Impact of the COVID-19 pandemic on patients with osteogenesis imperfecta

OBJECTIVES: On March 11, 2020, the WHO classified COVID-19 as a global pandemic. Measures to quell the pandemic included limiting non-essential activities including clinic visits and procedures. It is unclear if individuals with OI had disruptions in their access to healthcare or medications, and if such disruptions affected patients' symptoms. METHOD(S): A REDCap survey was distributed through the OI Foundation on August 31. Surveys completed through September 11 by individuals with OI or their caregiver are included in this analysis. Participants were asked to compare their symptoms and access to healthcare during the first 4 months of the pandemic to the 4 months before the pandemic. RESULT(S): 85 surveys were completed, and 6 were partially completed. The median age of participants was 40 years;35% were children. 32% of participants self-identified as having severe OI. Although most reported no changes in bone pain or fractures, 46% reported they were less likely to seek emergency medical care to treat a fracture, while 33% reported they were more likely to treat fractures at home (Fig 1A). There were delays in accessing all services, with greatest delays accessing dentistry (74%) and aquatic therapy (84%) (Fig 1B). 36% of participants receiving bisphosphonate infusions had delayed infusions because of the pandemic (Fig 1C). Of note, 50% of planned surgeries were delayed. CONCLUSION(S): Although many individuals with OI and their caregivers reported delays in accessing bone-related services/clinics during this 4-month period, there was not a concomitant increase in reported symptoms. This may have related to shelter-in-place restrictions and decreased activity. Limitations of this study include small sample size and potential selection bias because responses were obtained only from OIF members. To address these limitations, we are distributing the survey through healthcare providers of individuals with OI across major regions of the US from a variety of practice types including endocrine, orthopedics and multidisciplinary clinics. Furthermore, as the COVID-19 pandemic continues, we hope that this survey will provide information to address what aspects of healthcare may be in greatest need, as well as the modality through which services may be met. (Figure Presented).

A survival genome-wide association study to identify variants associated with COVID-19 risk of death

Background/Objectives: SARS-CoV-2 infection clinical manifestations hugely vary among patients, ranging from no symptoms, to life-threatening conditions. This variability is also due to host genetics: COVID-19 Host Genetics Initiative identified six loci associated with COVID-19 severity in a previous case-control genome-wide association study. A different approach to investigate the genetics of COVID-19 severity is looking for variants associated with mortality, e.g. by analyzing the association between genotypes and time-to-event data. Method(s): Here we perform a case-only genome-wide survival analysis, of 1,777 COVID-19 patients from the GEN-COVID cohort, 60 days after infection/hospitalization. Case-only studies has the advantage of eliminating selection biases and confounding related to control subjects. Patients were genotyped using Illumina Infinium Global Screening Arrays. PLINK software was used for data quality check and principal component analysis. GeneAbel R package was used for survival analysis and age, sex and the first four principal components were used as covariates in the Cox proportional hazard model. Result(s): We found four variants associated with COVID-19 patient survival at a nominal P < 1.0 x 10-6. Their minor alleles were associated with a higher mortality risk (i.e. hazard ratios (HR)>1). In detail, we observed: HR=1.03 for rs28416079 on chromosome 19 (P=1.34 x 10-7), HR=1.15 for rs72815354 on chromosome 10 (P=1.66 x 10-7), HR=2.12 for rs2785631 on chromosome 1 (P=5.14 x 10-7), and HR=2.27 for rs2785631 on chromosome 5 (P=6.65 x 10-7). Conclusion(s): The present results suggest that germline variants are COVID-19 prognostic factors. Replication in the remaining HGI COVID-19 patient cohort (EGAS00001005304) is ongoing at the time of submission.

Utilizing a Decentralized Clinical Study Approach for Expedited and Diverse Recruitment for Clinical Validation of a Novel Non-invasive Multitargeted Stool-based RNA Test

Introduction: Traditional clinical trials that utilize fixed sites often fail to recruit participants that are representative of the intended use population. Participants, particularly those from minority groups, cite geographical constraints, mistrust, miscommunication, and discrimination as barriers to successful recruitment. A decentralized clinical trial enrollment strategy offers reduced cost, reduced time requirements, and circumvents barriers associated with the recent pandemic outbreak. Method(s): After the mt-sRNA test system entered design-lock, a decentralized clinical trial (CRC-PREVENT) was launched through a digital campaign (https://www.colonscreeningstudy.com/;NCT04739722). Online advertisements were published on multiple social media sites, and engagement with materials directed patients to an online screener. Participants who completed the screener were eligible for enrollment if they met CRC-PREVENT inclusion and exclusion criteria and were willing to complete all clinical trial components, including providing a stool sample before an optical colonoscopy. Result(s): After 12 months of active enrollment, 276,400 individuals engaged with digital advertisements and completed pre-screener surveys to determine eligibility for the clinical trial. In total, 14,264 individuals consented to participate in the CRC-PREVENT clinical trial. Of these individuals, 58% were female (42% were male), and 65% were over 50. Regarding race and ethnicity, eligible individuals directly represented the intended use population: 16% were Black or African American, 0.2% were Native Hawaiian, Pacific Islander, American Indian, or Alaskan Native, and 7% were Hispanic or Latinx. Regarding socioeconomic status, the decentralized approach permitted access to individuals with healthcare inequities: 25% of participants had income under $29,999, 5% of participants were from rural areas (defined as a city center , 10,000 people), and 36.7% of participants were on public insurance. Individuals were derived from 7,644 unique zip codes across all 48 continental United States. (Table) Conclusion(s): A decentralized recruitment strategy permits highly successful enrollment in the face of screening burdens heightened by COVID-19 pandemic. This approach also offered a significantly more diverse population and could mitigate selection bias and attrition bias associated with the cohorts observed in traditional clinical studies.

12-MONTH CONSEQUENCES IN PEOPLE WITH HIV/SARS-CoV-2 COINFECTION: NATIONAL EHR COHORT

Background: Long-term consequences of COVID-19 are well characterized in general populations. Yet it remains unclear how existing HIV infection attributes to the risks of long-term consequences in people with coinfection of HIV/SARSCoV- 2. This study aims to examine the long-term consequences of people living with HIV (PLWH) at 12 months after the first SARS-CoV-2 infection. Method(s): Using the National COVID Cohort Collaborative (N3C), Electronic Health Records (EHR) sampled from 50 states and over 75 healthcare systems in the US, we constructed a cohort of PLWH with COVID-19 between March 1, 2020 and January 15, 2021, a historical control group (HIV individuals without COVID-19 between March 1, 2018 and January 15, 2019, two years predating the pandemic), and a contemporary control group (PLWH without COVID-19 between March 1, 2020 and January 15, 2021) to mitigate time/selection biases. The time of HIV infection was before March 1, 2020 for the cases and contemporary controls and, before March 1, 2018 for historical controls. The date of the first COVID-19 infection marked the start of a 12-month follow-up in the COVID-19 group. The start of follow-up in the contemporary controls was assigned by matching the same distribution of start dates of COVID-19 cases. We used logistic regression to examine odds ratios of health consequences at 12 months post COVID-19 comparing against contemporary and historical controls, respectively. Result(s): We identified 5,619, 41,791, and 24,240 patients for COVID-19 cases, contemporary controls, and historical controls, respectively. The COVID-19 group had significantly higher odds in acute respiratory distress syndrome [OR: 3.45, 95% CI (2.98, 3.99)], hypertension [OR: 1.41, 95% CI (1.29, 1.54)], congestive heart failure [OR: 1.36, 95% CI (1.14, 1.63)], myocardial infarction [OR: 1.51, 95% CI (1.22, 1.86)], and diabetes [OR: 1.62, 95% CI (1.42, 1.84)], compared to contemporary controls. Odds in these outcomes were significantly higher when compared to historical controls (Figure 1). Conclusion(s): This sentinel study for the first time reported elevated risks of multi-system dysfunction (i.e., respiratory, cardiovascular, and metabolic) among PLWH at 12 months post COVID-19. To our knowledge, it is the largest EHR cohort study assessing long-term consequences in PLWH. Our findings call for immediate attention to the post-COVID care among PLWH, including followup guidelines, care planning, and health policy tailored for PLWH.

Patients' and Pharmacists' Experiences of a Community Pharmacy-Based Diabetes Care Plan

