Integrating HIV Surveillance and Field Services: Data Quality and Care Continuum in King County, Washington, 2010–2015

Hood, Julia; Katz, David A.; Bennett, Amy; Buskin, Susan E.; Dombrowski, Julia C.; Hawes, Stephen E.; Golden, Matthew R.

doi:10.2105/ajph.2017.304069

Cited by 12 publications

(10 citation statements)

References 13 publications

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“…Figure 1 visually depicts the PHSKC CI/CT model. Similar to PHSKC's approach to HIV surveillance and linkage to care, 21 the COVID-19 CI/CT program integrated service referrals into case and contact interviews. After initially seeking to speak with each adult in the household, the program shifted to communicating primarily with a single household point of contact to collect names, dates of birth, and testing and symptom status of each household member, discuss I&Q guidelines tailored to each household member, and coordinate support services.…”

Section: Methodsmentioning

confidence: 99%

A Multifaceted Evaluation of a COVID-19 Contact Tracing Program in King County, Washington

Hood

Kubiak

Avoundjian

et al. 2022

Journal of Public Health Management and Practice

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Context: Despite the massive scale of COVID-19 case investigation and contact tracing (CI/CT) programs operating worldwide, the evidence supporting the intervention's public health impact is limited. Objective: To evaluate the Public Health-Seattle & King County (PHSKC) CI/CT program, including its reach, timeliness, effect on isolation and quarantine (I&Q) adherence, and potential to mitigate pandemic-related hardships. Design: This program evaluation used descriptive statistics to analyze surveillance records, case and contact interviews, referral records, and survey data provided by a sample of cases who had recently ended isolation. Setting: The PHSKC is one of the largest governmental local health departments in the United States. It serves more than 2.2 million people who reside in Seattle and 38 other municipalities. Participants: King County residents who were diagnosed with COVID-19 between July 2020 and June 2021. Intervention: The PHSKC integrated COVID-19 CI/CT with prevention education and service provision. Results:The PHSKC CI/CT team interviewed 42 900 cases (82% of cases eligible for CI/CT), a mean of 6.1 days after symptom onset and 3.4 days after SARS-CoV-2 testing. Cases disclosed the names and addresses of 10 817 unique worksites (mean = 0.8/interview) and 11 432 other recently visited locations (mean = 0.5/interview) and provided contact information for 62 987 household members (mean = 2.7/interview) and 14 398 nonhousehold contacts (mean = 0.3/interview). The CI/CT team helped arrange COVID-19 testing for 5650 contacts, facilitated grocery delivery for 7253 households, and referred 9127 households for financial assistance. End of I&Q Survey participants (n = 304, 54% of sampled) reported self-notifying an average of 4 nonhousehold contacts and 69% agreed that the information and referrals provided by the CI/CT team helped them stay in isolation. Conclusions: In the 12-month evaluation period, CI/CT reached 42 611 households and identified thousands of exposure venues. The timing of CI/CT relative to infectiousness and difficulty eliciting nonhousehold contacts may have attenuated the intervention's effect. Through promotion of I&Q guidance and services, CI/CT can help mitigate pandemic-related hardships.

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Section: Methodsmentioning

confidence: 99%

A Multifaceted Evaluation of a COVID-19 Contact Tracing Program in King County, Washington

Hood

Kubiak

Avoundjian

et al. 2022

Journal of Public Health Management and Practice

Self Cite

View full text Add to dashboard Cite

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“…Public Health−Seattle & King County (PHSKC) has an integrated HIV surveillance and partner services team, which investigates new HIV cases reported by laboratories and medical providers. 4 Staff review medical records for each new diagnosis and attempt to contact newly diagnosed residents and in-migrants not known to be virally suppressed. Collected data include sex assigned at birth, age, HIV risk factors during a window of possible seroconversion, laboratory test results, and housing status.…”

Section: National Health Surveillance System and Partner Servicesmentioning

confidence: 99%

Detection and Response to an HIV Cluster: People Living Homeless and Using Drugs in Seattle, Washington

Buskin

Erly

Glick

et al. 2021

American Journal of Preventive Medicine

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Introduction:The HIV epidemic in King County, Washington has traditionally been highly concentrated among men who have sex with men, and incidence has gradually declined over 2 decades. In 2018, King County experienced a geographically concentrated outbreak of HIV among heterosexual people who inject drugs.Methods: Data sources to describe the 2018 outbreak and King County's response were partner services interview data, HIV case reports, syringe service program client surveys, hospital data, and data from a rapid needs assessment of homeless individuals and people who inject drugs. In 2020, the authors examined the impact of delays in molecular sequence analyses and cluster member size thresholds, for identifying genetically similar clusters, on the timing of outbreak identification. Results:In 2018, the health department identified a North Seattle cluster, growing to 30 people with related HIV infections diagnosed in 2008−2019. In total, 70% of cluster members were female, 77% were people who inject drugs, 87% were homeless, and 27% reported exchanging sex. Intervention activities included a rapid needs assessment, 2,485 HIV screening tests in a jail and other outreach settings, provision of 87,488 clean syringes in the outbreak area, and public communications. A lower cluster size threshold and more rapid receipt and analyses of data would have identified this outbreak 4−16 months earlier. Conclusions:This outbreak shows the vulnerability of people who inject drugs to HIV infection, even in areas with robust syringe service programs and declining HIV epidemics. Although molecular HIV surveillance did not identify this outbreak, it may have done so with a lower threshold for defining clusters and more rapid receipt and analyses of HIV genetic sequences.

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“…A central goal of public health surveillance is to provide continuous and systematically collected health-related data to inform public health practice and guide interventions to improve individual and population health [1]. For example, health departments in the United States use HIV surveillance data [2][3][4][5] to identify people living with HIV (PLWH) who are not engaged in HIV care to provide assistance and services to facilitate care engagement-a strategy known as Data to Care [6][7][8][9][10][11][12]. In this way, surveillance data are used to improve both HIV care and prevention as well as to reduce inequities in access and utilization of HIV care resources to improve the well-being of vulnerable populations with HIV.…”

Section: Introductionmentioning

confidence: 99%

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

Avoundjian¹,

Dombrowski²,

Golden³

et al. 2020

JMIR Public Health Surveill

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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.

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Integrating HIV Surveillance and Field Services: Data Quality and Care Continuum in King County, Washington, 2010–2015

Abstract: Integration of HIV surveillance, partner services, and care linkage efforts may improve the accuracy of HIV surveillance data and facilitate timely linkage to care.

Cited by 12 publications

References 13 publications

A Multifaceted Evaluation of a COVID-19 Contact Tracing Program in King County, Washington

A Multifaceted Evaluation of a COVID-19 Contact Tracing Program in King County, Washington

Detection and Response to an HIV Cluster: People Living Homeless and Using Drugs in Seattle, Washington

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

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