Dataset Information

Implementing a digital system for contact tracing and case investigation during COVID-19 pandemic in San Francisco: a qualitative study.

ABSTRACT: During the COVID-19 pandemic, many health jurisdictions deployed digital informatics systems to support "manual" case investigation and contact tracing (CICT). This case study evaluates the implementation and use of a digital information system through the experiences of CICT workers in the City and County of San Francisco (CCSF). We conducted semi-structured, 90-min interviews with a sample of the CCSF CICT workforce (n = 37). Participants also completed standardized assessments of the digital system using the System Usability Scale (SUS). Qualitative analyses highlighted (1) the importance of digital tools to ensure rapid onboarding and effective data capture in a public health emergency; (2) the use of digital systems to support culturally sensitive care; and (3) the role of digitals tools in building supportive work environments. The mean SUS score was 70/100 (SD = 17), indicating relative ease of use. In summary, the analysis highlights the importance of digital tools to support manual CICT in the COVID-19 response.

SUBMITTER: Burgess H

PROVIDER: S-EPMC8653624 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Implementing a digital system for contact tracing and case investigation during COVID-19 pandemic in San Francisco: a qualitative study.

Burgess Hailey H Gutierrez-Mock Luis L Ho Yun-Xian YX Moghadassi Michelle M Lesh Neal N Krueger Elizabeth E Reid Michael M

JAMIA open 20211029 4

During the COVID-19 pandemic, many health jurisdictions deployed digital informatics systems to support "manual" case investigation and contact tracing (CICT). This case study evaluates the implementation and use of a digital information system through the experiences of CICT workers in the City and County of San Francisco (CCSF). We conducted semi-structured, 90-min interviews with a sample of the CCSF CICT workforce (<i>n</i> = 37). Participants also completed standardized assessments of the d ...[more]

PMID: 34888491

Similar Datasets

Project description:Digital contact tracing presents numerous advantages compared to manual contact tracing methods, especially in terms of enhanced speed and automation. Nevertheless, a lack of comprehensive evaluation regarding functionality, efficiency, benefits, and acceptance within communities remains. Here we primarily focus on the functionality of THEA-GS, an open-source digital contact tracing tool developed through consultation with stakeholders. Additionally, we provide insights from its implementation on a limited sample of haulage drivers in Uganda, serving as a representative case for a low- and middle-income country. THEA-GS comprises two primary components: (a) a smartphone application, and (b) a suite of server-programs responsible for data processing and analysis, including databases and a web-based interface featuring dashboards. In essence, the mobile application records the timestamped location of haulage drivers within the road network and identifies possible transmission hotspots by analyzing factors such as the duration of stops and the communities associated with them. The tool can be integrated with national infrastructure to compare drivers' diagnostic results and contact structure, thereby generating individual and community risk assessments relative to the road network. During the Omicron-variant wave of the COVID-19 pandemic, a total of 3,270 haulage drivers were enrolled between October 2021 and October 2022. Around 75% of these drivers utilized THEA-GS for approximately two months. Based on an analysis of 3,800 test results, which included 48 positive cases, 125 contacts, and 40 million time-stamped GPS points, THEA-GS shows a significant speed improvement, being approximately 90 times faster than MCT. For instance, the average time from sample collection to notifying a case and their contacts was approximately 70 and 80 min, respectively. The adoption of this tool encountered challenges, mainly due to drivers' awareness of its purpose and benefits for public health. THEA-GS is a place-based digital contact tracing tool specifically designed to assist National Public Health Institutions in managing infectious disease outbreaks involving the haulage industry as a high-risk group. While its utility, acceptance, and accuracy have not been fully evaluated, our preliminary tests conducted in Uganda indicate the tool's functionality is robust, but social acceptance and adoption are heavily reliant on establishing trust among users.

Project description:Digital contact tracing (DCT) applications have been introduced in many countries to aid the containment of COVID-19 outbreaks. Initially, enthusiasm was high regarding their implementation as a non-pharmaceutical intervention (NPI). However, no country was able to prevent larger outbreaks without falling back to harsher NPIs. Here, we discuss results of a stochastic infectious-disease model that provide insights in how the progression of an outbreak and key parameters such as detection probability, app participation and its distribution, as well as engagement of users impact DCT efficacy informed by results of empirical studies. We further show how contact heterogeneity and local contact clustering impact the intervention’s efficacy. We conclude that DCT apps might have prevented cases on the order of single-digit percentages during single outbreaks for empirically plausible ranges of parameters, ignoring that a substantial part of these contacts would have been identified by manual contact tracing. This result is generally robust against changes in network topology with exceptions for homogeneous-degree, locally-clustered contact networks, on which the intervention prevents more infections. An improvement of efficacy is similarly observed when app participation is highly clustered. We find that DCT typically averts more cases during the super-critical phase of an epidemic when case counts are rising and the measured efficacy therefore depends on the time of evaluation. Author summary Many countries relied on non-pharmaceutical interventions (NPIs) to mitigate or contain outbreaks during the COVID-19 pandemic. Because NPIs can have a dramatic socio-economic impact, policy makers were looking for less severe interventions to combat this global crisis. Since mid-2020, digital contact tracing (DCT) solutions have been implemented in many countries, raising the expectation that this intervention may effectively contain outbreaks without requiring more severe NPIs. Analyzing a stochastic infectious-disease network model that captures the essential elements of realistic contact structures, disease dynamics, NPIs, testing, and is based on empirical results regarding app adoption and usage behavior, we estimate that the intervention’s success with regard to the expected reduction of infections is on the order of single-digit percentages, mostly regardless of contact network structure. Only when contact networks either exhibit both high local clustering and a narrow degree distribution, or when app participation is highly clustered will DCT efficacy be increased.

