Risk of post-acute sequelae of SARS-CoV-2 infection associated with pre-coronavirus disease obstructive sleep apnea diagnoses: an electronic health record-based analysis from the RECOVER initiative.

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) has been associated with more severe acute coronavirus disease-2019 (COVID-19) outcomes. We assessed OSA as a potential risk factor for Post-Acute Sequelae of SARS-CoV-2 (PASC). METHODS: We assessed the impact of preexisting OSA on the risk for probable PASC in adults and children using electronic health record data from multiple research networks. Three research networks within the REsearching COVID to Enhance Recovery initiative (PCORnet Adult, PCORnet Pediatric, and the National COVID Cohort Collaborative [N3C]) employed a harmonized analytic approach to examine the risk of probable PASC in COVID-19-positive patients with and without a diagnosis of OSA prior to pandemic onset. Unadjusted odds ratios (ORs) were calculated as well as ORs adjusted for age group, sex, race/ethnicity, hospitalization status, obesity, and preexisting comorbidities. RESULTS: Across networks, the unadjusted OR for probable PASC associated with a preexisting OSA diagnosis in adults and children ranged from 1.41 to 3.93. Adjusted analyses found an attenuated association that remained significant among adults only. Multiple sensitivity analyses with expanded inclusion criteria and covariates yielded results consistent with the primary analysis. CONCLUSIONS: Adults with preexisting OSA were found to have significantly elevated odds of probable PASC. This finding was consistent across data sources, approaches for identifying COVID-19-positive patients, and definitions of PASC. Patients with OSA may be at elevated risk for PASC after SARS-CoV-2 infection and should be monitored for post-acute sequelae.

Relative validity of a Diet Risk Score (DRS) for Chinese American adults

ObjectiveThe objective of this study was to evaluate the relative validity of the nine-item Diet Risk Score (DRS) among Chinese American adults using Healthy Eating Index (HEI)-2015 scores. We provide insights into the application of the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) for this population, and report on lessons learned from carrying out participant recruitment during the COVID-19 pandemic.MethodsThirty-three Chinese American adults (mean age=40;36% male) were recruited from the community and through ResearchMatch. Participants completed the DRS and two 24-hour food records, which were entered into the ASA 24-Hour Dietary Assessment Tool (ASA24) by community health workers (CHWs). HEI-2015 scores were calculated from each food record and an average score was obtained for each participant. One-way analysis of variance and Spearman correlations were used to compare total and component scores between the DRS and HEI-2015.ResultsMean HEI-2015 score was 56.7/100 (SD 10.6) and mean DRS score was 11.8/27 (SD 4.7), with higher scores reflecting better and worse diets, respectively. HEI-2015 and DRS scores were inversely correlated (r=−0.43, p<0.05). The strongest correlations were between HEI-2015 Total Vegetables and DRS Vegetables (r=−0.5, p<0.01), HEI-2015 Total Vegetables and Green Vegetables (r=−0.43, p=0.01) and HEI-2015 Seafood/Plant Protein and DRS Fish (r=−0.47, p<0.01). The inability to advertise and recruit for the study in person at community centres due to pandemic restrictions impeded the recruitment of less-acculturated individuals. A lack of cultural food items in the ASA24 database made it difficult to record dietary intake as reported by participants.ConclusionThe DRS can be a valuable tool for physicians to identify and reach Chinese Americans at risk of cardiometabolic disease.

Online Grocery Shopping Behaviors and Attitudes Among Asian Americans.

How online grocery shopping behaviors differ among Asian American (AA) ethnic subgroups and acculturation level is unknown. From June 9-15, 2020, we administered an online survey to a nationally-derived nonprobability sample of 2,895 AA adults, including 1,737 East, 570 South, and 587 Southeast Asian adults, assessing online grocery shopping (yes/no, frequency, reasons). We used logistic regression to compare responses by subgroup and acculturation score, controlling for sociodemographics. Thirty-percent of participants reported shopping online for groceries in a typical month, with a higher percentage among South (45%) versus East Asian adults (23%). Participants with low (vs. high) acculturation scores were more likely to report a lack of special foods (OR = 0.7; 95% CI: 0.5-0.98) and poor food quality (OR = 0.6; 95% CI: 0.4-0.7) as preventing them from shopping online. Online grocery shopping has the capacity to address inequities in health, potentially via culturally-tailored programs designed for less-acculturated AA adults.

