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.

Associations Between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants and Risk of Coronavirus Disease 2019 (COVID-19) Hospitalization Among Confirmed Cases in Washington State: A Retrospective Cohort Study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is dominated by variant viruses; the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with 7 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. METHODS: Our study includes individuals with positive SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) in the Washington Disease Reporting System with available viral genome data, from 1 December 2020 to 14 January 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. RESULTS: In total, 58 848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95% confidence interval [CI] 2.40-4.26), Beta (HR 2.85, 95% CI 1.56-5.23), Delta (HR 2.28 95% CI 1.56-3.34), or Alpha (HR 1.64, 95% CI 1.29-2.07) compared to infections with ancestral lineages; Omicron (HR 0.92, 95% CI .56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. CONCLUSIONS: Infection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.

The Lines That Held Us: Assessing Racial and Socioeconomic Disparities in SARS-CoV-2 Testing.

BACKGROUND: Racial disparities in SARS-CoV-2 prevalence are apparent. Race is a sociocultural construct, necessitating investigation into how sociocultural factors contribute. METHODS: This cross-sectional study linked laboratory data of adult patients between February 29 and May 15, 2020 with socio-demographics variables from the 2018 American Community Survey (ACS). Medical sites included healthcare organizations in Michigan, New York, North Carolina, California, Florida, Pennsylvania, and Washington. Race was treated as a proxy for racism and not biological essentialism. Laboratory data included patient age, sex, race, ethnicity, test result, test location, and residential ZIP code. ACS data included economic and educational variables contributing to an SES Index, population density, proportion Medicaid, and racial composition for corresponding ZIP code. Associations between race/socioeconomic variables and test results were examined using odds ratios (OR). RESULTS: Of 126 452 patients [mean (SD) age 51.9 (18.4) years; 52 747 (41.7%) men; 68 856 (54.5%) White and 27 805 (22.0%) Black], 18 905 (15.0%) tested positive. Of positive tests, 5238 (SD 27.7%) were White and 7223 (SD 38.2%) were Black. Black race increased the odds of a positive test; this finding was consistent across sites [OR 2.11 (95% CI 1.95-2.29)]. When subset by race, higher SES increased the odds of a positive test for White patients [OR 1.10 (95% CI 1.05-1.16)] but decreased the odds for Black patients [OR 0.92 (95% CI 0.86-0.99)]. Black patients, but not White patients, who tested positive overwhelmingly resided in more densely populated areas. CONCLUSIONS: Black race was associated with SARS-CoV-2 positivity and the relationship between SES and test positivity differed by race, suggesting the impact of socioeconomic status on test positivity is race-specific.

Hospitalization and mortality associated with SARS-CoV-2 viral clades in COVID-19.

The COVID-19 epidemic of 2019-20 is due to the novel coronavirus SARS-CoV-2. Following first case description in December, 2019 this virus has infected over 10 million individuals and resulted in at least 500,000 deaths world-wide. The virus is undergoing rapid mutation, with two major clades of sequence variants emerging. This study sought to determine whether SARS-CoV-2 sequence variants are associated with differing outcomes among COVID-19 patients in a single medical system. Whole genome SARS-CoV-2 RNA sequence was obtained from isolates collected from patients registered in the University of Washington Medicine health system between March 1 and April 15, 2020. Demographic and baseline clinical characteristics of patients and their outcome data including their hospitalization and death were collected. Statistical and machine learning models were applied to determine if viral genetic variants were associated with specific outcomes of hospitalization or death. Full length SARS-CoV-2 sequence was obtained 190 subjects with clinical outcome data. 35 (18.4%) were hospitalized and 14 (7.4%) died from complications of infection. A total of 289 single nucleotide variants were identified. Clustering methods demonstrated two major viral clades, which could be readily distinguished by 12 polymorphisms in 5 genes. A trend toward higher rates of hospitalization of patients with Clade 2 infections was observed (p = 0.06, Fisher's exact). Machine learning models utilizing patient demographics and co-morbidities achieved area-under-the-curve (AUC) values of 0.93 for predicting hospitalization. Addition of viral clade or sequence information did not significantly improve models for outcome prediction. In summary, SARS-CoV-2 shows substantial sequence diversity in a community-based sample. Two dominant clades of virus are in circulation. Among patients sufficiently ill to warrant testing for virus, no significant difference in outcomes of hospitalization or death could be discerned between clades in this sample. Major risk factors for hospitalization and death for either major clade of virus include patient age and comorbid conditions.

Performance Characteristics of the Abbott Architect SARS-CoV-2 IgG Assay and Seroprevalence in Boise, Idaho.

Coronavirus disease 2019 (COVID-19), the novel respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is associated with severe morbidity and mortality. The rollout of diagnostic testing in the United States was slow, leading to numerous cases that were not tested for SARS-CoV-2 in February and March 2020 and necessitating the use of serological testing to determine past infections. Here, we evaluated the Abbott SARS-CoV-2 IgG test for detection of anti-SARS-CoV-2 IgG antibodies by testing 3 distinct patient populations. We tested 1,020 serum specimens collected prior to SARS-CoV-2 circulation in the United States and found one false positive, indicating a specificity of 99.90%. We tested 125 patients who tested reverse transcription-PCR (RT-PCR) positive for SARS-CoV-2 for whom 689 excess serum specimens were available and found that sensitivity reached 100% at day 17 after symptom onset and day 13 after PCR positivity. Alternative index value thresholds for positivity resulted in 100% sensitivity and 100% specificity in this cohort. We tested specimens from 4,856 individuals from Boise, ID, collected over 1 week in April 2020 as part of the Crush the Curve initiative and detected 87 positives for a positivity rate of 1.79%. These data demonstrate excellent analytical performance of the Abbott SARS-CoV-2 IgG test as well as the limited circulation of the virus in the western United States. We expect that the availability of high-quality serological testing will be a key tool in the fight against SARS-CoV-2.