Project description:BackgroundHealth systems had to rapidly implement infection control strategies to sustain their workforces during the COVID-19 pandemic. Various outbreak response tools, such as digital contact tracing (DCT), have been developed to monitor exposures and symptoms of health care workers (HCWs). Limited research evidence exists on the experiences with these technologies and the impacts of DCT innovations from the perspective of stakeholders in health care environments.ObjectiveThis study aims to identify the factors influencing the adoption of DCT, highlight variations in perspectives across 3 key stakeholder groups concerning the impact of DCT, and provide benchmarking evidence for future pandemic preparedness.MethodsGuided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, we conducted an exploratory qualitative study to investigate the implementation and impact of DCT at the Children's Hospital of Eastern Ontario between December 2022 and April 2023. We conducted 21 semistructured interviews with key stakeholders, including health care administrators (6/21, 29%), occupational health and safety specialists (8/21, 38%), and HCWs (7/21, 33%). Stakeholders were asked about the factors influencing engagement with the DCT tool, organizational-level uptake, the implementation process, long-term use and sustainability of DCT, and unintended consequences. Verbatim transcripts were subject to thematic analysis using NVivo (QSR International).ResultsThe implementation of DCT was viable and well received. End users indicated that their engagement with the DCT tool was facilitated by its perceived ease of use and the ability to gain awareness of probable COVID-19 exposures; however, risk assessment consequences and access concerns were reported as barriers (reach). Participants commonly agreed that the DCT technology had a positive influence on the hospital's capacity to meet the demands of COVID-19 (effectiveness). Implementors and occupational specialists referred to negative staffing impacts and the loss of nuanced information as unintended consequences (effectiveness). Safety-focused communication strategies and having a DCT tool that was human-centered were crucial factors driving staff adoption of the technology. Conversely, adoption was challenged by the misaligned delivery of the DCT tool with HCWs' standard practices, alongside the evolving perceived threat of COVID-19. Stakeholders collectively agreed on the viability of DCT and its applicability to infectious disease practices (maintenance).ConclusionsHospital stakeholders were highly satisfied with DCT technology and it was perceived as feasible, efficient, and having a positive impact on organizational safety. Challenges related to the alignment and delivery of DCT, alongside the evolving perspectives on COVID-19, posed obstacles to continued adoption by HCWs. Our findings contribute to evidence-based practices and present benchmarks that can inform preparedness for future pandemics and infectious disease outbreaks and help other organizations implement similar technologies.

Project description:BackgroundRapid and mass transmission of the SARS-CoV-2 virus amongst vulnerable people led to devastating effects from COVID-19 in care homes. The CONTACT intervention introduced Bluetooth Low Energy 'smart' wearable devices (BLE wearables) as a basis for automated contact tracing in, and feedback on infection risks and patterns to, care homes to try and improve infection prevention and control (IPC). We planned a cluster randomised controlled trial (RCT) of CONTACT. To be feasible, homes had to adopt CONTACT's technology and new ways of working. This paper reports on the process evaluation conducted alongside CONTACT's feasibility study and explains why it lacked the feasibility and acceptability for a definitive RCT.MethodsThis mixed method process evaluation used Normalisation Process Theory (NPT) qualitative (interviews, field notes, study case report forms and documents, and observation) and quantitative (survey instruments, counts of activity) data to plan, implement, and analyse the mechanisms, effects, and contextual factors that shaped the feasibility and acceptability of the CONTACT intervention.ResultsThirteen themes within four core NPT constructs explained CONTACT's lack of feasibility. Coherence: the home's varied in the scale and extent of commitment and understanding of the technology and study procedures. Leadership credibility was important but compromised by competing priorities. Management and direct care staff saw CONTACT differently. Work to promote (cognitive participation) and enact (collective action) CONTACT was burdensome and failed to be prioritised over competing COVID-19-related demands on time and scarce human and cognitive resources. Ultimately, staff appraisal of the value of CONTACT-generated information and study procedures (reflexivity) was that any utility for IPC was insufficient to outweigh the perceived burden and complexity involved.ConclusionsDespite implementation failure, dismissing BLE wearables' potential for contact tracing is premature. In non-pandemic conditions, with more time, better co-design and integration of theory-driven implementation strategies tailored to care homes' unique contexts, researchers could enhance normalisation in readiness for future pandemic challenges.Trial registrationISRCTN registration: 11,204,126 registered 17/02/2021.

Dataset Information

Implementing a digital system for contact tracing and case investigation during COVID-19 pandemic in San Francisco: a qualitative study.

Publications

Implementing a digital system for contact tracing and case investigation during COVID-19 pandemic in San Francisco: a qualitative study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets