Use of Digital COVID-19 Exposure Notifications at a Large Gathering: Survey Analysis of Public Health Conference Attendees.

BACKGROUND: WA Notify was Washington State's smartphone-based COVID-19 digital exposure notification (EN) tool, which was used to help limit the spread of COVID-19 between November 30, 2020, and May 11, 2023. Following the 2022 Washington State Public Health Association Annual Conference, attendees who had WA Notify activated began receiving ENs alerting them to a possible COVID-19 exposure during the conference. A survey was emailed to all conference attendees to measure WA Notify adoption, mechanisms through which attendees received ENs, and self-reported engagement in protective behaviors postexposure. OBJECTIVE: This study aimed to learn more about the experiences of WA Notify adopters and nonadopters who may have been exposed to COVID-19 at a large group gathering. METHODS: A web-based survey administered through REDCap (Research Electronic Data Capture; Vanderbilt University) was sent to all attendees of the Washington State Public Health Association conference. Self-reported demographic information and characteristics of respondents were summarized. Regression models were used to estimate relative risks to compare WA Notify adoption and testing behaviors between groups. RESULTS: Of the 464 total registered attendees who were sent the survey, 205 (44%) responses were received; 201 eligible attendees were included in this analysis. Of those, 149 (74%) respondents reported having WA Notify activated on their phones at the time of the conference. Among respondents with WA Notify activated, 54% (n=77) reported learning of their potential exposure from a WA Notify EN. Respondents who reported that they did not have WA Notify activated and learned of their potential exposure via the event-wide email from conference organizers were 39% less likely to test for COVID-19 compared to respondents with WA Notify activated who learned of their potential exposure from the email (relative risk 0.61, 95% CI 0.40-0.93; P=.02), and this gap was even larger when compared to respondents who learned of their exposure from a WA Notify EN. The most commonly cited reason for not having WA Notify activated was privacy concerns (n=17, 35%), followed by not wanting to receive ENs (n=6, 12%) and being unaware of WA Notify (n=5, 10%). CONCLUSIONS: Digital EN systems are an important tool to directly and anonymously notify close contacts of potential exposures and provide guidance on the next steps in a timely manner. Given the privacy concerns, there is still a need for increasing transparency surrounding EN technology to increase uptake by the public if this technology were to be used in the future to slow the spread of communicable diseases.

Changing genomic epidemiology of COVID-19 in long-term care facilities during the 2020-2022 pandemic, Washington State.

BACKGROUND: Long-term care facilities (LTCFs) are vulnerable to disease outbreaks. Here, we jointly analyze SARS-CoV-2 genomic and paired epidemiologic data from LTCFs and surrounding communities in Washington state (WA) to assess transmission patterns during 2020-2022, in a setting of changing policy. We describe sequencing efforts and genomic epidemiologic findings across LTCFs and perform in-depth analysis in a single county. METHODS: We assessed genomic data representativeness, built phylogenetic trees, and conducted discrete trait analysis to estimate introduction sizes over time, and explored selected outbreaks to further characterize transmission events. RESULTS: We found that transmission dynamics among cases associated with LTCFs in WA changed over the course of the COVID-19 pandemic, with variable introduction rates into LTCFs, but decreasing amplification within LTCFs. SARS-CoV-2 lineages circulating in LTCFs were similar to those circulating in communities at the same time. Transmission between staff and residents was bi-directional. CONCLUSIONS: Understanding transmission dynamics within and between LTCFs using genomic epidemiology on a broad scale can assist in targeting policies and prevention efforts. Tracking facility-level outbreaks can help differentiate intra-facility outbreaks from high community transmission with repeated introduction events. Based on our study findings, methods for routine tree building and overlay of epidemiologic data for hypothesis generation by public health practitioners are recommended. Discrete trait analysis added valuable insight and can be considered when representative sequencing is performed. Cluster detection tools, especially those that rely on distance thresholds, may be of more limited use given current data capture and timeliness. Importantly, we noted a decrease in data capture from LTCFs over time. Depending on goals for use of genomic data, sentinel surveillance should be increased or targeted surveillance implemented to ensure available data for analysis.

Sentinel Surveillance System Implementation and Evaluation for SARS-CoV-2 Genomic Data, Washington, USA, 2020-2021.