Rapid Community Engagement in Response to SARS-CoV-2 Funding Opportunities: New York City, 2020–2021

In response to fast-turnaround funding opportunities, collaborations have been forming across the country to address severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disparities. Here we describe the process, notes from the field, and evaluation results from a new collaboration involving multiple partners, formed in October 2020 in New York City as part of the Rapid Acceleration of Diagnostics initiative. We used the validated Research Engagement Survey Tool to evaluate the partnership. Results can inform future research and improve engagement efforts aimed at reducing SARS-CoV-2 disparities. (AmJ Public Health. 2022;112(S9):S904-S908. https://doi.org/10.2105/AJPH. 2022.307072)

Disparities in routine healthcare utilization disruptions during COVID-19 pandemic among veterans with type 2 diabetes.

BACKGROUND: While emerging studies suggest that the COVID-19 pandemic caused disruptions in routine healthcare utilization, the full impact of the pandemic on healthcare utilization among diverse group of patients with type 2 diabetes is unclear. The purpose of this study is to examine trends in healthcare utilization, including in-person and telehealth visits, among U.S. veterans with type 2 diabetes before, during and after the onset of the COVID-19 pandemic, by demographics, pre-pandemic glycemic control, and geographic region. METHODS: We longitudinally examined healthcare utilization in a large national cohort of veterans with new diabetes diagnoses between January 1, 2008 and December 31, 2018. The analytic sample was 733,006 veterans with recently-diagnosed diabetes, at least 1 encounter with veterans administration between March 2018-2020, and followed through March 2021. Monthly rates of glycohemoglobin (HbA1c) measurements, in-person and telehealth outpatient visits, and prescription fills for diabetes and hypertension medications were compared before and after March 2020 using interrupted time-series design. Log-linear regression model was used for statistical analysis. Secular trends were modeled with penalized cubic splines. RESULTS: In the initial 3 months after the pandemic onset, we observed large reductions in monthly rates of HbA1c measurements, from 130 (95%CI,110-140) to 50 (95%CI,30-80) per 1000 veterans, and in-person outpatient visits, from 1830 (95%CI,1640-2040) to 810 (95%CI,710-930) per 1000 veterans. However, monthly rates of telehealth visits doubled between March 2020-2021 from 330 (95%CI,310-350) to 770 (95%CI,720-820) per 1000 veterans. This pattern of increases in telehealth utilization varied by community type, with lowest increase in rural areas, and by race/ethnicity, with highest increase among non-hispanic Black veterans. Combined in-person and telehealth outpatient visits rebounded to pre-pandemic levels after 3 months. Despite notable changes in HbA1c measurements and visits during that initial window, we observed no changes in prescription fills rates. CONCLUSIONS: Healthcare utilization among veterans with diabetes was substantially disrupted at the onset of the pandemic, but rebounded after 3 months. There was disparity in uptake of telehealth visits by geography and race/ethnicity.

Attitudes, perceptions, and preferences towards SARS CoV-2 testing and vaccination among African American and Hispanic public housing residents, New York City: 2020-2021.

