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Nature ; 609(7925): 101-108, 2022 09.
Article in English | MEDLINE | ID: covidwho-1921636


As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1-3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

COVID-19 , SARS-CoV-2 , Wastewater-Based Epidemiological Monitoring , Wastewater , COVID-19/epidemiology , COVID-19/transmission , COVID-19/virology , Humans , RNA, Viral/analysis , RNA, Viral/genetics , SARS-CoV-2/classification , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Sequence Analysis, RNA , Wastewater/virology
J Am Coll Health ; 70(7): 1968-1974, 2022 10.
Article in English | MEDLINE | ID: covidwho-919339


ObjectiveTo detail the implementation, benefits and challenges of onboarding campus-based health services onto a health system's electronic health record.ParticipantsUC San Diego Student Health and Well-Being offers medical services to over 39,000 students. UC San Diego Health is an academic medical center.Methods20 workstreams and 9 electronic modules, systems, or interfaces were converted to new electronic systems.Results36,023 student-patient medical records were created. EHR-integration increased security while creating visibility to 19,700 shared patient visits and records from 236 health systems across the country over 6 months. Benefits for the COVID-19 response included access to screening tools, decision support, telehealth, patient alerting system, reporting and analytics, COVID-19 dashboard, and increased testing capabilities.ConclusionIntegration of an interoperable EHR between neighboring campus-based health services and an affiliated academic medical center can streamline case management, improve quality and safety, and increase access to valuable health resources in times of need. Pertinent examples during the COVID-19 pandemic included uninterrupted and safe provision of clinical services through access to existing telehealth platforms and increased testing capacity.

COVID-19 , Telemedicine , Humans , Pandemics/prevention & control , Students , Universities