SARS-CoV-2 Viral Load on Admission Is Associated With 30-Day Mortality.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load on admission was associated with a significantly increased 30-day mortality (odds ratio [OR], 4.20; 95% CI, 1.62-10.86), and anti-SARS-CoV-2 nucleocapisid IgG seropositivity on admission trended toward a reduced 30-day mortality (OR, 0.43; 95% CI, 0.15-1.26). Reporting of quantitative SARS-CoV-2 viral load and serologic assays may offer prognostic clinical information.

Outcomes associated with SARS-CoV-2 viral clades in COVID-19.

Background The COVID-19 epidemic of 2019-20 is due to the novel coronavirus SARS-CoV-2. Following first case description in December, 2019 this virus has infected over 10 million individuals and resulted in at least 500,000 deaths world-wide. The virus is undergoing rapid mutation, with two major clades of sequence variants emerging. This study sought to determine whether SARS-CoV-2 sequence variants are associated with differing outcomes among COVID-19 patients in a single medical system. Methods Whole genome SARS-CoV-2 RNA sequence was obtained from isolates collected from patients registered in the University of Washington Medicine health system between March 1 and April 15, 2020. Demographic and baseline medical data along with outcomes of hospitalization and death were collected. Statistical and machine learning models were applied to determine if viral genetic variants were associated with specific outcomes of hospitalization or death. Findings Full length SARS-CoV-2 sequence was obtained 190 subjects with clinical outcome data. 35 (18.4%) were hospitalized and 14 (7.4%) died from complications of infection. A total of 289 single nucleotide variants were identified. Clustering methods demonstrated two major viral clades, which could be readily distinguished by 12 polymorphisms in 5 genes. A trend toward higher rates of hospitalization of patients with Clade 2 was observed (p=0.06). Machine learning models utilizing patient demographics and co-morbidities achieved area-under-the-curve (AUC) values of 0.93 for predicting hospitalization. Addition of viral clade or sequence information did not significantly improve models for outcome prediction. Conclusion SARS-CoV-2 shows substantial sequence diversity in a community-based sample. Two dominant clades of virus are in circulation. Among patients sufficiently ill to warrant testing for virus, no significant difference in outcomes of hospitalization or death could be discerned between clades in this sample. Major risk factors for hospitalization and death for either major clade of virus include patient age and comorbid conditions.

Detection of SARS-CoV-2 by bronchoscopy after negative nasopharyngeal testing: Stay vigilant for COVID-19.

PURPOSE: Real-time polymerase chain reaction (RT-PCR) detection of severe acute respiratory syndrome coronavirus (SARS-CoV-2) is required for diagnosis of coronavirus disease 2019 (COVID-19). Sensitivity of RT-PCR nasopharyngeal (NP) testing is presumed to be high, but there is no gold standard against which this has been determined. The objective was to determine whether lower respiratory tract infection (LRTI), detected in bronchoalveolar lavage fluid (BALF), occurs in the absence of upper respiratory tract infection with clinical testing of both specimen types. METHODS: Between March 26, 2020 and April 17, 2020 at the University of Washington Medical Center all patients with BALF specimens clinically tested for SARS-CoV-2 were identified. We assessed the proportion of patients with positive RT-PCR for SARS-CoV-2 in BALF after negative NP testing. We describe 3 cases with positive testing in BALF. RESULTS: Among 16 patients with BALF samples, 3 cases (19%) had SARS-CoV-2 detected in BALF. In Case 1, negative NP testing occurred early in the infection and respiratory symptoms may have been missed due to neurologic injury. In Case 2, outpatient diagnosis was aspiration pneumonia, but clinical suspicion remained high for COVID-19 at hospitalization based on epidemiological and clinical features. All 3 cases involved older adults (age >65 years), one of whom was immunosuppressed in the setting of lung transplantation (Case 3). CONCLUSIONS: These data demonstrate that SARS-CoV-2 LRTI occurs in the presence of negative NP testing. NP testing may underestimate the prevalence of COVID-19 and has implications for spread of SARS-CoV2 in the community and healthcare setting.

Responding to COVID-19: The UW Medicine Information Technology Services Experience.

BACKGROUND: UW Medicine was one of the first health systems to encounter and treat COVID-19 patients in the United States, starting in late February 2020. OBJECTIVE: Here we describe the rapid rollout of capabilities by UW Medicine Information Technology Services (ITS) to support our clinical response to the COVID-19 pandemic and provide recommendations for health systems to urgently consider, as they plan their own response to this and potentially other future pandemics. METHODS: Our recommendations include establishing a hospital incident command structure that includes tight integration with IT, creating automated dashboards for incident command, optimizing emergency communication to staff and patients, and preparing human resources, security, other policies, and equipment to support the transition of all nonessential staff to telework.We describe how UW Medicine quickly expanded telemedicine capabilities to include most primary care providers and increasing numbers of specialty providers. We look at how we managed expedited change control processes to quickly update electronic health records (EHR) with new COVID-19 laboratory and clinical workflows. We also examine the integration of new technology such as tele-intensive care (ICU) equipment and improved integration with teleconferencing software into our EHR. To support the rapid preparation for COVID-19 at other health systems, we include samples of the UW Medicine's COVID-19 order set, COVID-19 documentation template, dashboard metric categories, and a list of the top 10 things your health care IT organization can do now to prepare. CONCLUSION: The COVID-19 response requires new and expedited ways of approaching ITS support to clinical needs. UW Medicine ITS leadership hope that by quickly sharing our nimble response to clinical and operational requests, we can help other systems prepare to respond to this public health emergency.