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

Development of a University-Government Partnership for Public Health Response and Workforce Development in the State of Oregon

The COVID-19 pandemic exposed and exacerbated a public health workforce shortage and national strategies have called for the development of clear occupational pathways for students to enter the public health workforce and meaningful public health careers. In response to the immediate need for public health workers during the pandemic, several universities and academic hospitals rapidly mobilized students and employees and partnered with local or state health departments. However, many of those partnerships were based on short-term volunteer effort to support critical COVID-19 public health efforts. In this article, we document the development of Oregon's Public Health Practice Team, a student, staff, and faculty workforce developed at the Oregon Health & Science University-Portland State University (OHSU-PSU) School of Public Health in close collaboration with the Oregon Health Authority (OHA). This project contributed significant effort to several phases of Oregon's statewide public health response to COVID-19, and over time developed into a lasting, multi-purpose, inter-agency collaborative public health practice program. Health equity has been centered at every stage of this work. We describe the phases of the partnership development, the current team structure and operations, and highlight key challenges and lessons learned. This provides a case-study of how an innovative and flexible university-government partnership can contribute to immediate pandemic response needs, and also support ongoing public health responses to emerging needs, while contributing to the development of a skilled and diverse public health workforce.

Looking under the lamp-post: quantifying the performance of contact tracing in the United States during the SARS-CoV-2 pandemic

Contact tracing forms a crucial part of the public-health toolbox in mitigating and understanding emergent pathogens and nascent disease outbreaks. Contact tracing in the United States was conducted during the pre-Omicron phase of the ongoing COVID-19 pandemic. This tracing relied on voluntary reporting and responses, often using rapid antigen tests due to lack of accessibility to PCR tests. These limitations, combined with SARS-CoV-2's propensity for asymptomatic transmission, raise the question "how reliable was contact tracing for COVID-19 in the United States"? We answered this question using a Markov model to examine the efficiency with which transmission could be detected based on the design and response rates of contact tracing studies in the United States. Our results suggest that contact tracing protocols in the U.S. are unlikely to have identified more than 1.65% (95% uncertainty interval: 1.62-1.68%) of transmission events with PCR testing and 1.00% (95% uncertainty interval 0.98-1.02%) with rapid antigen testing. When considering a more robust contact tracing scenario, based on compliance rates in East Asia with PCR testing, this increases to 62.7% (95% uncertainty interval: 62.6-62.8%). We did not assume presence of asymptomatic transmission or superspreading, making our estimates upper bounds on the actual percentages traced. These findings highlight the limitations in interpretability for studies of SARS-CoV-2 disease spread based on U.S. contact tracing and underscore the vulnerability of the population to future disease outbreaks, for SARS-CoV-2 and other pathogens.

COVID-19 Infection and Contact Tracing Among Refugees in the United States, 2020-2021

Refugees in the United States are believed to be at high risk of COVID-19. A cross-sectional study design was utilized to collect anonymous, online surveys from refugee communities in the United States during December 2020 to January 2021. We invited bilingual community leaders to share the survey link with other refugees aged ≥18 years. We identified factors associated with COVID-19 infection and measured the distribution of contact tracing among those who tested positive. Of 435 refugees who completed the survey, 26.4% reported testing positive for COVID-19. COVID-19 infection was associated with having an infected family member and knowing people in one's immediate social environment who were infected. Among respondents who tested positive, 84.4% reported that they had been contacted for contact tracing. To prepare for future pandemics, public health authorities should continue partner with refugee community leaders and organizations to ensure efficient programs are inclusive of refugee communities.

Scalable Strategies to Increase Efficiency and Augment Public Health Activities During Epidemic Peaks

OBJECTIVE

Scalable strategies to reduce the time burden and increase contact tracing efficiency are crucial during early waves and peaks of infectious transmission.

DESIGN

We enrolled a cohort of SARS-CoV-2-positive seed cases into a peer recruitment study testing social network methodology and a novel electronic platform to increase contact tracing efficiency.