BACKGROUND: African American and Hispanic populations have been affected disproportionately by COVID-19. Reasons are multifactorial and include social and structural determinants of health. During the onset and height of the pandemic, evidence suggested decreased access to SARS CoV-2 testing. In 2020, the National Institutes of Health launched the Rapid Acceleration of Diagnostics (RADx)- Underserved Populations initiative to improve SARS CoV-2 testing in underserved communities. In this study, we explored attitudes, experiences, and barriers to SARS CoV-2 testing and vaccination among New York City public housing residents. METHODS: Between December 2020 and March 2021, we conducted 9 virtual focus groups among 36 low-income minority residents living in New York City public housing. RESULTS: Among residents reporting a prior SARS CoV-2 test, main reasons for testing were to prepare for a medical procedure or because of a high-risk exposure. Barriers to testing included fear of discomfort from the nasal swab, fear of exposure to COVID-19 while traveling to get tested, concerns about the consequences of testing positive and the belief that testing was not necessary. Residents reported a mistrust of information sources and the health care system in general; they depended more on "word of mouth" for information. The major barrier to vaccination was lack of trust in vaccine safety. Residents endorsed more convenient testing, onsite testing at residential buildings, and home self-test kits. Residents also emphasized the need for language-concordant information sharing and for information to come from "people who look like [them] and come from the same background as [them]". CONCLUSIONS: Barriers to SARS CoV-2 testing and vaccination centered on themes of a lack of accurate information, fear, mistrust, safety, and convenience. Resident-endorsed strategies to increase testing include making testing easier to access either through home or onsite testing locations. Education and information sharing by trusted members of the community are important tools to combat misinformation and build trust.

Accessibility of HIV Services in Philadelphia: Location-Allocation Analysis.

INTRODUCTION: As the first step in the HIV care continuum, timely diagnosis is central to reducing transmission of the virus and ending the HIV epidemic. Studies have shown that distance from a testing site is essential for ease of access to services and educational material. This study shows how location-allocation analysis can be used to improve allocation of HIV testing services utilizing existing publicly available data from 2015 to 2019 on HIV prevalence, testing site location, and factors related to HIV in Philadelphia, Pennsylvania. METHODS: The ArcGIS Location-Allocation analytic tool was used to calculate locations for HIV testing sites using a method that minimizes the distance between demand-point locations and service facilities. ZIP code level demand was initially specified on the basis of the percentage of late HIV diagnoses and in a sensitivity analysis on the basis of a composite of multiple factors. Travel time and distance from demand to facilities determined the facility location allocation. This analysis was conducted from 2021 to 2022. RESULTS: Compared with the 37 facilities located in 20 (43%) Philadelphia ZIP codes, the model proposed reallocating testing facilities to 37 (79%) ZIP codes using percent late diagnoses to define demand. On average, this would reduce distance to the facilities by 65% and travel time to the facilities by 56%. Results using the sensitivity analysis were similar. CONCLUSIONS: A wider distribution of HIV testing services across the city of Philadelphia may reduce distance and travel time to facilities, improve accessibility of testing, and in turn increase the percentage of people with knowledge of their status.

Rapid Community Engagement in Response to SARS-CoV-2 Funding Opportunities: New York City, 2020‒2021.

In response to fast-turnaround funding opportunities, collaborations have been forming across the country to address severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disparities. Here we describe the process, notes from the field, and evaluation results from a new collaboration involving multiple partners, formed in October 2020 in New York City as part of the Rapid Acceleration of Diagnostics initiative. We used the validated Research Engagement Survey Tool to evaluate the partnership. Results can inform future research and improve engagement efforts aimed at reducing SARS-CoV-2 disparities. (Am J Public Health. 2022;112(S9):S904-S908. https://doi.org/10.2105/AJPH.2022.307072).

Gut microbiome dysbiosis in antibiotic-treated COVID-19 patients is associated with microbial translocation and bacteremia.

Although microbial populations in the gut microbiome are associated with COVID-19 severity, a causal impact on patient health has not been established. Here we provide evidence that gut microbiome dysbiosis is associated with translocation of bacteria into the blood during COVID-19, causing life-threatening secondary infections. We first demonstrate SARS-CoV-2 infection induces gut microbiome dysbiosis in mice, which correlated with alterations to Paneth cells and goblet cells, and markers of barrier permeability. Samples collected from 96 COVID-19 patients at two different clinical sites also revealed substantial gut microbiome dysbiosis, including blooms of opportunistic pathogenic bacterial genera known to include antimicrobial-resistant species. Analysis of blood culture results testing for secondary microbial bloodstream infections with paired microbiome data indicates that bacteria may translocate from the gut into the systemic circulation of COVID-19 patients. These results are consistent with a direct role for gut microbiome dysbiosis in enabling dangerous secondary infections during COVID-19.

