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In the face of scarce public health resources, it is critical to understand which disease surveillance strategies are effective, yet such validation has historically been difficult. From May 1 to December 31, 2021, a cohort study was carried out in Santa Clara County, California, in which 10,131 high-quality genomic sequences from COVID-19 polymerase chain reaction tests were merged with disease surveillance data. We measured the informational value, the fraction of sequenced links surfaced that are biologically plausible according to genomic sequence data, of different disease surveillance strategies. Contact tracing appeared more effective than spatiotemporal methods at uncovering nonresidential spread settings, school reporting appeared more fruitful than workplace reporting, and passively retrieved links through survey information presented some promise. Given the rapidly dwindling cost of sequencing, the informational value metric may enable near real-time, readily available evaluation of strategies by public health authorities to fight viral diseases beyond COVID-19., Competing Interests: The authors declare no competing interest., (© 2023 The Author(s).)

We describe a large outbreak of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) involving an acute-care hospital emergency department during December 2020 and January 2021, in which 27 healthcare personnel worked while infectious, resulting in multiple opportunities for SARS-CoV-2 transmission to patients and other healthcare personnel. We provide recommendations for improving infection prevention and control.

COVID-19 exposed and exacerbated health disparities, and a core challenge has been how to adapt pandemic response and public health in light of these disproportionate health burdens. Responding to this challenge, the County of Santa Clara Public Health Department designed a model of "high-touch" contact tracing that integrated social services with disease investigation, providing continued support and resource linkage for clients from structurally vulnerable communities. We report results from a cluster randomized trial of 5,430 cases from February to May 2021 to assess the ability of high-touch contact tracing to aid with isolation and quarantine. Using individual-level data on resource referral and uptake outcomes, we find that the intervention, randomized assignment to the high-touch program, increased the referral rate to social services by 8.4% (95% confidence interval, 0.8%-15.9%) and the uptake rate by 4.9% (-0.2%-10.0%), with the most pronounced increases in referrals and uptake of food assistance. These findings demonstrate that social services can be effectively combined with contact tracing to better promote health equity, demonstrating a novel path for the future of public health., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Lu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Case investigation and contact tracing (CICT) is an important tool for communicable disease control, both to proactively interrupt chains of transmission and to collect information for situational awareness. We run the first randomized trial of COVID-19 CICT to investigate the utility of manual ( i.e. , call-based) vs. automated ( i.e. , survey-based) CICT for pandemic surveillance., Methods: Between December 15, 2021 and February 5, 2022, a stepped wedge cluster randomized trial was run in which Santa Clara County ZIP Codes progressively transitioned from manual to automated CICT. Eleven individual-level data fields on demographics and disease dynamics were observed for non-response. The data contains 106,522 positive cases across 29 ZIP Codes., Findings: Automated CICT reduced overall collected information by 29 percentage points (SE = 0.08, p  < 0.01), as well as the response rate for individual fields. However, we find no evidence of differences in information loss by race or ethnicity., Interpretations: Automated CICT can serve as a useful alternative to manual CICT, with no substantial evidence of skewing data along racial or ethnic lines, but manual CICT improves completeness of key data for monitoring epidemiologic patterns., Funding: This research was supported in part by the Stanford Office of Community Engagement and the Stanford Institute for Human-Centered Artificial Intelligence., Competing Interests: The authors declare no competing interest., (© 2022 The Author(s).)

Background: Outbreaks of SARS-CoV-2 in long-term care facilities (LTCFs) cause significant morbidity and mortality. Mapping viral transmission within and between facilities by combining genomic sequencing with epidemiologic investigations enables targeting infection-control interventions., Methods: We conducted weekly surveillance of residents and staff in LTCFs in Santa Clara County, California, with ≥1 confirmed COVID-19 case between March and July 2020. Positive samples were referred for whole-genome sequencing. Epidemiological investigations and phylogenetic analyses of the largest outbreaks (>30 cases) were carried out in 6 LTCFs (Facilities A through F)., Results: Among the 61 LTCFs in the county, 41 had ≥1 confirmed case during the study period, triggering weekly SARS-CoV-2 testing. The 6 largest outbreaks accounted for 60% of cases and 90% of deaths in LTCFs, although the bed capacity of these facilities represents only 11% of the LTCF beds in the county. Phylogenetic analysis of 196 whole-genome sequences recovered from those facilities showed that each outbreak was monophyletic, with staff and residents sharing a common viral lineage. Outbreak investigations revealed that infected staff members often worked at multiple facilities, and in 1 instance, a staff member infected while working in 1 facility was the likely index case in another., Conclusions: We detected a pattern of rapid and sustained transmission after a single introduction of SARS-CoV-2 in 6 large LTCF outbreaks, with staff playing a key role in transmission within and between facilities. Infection control, testing, and occupational policies to reduce exposure and transmission risk for staff are essential components to keeping facility residents safe., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)