ, Taylor MM, Moonan PK. Isolation and Quarantine for Coronavirus Disease 2019 in the United States, 2020-2022. Clin Infect Dis 2023; 77:212-219. [PMID: 36947142 PMCID: PMC11094624 DOI: 10.1093/cid/ciad163] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 02/21/2023] [Accepted: 03/17/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Public health programs varied in ability to reach people with coronavirus disease 2019 (COVID-19) and their contacts to encourage separation from others. For both adult case patients with COVID-19 and their contacts, we estimated the impact of contact tracing activities on separation behaviors from January 2020 until March 2022. METHODS We used a probability-based panel survey of a nationally representative sample to gather data for estimates and comparisons. RESULTS An estimated 64 255 351 adults reported a positive severe acute respiratory syndrome coronavirus 2 test result; 79.6% isolated for ≥5 days, 60.2% isolated for ≥10 days, and 79.2% self-notified contacts. A total of, 24 057 139 (37.7%) completed a case investigation, and 46.2% of them reported contacts to health officials. More adults who completed a case investigation isolated than those who did not complete a case investigation (≥5 days, 82.6% vs 78.2%, respectively; ≥10 days, 69.8% vs 54.8%; both P < .05). A total of 84 946 636 adults were contacts of a COVID-19 case patient. Of these, 73.1% learned of their exposure directly from a case patient; 49.4% quarantined for ≥5 days, 18.7% quarantined for ≥14 days, and 13.5% completed a contact tracing call. More quarantined among those who completed a contact tracing call than among those who did not complete a tracing call (≥5 days, 61.2% vs 48.5%, respectively; ≥14 days, 25.2% vs 18.0%; both P < .05). CONCLUSIONS Engagement in contact tracing was positively correlated with isolation and quarantine. However, most adults with COVID-19 isolated and self-notified contacts regardless of whether the public health workforce was able to reach them. Identifying and reaching contacts was challenging and limited the ability to promote quarantining, and testing.
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Affiliation(s)
- John E Oeltmann
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Divya Vohra
- Health Division, Mathematica, Princeton, New Jersey, USA
| | | | - Nickolas DeLuca
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Jonathan P Smith
- School of Public Health, Yale University, New Haven, Connecticut, USA
| | | | - R Ryan Lash
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Barrington Harvey
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Melissa Boyette
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Alicia Edwards
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Philip M Talboy
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Odessa Dubose
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Paul Regan
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Penny Loosier
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Elise Caruso
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Dolores J Katz
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Melanie M Taylor
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
| | - Patrick K Moonan
- US Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, Georgia, USA
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10
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Büchler AC, Shahab SN, Severin JA, Vos MC, Voor In 't Holt AF. Outbreak investigations after identifying carbapenem-resistant Pseudomonas aeruginosa: a systematic review. Antimicrob Resist Infect Control 2023; 12:28. [PMID: 37013661 PMCID: PMC10068724 DOI: 10.1186/s13756-023-01223-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 02/23/2023] [Indexed: 04/05/2023] Open
Abstract
BACKGROUND Carbapenem-resistant Pseudomonas aeruginosa (CRPA) are a serious cause of healthcare-associated infections. Part of the infection prevention and control measures are outbreak investigations (OI) of patients, healthcare workers (HCW), and the environment after identifying a CRPA in order to identify carriers and environmental reservoirs, so that targeted actions can be taken to prevent further transmission. However, little is known on when and how to perform such OI. Therefore, this systematic review aims to summarize OI performed after detection of CRPA in the endemic and epidemic hospital setting. MAIN TEXT Articles related to our research question were identified through a literature research in multiple databases (Embase, Medline Ovid, Cochrane, Scopus, Cinahl, Web of Science, and Google Scholar) until January 12, 2022 (Prospero registration number CRD42020194165). Hundred-twenty-six studies were included. In both the endemic and the epidemic setting, a median number of two out of seven predefined components of OI were identified. In the endemic setting, the most frequent component of OI was screening of the environment (28 studies, 62.2%). In the epidemic setting, screening of the environment (72 studies, 88.9%), and screening of patients during hospitalization (30 studies, 37%) were most frequently performed. Only 19 out of 126 studies (15.1%) reported screening of contact patients, and 37 studies reported screening of healthcare workers (HCW, 29.4%). CONCLUSION Due to probable underreporting of OI in the literature, the available evidence for the usefulness of the individual components of OI is scarce. This could lead to inhomogeneous performance of OI after detection of CRPA in the healthcare setting, and with this, potential under- or overscreening. While we could show evidence for the usefulness for environmental screening in order to identify the mode of transmission, evidence for HCW screening is scarce and might not lead to the identification of modes of transmission. Further studies are needed to better understand CI in different settings and, finally, develop guidance on when and how to best perform OI.