Post-acute sequelae of COVID-19 symptom phenotypes and therapeutic strategies: A prospective, observational study.

BACKGROUND: Post-acute sequelae of COVID-19 (PASC) includes a heterogeneous group of patients with variable symptomatology, who may respond to different therapeutic interventions. Identifying phenotypes of PASC and therapeutic strategies for different subgroups would be a major step forward in management. METHODS: In a prospective cohort study of patients hospitalized with COVID-19, 12-month symptoms and quantitative outcome metrics were collected. Unsupervised hierarchical cluster analyses were performed to identify patients with: (1) similar symptoms lasting ≥4 weeks after acute SARS-CoV-2 infection, and (2) similar therapeutic interventions. Logistic regression analyses were used to evaluate the association of these symptom and therapy clusters with quantitative 12-month outcome metrics (modified Rankin Scale, Barthel Index, NIH NeuroQoL). RESULTS: Among 242 patients, 122 (50%) reported ≥1 PASC symptom (median 3, IQR 1-5) lasting a median of 12-months (range 1-15) post-COVID diagnosis. Cluster analysis generated three symptom groups: Cluster1 had few symptoms (most commonly headache); Cluster2 had many symptoms including high levels of anxiety and depression; and Cluster3 primarily included shortness of breath, headache and cognitive symptoms. Cluster1 received few therapeutic interventions (OR 2.6, 95% CI 1.1-5.9), Cluster2 received several interventions, including antidepressants, anti-anxiety medications and psychological therapy (OR 15.7, 95% CI 4.1-59.7) and Cluster3 primarily received physical and occupational therapy (OR 3.1, 95%CI 1.3-7.1). The most severely affected patients (Symptom Cluster 2) had higher rates of disability (worse modified Rankin scores), worse NeuroQoL measures of anxiety, depression, fatigue and sleep disorder, and a higher number of stressors (all P<0.05). 100% of those who received a treatment strategy that included psychiatric therapies reported symptom improvement, compared to 97% who received primarily physical/occupational therapy, and 83% who received few interventions (P = 0.042). CONCLUSIONS: We identified three clinically relevant PASC symptom-based phenotypes, which received different therapeutic interventions with varying response rates. These data may be helpful in tailoring individual treatment programs.

ACE2-containing defensosomes serve as decoys to inhibit SARS-CoV-2 infection.

Extracellular vesicles of endosomal origin, exosomes, mediate intercellular communication by transporting substrates with a variety of functions related to tissue homeostasis and disease. Their diagnostic and therapeutic potential has been recognized for diseases such as cancer in which signaling defects are prominent. However, it is unclear to what extent exosomes and their cargo inform the progression of infectious diseases. We recently defined a subset of exosomes termed defensosomes that are mobilized during bacterial infection in a manner dependent on autophagy proteins. Through incorporating protein receptors on their surface, defensosomes mediated host defense by binding and inhibiting pore-forming toxins secreted by bacterial pathogens. Given this capacity to serve as decoys that interfere with surface protein interactions, we investigated the role of defensosomes during infection by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiological agent of Coronavirus Disease 2019 (COVID-19). Consistent with a protective function, exosomes containing high levels of the viral receptor ACE2 in bronchoalveolar lavage fluid (BALF) from critically ill COVID-19 patients was associated with reduced intensive care unit (ICU) and hospitalization times. We found ACE2+ exosomes were induced by SARS-CoV-2 infection and activation of viral sensors in cell culture, which required the autophagy protein ATG16L1, defining these as defensosomes. We further demonstrate that ACE2+ defensosomes directly bind and block viral entry. These findings suggest that defensosomes may contribute to the antiviral response against SARS-CoV-2 and expand our knowledge on the regulation and effects of extracellular vesicles during infection.

