Psychometric analysis of the modified Covid-19 Yorkshire Rehabilitation Scale (C19-YRSm) in a prospective multicentre study (preprint)

BckgroundLong COVID is a novel multisystem clinical syndrome affecting millions of individuals worldwide. The modified COVID-19 Yorkshire Rehabilitation Scale (C19-YRSm) is a condition-specific patient-reported outcome measure designed for assessment and monitoring of people with Long COVID (LC). ObjectivesTo evaluate the psychometric properties of the C19-YRSm in a prospective sample of people with Long COVID. Methods1314 patients attending UK specialist Long COVID clinics completed C19-YRSm and EQ-5D-5L longitudinally. Scale characteristics were derived for C19-YRSm subscales (Symptom Severity, SS; Functional Disability, FD; and Overall Health, OH) and internal consistency (Cronbachs alpha). Convergent validity was assessed using the FACIT-Fatigue scale. Known groups validity was assessed for the Other Symptoms (OS) subscale as tertiles, hospitalisation and intensive care admission. Responsiveness and test-retest reliability was evaluated for C19-YRSm subscales and EQ-5D-5L. The minimal important difference (MID) and minimal clinically important difference (MCID) were estimated. Confirmatory factor analysis was applied to determine the instruments two-factor structure. ResultsC19-YRSm demonstrated good scale characteristic properties. Item-total correlations were between 0.37 to 0.65 (for SS and FD), with good internal reliability (Cronbachs alphas >0.8). Item correlations between subscales ranged between 0.46 to 0.72. Convergent validity with FACIT was good (-0.46 to -0.62). The three subscales discriminated between different levels of symptom burden (p<0.001), and between patients admitted to hospital and intensive care. There was moderate responsiveness for the three subscales ranging from 0.22 (OH) to 0.50 (SS) and was greater than the EQ-5D-5L. Test-retest reliability was good for both SS 0.86 and FD 0.78. MID was 2 for SS, 2 for FD, and 1 for OH; MCID was 4 for both the SS and FD. The factor analysis supported the two-factor SS and FD structure. ConclusionsThe C19-YRSm is a condition-specific, reliable, valid, and responsive patient-reported outcome measure for Long COVID. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSLong Covid or Post-COVID-19 syndrome is a multisystem, fluctuating condition. C19-YRSm is literatures first condition-specific patient reported outcome measure which needed validation in a large population sample. What this study addsC19-YRSm is a valid, reliable, responsive and easy to administer measure which is able to show clinically meaningful change in the status of the condition in people living with Long Covid. How this study might affect research, practice or policyC19-YRSm can be used in clinical and research settings to reliably capture the condition trajectory and the effect of interventions and also help inform clinical policy.

Predicting Delayed Shock in Multisystem Inflammatory Disease in Children: A Multicenter Analysis From the New York City Tri-State Region.

OBJECTIVES: Patients with multisystem inflammatory disease in children (MIS-C) are at risk of developing shock. Our objectives were to determine independent predictors associated with development of delayed shock (≥3 hours from emergency department [ED] arrival) in patients with MIS-C and to derive a model predicting those at low risk for delayed shock. METHODS: We conducted a retrospective cross-sectional study of 22 pediatric EDs in the New York City tri-state area. We included patients meeting World Health Organization criteria for MIS-C and presented April 1 to June 30, 2020. Our main outcomes were to determine the association between clinical and laboratory factors to the development of delayed shock and to derive a laboratory-based prediction model based on identified independent predictors. RESULTS: Of 248 children with MIS-C, 87 (35%) had shock and 58 (66%) had delayed shock. A C-reactive protein (CRP) level greater than 20 mg/dL (adjusted odds ratio [aOR], 5.3; 95% confidence interval [CI], 2.4-12.1), lymphocyte percent less than 11% (aOR, 3.8; 95% CI, 1.7-8.6), and platelet count less than 220,000/uL (aOR, 4.2; 95% CI, 1.8-9.8) were independently associated with delayed shock. A prediction model including a CRP level less than 6 mg/dL, lymphocyte percent more than 20%, and platelet count more than 260,000/uL, categorized patients with MIS-C at low risk of developing delayed shock (sensitivity 93% [95% CI, 66-100], specificity 38% [95% CI, 22-55]). CONCLUSIONS: Serum CRP, lymphocyte percent, and platelet count differentiated children at higher and lower risk for developing delayed shock. Use of these data can stratify the risk of progression to shock in patients with MIS-C, providing situational awareness and helping guide their level of care.