Genomic data provides useful information for public health practice, particularly when combined with epidemiologic data. However, sampling bias is a concern because inferences from nonrandom data can be misleading. In March 2021, the Washington State Department of Health, USA, partnered with submitting and sequencing laboratories to establish sentinel surveillance for SARS-CoV-2 genomic data. We analyzed available genomic and epidemiologic data during presentinel and sentinel periods to assess representativeness and timeliness of availability. Genomic data during the presentinel period was largely unrepresentative of all COVID-19 cases. Data available during the sentinel period improved representativeness for age, death from COVID-19, outbreak association, long-term care facility-affiliated status, and geographic coverage; timeliness of data availability and captured viral diversity also improved. Hospitalized cases were underrepresented, indicating a need to increase inpatient sampling. Our analysis emphasizes the need to understand and quantify sampling bias in phylogenetic studies and continue evaluation and improvement of public health surveillance systems.

Improving Foodborne Disease Surveillance and Outbreak Detection and Response Using Peer Networks-The Integrated Food Safety Centers of Excellence.

CONTEXT: Foodborne disease surveillance and outbreak investigations are foundational to the prevention and control of foodborne disease in the United States, where contaminated foods cause an estimated 48 million illnesses, 128 000 hospitalizations, and 3000 deaths each year. Surveillance activities and rapid detection and investigation of foodborne disease outbreaks require a trained and coordinated workforce across epidemiology, environmental health, and laboratory programs. PROGRAM: Under the 2011 Food Safety Modernization Act, the Centers for Disease Control and Prevention (CDC) was called on to establish Integrated Food Safety (IFS) Centers of Excellence (CoEs) at state health departments, which would collaborate with academic partners, to identify, implement, and evaluate model practices in foodborne disease surveillance and outbreak response and to serve as a resource for public health professionals. IMPLEMENTATION: CDC designated 5 IFS CoEs in August 2012 in Colorado, Florida, Minnesota, Oregon, and Tennessee; a sixth IFS CoE in New York was added in August 2014. For the August 2019-July 2024 funding period, 5 IFS CoEs were designated in Colorado, Minnesota, New York, Tennessee, and Washington. Each IFS CoE is based at the state health department that partners with at least one academic institution. EVALUATION: IFS CoEs have built capacity across public health agencies by increasing the number of workforce development opportunities (developing >70 trainings, tools, and resources), supporting outbreak response activities (responding to >50 requests for outbreak technical assistance annually), mentoring students, and responding to emerging issues, such as changing laboratory methods and the COVID-19 pandemic.

Trading-off privacy and utility: the Washington State experience assessing the performance of a public health digital exposure notification system for coronavirus disease 2019.

OBJECTIVE: Digital exposure notifications (DEN) systems were an emergency response to the coronavirus disease 2019 (COVID-19) pandemic, harnessing smartphone-based technology to enhance conventional pandemic response strategies such as contact tracing. We identify and describe performance measurement constructs relevant to the implementation of DEN tools: (1) reach (number of users enrolled in the intervention); (2) engagement (utilization of the intervention); and (3) effectiveness in preventing transmissions of COVID-19 (impact of the intervention). We also describe WA State's experience utilizing these constructs to design data-driven evaluation approaches. METHODS: We conducted an environmental scan of DEN documentation and relevant publications. Participation in multidisciplinary collaborative environments facilitated shared learning. Compilation of available data sources and their relevance to implementation and operation workflows were synthesized to develop implementation evaluation constructs. RESULTS: We identified 8 useful performance indicators within reach, engagement, and effectiveness constructs. DISCUSSION: We use implementation science to frame the evaluation of DEN tools by linking the theoretical constructs with the metrics available in the underlying disparate, deidentified, and aggregate data infrastructure. Our challenges in developing meaningful metrics include limited data science competencies in public health, validation of analytic methodologies in the complex and evolving pandemic environment, and the lack of integration with the public health infrastructure. CONCLUSION: Continued collaboration and multidisciplinary consensus activities can improve the utility of DEN tools for future public health emergencies.

Engagement in Protective Behaviors by Digital Exposure Notification Users During the COVID-19 Pandemic, Washington State, January-June 2021.

OBJECTIVES: Smartphone-based digital exposure notification (EN) tools were introduced during the COVID-19 pandemic to supplement strained case investigation and contact tracing efforts. We examined the influence of an EN tool implemented in Washington State, WA Notify, on user engagement in behaviors that protect against COVID-19 transmission. METHODS: From January 25 through June 30, 2021, we administered 2 surveys to WA Notify users who received notification of a possible COVID-19 exposure. The initial survey, sent when users received a notification, focused on intent to engage in protective behaviors. The follow-up survey captured data on self-reported actual engagement in protective behaviors and contact by a public health contact tracer. RESULTS: Of 1507 WA Notify users who completed the initial survey, 40.1% (n = 604) reported intending to seek COVID-19 testing and 67.1% (n = 1011) intended to watch for COVID-19 symptoms. Of 407 respondents to the follow-up survey, 57.5% (n = 234) reported getting tested and 84.3% (n = 343) reported watching for COVID-19 symptoms. Approximately 84% (n = 1266) of respondents to the initial survey received a notification from WA Notify before being reached by public health contact tracers; on follow-up, 42.5% (n = 173) of respondents reported never being contacted by public health. CONCLUSIONS: Our findings suggest that WA Notify users may initiate protective behaviors earlier than nonusers who will not know of an exposure until notified by public health or by a known contact. Digital EN tools may be a valuable addition to existing public health outbreak investigation and response activities.

Equity and Accessibility of Washington State's COVID-19 Digital Exposure Notification Tool (WA Notify): Survey and Listening Sessions Among Community Leaders.

BACKGROUND: In November 2020, WA Notify, Washington State's COVID-19 digital exposure notification tool, was launched statewide to mitigate ongoing COVID-19 transmission. WA Notify uses the Bluetooth proximity-triggered, Google/Apple Exposure Notification Express framework to distribute notifications to users who have added or activated this tool on their smartphones. This smartphone-based tool relies on sufficient population-level activation to be effective; however, little is known about its adoption among communities disproportionately impacted by the COVID-19 pandemic or what barriers might limit its adoption and use among diverse populations. OBJECTIVE: We sought to (1) conduct a formative exploration of equity-related issues that may influence the access, adoption, and use of WA Notify, as perceived by community leaders of populations disproportionately impacted by the COVID-19 pandemic; and (2) generate recommendations for promoting the equitable access to and impact of this novel intervention for these communities. METHODS: We used a 2-step data collection process to gather the perspectives of community leaders across Washington regarding the launch and implementation of WA Notify in their communities. A web-based, brief, and informational survey measured the perceptions of the community-level familiarity and effectiveness of WA Notify at slowing the spread of COVID-19 and identified potential barriers and concerns to accessing and adopting WA Notify (n=17). Semistructured listening sessions were conducted to expand upon survey findings and explore the community-level awareness, barriers, facilitators, and concerns related to activating WA Notify in greater depth (n=13). RESULTS: Our findings overlap considerably with those from previous mobile health equity studies. Digital literacy, trust, information accessibility, and misinformation were highlighted as key determinants of the adoption and use of WA Notify. Although WA Notify does not track users or share data, community leaders expressed concerns about security, data sharing, and personal privacy, which were cited as outweighing the potential benefits to adoption. Both the survey and informational sessions indicated low community-level awareness of WA Notify. Community leaders recommended the following approaches to improve engagement: tailoring informational materials for low-literacy levels, providing technology navigation, describing more clearly that WA Notify can help the community, and using trusted messengers who are already engaged with the communities to communicate about WA Notify. CONCLUSIONS: As digital public health tools, such as WA Notify, emerge to address public health problems, understanding the key determinants of adoption and incorporating equity-focused recommendations into the development, implementation, and communication efforts around these tools will be instrumental to their adoption, use, and retention.

Developing a Concept of Operations Template to Guide Collaborative Disaster Research Response Between Academic Public Health and Public Health Agencies.

Research conducted in the context of a disaster or public health emergency is essential to improve knowledge about its short- and long-term health consequences, as well as the implementation and effectiveness of response and recovery strategies. Integrated approaches to conducting Disaster Research Response (DR2) can answer scientific questions, while also providing attendant value for operational response and recovery. Here, we propose a Concept of Operations (CONOPS) template to guide the collaborative development and implementation of DR2 among academic public health and public health agencies, informed by previous literature, semi-structured interviews with disaster researchers from academic public health across the United States, and discussion groups with public health practitioners. The proposed CONOPS outlines actionable strategies to address DR2 issues before, during, and after disasters for public health scholars and practitioners who seek to operationalize or enhance their DR2 programs. Additional financial and human resources will be necessary to promote widespread implementation of collaborative DR2 programs.

WA Notify: the planning and implementation of a Bluetooth exposure notification tool for COVID-19 pandemic response in Washington State.

Bluetooth exposure notification tools for mobile phones have emerged as one way to support public health contact tracing and mitigate the spread of COVID-19. Many states have launched their own versions of these tools. Washington State's exposure notification tool, WA Notify, became available on November 30, 2020, following a one-month Seattle campus pilot at the University of Washington. By the end of April 2021, 25% of the state's population had activated WA Notify, one of the highest adoption rates in the country. Washington State's formation of an Exposure Notification Advisory Committee, early pilot testing, and use of the EN Express system framework were all important factors in its adoption. Continuous monitoring and willingness to make early adjustments such as switching to automated texting of verification codes have also been important for improving the tool's value. Evaluation work is ongoing to determine and quantify WA Notify's effectiveness, timeliness, and accessibility.

State-Level Evaluation of Washington's State Innovation Models (SIM) Initiative.

The Washington State Innovation Models (SIM) $65 million Test Award from the Center for Medicare & Medicaid Services' Innovation Center is a statewide intervention expected to improve population health, quality of care, and cost growth through four initiatives: 1) regional accountable communities of health linking health and social services to address local needs; 2) a practice transformation support hub; 3) four value-based payment reform pilot projects mainly in state employee and Medicaid populations; and 4) data and analytic infrastructure development to support system transformation with common measures. We develop a conceptual model based on diffusion theory and apply the RE-AIM evaluation framework (Reach, Effectiveness, Adoption, Implementation, and Maintenance) to structure our evaluation. We find that in three years (2016-2018), SIM built the infrastructure for system transformation and increased Washington's readiness for health system change in the next decade. However, the initiatives have not spread statewide, which may take over 10 years.

Whole Genome Sequencing Detects Minimal Clustering Among Escherichia coli Sequence Type 131-H30 Isolates Collected From United States Children's Hospitals.

We applied whole genome sequencing to identify putative transmission clusters among clinical multidrug-resistant Escherichia coli sequence type 131-H30 isolates from 4 United States children's hospitals. Of 126 isolates, 17 were involved in 8 putative transmission clusters; 4 clusters showed evidence of healthcare-associated epidemiologic linkages. Geographic clustering analyses showed weak geographic clustering.

Mixed-Methods Evaluation of the Washington State Practice Transformation Support Hub.

PURPOSE: Practice transformation initiatives have the potential to promote collaborations between public health, primary care, and behavioral health, but limited empirical evidence is available on how these programs affect participating clinical practices. OBJECTIVE: To report the findings from a mixed-methods program evaluation of the Washington Practice Transformation Support Hub (Hub), a publicly funded, multicomponent practice transformation initiative in Washington State. DESIGN: We used quantitative and qualitative methods to evaluate the impact of Hub activities on participating primary care and behavioral health practices. Pre- and posttest survey data were combined with administrative program data to understand the effect of program components. Qualitative interviews contextualized findings. SETTING: Urban and rural primary care and behavioral health practices in Washington State. PARTICIPANTS: One hundred seventy-five practices that were recruited to receive Hub coaching and facilitation from 8 coaches; of these, 13 practices and all coaches participated in key informant interviews. INTERVENTION: Practice coaching and facilitation supported by an online resource portal, from January 2017 through January 2019. MAIN OUTCOME MEASURES: Self-reported progress in specific activities in 3 practice-level domains: bidirectional integration of physical and behavioral health care (care integration); alignment with community-based services for whole-person care (clinical-community linkages); and value-based payment. RESULTS: Participation in Hub activities was associated with improvements in care integration and clinical-community linkages but not with progress toward value-based payment. Qualitative results indicated that practice progress was influenced by communication with practices, the culture of the practice, resource constraints (particularly in rural areas), and perceptions about sustainability. CONCLUSIONS: This statewide practice transformation initiative was successful in strengthening primary care and behavioral health integration and clinical-community linkages among participating practices but not value-based payment. Future practice transformation efforts may benefit from addressing barriers posed by communication, limited application of value-based payment, culture change, competing priorities, and resource limitations, particularly for rural communities.

Comparing Methods for Record Linkage for Public Health Action: Matching Algorithm Validation Study.

BACKGROUND: Many public health departments use record linkage between surveillance data and external data sources to inform public health interventions. However, little guidance is available to inform these activities, and many health departments rely on deterministic algorithms that may miss many true matches. In the context of public health action, these missed matches lead to missed opportunities to deliver interventions and may exacerbate existing health inequities. OBJECTIVE: This study aimed to compare the performance of record linkage algorithms commonly used in public health practice. METHODS: We compared five deterministic (exact, Stenger, Ocampo 1, Ocampo 2, and Bosh) and two probabilistic record linkage algorithms (fastLink and beta record linkage [BRL]) using simulations and a real-world scenario. We simulated pairs of datasets with varying numbers of errors per record and the number of matching records between the two datasets (ie, overlap). We matched the datasets using each algorithm and calculated their recall (ie, sensitivity, the proportion of true matches identified by the algorithm) and precision (ie, positive predictive value, the proportion of matches identified by the algorithm that were true matches). We estimated the average computation time by performing a match with each algorithm 20 times while varying the size of the datasets being matched. In a real-world scenario, HIV and sexually transmitted disease surveillance data from King County, Washington, were matched to identify people living with HIV who had a syphilis diagnosis in 2017. We calculated the recall and precision of each algorithm compared with a composite standard based on the agreement in matching decisions across all the algorithms and manual review. RESULTS: In simulations, BRL and fastLink maintained a high recall at nearly all data quality levels, while being comparable with deterministic algorithms in terms of precision. Deterministic algorithms typically failed to identify matches in scenarios with low data quality. All the deterministic algorithms had a shorter average computation time than the probabilistic algorithms. BRL had the slowest overall computation time (14 min when both datasets contained 2000 records). In the real-world scenario, BRL had the lowest trade-off between recall (309/309, 100.0%) and precision (309/312, 99.0%). CONCLUSIONS: Probabilistic record linkage algorithms maximize the number of true matches identified, reducing gaps in the coverage of interventions and maximizing the reach of public health action.

Evaluation of an Emergency Department and Hospital-Based Data Exchange to Improve HIV Care Engagement and Viral Suppression.

BACKGROUND: Emergency department (ED) visits and inpatient (IP) admissions may provide an opportunity to reengage poorly engaged people living with HIV and facilitate viral suppression. In 2015, Public Health Seattle and King County partnered with the University of Washington Medicine to implement a real-time data exchange to identify virally unsuppressed people living with HIV seen at the ED/IP hospital and reengage them in HIV care. We evaluated the impact of the data exchange on care engagement and viral suppression. METHODS: Public Health Seattle and King County received a text alert on weekdays 8 AM to 6 PM for ED/IP patients previously diagnosed with HIV with a most recent viral load ≥200 copies/mL. We compared viral load testing <3 months and viral suppression <6 months after an alert-eligible visit in the 2 years after intervention and the 7 to 30 months before intervention. To account for secular trends, we used difference-in-differences models to compare patients with alert-window visits to patients with visits outside the alert window before and after intervention. RESULTS: Patients with visits within the alert window in the postintervention period were 1.08 (95% confidence interval [CI], 0.97-1.20) times more likely to have a viral load test within 3 months after an ED visit/IP admission and 1.50 (95% CI, 1.27-1.76) times more likely to achieve viral suppression within 6 months than patients in the preintervention period. However, care engagement (difference-in-differences relative risk, 1.00; 95% CI, 0.84-1.18) and viral suppression (difference-in-differences relative risk, 1.01; 95% CI, 0.84-1.20) trends were similar among patients with visits outside the alert window. CONCLUSIONS: Real-time data exchange with ED/IP hospitals was associated with improved viral suppression, but not increased care engagement. However, our results may reflect secular trends resulting from diverse interventions, of which ours was only one. More efforts are needed to improve the effectiveness of relinkage interventions guided by real-time data exchange.

RE-AIM Evaluation Plan for Washington State Innovation Models Project.

The State of Washington received a State Innovation Models (SIM) $65 million award from the federal Centers for Medicare & Medicaid Services to improve population health and quality of care and reduce the growth of health care costs in the entire state, which has over 7 million residents. SIM is a "complex intervention" that implements several interacting components in a complex, decentralized health system to achieve goals, which poses challenges for evaluation. Our purpose is to present the state-level evaluation methods for Washington's SIM, a 3-year intervention (2016-2018). We apply the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) evaluation framework to structure our evaluation. We create a conceptual model and a plan to use multiple and mixed methods to study SIM performance in the RE-AIM components from a statewide, population-based perspective.

Field-based evaluation of malaria outbreak detection and response in Mudzi and Goromonzi districts, Zimbabwe - 2017.

National-level evaluations may fail to identify capacity improvements for detecting and responding to outbreaks which begin and are first detected at the local level. In response to this issue, we conducted a field-based assessment of the malaria outbreak surveillance system in Mashonaland East, Zimbabwe. We visited eleven clinics in Mudzi and Goromonzi districts. Twenty-one interviews were conducted with key informants from the provincial (n = 2), district (n = 7), and clinic (n = 12) levels. Interviews focused on surveillance system activities, preparedness, data quality, timeliness, stability, and usefulness. Main themes were captured utilising standard qualitative data analysis techniques. While the surveillance system detects malaria outbreaks at all levels, we identified several gaps. Clinics experience barriers to timely and reliable reporting of outbreaks to the district level and staff cross-training. Stability of resources, including transportation (33% of informants, n = 7) and staff capacity (48% of informants, n = 10), presented barriers. Strengthening these surveillance barriers may improve staff readiness to detect malaria outbreaks, resulting in timelier outbreak response and a reduction in malaria outbreaks, cases, and deaths. By focusing at the local level, our assessment approach provides a framework for identifying and addressing gaps that may be overlooked when utilising tools that evaluate surveillance capacity at the national level.

Destress 9-1-1-an online mindfulness-based intervention in reducing stress among emergency medical dispatchers: a randomised controlled trial.

OBJECTIVES: Emergency medical dispatchers (EMDs) experience significant stress in the workplace. Yet, interventions aimed at reducing work-related stress are difficult to implement due to the logistic challenges associated with the relatively unique EMD work environment. This investigation tested the efficacy of a 7-week online mindfulness-based intervention (MBI) tailored to the EMD workforce. METHODS: Active-duty EMDs from the USA and Canada (n=323) were randomly assigned to an intervention or wait list control condition. Participants completed surveys of stress and mindfulness at baseline, post intervention, and 3 months follow-up. Repeated measures mixed effects models were used to assess changes in stress and mindfulness. RESULTS: Differences between the intervention group and control group in pre-post changes in stress using the Calgary Symptoms of Stress Inventory were statistically significant, with a difference of -10.0 (95% CI: -14.9, -5.2, p<0.001) for change from baseline to post intervention, and a difference of -6.5 (95% CI: -11.9, -1.1, p=0.02) for change from baseline to 3 months follow-up. Change in mindfulness scores did not differ between groups. However, increases in mindfulness scores were correlated with greater reductions in stress for all participants, regardless of group (r=-0.53, p<0.001). CONCLUSIONS: Development of tailored online MBIs for employees working in challenging work environments offer a promising direction for prevention and intervention. This study found that a short, weekly online MBI for EMDs resulted in reductions in reports of stress. Implications of online MBIs in other emergency responding populations and directions for future research are discussed.

An Academic-Practice Partnership at the University of Washington School of Public Health: The Student Epidemic Action Leaders (SEAL) Team.

In 2015, the University of Washington School of Public Health, Department of Epidemiology established the Student Epidemic Action Leaders (SEAL) team to provide public health students with experience in field epidemiology in state and local public health communicable disease divisions. The University of Washington Department of Epidemiology developed the SEAL team in collaboration with the Washington State Department of Health to offer public health graduate students opportunities to contribute to the real-time needs of public health agencies during a communicable disease event and/or preparedness event. The SEAL team combines classroom and field-based training in public health practice and applied epidemiology. During the first 2 years of the SEAL team (2016-2018), 34 SEALs were placed at 4 agencies contributing more than 1300 hours of assistance on 24 public health projects.