Mental illness and COVID-19 vaccination: a multinational investigation of observational & register-based data (preprint)

Background: Individuals with mental illness are at higher risk of severe COVID-19 outcomes. However, previous studies on the uptake of COVID-19 vaccination in this population have reported conflicting results. Therefore, we aimed to investigate the association between mental illness and COVID-19 vaccination uptake, using data from five countries. Methods: Data from seven cohort studies (N=325,298), and the Swedish registers (8,080,234), were used to identify mental illness and COVID-19 vaccination uptake. Multivariable modified Poisson regression models were conducted to calculate the prevalence ratio (PR) and 95% CIs of vaccination uptake among individuals with v.s. without mental illness. Results from the cohort studies were pooled using random effects meta-analyses. Findings: Most of the meta-analyses performed using the COVIDMENT study population showed no significant association between mental illness and vaccination uptake. In the Swedish register study population, we observed a very small reduction in the uptake of both the first (prevalence ratio [PR]: 0.98, 95% CI: 0.98-0.99, p<0.001) and second dose among individuals with mental illness; the reduction was however greater among those not using pyschiatric medication (PR: 0.91, 95% CI: 0.91-0.91, p<0.001). Conclusions: The high uptake of COVID-19 vaccination observed among individuals with most types of mental illness highlights the comprehensiveness of the vaccination campaign , however lower levels of vaccination uptake among subgroups of individuals with unmedicated mental illness warrants attention in future vaccination campaigns.

Mental illness and COVID-19 vaccination: a multinational investigation of observational & register-based data (preprint)

Background: Individuals with mental illness are at higher risk of severe COVID-19 outcomes. However, previous studies on the uptake of COVID-19 vaccination in this population have reported conflicting results. Therefore, we aimed to investigate the association between mental illness and COVID-19 vaccination uptake, using data from five countries. Methods: Data from seven cohort studies (N=325,298), and the Swedish registers (8,080,234), were used to identify mental illness and COVID-19 vaccination uptake. Multivariable modified Poisson regression models were conducted to calculate the prevalence ratio (PR) and 95% CIs of vaccination uptake among individuals with v.s. without mental illness. Results from the cohort studies were pooled using random effects meta-analyses. Findings: Most of the meta-analyses performed using the COVIDMENT study population showed no significant association between mental illness and vaccination uptake. In the Swedish register study population, we observed a very small reduction in the uptake of both the first (prevalence ratio [PR]: 0.98, 95% CI: 0.98-0.99, p<0.001) and second dose among individuals with mental illness; the reduction was however greater among those not using pyschiatric medication (PR: 0.91, 95% CI: 0.91-0.91, p<0.001). Conclusions: The high uptake of COVID-19 vaccination observed among individuals with most types of mental illness highlights the comprehensiveness of the vaccination campaign , however lower levels of vaccination uptake among subgroups of individuals with unmedicated mental illness warrants attention in future vaccination campaigns.

Comparison of clinician diagnosis of COVID-19 with real time polymerase chain reaction in an adult-representative population in Sweden (preprint)

Background: Due to the high transmissibility of SARS-CoV-2, accurate diagnosis is essential for effective infection control, but the gold standard, real-time reverse transcriptase-polymerase chain reaction (RT-PCR), is costly, slow, and test capacity has at times been insufficient. We compared the accuracy of clinician diagnosis of COVID-19 against RT-PCR in a general adult population. Methods: COVID-19 diagnosis data by 30thSeptember 2021 for participants in an ongoing population-based cohort study of adults in Western Sweden were retrieved from registers, based on positive RT-PCR and clinician diagnosis using recommended ICD-10 codes. We calculated accuracy measures of clinician diagnosis using RT-PCR as reference for all subjects and stratified by age, gender, BMI, and comorbidity collected pre-COVID-19. Results: Of 42,621 subjects, 3,936 (9.2%) and 5,705 (13.4%) had had COVID-19 identified by RT-PCR and clinician diagnosis, respectively. Sensitivity and specificity of clinician diagnosis against RT-PCR were 78% (95%CI 77-80%) and 93% (95%CI 93-93%), respectively. Positive predictive value (PPV) was 54% (95%CI 53-55%), while negative predictive value (NPV) was 98% (95%CI 98-98%) and Youden’s index 71% (95%CI 70-72%). These estimates were similar between men and women, across age groups, BMI categories, and between patients with and without asthma. However, while specificity, NPV, and Youden’s index were similar between patients with and without chronic obstructive pulmonary disease (COPD), sensitivity was slightly higher in patients with (84% [95%CI 74-90%]) than those without (78% [95%CI 77-79%]) COPD. Conclusions: The accuracy of clinician diagnosis for COVID-19 is adequate, regardless of gender, age, BMI,and asthma, andthus can be used for screening purposes to supplement RT-PCR.