Administration and Scoring Errors on the Woodcock–Johnson IV Tests of Achievement: Before and During COVID-19

Eighty Woodcock–Johnson IV Tests of Achievement protocols from 40 test administrators were examined to determine the types and frequencies of administration and scoring errors made. Non-critical errors (e.g., failure to record verbatim) were found on every protocol (M = 37.2). Critical (e.g., standard score, start point) errors were found on 98.8% of protocols (M = 15.3). Additionally, a series of paired samples t-test were conducted to determine differences in total, critical, and non-critical errors pre- and during-COVID-19. No statistic differences were found. Our findings add to a growing body of research that suggests that errors on norm-referenced tests of achievement are pervasive. However, the frequency of errors did not appear to be affected by COVID-19 stressors or social distancing requirements. Implications of these findings for training and practice are discussed. Suggestions for future research are also provided.

Geographic distribution of IBV lineages

Infectious bronchitis virus (IBV) is a leading cause of economic losses within the poultry industry, affecting both meat-type birds and layers. The highly contagious viral disease caused by Avian Coronavirus was first described in the 1930s and still remains a global problem for the poultry industry. Infection by Avian Coronavirus causes respiratory disease, nephritis, decreased egg produc­tion depending on the viral pathotype and the age of the affected flocks. Live attenuated and inactivated vaccines are used to control the disease, but poor cross-protection between different serotypes complicates control efforts. IBV exists in a wide variety of genetically distinct types and new variants are identi­fied relatively frequently. As the emergence of new IBV variants may impede the efficacy of the vaccines, monitoring the prevalence and genetic characteristics of IBV is of utmost importance. Currently, a phylogeny-based classification system defined by Valastro and co­workers is used for the classification of IBV strains. At present, IBV strains are divided into 8 genotypes (GI-GVIIl) and 39 distinct lineages (GI-1 to GI-31, GII-1, GII-2, GIII-1, GIV-1, GV-1, GVI-1, GVII-1 and GVIII-1) and a huge number of unclassi­fied inter-lineage recombinants. Most IBV lineages are confined to specific geo­graphic regions, and some countries report the circulation of unique lineages. In contrast, the GI-1, GI-13, GI-16 and GI-19 lineages are widely distributed. The aim of this review is to summarize the most recent knowledge about the distribution of the genetic groups of Avian Coronavirus. © 2022 Herman Otto Intezet. All rights reserved.

Religiousness in the first year of COVID-19: A systematic review of empirical research.

The COVID-19 pandemic emerged suddenly in early 2020, posing a serious health threat and creating tremendous stress and distress across the world. Religion has been shown to play important and varied roles in previous disasters and health crises, but its roles in the pandemic have yet to be outlined. We aimed to summarize the research conducted on religion and COVID-19 in the first year of the pandemic with a systematic review of studies that specifically involved individual-level religiousness and COVID-19. Searches were conducted in PubMed, Scopus, CINAHL, and PsycINFO covering a one-year period from the first published mention of the novel coronavirus (Jan. 5, 2020) through January 4, 2021. We included articles about COVID-19 that were peer-reviewed and empirical, measured and reported results on religion on an individual level, and were available in English. Our search produced 137 empirical articles that met the inclusion criteria. In the course of sorting studies by their primary focus, eight categories of empirical findings emerged: general distress and wellbeing (53 articles), COVID-19-specific stress (24 articles), beliefs in science, conspiracies, and misinformation (15 articles), COVID-19 public health behaviors (12 articles), perceived risk of COVID-19 (10 articles), perceived growth or positive changes taking place during the pandemic (nine articles), health behaviors (three articles), and consumer behavior (three articles). Findings indicated that religiousness was associated with both unique benefits and challenges and played a significant role in the pandemic. Religiousness was associated with a broad range of outcomes across geographical regions and populations during the first year of COVID-19. It was a commonly reported coping mechanism with varying levels of favorable associations with mental health and COVID-19-related behaviors.

Mental health among university employees during the COVID-19 pandemic: The role of previous life trauma and current posttraumatic stress symptoms.

OBJECTIVE: Previous studies indicated that the coronavirus disease 2019 (COVID-19) pandemic has harmed the mental health of diverse samples. Adopting a trauma lens with a sample of university faculty and staff, this study examined risk conferred by previous exposure to traumatic life events (TLE) on pandemic-related mental health harm (MHH) and stress and the mediating influence of posttraumatic stress disorder (PTSD) symptoms. METHOD: In Spring 2021, employees (N = 641) of a public university in the United States completed an online cross-sectional survey, including validated scales of TLE and PTSD and single-item measures of MHH and stress taken from published COVID-19 studies. A structural probit model was used to estimate: (a) direct effects of cumulative TLE on PTSD, MHH, and stress; and (b) indirect effects of cumulative TLE via PTSD adjusting for age. Gender was tested as a moderating influence. RESULTS: Nearly 36% of the sample reported positive PTSD screens along with high levels of MHH (22.5%) and stress (42.3%). Cumulative TLE was significantly and positively associated with MHH and stress. Both genders experienced a negative impact on mental health and stress either fully or partially through PTSD symptoms; however, the gender by trauma interaction term was not significant. As age decreased, PTSD and MHH increased. CONCLUSION: Results suggest that PTSD symptoms play a crucial role in the experience of MHH and stress during the pandemic for those who endured previous trauma. Implications for employer policies, public health messaging, and mental health services are explored. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Longitudinal Assessment of Cardiac Function Following Multisystem Inflammatory Syndrome in Children Associated with COVID-19.

Multisystem inflammatory syndrome in children (MIS-C) after COVID-19 is commonly associated with cardiac involvement. Studies found myocardial dysfunction, as measured by decreased ejection fraction and abnormal strain, to be common early in illness. However, there is limited data on longitudinal cardiac outcomes. We aim to describe the evolution of cardiac findings in pediatric MIS-C from acute illness through at least 2-month follow-up. A retrospective single-center review of 36 patients admitted with MIS-C from April 2020 through September 2021 was performed. Echocardiographic data including cardiac function and global longitudinal strain (GLS) were analyzed at initial presentation, discharge, 2-4-week follow-up, and at least 2-month follow-up. Patients with mild and severe disease, normal and abnormal left ventricular ejection fraction (LVEF), and normal and abnormal GLS at presentation were compared. On presentation, 42% of patients with MIS-C had decreased LVEF < 55%. In patients in whom GLS was obtained (N = 18), 44% were abnormal (GLS < |- 18|%). Of patients with normal LVEF, 22% had abnormal GLS. There were no significant differences in troponin or brain natriuretic peptide between those with normal and abnormal LVEF. In most MIS-C patients with initial LVEF < 55% (90%), LVEF normalized upon discharge. At 2-month follow-up, all patients had normal LVEF with 21% having persistently abnormal GLS. Myocardial systolic dysfunction and abnormal deformation were common findings in MIS-C at presentation. While EF often normalized by 2 months, persistently abnormal GLS was more common, suggesting ongoing subclinical dysfunction. Our study offers an optimistic outlook for recovery in patients with MIS-C and carditis, however ongoing investigation for longitudinal effects is warranted.