SETTING

Index cases were recruited from an academic medical center and requested to recruit their local social contacts for enrollment and SARS-CoV-2 testing.

PARTICIPANTS

A total of 509 adult participants enrolled over 19 months (384 seed cases and 125 social peers).

INTERVENTION

Participants completed a survey and were then eligible to recruit their social contacts with unique "coupons" for enrollment. Peer participants were eligible for SARS-CoV-2 and respiratory pathogen screening.

MAIN OUTCOME MEASURES

The main outcome measures were the percentage of tests administered through the study that identified new SARS-CoV-2 cases, the feasibility of deploying the platform and the peer recruitment strategy, the perceived acceptability of the platform and the peer recruitment strategy, and the scalability of both during pandemic peaks.

RESULTS

After development and deployment, few human resources were needed to maintain the platform and enroll participants, regardless of peaks. Platform acceptability was high. Percent positivity tracked with other testing programs in the area.

CONCLUSIONS

An electronic platform may be a suitable tool to augment public health contact tracing activities by allowing participants to select an online platform for contact tracing rather than sitting for an interview.

Evaluating the impact on health outcomes of an event that resulted in a delay in contact tracing of COVID-19 cases in England, September 2020: an observational study

OBJECTIVE

In September 2020, 15 861 SARS-CoV-2 case records failed to upload from the Second Generation Surveillance System (SGSS) to the Contact Tracing Advisory Service (CTAS) tool, delaying the contact tracing of these cases. This study used CTAS data to determine the impact of this delay on population health outcomes: transmission events, hospitalisations and mortality. Previously, a modelling study suggested a substantial impact.

DESIGN

Observational study.

SETTING

England.

POPULATION

Individuals testing positive for SARS-CoV-2 and their reported contacts.

MAIN OUTCOME MEASURES

Secondary attack rates (SARs), hospitalisations and deaths among primary and secondary contacts were calculated, compared with all other concurrent, unaffected cases. Affected SGSS records were matched to CTAS records. Successive contacts and cases were identified and matched to hospital episode and mortality outcomes.

RESULTS

Initiation of contact tracing was delayed by 3 days on average in the primary cases in the delay group (6 days) compared with the control group (3 days). This was associated with lower completion of contact tracing: 80% (95% CI: 79% to 81%) in delay group and 83% (95% CI: 83% to 84%) in control group. There was some evidence to suggest increased transmission to non-household contacts among those affected by the delay. The SAR for non-household contacts was higher among secondary contacts in the delay group than the control group (delay group: 7.9%, 95% CI: 6.5% to 9.2%; control group: 5.9%, 95% CI: 5.3% to 6.6%). There did not appear to be a significant difference between the delay and control groups in the odds of hospitalisation (crude OR: 1.1 (95% CI: 0.9 to 1.2)) or death (crude OR: 0.7 (95% CI: 0.1 to 4.0)) among secondary contacts.

CONCLUSIONS

Our analysis suggests that the delay in contact tracing had a limited impact on population health outcomes; however, contact tracing was not completed for all individuals, so some transmission events might not be captured.

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

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.

Interplay of demographics, geography and COVID-19 pandemic responses in the Puget Sound region: The Vashon, Washington Medical Reserve Corps experience

BACKGROUND

Rural U.S. communities are at risk from COVID-19 due to advanced age and limited access to acute care. Recognizing this, the Vashon Medical Reserve Corps (VMRC) in King County, Washington, implemented an all-volunteer, community-based COVID-19 response program. This program integrated public engagement, SARS-CoV-2 testing, contact tracing, vaccination, and material community support, and was associated with the lowest cumulative COVID-19 case rate in King County. This study aimed to investigate the contributions of demographics, geography and public health interventions to Vashon's low COVID-19 rates.

METHODS

This observational cross-sectional study compares cumulative COVID-19 rates and success of public health interventions from February 2020 through November 2021 for Vashon Island with King County (including metropolitan Seattle) and Whidbey Island, located ~50 km north of Vashon. To evaluate the role of demography, we developed multiple linear regression models of COVID-19 rates using metrics of age, race/ethnicity, wealth and educational attainment across 77 King County zip codes. To investigate the role of remote geography we expanded the regression models to include North, Central and South Whidbey, similarly remote island communities with varying demographic features. To evaluate the effectiveness of VMRC's community-based public health measures, we directly compared Vashon's success of vaccination and contact tracing with that of King County and South Whidbey, the Whidbey community most similar to Vashon.

RESULTS

Vashon's cumulative COVID-19 case rate was 29% that of King County overall (22.2 vs 76.8 cases/K). A multiple linear regression model based on King County demographics found educational attainment to be a major correlate of COVID-19 rates, and Vashon's cumulative case rate was just 38% of predicted (p < .05), so demographics alone do not explain Vashon's low COVID-19 case rate. Inclusion of Whidbey communities in the model identified a major effect of remote geography (-49 cases/K, p < .001), such that observed COVID-19 rates for all remote communities fell within the model's 95% prediction interval. VMRC's vaccination effort was highly effective, reaching a vaccination rate of 1500 doses/K four months before South Whidbey and King County and maintaining a cumulative vaccination rate 200 doses/K higher throughout the latter half of 2021 (p < .001). Including vaccination rates in the model reduced the effect of remote geography to -41 cases/K (p < .001). VMRC case investigation was also highly effective, interviewing 96% of referred cases in an average of 1.7 days compared with 69% in 3.7 days for Washington Department of Health investigating South Whidbey cases and 80% in 3.4 days for Public Health-Seattle & King County (both p<0.001). VMRC's public health interventions were associated with a 30% lower case rate (p<0.001) and 55% lower hospitalization rate (p = 0.056) than South Whidbey.

CONCLUSIONS

While the overall magnitude of the pre-Omicron COVID-19 pandemic in rural and urban U.S. communities was similar, we show that island communities in the Puget Sound region were substantially protected from COVID-19 by their geography. We further show that a volunteer community-based COVID-19 response program was highly effective in the Vashon community, augmenting the protective effect of geography. We suggest that Medical Reserve Corps should be an important element of future pandemic planning.

Implementing strategies to prevent infections in acute-care settings

This document introduces and explains common implementation concepts and frameworks relevant to healthcare epidemiology and infection prevention and control and can serve as a stand-alone guide or be paired with the "SHEA/IDSA/APIC Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals: 2022 Updates," which contain technical implementation guidance for specific healthcare-associated infections. This Compendium article focuses on broad behavioral and socio-adaptive concepts and suggests ways that infection prevention and control teams, healthcare epidemiologists, infection preventionists, and specialty groups may utilize them to deliver high-quality care. Implementation concepts, frameworks, and models can help bridge the "knowing-doing" gap, a term used to describe why practices in healthcare may diverge from those recommended according to evidence. It aims to guide the reader to think about implementation and to find resources suited for a specific setting and circumstances by describing strategies for implementation, including determinants and measurement, as well as the conceptual models and frameworks: 4Es, Behavior Change Wheel, CUSP, European and Mixed Methods, Getting to Outcomes, Model for Improvement, RE-AIM, REP, and Theoretical Domains.

Looking under the lamp-post: quantifying the performance of contact tracing in the United States during the SARS-CoV-2 pandemic

Contact tracing forms a crucial part of the public-health toolbox in mitigating and understanding emergent pathogens and nascent disease outbreaks. Contact tracing in the United States was conducted during the pre-Omicron phase of the ongoing COVID-19 pandemic. This tracing relied on voluntary reporting and responses, often using rapid antigen tests (with a high false negative rate) due to lack of accessibility to PCR tests. These limitations, combined with SARS-CoV-2's propensity for asymptomatic transmission, raise the question "how reliable was contact tracing for COVID-19 in the United States"? We answered this question using a Markov model to examine the efficiency with which transmission could be detected based on the design and response rates of contact tracing studies in the United States. Our results suggest that contact tracing protocols in the U.S. are unlikely to have identified more than 1.65% (95% uncertainty interval: 1.62%-1.68%) of transmission events with PCR testing and 0.88% (95% uncertainty interval 0.86%-0.89%) with rapid antigen testing. When considering an optimal scenario, based on compliance rates in East Asia with PCR testing, this increases to 62.7% (95% uncertainty interval: 62.6%-62.8%). These findings highlight the limitations in interpretability for studies of SARS-CoV-2 disease spread based on U.S. contact tracing and underscore the vulnerability of the population to future disease outbreaks, for SARS-CoV-2 and other pathogens.

Retrospective, Observational Studies for Estimating Vaccine Effects on the Secondary Attack Rate of SARS-CoV-2

Coronavirus disease 2019 (COVID-19) vaccines are highly efficacious at preventing symptomatic infection, severe disease, and death. Most of the evidence that COVID-19 vaccines also reduce transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is based on retrospective, observational studies. Specifically, an increasing number of studies are evaluating vaccine effectiveness against the secondary attack rate of SARS-CoV-2 using data available in existing health-care databases or contact-tracing databases. Since these types of databases were designed for clinical diagnosis or management of COVID-19, they are limited in their ability to provide accurate information on infection, infection timing, and transmission events. We highlight challenges with using existing databases to identify transmission units and confirm potential SARS-CoV-2 transmission events. We discuss the impact of common diagnostic testing strategies, including event-prompted and infrequent testing, and illustrate their potential biases in estimating vaccine effectiveness against the secondary attack rate of SARS-CoV-2. We articulate the need for prospective observational studies of vaccine effectiveness against the SARS-CoV-2 secondary attack rate, and we provide design and reporting considerations for studies using retrospective databases.

Implementation of a Hardware-Assisted Bluetooth-Based COVID-19 Tracking Device in a High School: Mixed Methods Study

BACKGROUND

Contact tracing is a vital public health tool used to prevent the spread of infectious diseases. However, traditional interview-format contact tracing (TCT) is labor-intensive and time-consuming and may be unsustainable for large-scale pandemics such as COVID-19.

OBJECTIVE

In this study, we aimed to address the limitations of TCT. The Yale School of Engineering developed a Hardware-Assisted Bluetooth-based Infection Tracking (HABIT) device. Following the successful implementation of HABIT in a university setting, this study sought to evaluate the performance and implementation of HABIT in a high school setting using an embedded mixed methods design.

METHODS

In this pilot implementation study, we first assessed the performance of HABIT using mock case simulations in which we compared contact tracing data collected from mock case interviews (TCT) versus Bluetooth devices (HABIT). For each method, we compared the number of close contacts identified and identification of unique contacts. We then conducted an embedded mixed methods evaluation of the implementation outcomes of HABIT devices using pre- and postimplementation quantitative surveys and qualitative focus group discussions with users and implementers according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework.

RESULTS

In total, 17 students and staff completed mock case simulations in which 161 close contact interactions were detected by interview or Bluetooth devices. We detected significant differences in the number of close contacts detected by interview versus Bluetooth devices (P<.001), with most (127/161, 78.9%) contacts being reported by interview only. However, a significant number (26/161, 16.1%; P<.001) of contacts were uniquely identified by Bluetooth devices. The interface, ease of use, coherence, and appropriateness were highly rated by both faculty and students. HABIT provided emotional security to users. However, the prototype design and technical difficulties presented barriers to the uptake and sustained use of HABIT.

CONCLUSIONS

Implementation of HABIT in a high school was impeded by technical difficulties leading to decreased engagement and adherence. Nonetheless, HABIT identified a significant number of unique contacts not reported by interview, indicating that electronic technologies may augment traditional contact tracing once user preferences are accommodated and technical glitches are overcome. Participants indicated a high degree of acceptance, citing emotional reassurance and a sense of security with the device.