Building Public Health Surveillance 3.0: Emerging Timely Measures of Physical, Economic, and Social Environmental Conditions Affecting Health.

In response to rapidly changing societal conditions stemming from the COVID-19 pandemic, we summarize data sources with potential to produce timely and spatially granular measures of physical, economic, and social conditions relevant to public health surveillance, and we briefly describe emerging analytic methods to improve small-area estimation. To inform this article, we reviewed published systematic review articles set in the United States from 2015 to 2020 and conducted unstructured interviews with senior content experts in public heath practice, academia, and industry. We identified a modest number of data sources with high potential for generating timely and spatially granular measures of physical, economic, and social determinants of health. We also summarized modeling and machine-learning techniques useful to support development of time-sensitive surveillance measures that may be critical for responding to future major events such as the COVID-19 pandemic. (Am J Public Health. 2022;112(10):1436-1445. https://doi.org/10.2105/AJPH.2022.306917).

Validation of a neighborhood-level COVID Local Risk Index in 47 large U.S. cities.

OBJECTIVES: To present the COVID Local Risk Index (CLRI), a measure of city- and neighborhood-level risk for SARS COV-2 infection and poor outcomes, and validate it using sub-city SARS COV-2 outcome data from 47 large U.S. cities. METHODS: Cross-sectional validation analysis of CLRI against SARS COV-2 incidence, percent positivity, hospitalization, and mortality. CLRI scores were validated against ZCTA-level SARS COV-2 outcome data gathered in 2020-2021 from public databases or through data use agreements using a negative binomial model. RESULTS: CLRI was associated with each SARS COV-2 outcome in pooled analysis. In city-level models, CLRI was positively associated with positivity in 11/14 cities for which data were available, hospitalization in 6/6 cities, mortality in 13/14 cities, and incidence in 33/47 cities. CONCLUSIONS: CLRI is a valid tool for assessing sub-city risk of SARS COV-2 infection and illness severity. Stronger associations with positivity, hospitalization and mortality may reflect differential testing access, greater weight on components associated with poor outcomes than transmission, omitted variable bias, or other reasons. City stakeholders can use the CLRI, publicly available on the City Health Dashboard (www.cityhealthdashboard.com), to guide SARS COV-2 resource allocation.

Data Dashboards for Advancing Health and Equity: Proving Their Promise?

Some analyze health and health equity data to distinct geographic boundaries.3 Others present and disseminate a new metric.4 Still others aggregate local policies and laws that affect population health to guide research and advocacy.5 During the rapidly unfolding COVID-19 pandemic, many state and local health departments struggled to make data publicly available, and the Johns Hopkins University COVID Tracker quickly became the "go-to" data source for by-the-day counts of COVID-19 cases, deaths, tests, and vaccinations.6 Other COVID-19 dashboards have since drawn explicit attention to COVID-19 inequities7-9 (see Table 1 for examples). [...]quantitative indicators of a dashboard's usefulness must also be measured, including visit and revisit frequency data from Web site analytics, as well as media, social media, and scientific article citations.10 Dashboards generally seek to "liberate" access to data. [...]in early 2020, the Opportunity Atlas team at Harvard University used data from private companies to add granular measures of local shifts in economic activity resulting from pandemic shutdowns.12 The City Health Dashboard added a census tract-level measure of COVID-19 local riskto guide local testing and vaccination efforts.3 Rigorous methods to measure a dashboard's actual impact on health and health equity are more elusive. The more complex a Web site is in terms of data and functionality (e.g., number of metrics, number of underlying data sources, range of geographies, comparison functions, multiyear data), the more staff time is required to ensure that all facets are updated regularly. Because of this, and because there will always be salient new and creative ways to combine data, we anticipate that health data dashboards will continue to be developed by both public and nonpublic actors, with financial support from foundation and federal agency grants.

Pathogen Species Is Associated With Mortality in Nosocomial Bloodstream Infection in Patients With COVID-19.