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Affiliation(s)
- Andrea C Büchler
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Selvi N Shahab
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Clinical Microbiology, Dr. Cipto Mangunkusumo General Hospital - Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia
| | - Juliëtte A Severin
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Margreet C Vos
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Anne F Voor In 't Holt
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
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11
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Jeon S, Rainisch G, Harris AM, Shinabery J, Iqbal M, Pallavaram A, Hilton S, Karki S, Moonan PK, Oeltmann JE, Meltzer MI. Estimated Cases Averted by COVID-19 Digital Exposure Notification, Pennsylvania, USA, November 8, 2020-January 2, 2021. Emerg Infect Dis 2023; 29:426-430. [PMID: 36639132 PMCID: PMC9881797 DOI: 10.3201/eid2902.220959] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
We combined field-based data with mathematical modeling to estimate the effectiveness of smartphone-enabled COVID-19 exposure notification in Pennsylvania, USA. We estimated that digital notifications potentially averted 7-69 cases/1,000 notifications during November 8, 2020-January 2, 2021. Greater use and increased compliance could increase the effectiveness of digital notifications.
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12
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Udeagu CCN, Pitiranggon M, Misra K, Huang J, Terilli T, Ramos Y, Alexander M, Kim C, Lee D, Blaney K, Keeley C, Long T, Vora NM. Outcomes of a Community Engagement and Information Gathering Program to Support Telephone-Based COVID-19 Contact Tracing: Descriptive Analysis. JMIR Public Health Surveill 2022; 8:e40977. [PMID: 36240019 PMCID: PMC9668330 DOI: 10.2196/40977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 09/27/2022] [Accepted: 10/13/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Contact tracing is an important public health tool for curbing the spread of infectious diseases. Effective and efficient contact tracing involves the rapid identification of individuals with infection and their exposed contacts and ensuring their isolation or quarantine, respectively. Manual contact tracing via telephone call and digital proximity app technology have been key strategies in mitigating the spread of COVID-19. However, many people are not reached for COVID-19 contact tracing due to missing telephone numbers or nonresponse to telephone calls. The New York City COVID-19 Trace program augmented the efforts of telephone-based contact tracers with information gatherers (IGs) to search and obtain telephone numbers or residential addresses, and community engagement specialists (CESs) made home visits to individuals that were not contacted via telephone calls. OBJECTIVE The aim of this study was to assess the contribution of information gathering and home visits to the yields of COVID-19 contact tracing in New York City. METHODS IGs looked for phone numbers or addresses when records were missing phone numbers to locate case-patients or contacts. CESs made home visits to case-patients and contacts with no phone numbers or those who were not reached by telephone-based tracers. Contact tracing management software was used to triage and queue assignments for the telephone-based tracers, IGs, and CESs. We measured the outcomes of contact tracing-related tasks performed by the IGs and CESs from July 2020 to June 2021. RESULTS Of 659,484 cases and 861,566 contact records in the Trace system, 28% (185,485) of cases and 35% (303,550) of contacts were referred to IGs. IGs obtained new phone numbers for 33% (61,804) of case-patients and 11% (31,951) of contacts; 50% (31,019) of the case-patients and 46% (14,604) of the contacts with new phone numbers completed interviews; 25% (167,815) of case-patients and 8% (72,437) of contacts were referred to CESs. CESs attempted 80% (132,781) of case and 69% (49,846) of contact investigations, of which 47% (62,733) and 50% (25,015) respectively, completed interviews. An additional 12,192 contacts were identified following IG investigations and 13,507 following CES interventions. CONCLUSIONS Gathering new or missing locating information and making home visits increased the number of case-patients and contacts interviewed for contact tracing and resulted in additional contacts. When possible, contact tracing programs should add information gathering and home visiting strategies to increase COVID-19 contact tracing coverage and yields as well as promote equity in the delivery of this public health intervention.
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Affiliation(s)
- Chi-Chi N Udeagu
- New York City Test & Trace Corps, New York City Department of Health & Mental Hygiene, Queens, NY, United States
| | - Masha Pitiranggon
- New York City Test & Trace Corps, New York City Department of Health & Mental Hygiene, Queens, NY, United States
| | - Kavita Misra
- New York City Test & Trace Corps, New York City Department of Health & Mental Hygiene, Queens, NY, United States
| | - Jamie Huang
- New York City Test & Trace Corps, New York City Department of Health & Mental Hygiene, Queens, NY, United States
| | - Thomas Terilli
- New York City Test & Trace Corps, New York City Department of Health & Mental Hygiene, Queens, NY, United States
| | - Yasmin Ramos
- New York City Test & Trace Corps, New York City Department of Health & Mental Hygiene, Queens, NY, United States
| | - Martha Alexander
- New York City Test & Trace Corps, New York City Department of Health & Mental Hygiene, Queens, NY, United States
| | - Christine Kim
- New York City Test & Trace Corps, New York City Department of Health & Mental Hygiene, Queens, NY, United States
| | - David Lee
- New York City Test & Trace Corps, New York City Department of Health & Mental Hygiene, Queens, NY, United States
| | - Kathleen Blaney
- New York City Test & Trace Corps, New York City Department of Health & Mental Hygiene, Queens, NY, United States
| | - Chris Keeley
- New York City Test & Trace Corps, New York City Health + Hospitals, New York City, NY, United States
| | - Theodore Long
- New York City Test & Trace Corps, New York City Health + Hospitals, New York City, NY, United States
| | - Neil M Vora
- New York City Test & Trace Corps, New York City Department of Health & Mental Hygiene, Queens, NY, United States
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13
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Barnes-Josiah D, Kundeti H, Cramer D. Factors Influencing the Results of COVID-19 Case Outreach-Results From a California Case Investigation/Contact Tracing Program. JOURNAL OF PUBLIC HEALTH MANAGEMENT AND PRACTICE 2022; 28:639-649. [PMID: 36070585 PMCID: PMC9555609 DOI: 10.1097/phh.0000000000001622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
CONTEXT Considerable research has examined impacts of case investigation and contact tracing (CI/CT) programs on the spread of infectious diseases such as COVID-19, but there are few reports on factors affecting the ability of these programs to obtain interviews and acquire key information. OBJECTIVE To investigate programmatic and case-specific factors associated with CI outcomes using data from the Public Health Institute's Tracing Health CI/CT program. Analyses were designed to detect variability in predictors of whether interviews and key information were obtained rather than quantify specific relationships. DESIGN Logistic regression models examined variability in the predictive value of interview timeliness and respondent characteristics on outreach outcomes and interview results. SETTING AND PARTICIPANTS Participants were members of a large California health care network with a positive laboratory test for COVID-19 and outreach from January 1 to July 31, 2021. MAIN OUTCOME MEASURES The primary outcome was the result of outreach attempts: completed interview, refused interview, or failure to reach the infected person. Secondary outcomes considered whether respondents provided information on symptom onset, employment, and contact information or a reason for declining to provide information, and whether resource support was requested or accepted. RESULTS Of 9391 eligible records, 65.6% were for completed interviews, 6.0% were refusals, and 28.3% were failed outreach. One-third of respondents (36.7%) provided information on contacts (mean = 0.97 contacts per respondent, 2.6 for those naming at least 1). Privacy concerns were the most common reasons for not providing contact information. Among respondent characteristics and interview timeliness, only race and number of symptoms showed statistically significant effects in all adjusted analyses. CONCLUSIONS Significant variation existed in outreach outcomes by subject characteristics and interview timeliness. CI/CT programs carefully focused to characteristics and needs of specific communities will likely have the greatest impact on the spread of COVID-19 and other communicable diseases.
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Affiliation(s)
- Debora Barnes-Josiah
- Correspondence: Debora Barnes-Josiah, PhD, MSPH, Tracing Health Program, Public Health Institute, 555 12th Street, Oakland, CA 94607 ()
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14
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Blaney K, Foerster S, Baumgartner J, Benckert M, Blake J, Bray J, Chamany S, Devinney K, Fine A, Gindler M, Guerra L, Johnson A, Keeley C, Lee D, Lipsit M, McKenney S, Misra K, Perl S, Peters D, Ray M, Saad E, Thomas G, Trieu L, Udeagu CC, Watkins J, Wong M, Zielinski L, Long T, Vora NM. COVID-19 Case Investigation and Contact Tracing in New York City, June 1, 2020, to October 31, 2021. JAMA Netw Open 2022; 5:e2239661. [PMID: 36322090 PMCID: PMC9631107 DOI: 10.1001/jamanetworkopen.2022.39661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
IMPORTANCE Contact tracing is a core strategy for preventing the spread of many infectious diseases of public health concern. Better understanding of the outcomes of contact tracing for COVID-19 as well as the operational opportunities and challenges in establishing a program for a jurisdiction as large as New York City (NYC) is important for the evaluation of this strategy. OBJECTIVE To describe the establishment, scaling, and maintenance of Trace, NYC's contact tracing program, and share data on outcomes during its first 17 months. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study included people with laboratory test-confirmed and probable COVID-19 and their contacts in NYC between June 1, 2020, and October 31, 2021. Trace launched on June 1, 2020, and had a workforce of 4147 contact tracers, with the majority of the workforce performing their jobs completely remotely. Data were analyzed in March 2022. MAIN OUTCOMES AND MEASURES Number and proportion of persons with COVID-19 and contacts on whom investigations were attempted and completed; timeliness of interviews relative to symptom onset or exposure for symptomatic cases and contacts, respectively. RESULTS Case investigations were attempted for 941 035 persons. Of those, 840 922 (89.4%) were reached and 711 353 (75.6%) completed an intake interview (women and girls, 358 775 [50.4%]; 60 178 [8.5%] Asian, 110 636 [15.6%] Black, 210 489 [28.3%] Hispanic or Latino, 157 349 [22.1%] White). Interviews were attempted for 1 218 650 contacts. Of those, 904 927 (74.3%) were reached, and 590 333 (48.4%) completed intake (women and girls, 219 261 [37.2%]; 47 403 [8.0%] Asian, 98 916 [16.8%] Black, 177 600 [30.1%] Hispanic or Latino, 116 559 [19.7%] White). Completion rates were consistent over time and resistant to changes related to vaccination as well as isolation and quarantine guidance. Among symptomatic cases, median time from symptom onset to intake completion was 4.7 days; a median 1.4 contacts were identified per case. Median time from contacts' last date of exposure to intake completion was 2.3 days. Among contacts, 30.1% were tested within 14 days of notification. Among cases, 27.8% were known to Trace as contacts. The overall expense for Trace from May 6, 2020, through October 31, 2021, was approximately $600 million. CONCLUSIONS AND RELEVANCE Despite the complexity of developing a contact tracing program in a diverse city with a population of over 8 million people, in this case study we were able to identify 1.4 contacts per case and offer resources to safely isolate and quarantine to over 1 million cases and contacts in this study period.
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Affiliation(s)
- Kathleen Blaney
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Steffen Foerster
- New York City Department of Health and Mental Hygiene, Queens, New York
| | | | | | - Janice Blake
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Jackie Bray
- New York City Health + Hospitals, New York, New York
- Now with New York State Division of Homeland Security and Emergency Services, Albany, New York
| | - Shadi Chamany
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Katelynn Devinney
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Annie Fine
- New York City Department of Health and Mental Hygiene, Queens, New York
- Now with Council of State and Territorial Epidemiologists, Atlanta, Georgia
| | - Masha Gindler
- New York City Health + Hospitals, New York, New York
| | - Laura Guerra
- New York City Health + Hospitals, New York, New York
| | | | - Chris Keeley
- New York City Health + Hospitals, New York, New York
| | - David Lee
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Mia Lipsit
- New York City Health + Hospitals, New York, New York
| | - Sarah McKenney
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Kavita Misra
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Sarah Perl
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Dana Peters
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Madhury Ray
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Eduardo Saad
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Guajira Thomas
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Lisa Trieu
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Chi-Chi Udeagu