Lessons Learned from the Lessons Learned in Public Health during the First Years of COVID-19 Pandemic

(1) Objectives: to investigate the main lessons learned from the public health (PH) response to COVID-19, using the global perspective endorsed by the WHO pillars, and understand what countries have learned from their practical actions. (2) Methods: we searched for articles in PubMed and CINAHL from 1 January 2020 to 31 January 2022. 455 articles were included. Inclusion criteria were PH themes and lessons learned from the COVID-19 pandemic. One hundred and forty-four articles were finally included in a detailed scoping review. (3) Findings: 78 lessons learned were available, cited 928 times in the 144 articles. Our review highlighted 5 main lessons learned among the WHO regions: need for continuous coordination between PH institutions and organisations (1); importance of assessment and evaluation of risk factors for the diffusion of COVID-19, identifying vulnerable populations (2); establishment of evaluation systems to assess the impact of planned PH measures (3); extensive application of digital technologies, telecommunications and electronic health records (4); need for periodic scientific reviews to provide regular updates on the most effective PH management strategies (5). (4) Conclusion: lessons found in this review could be essential for the future, providing recommendations for an increasingly flexible, fast and efficient PH response to a healthcare emergency such as the COVID-19 pandemic.

Factors Influencing the Results of COVID-19 Case Outreach-Results From a California Case Investigation/Contact Tracing Program

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.

Centering Health Equity Within COVID-19 Contact Tracing: Connecticut's Community Outreach Specialist Program

CONTEXT

The COVID-19 pandemic has disproportionately impacted vulnerable populations, including those who are non-English-speaking and those with lower socioeconomic status; yet, participation of these groups in contact tracing was initially low. Distrust of government agencies, anticipated COVID-19-related stigma, and language and cultural barriers between contact tracers and communities are common challenges.

PROGRAM

The Community Outreach Specialist (COS) program was established within the Connecticut Department of Public Health (DPH) COVID-19 contact tracing program to encourage participation in contact tracing and address a need for culturally competent care and social and material support among socially vulnerable and non-English-speaking populations in 11 high-burden jurisdictions in Connecticut.

IMPLEMENTATION

In partnership with state and local health departments, we recruited 25 COS workers with relevant language skills from target communities and trained them to deliver contact tracing services to vulnerable and non-English speaking populations.

EVALUATION

We conducted a cross-sectional analysis using data from ContaCT, DPH's enterprise contact tracing system. Overall, the COS program enrolled 1938 cases and 492 contacts. The proportion of residents reached (ie, called and interviewed) in the COS program was higher than that in the regular contact tracing program for both cases (70% vs 57%, P < .001) and contacts (84% vs 64%, P < .001). After adjusting for client age, sex, race and ethnicity, language, and jurisdiction, we found that the COS program was associated with increased reach for contacts (odds ratio [OR] = 1.52; 95% confidence interval [95% CI], 1.17-1.99) but not for cases (OR = 0.78; 95% CI, 0.70-0.88). Rapid qualitative analysis of programmatic field notes and meeting reports provided evidence that the COS program was feasible and acceptable to clients and contributed to COVID-19 education and communication efforts.

CONCLUSION

A COS program employing a client-centered, community-engaged strategy for reaching vulnerable and non-English-speaking populations was feasible and more effective at reaching contacts than standard COVID-19 contact tracing.

Unified Response to COVID-19 Case Investigation and Contact Tracing, Chicago, December 2020-April 2021

OBJECTIVES

We evaluated 2 innovative approaches that supported COVID-19 case investigation and contact tracing (CI/CT) in Chicago communities: (1) early engagement of people diagnosed with COVID-19 by leveraging the existing Healthcare Alert Network to send automated telephone calls and text messages and (2) establishment of a network of on-site case investigators and contact tracers within partner health care facilities (HCFs) and community-based organizations (CBOs).

METHODS

The Chicago Department of Public Health used Healthcare Alert Network data to calculate the proportion of people with confirmed COVID-19 who successfully received an automated telephone call or text message during December 27, 2020-April 24, 2021. The department also used CI/CT data to calculate the proportion of cases successfully interviewed and named contacts successfully notified, as well as the time to successful case interview and to successful contact notification.

RESULTS

Of 67 882 people with COVID-19, 94.3% (n = 64 011) received an automated telephone call and 91.7% (n = 62 239) received a text message. Of the 65 470 COVID-19 cases pulled from CI/CT data, 24 450 (37.3%) interviews were completed, including 6212 (61.3%) of the 10 126 cases diagnosed in HCFs. The median time from testing to successful case interview was 3 days for Chicago Department of Public Health investigators and 4 days for HCF investigators. Overall, 34 083 contacts were named; 13 117 (38.5%) were successfully notified, including 9068 (36.6%) of the 24 761 contacts assigned to CBOs. The median time from contact elicitation to completed notification by CBOs was <24 hours.

CONCLUSIONS

Partnerships with HCFs and CBOs helped deliver timely CI/CT during the COVID-19 pandemic, suggesting a potential benefit of engaging non-public health institutions in CI/CT for existing and emerging diseases.

"I can't do it": A qualitative study exploring case and contact experiences with COVID-19 contact tracing

BACKGROUND

Low engagement in contact tracing for COVID-19 dramatically reduces its impact, but little is known about how experiences, environments and characteristics of cases and contacts influence engagement.

METHODS

We recruited a convenience sample of COVID-19 cases and contacts from the New Haven Health Department's contact tracing program for interviews about their contact tracing experiences. We analyzed transcripts thematically, organized themes using the Capability, Opportunity, Motivation, Behavior (COM-B) model, and identified candidate interventions using the linked Behavior Change Wheel Framework.

RESULTS

We interviewed 21 cases and 12 contacts. Many felt physically or psychologically incapable of contact tracing participation due to symptoms or uncertainty about protocols. Environmental factors and social contacts also influenced engagement. Finally, physical symptoms, emotions and low trust in and expectations of public health authorities influenced motivation to participate.

CONCLUSION

To improve contact tracing uptake, programs should respond to clients' physical and emotional needs; increase clarity of public communications; address structural and social factors that shape behaviors and opportunities; and establish and maintain trust. We identify multiple potential interventions that may help achieve these goals.

A State Health Department and Health Information Exchange Partnership: an Effective Collaboration for a Data-Driven Response for COVID-19 Contact Tracing in Maryland

BACKGROUND

Accurate, complete, timely data were essential to effective contact tracing for COVID-19. Maryland Department of Health partnered with Maryland's designated health information exchange, Chesapeake Regional Information System for Our Patients (CRISP), to establish data enhancement processes that provided the foundation for Maryland's successful contact tracing program.

METHODS

Hourly, electronic positive COVID-19 test results were routed through CRISP to the contact tracing data platform. CRISP matched reports against its master patient index to enhance the record with demographic, locating, fatality, vaccination, and hospitalization data. Records were de-duplicated and flagged if associated with a congregate setting, select state universities, or recent international travel. Chi-square tests were used to assess if CRISP-added phone numbers resulted in better contact tracing outcomes.

RESULTS

During June 15, 2020-September 1, 2021, CRISP pushed 531,094 records to the state's contact tracing data platform within an hour of receipt; of those eligible for investigation, 99% had a phone number. CRISP matched 521,731 (98%) records to their master patient index, allowing for deduplication and enrichment. CRISP flagged 15,615 cases in congregate settings and 3,304 cases as university students; these records were immediately routed for outbreak investigation. Records with an added phone number were significantly more likely to be successfully reached compared to cases with no added phone number (p = 0.01).

CONCLUSIONS

CRISP enhanced COVID-19 electronic laboratory reports with a near-instant impact on public health actions. The partnership and data processing workflows can serve as a blueprint for data modernization in public health agencies across the United States.

Design, Implementation, and Outcomes of a Volunteer-Staffed Case Investigation and Contact Tracing Initiative at an Urban Academic Medical Center

IMPORTANCE

The COVID-19 pandemic has claimed nearly 6 million lives globally as of February 2022. While pandemic control efforts, including contact tracing, have traditionally been the purview of state and local health departments, the COVID-19 pandemic outpaced health department capacity, necessitating actions by private health systems to investigate and control outbreaks, mitigate transmission, and support patients and communities.

OBJECTIVE

To investigate the process of designing and implementing a volunteer-staffed contact tracing program at a large academic health system from April 2020 to May 2021, including program structure, lessons learned through implementation, results of case investigation and contact tracing efforts, and reflections on how constrained resources may be best allocated in the current pandemic or future public health emergencies.

DESIGN, SETTING, AND PARTICIPANTS

This case series study was conducted among patients at the University of Pennsylvania Health System and in partnership with the Philadelphia Department of Public Health. Patients who tested positive for COVID-19 were contacted to counsel them regarding safe isolation practices, identify and support quarantine of their close contacts, and provide resources, such as food and medicine, needed during isolation or quarantine.

RESULTS

Of 5470 individuals who tested positive for COVID-19 and received calls from a volunteer, 2982 individuals (54.5%; median [range] age, 42 [18-97] years; 1628 [59.4%] women among 2741 cases with sex data) were interviewed; among 2683 cases with race data, there were 110 Asian individuals (3.9%), 1476 Black individuals (52.7%), and 817 White individuals (29.2%), and among 2667 cases with ethnicity data, there were 366 Hispanic individuals (13.1%) and 2301 individuals who were not Hispanic (82.6%). Most individuals lived in a household with 2 to 5 people (2125 of 2904 individuals with household data [71.6%]). Of 3222 unique contacts, 1780 close contacts (55.2%; median [range] age, 40 [18-97] years; 866 [55.3%] women among 1565 contacts with sex data) were interviewed; among 1523 contacts with race data, there were 69 Asian individuals (4.2%), 705 Black individuals (43.2%), and 573 White individuals (35.1%), and among 1514 contacts with ethnicity data, there were 202 Hispanic individuals (12.8%) and 1312 individuals (83.4%) who were not Hispanic. Most contacts lived in a household with 2 to 5 people (1123 of 1418 individuals with household data [79.2%]). Of 3324 cases and contacts who completed a questionnaire on unmet social needs, 907 (27.3%) experienced material hardships that would make it difficult for them to isolate or quarantine safely. Such hardship was significantly less common among White compared with Black participants (odds ratio, 0.20; 95% CI, 0.16-0.25).

CONCLUSIONS AND RELEVANCE

These findings demonstrate the feasibility and challenges of implementing a case investigation and contact tracing program at an academic health system. In addition to successfully engaging most assigned COVID-19 cases and close contacts, contact tracers shared health information and material resources to support isolation and quarantine, thus filling local public health system gaps and supporting local pandemic control.

What Went Wrong with the IMMUNI Contact-Tracing App in Italy? A Cross-Sectional Survey on the Attitudes and Experiences among Healthcare University Students

The adoption of digital contact-tracing apps to limit the spread of SARS-CoV-2 has been sup-optimal, but studies that clearly identify factors associated with the app uptake are still limited. In April 2021, we administered a questionnaire to healthcare university students to investigate their attitudes towards and experiences of the IMMUNI app. A multivariable logistic regression model was built to identify app download predictors. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were calculated. We surveyed 247 students. Most respondents (65.6%) had not downloaded IMMUNI, reporting as the main reason the perceived app uselessness (32.7%). In the multivariable analysis, being advised to use the app (aOR: 3.21, 95%CI: 1.80-5.73), greater fear of infecting others (aOR: 1.50, 95%CI: 1.01-2.23), and greater trust in the institutional response to the emergency (aOR: 1.33, 95%CI: 1.00-1.76) were positively associated with the outcome, whereas greater belief in the "lab-leak theory" of COVID-19 was a negative predictor (aOR: 0.75, 95%CI: 0.60-0.93). Major technical issues were reported by app users. Targeted strategies aimed at improving awareness of digital health applications should be devised. Furthermore, institutions should invest in the development of these technologies, to minimize technical issues and make them accessible to the entire population.