Protective effects of statins on COVID-19 risk, severity and fatal outcome – a nationwide Swedish cohort study (preprint)

Background: The impact of statins on COVID-19 remains unclear. This study aims to investigate whether statin exposure assessed both in the population and in well-defined cohorts of COVID-19 patients may affect the risk and severity of COVID-19 using nationwide Swedish population-based register data.Methods: A population ≥40 years was selected by age/sex-stratified random sampling from the Swedish population on 1 Jan 2020. COVID-19 outcomes were identified from the SmiNet database, the National Patient Register and/or Cause-of-Death Register and linked with the National Prescribed Drug Register and sociodemographic registers. Statin exposure was defined as any statin prescriptions in the year before index date. In Cox regressions, confounding was addressed using propensity score ATT (Average Treatment effect in the Treated) weighting. Results: Of 572,695 individuals in the overall cohort, 22.3% had prior regular statin treatment. After ATT weighting, protective effects were observed among statin user for hospitalization and COVID-19 death in the overall cohort and onset cohort. In the hospitalized cohort, statin use was only associated with lower risk for death (HR=0.86, 95%CI 0.79-0.95), but not ICU admission. Conclusions: Statin-treated individuals appear to have lower COVID-19 mortality than nonusers, whether assessed in the general population, from COVID-19 onset or from hospitalization.

Short-term improvement of mental health after a COVID-19 vaccination (preprint)

Abstract Importance: The role of COVID-19 vaccination on the mental health of the general population remains poorly understood. Objective: To assess the short-term change of depressive and anxiety symptoms in relation to COVID-19 vaccination among Swedish adults. Design: A prospective cohort study with monthly data collections on self-reported depressive and anxiety symptoms from December 2020 to October 2021 and COVID-19 vaccination from July to October 2021. Setting: The Omtanke2020 Study, Sweden. Participants: 7,925 participants of the Omtanke2020 study with complete data on depressive and anxiety symptoms and vaccination status. Intervention(s) or Exposure(s): Receiving the first or second dose of a COVID-19 vaccine. Main outcomes(s) and Measure(s): Binary measures of depression (PHQ-9, cut-off [≥] 10) and anxiety (GAD-7, cut-off [≥] 10) one month before the first dose, one month after the first dose, and, if applicable, one month after the second dose. For individuals not vaccinated or chose to not report vaccination status (unvaccinated individuals), we selected three monthly measures of PHQ-9 and GAD-7 with 2-month intervals in-between based on data availability. Results: 5,079 (64.1%) individuals received two doses of COVID-19 vaccine, 1,977 (24.9%) received one dose, 305 (3.9%) were not vaccinated, and 564 (7.1%) chose not to report vaccination status. There was a lower prevalence of depression and anxiety among vaccinated, compared with unvaccinated, individuals, especially after the second dose. Among individuals receiving two doses of vaccine, the prevalence of depression and anxiety was lower after both first (aRR=0.82, 95%CI 0.76-0.88 for depression; aRR=0.81, 95%CI 0.73-0.89 for anxiety) and second (aRR=0.79, 95%CI 0.73-0.85 for depression; aRR=0.73, 95%CI 0.66-0.81 for anxiety) dose, compared with before vaccination. Similar results were observed among individuals receiving only one dose (aRR=0.76, 95%CI 0.68-0.84 for depression; aRR=0.82, 95%CI 0.72-0.94 for anxiety, comparing after first dose to before vaccination). These results were independent of age, sex, recruitment type, body mass index, smoking, relationship status, history of psychiatric disorder, number of comorbidities, COVID-19 infection status, and seasonality. Conclusions and Relevance: We observed a positive short-term change in depressive and anxiety symptoms among adults receiving a COVID-19 vaccine in the current pandemic.