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Julian Watkins
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Marcia Wong
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Lindsay Zielinski
- New York City Department of Health and Mental Hygiene, Queens, New York
| | - Theodore Long
- New York City Health + Hospitals, New York, New York
| | - Neil M. Vora
- New York City Department of Health and Mental Hygiene, Queens, New York
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Cohen SE, Stookey J, Anderson N, Morris D, Singzon T, Dann M, Burk K, Chen CC. Using Geocoding to Identify COVID-19 Outbreaks in Congregate Residential Settings: San Francisco's Outbreak Response in Single-Room Occupancy Hotels. Public Health Rep 2022; 138:7-13. [PMID: 36239486 PMCID: PMC9574538 DOI: 10.1177/00333549221128301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
More than 500 single-room occupancy hotels (SROs), a type of low-cost congregate housing with shared bathrooms and kitchens, are available in San Francisco. SRO residents include essential workers, people with disabilities, and multigenerational immigrant families. In March 2020, with increasing concerns about the potential for rapid transmission of COVID-19 among a population with disproportionate rates of comorbidity, poor access to care, and inability to self-isolate, the San Francisco Department of Public Health formed an SRO outbreak response team to identify and contain COVID-19 clusters in this congregate residential setting. Using address-matching geocoding, the team conducted active surveillance to identify new cases and outbreaks of COVID-19 at SROs. An outbreak was defined as 3 separate households in the SRO with a positive test result for COVID-19. From March 2020 through February 2021, the SRO outbreak response team conducted on-site mass testing of all residents at 52 SROs with outbreaks identified through geocoding. The rate of positive COVID-19 tests was significantly higher at SROs with outbreaks than at SROs without outbreaks (12.7% vs 6.4%; P < .001). From March through May 2020, the rate of COVID-19 cases among SRO residents was higher than among residents of other settings (ie, non-SRO residents), before decreasing and remaining at an equal level to non-SRO residents during later periods of 2020. The annual case fatality rate for SRO residents and non-SRO residents was similar (1.8% vs 1.5%). This approach identified outbreaks in a setting at high risk of COVID-19 and facilitated rapid deployment of resources. The geocoding surveillance approach could be used for other diseases and in any setting for which a list of addresses is available.
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Affiliation(s)
- Stephanie E. Cohen
- Disease Prevention and Control Branch, Population Health Division, San Francisco Department of Public Health, San Francisco, CA, USA,COVID Command Center, San Francisco Department of Public Health, San Francisco, CA, USA,Stephanie E. Cohen, MD, MPH, San Francisco Department of Public Health, Disease Prevention and Control Branch, Population Health Division, 356 7th St, San Francisco, CA 94103, USA.
| | - Jodi Stookey
- COVID Command Center, San Francisco Department of Public Health, San Francisco, CA, USA,Maternal, Child & Adolescent Health, San Francisco Department of Public Health, San Francisco, CA, USA
| | - Nora Anderson
- COVID Command Center, San Francisco Department of Public Health, San Francisco, CA, USA,Community Health Equity and Promotion Branch, Population Health Division, San Francisco Department of Public Health, San Francisco, CA, USA
| | - Devan Morris
- COVID Command Center, San Francisco Department of Public Health, San Francisco, CA, USA
| | - Trudy Singzon
- COVID Command Center, San Francisco Department of Public Health, San Francisco, CA, USA
| | - Maggie Dann
- COVID Command Center, San Francisco Department of Public Health, San Francisco, CA, USA
| | - Katie Burk
- COVID Command Center, San Francisco Department of Public Health, San Francisco, CA, USA,Community Health Equity and Promotion Branch, Population Health Division, San Francisco Department of Public Health, San Francisco, CA, USA
| | - Carol C. Chen
- COVID Command Center, San Francisco Department of Public Health, San Francisco, CA, USA,Department of Emergency Medicine, University of California San Francisco, San Francisco, CA, USA
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Haddad MB, McLean JE, Feldman SS, Sizemore EE, Taylor MM. Innovative Approaches to COVID-19 Case Investigation and Contact Tracing. Public Health Rep 2022; 137:5S-10S. [PMID: 36113066 PMCID: PMC9483134 DOI: 10.1177/00333549221120454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Affiliation(s)
- Maryam B. Haddad
- COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jody E. McLean
- COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Sue S. Feldman
- University of Alabama at Birmingham, Birmingham, AL, USA
| | - Erin E. Sizemore
- COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Melanie M. Taylor
- COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA
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