Background: The epidemiology of nosocomial bloodstream infections (NBSIs) in patients with coronavirus disease 2019 (COVID-19) is poorly understood, due in part to substantial disease heterogeneity resulting from multiple potential pathogens. Methods: We identified risk factors for NBSIs and examined the association between NBSIs and mortality in a retrospective cohort of patients hospitalized with COVID-19 in 2 New York City hospitals during the height of the pandemic. We adjusted for the potential effects of factors likely to confound that association, including age, race, illness severity upon admission, and underlying health status. Results: Between January 1 and October 1, 2020, 1403 patients had a positive blood culture, and 79 and 101 met the stringent criteria for NBSI among non-COVID-19 and COVID-19 patients, respectively. NBSIs occurred almost exclusively among patients who were severely ill with COVID-19 at hospital admission. NBSIs were associated with elevated mortality, even after adjusting for baseline differences in COVID-19 illness (55% cases vs 45% controls; P = .13). Mortality was concentrated in patients with early-onset pneumonia caused by S. aureus and gram-negative bacteria. Less virulent Candida (49%) and Enterococcus (12%) species were the predominant cause of NBSI in the latter stages of hospitalization, after antibiotic treatment and COVID-19 treatments that attenuate immune response. Most Enterococcus and Candida infections did not have an identifiable source and were not associated with common risk factors for infection by these organisms. Conclusions: Pathogen species and mortality exhibited temporal differences. Early recognition of risk factors among COVID-19 patients could potentially decrease NBSI-associated mortality through early COVID-19 and antimicrobial treatment.

Self-Assessed Severity as a Determinant of Coronavirus Disease 2019 Symptom Specificity: A Longitudinal Cohort Study.

Coronavirus disease 2019 symptom definitions rarely include symptom severity. We collected daily nasal swab samples and symptom diaries from contacts of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) case patients. Requiring ≥1 moderate or severe symptom reduced sensitivity to predict SARS-CoV-2 shedding from 60.0% (95% confidence interval [CI], 52.9%-66.7%) to 31.5% (95% CI, 25.7%- 38.0%) but increased specificity from 77.5% (95% CI, 75.3%-79.5%) to 93.8% (95% CI, 92.7%-94.8%).

Pathogen Species is Associated With Mortality in Nosocomial Bloodstream Infection in Patients with COVID-19

Background The epidemiology of nosocomial bloodstream infections (NBSI) in patients with coronavirus disease 2019 (COVID-19) is poorly understood, due in part to substantial disease heterogeneity resulting from multiple potential pathogens. Methods We identified risk factors for NBSI and examined the association between NBSI and mortality in a retrospective cohort of patients hospitalized with COVID-19 in two New York City hospitals during the pandemic height. We adjusted for the potential effects of factors likely to confound that association, including age, race, illness severity upon admission and underlying health status. Results Between January 1-October 1, 2020, 1403 patients had a positive blood culture, 79 and 101 met stringent criteria of NBSI among non-COVID-19 and COVID-19 patients, respectively. NBSI occurred almost exclusively among patients who were severely ill with COVID-19 at hospital admission. NBSI were associated with elevated mortality, even after adjusting for baseline differences in COVID-19 illness (55% cases vs 45% controls,p= 0.13). Mortality was concentrated in patients with early onset pneumonia caused by S. aureus and Gram-negative bacteria. Less virulent Candida (49%) and Enterococcus (12%) species were the predominant cause of NBSI in the latter stages of hospitalization, after antibiotic treatment and COVID-19 treatments that attenuate immune response. Most Enterococcus and Candida infections did not have an identifiable source and were not associated with common risk factors for infection by these organisms. Conclusions Pathogen species and mortality exhibited temporal differences. Early recognition of risk factors among COVID-19 patients could potentially decrease NBSI-associated mortality through early COVID-19 and antimicrobial treatment.

Trajectory of Viral RNA Load Among Persons With Incident SARS-CoV-2 G614 Infection (Wuhan Strain) in Association With COVID-19 Symptom Onset and Severity.