Ideal Test Time for Coronavirus Disease 2019 Contact Tracing

Background

Epidemiological contact tracing is a powerful tool to rapidly detect SARS-CoV-2 infection in persons with a close contact history with COVID-19-affected patients. However, it remains unclear whom and when should be PCR tested among the close contact subjects.

Methods

We retrospectively analyzed 817 close contact subjects, including 144 potentially SARS-CoV-2-infected persons. The patient characteristics and contact type, duration between the date of the close contact and specimen sampling, and PCR test results in PCR positive and negative persons were compared.

Results

We found that male gender {adjusted odds ratio 1.747 [95% confidence interval (CI) 1.180–2.608]}, age ≥ 60 [1.749 (95% CI 1.07–2.812)], and household contact [2.14 (95% CI 1.388–3.371)] are independent risk factors for close contact SARS-CoV-2 infection. Symptomatic subjects were predicted 6.179 (95% CI 3.985–9.61) times more likely to be infected compared to asymptomatic ones. We could observe PCR test positivity between days 1 and 17 after close contact. However, no subject could be found with a Ct-value <30, considered less infective, after day 14 of close contact.

Conclusions

Based on our results, we suggest that contact tracing should be performed on the high-risk subjects between days 3 and 13 after close contacts.

Risk factors for nosocomial SARS-CoV-2 infections in patients: results from a retrospective matched case-control study in a tertiary care university center

BACKGROUND

Factors contributing to the spread of SARS-CoV-2 outside the acute care hospital setting have been described in detail. However, data concerning risk factors for nosocomial SARS-CoV-2 infections in hospitalized patients remain scarce. To close this research gap and inform targeted measures for the prevention of nosocomial SARS-CoV-2 infections, we analyzed nosocomial SARS-CoV-2 cases in our hospital during a defined time period.

METHODS

Data on nosocomial SARS-CoV-2 infections in hospitalized patients that occurred between May 2020 and January 2021 at Charité university hospital in Berlin, Germany, were retrospectively gathered. A SARS-CoV-2 infection was considered nosocomial if the patient was admitted with a negative SARS-CoV-2 reverse transcription polymerase chain reaction test and subsequently tested positive on day five or later. As the incubation period of SARS-CoV-2 can be longer than five days, we defined a subgroup of "definite" nosocomial SARS-CoV-2 cases, with a negative test on admission and a positive test after day 10, for which we conducted a matched case-control study with a one to one ratio of cases and controls. We employed a multivariable logistic regression model to identify factors significantly increasing the likelihood of nosocomial SARS-CoV-2 infections.

RESULTS

A total of 170 patients with a nosocomial SARS-CoV-2 infection were identified. The majority of nosocomial SARS-CoV-2 patients (n = 157, 92%) had been treated at wards that reported an outbreak of nosocomial SARS-CoV-2 cases during their stay or up to 14 days later. For 76 patients with definite nosocomial SARS-CoV-2 infections, controls for the case-control study were matched. For this subgroup, the multivariable logistic regression analysis revealed documented contact to SARS-CoV-2 cases (odds ratio: 23.4 (95% confidence interval: 4.6-117.7)) and presence at a ward that experienced a SARS-CoV-2 outbreak (odds ratio: 15.9 (95% confidence interval: 2.5-100.8)) to be the principal risk factors for nosocomial SARS-CoV-2 infection.

CONCLUSIONS

With known contact to SARS-CoV-2 cases and outbreak association revealed as the primary risk factors, our findings confirm known causes of SARS-CoV-2 infections and demonstrate that these also apply to the acute care hospital setting. This underscores the importance of rapidly identifying exposed patients and taking adequate preventive measures.