Adverse events of special interest for COVID-19 vaccines - background incidences vary by sex, age and time period and are affected by the pandemic (preprint)

Background With large-scale COVID-19 vaccination implemented world-wide, safety signals needing rapid evaluation will emerge. We report population-based, age- and-sex-specific background incidence rates of conditions representing potential vaccine adverse events of special interest (AESI) for the Swedish general population using register data. Methods We studied an age/sex-stratified random 10% sample of the Swedish population on 1 Jan 2020, followed for AESI outcomes during 1 year, as the COVID-19 pandemic emerged and developed, before the start of vaccinations. We selected and defined the following outcomes based on information from regulatory authorities, large-scale adverse events initiatives and previous studies: aseptic meningitis, febrile seizure, Kawasaki syndrome, MISC, post-infectious arthritis, arthritis, myocarditis, ARDS, myocardial infarction, stroke, ischemic stroke, hemorrhagic stroke, venous thromboembolism, pulmonary embolism, kidney failure, liver failure, erythema multiforme, disseminated intravascular coagulation, autoimmune thyroiditis, and appendicitis. We calculated incidence rates stratified by age, sex and time period (quarters of 2020), and classified them using Council of International Organizations of Medical Sciences (CIOMS) categories: very common, common, uncommon, rare, or very rare. Results We included 972,723 study subjects, representing the Swedish national population on 1 Jan 2020. We found that AESI incidence rates vary greatly by age and in some cases sex. Several common AESIs showed expected increase with age, while some (e.g. appendicitis, aseptic meningitis, autoimmune thyroiditis, Kawasaki syndrome and MISC) were more common in young people, and others exhibited a flatter age pattern (e.g. myocarditis, DIC and erythema multiforme). Consequently, the CIOMS classification for AESIs varied widely according to age. Considerable variability was suggested for some AESI rates across the 4 quarters of 2020, potentially related to pandemic waves, seasonal variation, healthcare system overload or other healthcare delivery effects. Conclusion Age, sex, and timing of rates are important to consider when background AESI rates are compared to corresponding rates observed with COVID-19 vaccines.

Unraveling COVID-19: a large-scale characterization of 4.5 million COVID-19 cases using CHARYBDIS (preprint)

Background: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response [1,2]. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) [3] Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD.Methods: We conducted a descriptive cohort study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub [4]. Findings: We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts, and are available in an interactive website: https://data.ohdsi.org/Covid19CharacterizationCharybdis/. Interpretation: CHARYBDIS findings provide benchmarks that contribute to our understanding of COVID-19 progression, management and evolution over time. This can enable timely assessment of real-world outcomes of preventative and therapeutic options as they are introduced in clinical practice.

Characteristics and outcomes of 118,155 COVID-19 individuals with a history of cancer in the United States and Spain (preprint)

PurposeWe aimed to describe the demographics, cancer subtypes, comorbidities and outcomes of patients with a history of cancer with COVID-19 from March to June 2020. Secondly, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza. MethodsWe conducted a cohort study using eight routinely-collected healthcare databases from Spain and the US, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: i) diagnosed with COVID-19, ii) hospitalized with COVID-19, and iii) hospitalized with influenza in 2017-2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes. ResultsWe included 118,155 patients with a cancer history in the COVID-19 diagnosed and 41,939 in the COVID-19 hospitalized cohorts. The most frequent cancer subtypes were prostate and breast cancer (range: 5-19% and 1-14% in the diagnosed cohort, respectively). Hematological malignancies were also frequent, with non-Hodgkins lymphoma being among the 5 most common cancer subtypes in the diagnosed cohort. Overall, patients were more frequently aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 8% to 14% and from 18% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n=242,960) had a similar distribution of cancer subtypes, sex, age and comorbidities but lower occurrence of adverse events. ConclusionPatients with a history of cancer and COVID-19 have advanced age, multiple comorbidities, and a high occurence of COVID-19-related events. Additionaly, hematological malignancies were frequent in these patients.This observational study provides epidemiologic characteristics that can inform clinical care and future etiological studies.

Use of dialysis, tracheostomy, and extracorporeal membrane oxygenation among 240,392 patients hospitalized with COVID-19 in the United States (preprint)

Objective To estimate the proportion of patients hospitalized with COVID-19 who undergo dialysis, tracheostomy, and extracorporeal membrane oxygenation (ECMO). Design A network cohort study. Setting Six databases from the United States containing routinely-collected patient data: HealthVerity, Premier, IQVIA Open Claims, Optum EHR, Optum SES, and VA-OMOP. Patients Patients hospitalized with a clinical diagnosis or a positive test result for COVID-19. Interventions Dialysis, tracheostomy, and ECMO. Measurements and Main Results 240,392 patients hospitalized with COVID-19 were included (22,887 from HealthVerity, 139,971 from IQVIA Open Claims, 29,061 from Optum EHR, 4,336 from OPTUM SES, 36,019 from Premier, and 8,118 from VA-OMOP). Across the six databases, 9,703 (4.04% [95% CI: 3.96% to 4.11%]) patients received dialysis, 1,681 (0.70% [0.67% to 0.73%]) had a tracheostomy, and 398 (0.17% [95% CI: 0.15% to 0.18%]) patients underwent ECMO over the 30 days following hospitalization. Use of ECMO was generally concentrated among patients who were younger, male, and with fewer comorbidities except for obesity. Tracheostomy was used for a similar proportion of patients regardless of age, sex, or comorbidity. While dialysis was used for a similar proportion among younger and older patients, it was more frequent among male patients and among those with chronic kidney disease. Conclusion Use of dialysis among those hospitalized with COVID-19 is high at around 4%. Although less than one percent of patients undergo tracheostomy and ECMO, the absolute numbers of patients who have undergone these interventions is substantial and can be expected to continue grow given the continuing spread of the COVID-19.

Highly functional virus-specific cellular immune response in asymptomatic SARS-CoV-2 infection (preprint)

The efficacy of virus-specific T cells in clearing pathogens involves a fine balance between their antiviral and inflammatory features. SARS-CoV-2-specific T cells in individuals who clear SARS-CoV-2 infection without symptoms or disease could reveal non-pathological yet protective characteristics. We therefore compared the quantity and function of SARS-CoV-2-specific T cells in a cohort of asymptomatic individuals (n=85) with that of symptomatic COVID-19 patients (n=76), at different time points after antibody seroconversion. We quantified T cells reactive to structural proteins (M, NP and Spike) using ELISpot assays, and measured the magnitude of cytokine secretion (IL-2, IFN-{gamma}, IL-4, IL-6, IL-1{beta}, TNF- and IL-10) in whole blood following T cell activation with SARS-CoV-2 peptide pools as a functional readout. Frequencies of T cells specific for the different SARS-CoV-2 proteins in the early phases of recovery were similar between asymptomatic and symptomatic individuals. However, we detected an increased IFN-{gamma} and IL-2 production in asymptomatic compared to symptomatic individuals after activation of SARS-CoV-2-specific T cells in blood. This was associated with a proportional secretion of IL-10 and pro-inflammatory cytokines (IL-6, TNF- and IL-1{beta}) only in asymptomatic infection, while a disproportionate secretion of inflammatory cytokines was triggered by SARS-CoV-2-specific T cell activation in symptomatic individuals. Thus, asymptomatic SARS-CoV-2 infected individuals are not characterized by a weak antiviral immunity; on the contrary, they mount a robust and highly functional virus-specific cellular immune response. Their ability to induce a proportionate production of IL-10 might help to reduce inflammatory events during viral clearance.