Geographic distribution of IBV lineages

Infectious bronchitis virus (IBV) is a leading cause of economic losses within the poultry industry, affecting both meat-type birds and layers. The highly contagious viral disease caused by Avian Coronavirus was first described in the 1930s and still remains a global problem for the poultry industry. Infection by Avian Coronavirus causes respiratory disease, nephritis, decreased egg produc­tion depending on the viral pathotype and the age of the affected flocks. Live attenuated and inactivated vaccines are used to control the disease, but poor cross-protection between different serotypes complicates control efforts. IBV exists in a wide variety of genetically distinct types and new variants are identi­fied relatively frequently. As the emergence of new IBV variants may impede the efficacy of the vaccines, monitoring the prevalence and genetic characteristics of IBV is of utmost importance. Currently, a phylogeny-based classification system defined by Valastro and co­workers is used for the classification of IBV strains. At present, IBV strains are divided into 8 genotypes (GI-GVIIl) and 39 distinct lineages (GI-1 to GI-31, GII-1, GII-2, GIII-1, GIV-1, GV-1, GVI-1, GVII-1 and GVIII-1) and a huge number of unclassi­fied inter-lineage recombinants. Most IBV lineages are confined to specific geo­graphic regions, and some countries report the circulation of unique lineages. In contrast, the GI-1, GI-13, GI-16 and GI-19 lineages are widely distributed. The aim of this review is to summarize the most recent knowledge about the distribution of the genetic groups of Avian Coronavirus. © 2022 Herman Otto Intezet. All rights reserved.

Geographic distribution of IBV lineages

Infectious bronchitis virus (IBV) is a leading cause of economic losses within the poultry industry, affecting both meat-type birds and layers. The highly contagious viral disease caused by Avian coronavirus was first described in the 1930s and still remains a global problem for the poultry industry. Infection by Avian coronavirus causes respiratory disease, nephritis, decreased egg production depending on the viral pathotype and the age of the affected flocks. Live attenuated and inactivated vaccines are used to control the disease, but poor cross-protection between different serotypes complicates control efforts. IBV exists in a wide variety of genetically distinct types and new variants are identified relatively frequently. As the emergence of new IBV variants may impede the efficacy of the vaccines, monitoring the prevalence and genetic characteristics of IBV is of utmost importance. Currently, a phylogeny-based classification system defined by Valastro and coworkers is used for the classification of IBV strains. At present, IBV strains are divided into 8 genotypes (GI-GVIII) and 39 distinct lineages (GI-1 to GI-31, GII-1, GII-2, GIII-1, GIV-1, GV-1, GVI-1, GVII-1 and GVIII-1) and a huge number of unclassified inter-lineage recombinants. Most IBV lineages are confined to specific geographic regions, and some countries report the circulation of unique lineages. In contrast, the GI-1, GI-13, GI-16 and GI-19 lineages are widely distributed. The aim of this review is to summarize the most recent knowledge about the distribution of the genetic groups of Avian coronavirus.

Acceptance of a computer vision facilitated protocol to measure adherence to face mask use: a single-site, observational cohort study among hospital staff.

OBJECTIVES: Mask adherence continues to be a critical public health measure to prevent transmission of aerosol pathogens, such as SARS-CoV-2. We aimed to develop and deploy a computer vision algorithm to provide real-time feedback of mask wearing among staff in a hospital. DESIGN: Single-site, observational cohort study. SETTING: An urban, academic hospital in Boston, Massachusetts, USA. PARTICIPANTS: We enrolled adult hospital staff entering the hospital at a key ingress point. INTERVENTIONS: Consenting participants entering the hospital were invited to experience the computer vision mask detection system. Key aspects of the detection algorithm and feedback were described to participants, who then completed a quantitative assessment to understand their perceptions and acceptance of interacting with the system to detect their mask adherence. OUTCOME MEASURES: Primary outcomes were willingness to interact with the mask system, and the degree of comfort participants felt in interacting with a public facing computer vision mask algorithm. RESULTS: One hundred and eleven participants with mean age 40 (SD15.5) were enrolled in the study. Males (47.7%) and females (52.3%) were equally represented, and the majority identified as white (N=54, 49%). Most participants (N=97, 87.3%) reported acceptance of the system and most participants (N=84, 75.7%) were accepting of deployment of the system to reinforce mask adherence in public places. One third of participants (N=36) felt that a public facing computer vision system would be an intrusion into personal privacy.Public-facing computer vision software to detect and provide feedback around mask adherence may be acceptable in the hospital setting. Similar systems may be considered for deployment in locations where mask adherence is important.

Evaluation of S/F94 as a proxy for COVID-19 severity (preprint)

Optimising statistical power in early-stage trials and observational studies accelerates discovery and improves the reliability of results. Ideally, intermediate outcomes should be continuously distributed and lie on the causal pathway between an intervention and a definitive outcome such as mortality. In order to optimise power for an intermediate outcome in the RECOVERY trial, we devised and evaluated a modification to a simple, pragmatic measure of oxygenation function - the SaO2/FIO2 (S/F) ratio. We demonstrate that, because of the ceiling effect in oxyhaemoglobin saturation, S/F ceases to reflect pulmonary oxygenation function at high values of SaO2. Using synthetic and real data, we found that the correlation of S/F with a gold standard (PaO2/FIO2, P/F ratio) improved substantially when measurements with SaO2 > 0.94 are excluded(Spearman r, synthetic data: S/F: 0.31; S/F94: 0.85). We refer to this measure as S/F94. In order to test the underlying assumptions and validity of S/F94 as a predictor of a definitive outcome (mortality), we collected an observational dataset including over 39,000 hospitalised patients with COVID-19 in the ISARIC4C study. We first demonstrated that S/F94 is predictive of mortality in COVID-19. We then compared the sample sizes required for trials using different outcome measures (S/F94, the WHO ordinal scale, sustained improvement at day 28 and mortality at day 28) ensuring comparable effect sizes. The smallest sample size was needed when S/F94 on day 5 was used as an outcome measure. To facilitate future study design, we provide an online user interface to quantify realworld power for a range of outcomes and inclusion criteria, using a synthetic dataset retaining the population-level clinical associations in real data accrued in ISARIC4C https://isaric4c.net/endpoints. We demonstrated that S/F94 is superior to S/F as a measure of pulmonary oxygenation function and is an effective intermediate outcome measure in COVID-19. It is a simple and non-invasive measurement, representative of disease severity and provides greater statistical power to detect treatment differences than other intermediate endpoints.

Effects of the COVID‐19 pandemic on 2020 spring turkey hunting across the United States

Spring wild turkey (Meleagris gallopavo) hunting is a foundational activity for many hunters across North America. Managing turkey hunters and turkey hunting is, therefore, a priority for state and provincial fish and wildlife management agencies. Early stages of the current SARS‐CoV‐2 (COVID‐19) pandemic in the United States coincided with 2020 spring turkey hunting seasons across the U.S. Potential effects of increases in peoples' time available for hunting on effort and turkey populations could have been substantial. We surveyed the primary wildlife biologist tasked with wild turkey management for each state and provincial jurisdiction with a huntable wild turkey population to determine turkey hunter and hunting dynamics before and during the spring 2020 turkey season. Biologists in 47 states responded to the survey. Results varied among states but hunting license sales, the number of hunters afield, harvest, total hunter‐days afield, and the number of days individual hunters were afield were greater in 2020 than the mean from the previous 3 years (2017–2019) in many states. Although hunting effort and total reported harvest increased in most states in 2020 from the previous 3‐year average, take‐per‐unit‐effort (i.e., harvest per hunter day) decreased in 93% of jurisdictions from which data were available, supporting the finding that increases in turkey harvest in spring 2020 were a result of a COVID‐related increase in participation and effort and not increases in turkey abundance. We recommend using these reference data for turkey population and turkey hunter monitoring pre‐ and post‐pandemic. Monitoring efforts should include wildlife population and habitat evaluations and study of hunter dynamics in a social science framework. We evaluated turkey hunter and hunting dynamics before and during the spring 2020 turkey season corresponding with the outbreak of the 2020 COVID‐19 pandemic. Hunting license sales, the number of hunters afield, harvest, total hunter‐days afield, and the number of days individual hunters were afield increased in 2020. Although hunting effort and total reported harvest increased in most states, take‐per‐unit‐effort decreased in 93% of jurisdictions, supporting the finding that increases in turkey harvest in spring 2020 were a result of a COVID‐related increase in participation and effort and not increases in turkey abundance.