Importance: The SARS-CoV-2 viral trajectory has not been well characterized in incident infections. These data are needed to inform natural history, prevention practices, and therapeutic development. Objective: To characterize early SARS-CoV-2 viral RNA load (hereafter referred to as viral load) in individuals with incident infections in association with COVID-19 symptom onset and severity. Design, Setting, and Participants: This prospective cohort study was a secondary data analysis of a remotely conducted study that enrolled 829 asymptomatic community-based participants recently exposed (<96 hours) to persons with SARS-CoV-2 from 41 US states from March 31 to August 21, 2020. Two cohorts were studied: (1) participants who were SARS-CoV-2 negative at baseline and tested positive during study follow-up, and (2) participants who had 2 or more positive swabs during follow-up, regardless of the initial (baseline) swab result. Participants collected daily midturbinate swab samples for SARS-CoV-2 RNA detection and maintained symptom diaries for 14 days. Exposure: Laboratory-confirmed SARS-CoV-2 infection. Main Outcomes and Measures: The observed SARS-CoV-2 viral load among incident infections was summarized, and piecewise linear mixed-effects models were used to estimate the characteristics of viral trajectories in association with COVID-19 symptom onset and severity. Results: A total of 97 participants (55 women [57%]; median age, 37 years [IQR, 27-52 years]) developed incident infections during follow-up. Forty-two participants (43%) had viral shedding for 1 day (median peak viral load cycle threshold [Ct] value, 38.5 [95% CI, 38.3-39.0]), 18 (19%) for 2 to 6 days (median Ct value, 36.7 [95% CI, 30.2-38.1]), and 31 (32%) for 7 days or more (median Ct value, 18.3 [95% CI, 17.4-22.0]). The cycle threshold value has an inverse association with viral load. Six participants (6%) had 1 to 6 days of viral shedding with censored duration. The peak mean (SD) viral load was observed on day 3 of shedding (Ct value, 33.8 [95% CI, 31.9-35.6]). Based on the statistical models fitted to 129 participants (60 men [47%]; median age, 38 years [IQR, 25-54 years]) with 2 or more SARS-CoV-2-positive swab samples, persons reporting moderate or severe symptoms tended to have a higher peak mean viral load than those who were asymptomatic (Ct value, 23.3 [95% CI, 22.6-24.0] vs 30.7 [95% CI, 29.8-31.4]). Mild symptoms generally started within 1 day of peak viral load, and moderate or severe symptoms 2 days after peak viral load. All 535 sequenced samples detected the G614 variant (Wuhan strain). Conclusions and Relevance: This cohort study suggests that having incident SARS-CoV-2 G614 infection was associated with a rapid viral load peak followed by slower decay. COVID-19 symptom onset generally coincided with peak viral load, which correlated positively with symptom severity. This longitudinal evaluation of the SARS-CoV-2 G614 with frequent molecular testing serves as a reference for comparing emergent viral lineages to inform clinical trial designs and public health strategies to contain the spread of the virus.

The COVID-19 Healthcare Personnel Study (CHPS): Overview, Methods, and Preliminary Findings.

INTRODUCTION: The COVID-19 Healthcare Personnel Study (CHPS) was designed to assess adverse short-term and long-term physical and mental health impacts of the coronavirus disease-2019 (COVID-19) pandemic on New York's physicians, nurse practitioners, and physician assistants. METHODS: Online population-based survey. Survey-weighted descriptive results, frequencies, proportions, and means, with 95% confidence intervals (95% CI). Odds ratios (ORs) for association. RESULTS: Over half (51.5%; 95% CI: 49.1, 54.0) of respondents worked directly with COVID-19 patients; 27.3% (95% CI: 22.5, 32.2) tested positive. The majority (57.6%; 95% CI: 55.2, 60.0) reported a negative impact on their mental health. Negative mental health was associated with COVID-19 symptoms (OR=1.7, 95% CI: 1.3, 2.1) and redeployment to unfamiliar functions (OR=1.3, 95% CI: 1.1, 1.6). CONCLUSIONS: A majority of New York health care providers treated COVID-19 patients and reported a negative impact on their mental health.