Unheeded SARS-CoV-2 protein? Look deep into negative-sense RNA (preprint)

SARS-CoV-2 is a novel ssRNA+ virus from the Coronaviridae family, which has caused the global COVID-19 pandemic. The genome of SARS-CoV-2 is one of the largest of RNA viruses, comprising of 26 known protein-coding loci. This study aimed to explore the coding potential of negative-strand RNA intermediate for its potential to contain additional protein coding-loci. Surprisingly, we have found several putative ORFs and one brandt new functional SARS-CoV-2 protein-coding loci and called it Avo1 (Ambient viral ORF1). This sequence is located on negative-sense RNA intermediate and bona fide coding for 81 amino acid residues long protein and contains strong Kozak sequence for translation on eukaryotic ribosomes. In silico translated protein Avo1 has a predominantly alpha-helical structure. The existence of Avo1 gene is supported also by its evolutionarily and structural conservation in RaTG13 bat coronavirus. The nucleotide sequence of Avo1 also contains a unique SREBP2 binding site which is closely related to the so-called cytokine storm in severe COVID-19 patients. Altogether, our results suggest the existence of still undescribed SARS-CoV-2 protein, which may play an important role in the viral lifecycle and COVID-19 pathogenesis.

A Novel Cell Therapy for COVID-19 and Potential Future Pandemics: Virus Induced Lymphocytes (VIL) (preprint)

The a priori T cell repertoire and immune response against SARS-CoV-2 viral antigens may explain the varying clinical course and prognosis of patients having a mild COVID-19 infection as opposed to those developing more fulminant multisystem organ failure and associated mortality. Using a novel SARS-Cov-2-specific artificial antigen presenting cell (aAPC), coupled with a rapid expansion protocol (REP) as practiced in tumor infiltrating lymphocytes (TIL) therapy, we generate an immune catalytic quantity of Virus Induced Lymphocytes (VIL). Using T cell receptor (TCR)-specific aAPCs carrying co-stimulatory molecules and major histocompatibility complex (MHC) class-I immunodominant SARS-CoV-2 peptide-pentamer complexes, we expand virus-specific VIL derived from peripheral blood mononuclear cells (PBMC) of convalescent COVID-19 patients up to 1,000-fold. This is achieved in a clinically relevant 7-day vein-to-vein time-course as a potential adoptive cell therapy (ACT) for COVID-19. We also evaluate this approach for other viral pathogens using Cytomegalovirus (CMV)-specific VIL from donors as a control. Rapidly expanded VIL are enriched in virus antigen-specificity and show an activated, polyfunctional cytokine profile and T effector memory phenotype which may contribute to a robust immune response. Virus-specific T cells can also be delivered allogeneically via MHC-typing and patient human leukocyte antigen (HLA)-matching to provide pragmatic treatment in a large-scale therapeutic setting. These data suggest that VIL may represent a novel therapeutic option that warrants further clinical investigation in the armamentarium against COVID-19 and other possible future pandemics.

Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis (preprint)

Objective: Patients with autoimmune diseases were advised to shield to avoid COVID-19, but information on their prognosis is lacking. We characterised 30-day outcomes and mortality after hospitalisation with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza. Design: Multinational network cohort study Setting: Electronic health records data from Columbia University Irving Medical Center (CUIMC) (NYC, United States [US]), Optum [US], Department of Veterans Affairs (VA) (US), Information System for Research in Primary Care-Hospitalisation Linked Data (SIDIAP-H) (Spain), and claims data from IQVIA Open Claims (US) and Health Insurance and Review Assessment (HIRA) (South Korea). Participants: All patients with prevalent autoimmune diseases, diagnosed and/or hospitalised between January and June 2020 with COVID-19, and similar patients hospitalised with influenza in 2017-2018 were included. Main outcome measures: 30-day complications during hospitalisation and death Results: We studied 133,589 patients diagnosed and 48,418 hospitalised with COVID-19 with prevalent autoimmune diseases. The majority of participants were female (60.5% to 65.9%) and aged [≥]50 years. The most prevalent autoimmune conditions were psoriasis (3.5 to 32.5%), rheumatoid arthritis (3.9 to 18.9%), and vasculitis (3.3 to 17.6%). Amongst hospitalised patients, Type 1 diabetes was the most common autoimmune condition (4.8% to 7.5%) in US databases, rheumatoid arthritis in HIRA (18.9%), and psoriasis in SIDIAP-H (26.4%). Compared to 70,660 hospitalised with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2% to 4.3% versus 6.3% to 24.6%). Conclusions: Patients with autoimmune diseases had high rates of respiratory complications and 30-day mortality following a hospitalization with COVID-19. Compared to influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality. Future studies should investigate predictors of poor outcomes in COVID-19 patients with autoimmune diseases.

Baseline characteristics, management, and outcomes of 55,270 children and adolescents diagnosed with COVID-19 and 1,952,693 with influenza in France, Germany, Spain, South Korea and the United States: an international network cohort study (preprint)

Objectives To characterize the demographics, comorbidities, symptoms, in-hospital treatments, and health outcomes among children/adolescents diagnosed or hospitalized with COVID-19. Secondly, to describe health outcomes amongst children/adolescents diagnosed with previous seasonal influenza. Design International network cohort. Setting Real-world data from European primary care records (France/Germany/Spain), South Korean claims and US claims and hospital databases. Participants Diagnosed and/or hospitalized children/adolescents with COVID-19 at age <18 between January and June 2020; diagnosed with influenza in 2017-2018. Main outcome measures Baseline demographics and comorbidities, symptoms, 30-day in-hospital treatments and outcomes including hospitalization, pneumonia, acute respiratory distress syndrome (ARDS), multi-system inflammatory syndrome (MIS-C), and death. Results A total of 55,270 children/adolescents diagnosed and 3,693 hospitalized with COVID-19 and 1,952,693 diagnosed with influenza were studied. Comorbidities including neurodevelopmental disorders, heart disease, and cancer were all more common among those hospitalized vs diagnosed with COVID-19. The most common COVID-19 symptom was fever. Dyspnea, bronchiolitis, anosmia and gastrointestinal symptoms were more common in COVID-19 than influenza. In-hospital treatments for COVID-19 included repurposed medications (<10%), and adjunctive therapies: systemic corticosteroids (6.8% to 37.6%), famotidine (9.0% to 28.1%), and antithrombotics such as aspirin (2.0% to 21.4%), heparin (2.2% to 18.1%), and enoxaparin (2.8% to 14.8%). Hospitalization was observed in 0.3% to 1.3% of the COVID-19 diagnosed cohort, with undetectable (N<5 per database) 30-day fatality. Thirty-day outcomes including pneumonia, ARDS, and MIS-C were more frequent in COVID-19 than influenza. Conclusions Despite negligible fatality, complications including pneumonia, ARDS and MIS-C were more frequent in children/adolescents with COVID-19 than with influenza. Dyspnea, anosmia and gastrointestinal symptoms could help differential diagnosis. A wide range of medications were used for the inpatient management of pediatric COVID-19.

Baseline phenotype and 30-day outcomes of people tested for COVID-19: an international network cohort including >3.32 million people tested with real-time PCR and >219,000 tested positive for SARS-CoV-2 in South Korea, Spain and the United States (preprint)

Early identification of symptoms and comorbidities most predictive of COVID-19 is critical to identify infection, guide policies to effectively contain the pandemic, and improve health systems' response. Here, we characterised socio-demographics and comorbidity in 3,316,107 persons tested and 219,072 persons tested positive for SARS-CoV-2 since January 2020, and their key health outcomes in the month following the first positive test. Routine care data from primary care electronic health records (EHR) from Spain, hospital EHR from the United States (US), and claims data from South Korea and the US were used. The majority of study participants were women aged 18-65 years old. Positive/tested ratio varied greatly geographically (2.2:100 to 31.2:100) and over time (from 50:100 in February-April to 6.8:100 in May-June). Fever, cough and dyspnoea were the most common symptoms at presentation. Between 4%-38% required admission and 1-10.5% died within a month from their first positive test. Observed disparity in testing practices led to variable baseline characteristics and outcomes, both nationally (US) and internationally. Our findings highlight the importance of large scale characterization of COVID-19 international cohorts to inform planning and resource allocation including testing as countries face a second wave.

Clinical characteristics, symptoms, management and health outcomes in 8,598 pregnant women diagnosed with COVID-19 compared to 27,510 with seasonal influenza in France, Spain and the US: a network cohort analysis (preprint)

OBJECTIVES: To describe comorbidities, symptoms at presentation, medication use, and 30-day outcomes after a diagnosis of COVID-19 in pregnant women, in comparison to pregnant women with influenza. DESIGN: Multinational network cohort SETTING: A total of 6 databases consisting of electronic medical records and claims data from France, Spain, and the United States. PARTICIPANTS: Pregnant women with [≥] 1 year in contributing databases, diagnosed and/or tested positive, or hospitalized with COVID-19. The influenza cohort was derived from the 2017-2018 influenza season. OUTCOMES: Baseline patient characteristics, comorbidities and presenting symptoms; 30-day inpatient drug utilization, maternal complications and pregnancy-related outcomes following diagnosis/hospitalization. RESULTS: 8,598 women diagnosed (2,031 hospitalized) with COVID-19 were included. Hospitalized women had, compared to those diagnosed, a higher prevalence of pre-existing comorbidities including renal impairment (2.2% diagnosed vs 5.1% hospitalized) and anemia (15.5% diagnosed vs 21.3% hospitalized). The ten most common inpatient treatments were systemic corticosteroids (29.6%), enoxaparin (24.0%), immunoglobulins (21.4%), famotidine (20.9%), azithromycin (18.1%), heparin (15.8%), ceftriaxone (7.9%), aspirin (7.0%), hydroxychloroquine (5.4%) and amoxicillin (3.5%). Compared to 27,510 women with influenza, dyspnea and anosmia were more prevalent in those with COVID-19. Women with COVID-19 had higher frequency of cesarean-section (4.4% vs 3.1%), preterm delivery (0.9% vs 0.5%), and poorer maternal outcomes: pneumonia (12.0% vs 2.7%), ARDS (4.0% vs 0.3%) and sepsis (2.1% vs 0.7%). COVID-19 fatality was negligible (N<5 in each database respectively). CONCLUSIONS: Comorbidities that were more prevalent with COVID-19 hospitalization (compared to COVID-19 diagnosed) in pregnancy included renal impairment and anemia. Multiple medications were used to treat pregnant women hospitalized with COVID-19, some with little evidence of benefit. Anosmia and dyspnea were indicative symptoms of COVID-19 in pregnancy compared to influenza, and may aid differential diagnosis. Despite low fatality, pregnancy and maternal outcomes were worse in COVID-19 than influenza.

Heterogeneity and temporal variation in the management of COVID-19: a multinational drug utilization study including 71,921 hospitalized patients from China, South Korea, Spain, and the United States of America (preprint)

Objectives: A plethora of medicines have been repurposed or used as adjunctive therapies for COVID-19. We characterized the utilization of medicines as prescribed in routine practice amongst patients hospitalized for COVID-19 in South Korea, China, Spain, and the USA. Design: International network cohort Setting: Hospital electronic health records from Columbia University Irving Medical Centre (NYC, USA), Stanford (CA, USA), Tufts (MA, USA), Premier (USA), Optum EHR (USA), department of veterans affairs (USA), NFHCRD (Honghu, China) and HM Hospitals (Spain); and nationwide claims from HIRA (South Korea) Participants: patients hospitalized for COVID-19 from January to June 2020 Main outcome measures: Prescription/dispensation of any medicine on or 30 days after hospital admission date Analyses: Number and percentage of users overall and over time Results: 71,921 people were included: 304 from China, 2,089 from Spain, 7,599 from South Korea, and 61,929 from the USA. A total of 3,455 medicines were identified. Common repurposed medicines included hydroxychloroquine (<2% in NFHCRD to 85.4% in HM), azithromycin (4.9% in NFHCRD to 56.5% in HM), lopinavir/ritonavir (<3% in all US but 34.9% in HIRA and 56.5% in HM), and umifenovir (0% in all except 78.3% in NFHCRD). Adjunctive medicines were used with great variability, with the ten most used treatments being (in descending order): bemiparin, enoxaparin, heparin, ceftriaxone, aspirin, vitamin D, famotidine, vitamin C, dexamethasone, and metformin. Hydroxychloroquine and azithromycin increased rapidly in use in March-April but declined steeply in May-June. Conclusions: Multiple medicines were used in the first months of COVID-19 pandemic, with substantial geographic and temporal variation. Hydroxychloroquine, azithromycin, lopinavir-ritonavir, and umifenovir (in China only) were the most prescribed repurposed medicines. Antithrombotics, antibiotics, H2 receptor antagonists and corticosteroids were often used as adjunctive treatments. Research is needed on the comparative risk and benefit of these treatments in the management of COVID-19.

Characteristics and outcomes of 627 044 COVID-19 patients with and without obesity in the United States, Spain, and the United Kingdom (preprint)

Background: COVID-19 may differentially impact people with obesity. We aimed to describe and compare the demographics, comorbidities, and outcomes of obese patients with COVID-19 to those of non-obese patients with COVID-19, or obese patients with seasonal influenza. Methods: We conducted a cohort study based on outpatient/inpatient care, and claims data from January to June 2020 from the US, Spain, and the UK. We used six databases standardized to the OMOP common data model. We defined two cohorts of patients diagnosed and/or hospitalized with COVID-19. We created corresponding cohorts for patients with influenza in 2017-2018. We followed patients from index date to 30 days or death. We report the frequency of socio-demographics, prior comorbidities, and 30-days outcomes (hospitalization, events, and death) by obesity status. Findings: We included 627 044 COVID-19 (US: 502 650, Spain: 122 058, UK: 2336) and 4 549 568 influenza (US: 4 431 801, Spain: 115 224, UK: 2543) patients. The prevalence of obesity was higher among hospitalized COVID-19 (range: 38% to 54%) than diagnosed COVID-19 (30% to 47%), or diagnosed/hospitalized influenza (15% to 48%) patients. Obese hospitalized COVID-19 patients were more often female and younger than non-obese COVID-19 patients or obese influenza patients. Obese COVID-19 patients were more likely to have prior comorbidities, present with cardiovascular and respiratory events during hospitalization, require intensive services, or die compared to non-obese COVID-19 patients. Obese COVID-19 patients were also more likely to require intensive services or die compared to obese influenza patients, despite presenting with fewer comorbidities. Interpretation: We show that obesity is more common among COVID-19 than influenza patients, and that obese patients present with more severe forms of COVID-19 with higher hospitalization, intensive services, and fatality than non-obese patients. These data are instrumental for guiding preventive strategies of COVID-19 infection and complications

Longitudinal single-cell immune profiling revealed distinct innate immune response in asymptomatic COVID-19 patients (preprint)

Recent studies have characterized the single-cell immune landscape of host immune response of coronavirus disease 2019 (COVID-19), specifically focus on the severe condition. However, the immune response in mild or even asymptomatic patients remains unclear. Here, we performed longitudinal single-cell transcriptome sequencing and T cell/B cell receptor sequencing on 3 healthy donors and 10 COVID-19 patients with asymptomatic, moderate, and severe conditions. We found asymptomatic patients displayed distinct innate immune responses, including increased CD56briCD16- NK subset, which was nearly missing in severe condition and enrichment of a new Th2-like cell type/state expressing a ciliated cell marker. Unlike that in moderate condition, asymptomatic patients lacked clonal expansion of effector CD8+ T cells but had a robust effector CD4+ T cell clonal expansion, coincide with previously detected SARS-CoV-2-reactive CD4+ T cells in unexposed individuals. Moreover, NK and effector T cells in asymptomatic patients have upregulated cytokine related genes, such as IFNG and XCL2. Our data suggest early innate immune response and type I immunity may contribute to the asymptomatic phenotype in COVID-19 disease, which could in turn deepen our understanding of severe COVID-19 and guide early prediction and therapeutics.