Aligning mission to digital health strategy in academic medical centers.

The strategies of academic medical centers arise from core values and missions that aim to provide unmatched clinical care, patient experience, research, education, and training. These missions drive nearly all activities. They should also drive digital health activities - and particularly now given the rapid adoption of digital health, marking one of the great transformations of healthcare; increasing pressures on health systems to provide more cost-effective care; the pandemic-accelerated funding and rise of well-funded new entrants and technology giants that provide more convenient forms of care; and a more favorable regulatory and reimbursement landscape to incorporate digital health approaches. As academic medical centers emerge from a pandemic-related reactionary digital health posture, where pressures to adopt more digital health technologies mount, a broad digital health realignment that leverages the strengths of such centers is required to accomplish their missions.

Effects of the COVID‐19 pandemic on 2020 spring turkey hunting across the United States

Spring wild turkey (Meleagris gallopavo) hunting is a foundational activity for many hunters across North America. Managing turkey hunters and turkey hunting is, therefore, a priority for state and provincial fish and wildlife management agencies. Early stages of the current SARS‐CoV‐2 (COVID‐19) pandemic in the United States coincided with 2020 spring turkey hunting seasons across the U.S. Potential effects of increases in peoples' time available for hunting on effort and turkey populations could have been substantial. We surveyed the primary wildlife biologist tasked with wild turkey management for each state and provincial jurisdiction with a huntable wild turkey population to determine turkey hunter and hunting dynamics before and during the spring 2020 turkey season. Biologists in 47 states responded to the survey. Results varied among states but hunting license sales, the number of hunters afield, harvest, total hunter‐days afield, and the number of days individual hunters were afield were greater in 2020 than the mean from the previous 3 years (2017–2019) in many states. Although hunting effort and total reported harvest increased in most states in 2020 from the previous 3‐year average, take‐per‐unit‐effort (i.e., harvest per hunter day) decreased in 93% of jurisdictions from which data were available, supporting the finding that increases in turkey harvest in spring 2020 were a result of a COVID‐related increase in participation and effort and not increases in turkey abundance. We recommend using these reference data for turkey population and turkey hunter monitoring pre‐ and post‐pandemic. Monitoring efforts should include wildlife population and habitat evaluations and study of hunter dynamics in a social science framework. [ FROM AUTHOR] Copyright of Wildlife Society Bulletin is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

COVIDNearTerm: A simple method to forecast COVID-19 hospitalizations.

Introduction: COVID-19 has caused tremendous death and suffering since it first emerged in 2019. Soon after its emergence, models were developed to help predict the course of various disease metrics, and these models have been relied upon to help guide public health policy. Methods: Here we present a method called COVIDNearTerm to "forecast" hospitalizations in the short term, two to four weeks from the time of prediction. COVIDNearTerm is based on an autoregressive model and utilizes a parametric bootstrap approach to make predictions. It is easy to use as it requires only previous hospitalization data, and there is an open-source R package that implements the algorithm. We evaluated COVIDNearTerm on San Francisco Bay Area hospitalizations and compared it to models from the California COVID Assessment Tool (CalCAT). Results: We found that COVIDNearTerm predictions were more accurate than the CalCAT ensemble predictions for all comparisons and any CalCAT component for a majority of comparisons. For instance, at the county level our 14-day hospitalization median absolute percentage errors ranged from 16 to 36%. For those same comparisons, the CalCAT ensemble errors were between 30 and 59%. Conclusion: COVIDNearTerm is a simple and useful tool for predicting near-term COVID-19 hospitalizations.

Binding of synthetic carbohydrate receptors to enveloped virus glycans: Insights from molecular dynamics simulations.

Can envelope glycans be targeted to stop viral pandemics? Here we address this question by using molecular dynamics simulations to study the binding between 10 synthetic carbohydrate receptors (SCRs) and the 33 N-glycans most commonly found on the surfaces of enveloped viruses, including Zika virus and SARS-CoV-2. Based on association quotients derived from these simulations, we classified the SCRs as weak binders, promiscuous binders, or selective binders. The SCRs almost exclusively associate at the Man3GlcNAc2 core, which is common to all N-glycans, but the binding affinity between the SCR⋅glycan pair depends on the noncovalent interactions between the heterocycle rings and the glycan antennae. Systematic variations in the glycan and SCR structures reveal relationships that could guide the design of SCRs to attain affinity and selectivity towards a chosen envelope glycan target. With these results, envelope glycans, which are currently considered "undruggable", could become viable targets for new therapeutic strategies.

Demonstrating an approach for evaluating synthetic geospatial and temporal epidemiologic data utility: results from analyzing >1.8 million SARS-CoV-2 tests in the United States National COVID Cohort Collaborative (N3C).

OBJECTIVE: This study sought to evaluate whether synthetic data derived from a national coronavirus disease 2019 (COVID-19) dataset could be used for geospatial and temporal epidemic analyses. MATERIALS AND METHODS: Using an original dataset (n = 1 854 968 severe acute respiratory syndrome coronavirus 2 tests) and its synthetic derivative, we compared key indicators of COVID-19 community spread through analysis of aggregate and zip code-level epidemic curves, patient characteristics and outcomes, distribution of tests by zip code, and indicator counts stratified by month and zip code. Similarity between the data was statistically and qualitatively evaluated. RESULTS: In general, synthetic data closely matched original data for epidemic curves, patient characteristics, and outcomes. Synthetic data suppressed labels of zip codes with few total tests (mean = 2.9 ± 2.4; max = 16 tests; 66% reduction of unique zip codes). Epidemic curves and monthly indicator counts were similar between synthetic and original data in a random sample of the most tested (top 1%; n = 171) and for all unsuppressed zip codes (n = 5819), respectively. In small sample sizes, synthetic data utility was notably decreased. DISCUSSION: Analyses on the population-level and of densely tested zip codes (which contained most of the data) were similar between original and synthetically derived datasets. Analyses of sparsely tested populations were less similar and had more data suppression. CONCLUSION: In general, synthetic data were successfully used to analyze geospatial and temporal trends. Analyses using small sample sizes or populations were limited, in part due to purposeful data label suppression-an attribute disclosure countermeasure. Users should consider data fitness for use in these cases.

Better together: Integrating biomedical informatics and healthcare IT operations to create a learning health system during the COVID-19 pandemic.

The growing availability of multi-scale biomedical data sources that can be used to enable research and improve healthcare delivery has brought about what can be described as a healthcare "data age." This new era is defined by the explosive growth in bio-molecular, clinical, and population-level data that can be readily accessed by researchers, clinicians, and decision-makers, and utilized for systems-level approaches to hypothesis generation and testing as well as operational decision-making. However, taking full advantage of these unprecedented opportunities presents an opportunity to revisit the alignment between traditionally academic biomedical informatics (BMI) and operational healthcare information technology (HIT) personnel and activities in academic health systems. While the history of the academic field of BMI includes active engagement in the delivery of operational HIT platforms, in many contemporary settings these efforts have grown distinct. Recent experiences during the COVID-19 pandemic have demonstrated greater coordination of BMI and HIT activities that have allowed organizations to respond to pandemic-related changes more effectively, with demonstrable and positive impact as a result. In this position paper, we discuss the challenges and opportunities associated with driving alignment between BMI and HIT, as viewed from the perspective of a learning healthcare system. In doing so, we hope to illustrate the benefits of coordination between BMI and HIT in terms of the quality, safety, and outcomes of care provided to patients and populations, demonstrating that these two groups can be "better together."