Introduction: The traditional view of healthcare professionals as the main decision-makers has changed, recognising the importance of people managing their own conditions (1). An evidence-informed Community Pharmacy-Based Diabetes Care Plan (2) provided personcentred care for adults living with type 2 diabetes in Lagos, Nigeria. Due to the Covid-19 pandemic, community pharmacists (n =20) had monthly remote consultations with patients (n =89) over six months, supporting patients in setting and reviewing their own goals. Aim(s): Part of a larger evaluation, this paper aims to describe patients' and pharmacists' experiences, acceptability and contextual barriers and facilitators to the care plan. Method(s): An invitation for all participants to participate in study interviews during months 4-6 of the care plan was sent via the pharmacists. The researcher contacted participants that sent their consent or consent to contact form in remotely. Semi-structured telephone interviews were conducted with consent. Participants' reasons for enrolling, participation experiences, barriers and facilitators were explored. Interviews were conducted in English, audio-recorded and transcribed verbatim. Transcripts were thematically analysed, aided by NVivo12. At study completion, all patients were provided with a post-study questionnaire (PSQ). Result(s): Seventy patients completed the PSQ. Of these, 88% were satisfied with the service on a 10-point satisfaction scale (1= very dissatisfied and 10= very satisfied). All respondents stated that the care plan helped them manage their conditions better. Based on their experience with the care plan, all respondents indicated they were likely or much more likely to recommend the care plan to friends and family if they need similar care. Interviews lasting 14-42 minutes were conducted with 10 pharmacists and 15 patients. Seven themes emerged from the data: reasons for agreeing to participate;perception of pharmacy (premises and profession);remote consultations - a new way of working;service delivery and care coordination;acceptability of the care plan;types of goals, goal attainment and patients' satisfaction;and facilitators, barriers, and recommendations to the care plan. The care plan was perceived as valuable, and it improved patients' confidence regarding diabetes management. Key benefits of the care plan were patients' empowerment, including better self-care and addition to therapeutics. Monthly online (majority) meetings between the pharmacists and patients maintained patients' engagement with the care plan and allowed improvements in goal achievements and better follow-up across the pharmacies. The remote consultations were perceived as innovative and useful, though a few patients were seen face to face in particular circumstances. Identified barriers included time and technology. Patients were satisfied and passionate about the new service, and pharmacists were excited about the opportunities to provide person-centred care in their pharmacies. Conclusion(s): This study is the first mixed-methods evaluation of a person-centred goal-setting intervention for people living with diabetes in Lagos, Nigeria. It showed that the care plan was acceptable and useful to patients and pharmacists. It supports the importance of personalised care in diabetes management. A key limitation was selection bias-only those who expressed interest were interviewed. No follow-up on non-participants was done because the research team had no access to patients' contact details.

On the economic evaluation of online learning in higher education during the COVID-19 pandemic: a willingness-to-accept approach

PurposeThis study, using a contingent valuation approach, aims to shed light on the economic evaluation of online learning during the first wave of the pandemic. Design/methodology/approachA sample of 959 higher education students was asked about their willingness-to-accept (WTA) a monetary compensation for the loss of well-being resulting from the unexpected and mandatory transition to the online space. In explaining WTA determinants, the authors test the appropriateness of the double-hurdle model against the alternative of a Tobit model and find that the factors affecting the participation decision are not the same as those that affect the quantity decision. FindingsResults show that a vast majority of the respondents think that the abrupt transition to online learning is detrimental to them, while those willing to accept a monetary compensation account for 77% of the sample, being the mean WTA between euro448 and euro595. As expected, WTA decreases with income and age, and it increases if some member of the family unit is unemployed. By aggregating the mean WTA by the population affected, total loss of well-being is obtained. Originality/valueTo the best of the authors' knowledge, to date, this method has not been used to value online learning in a WTA framework, much less in the particular context of the pandemic. Thus, based on the understanding that the economic evaluation of online learning could be very useful in providing guidance for decision-making, this paper contributes to the literature on the economic evaluation of higher education.

Real-World Experience on the Use of COVID-19 Vaccination in Multiple Sclerosis Patients Treated with Cladribine Tablets Participating in the ADVEVA Patient Support Program within the Gulf and Latin American Regions

Background: National Multiple Sclerosis Society and other international guidelines suggest that full COVID-19 vaccination status should be completed two to four weeks before starting Year 2 of treatment with cladribine tablets (CladT). CladT is administered twice over two years, Year 1 and Year 2. There is a special interest in real-world evidence on whether vaccination status may affect initiation of CladT treatment in Year 2. The objective of this analysis was to describe the proportion of patients treated with CladT who received COVID-19 vaccination, and whether this influenced the timing of initiating treatment with CladT in Year 2. Material(s) and Method(s): A vaccination questionnaire-based survey was sent to patients treated with CladT who were enrolled in the ADVEVA patient support program (PSP), upon their consent. The survey was carried out in the Gulf region (GULF) from Jun 2021 to Sept 2021, and in the Latin American region (LATAM) from Jan 2022 to Mar 2022. Demographics, COVID-19 vaccination status, type of vaccine(s), number of doses received, and dates of vaccination were collected. In each region, patient data from the survey were linked to data routinely collected by the PSP, with cut-off dates as mentioned. Fully vaccinated status was defined as having received 2 doses of mRNA vaccine, 1 dose of Johnson & Johnson vaccine or other vaccines approved by the World Health Organization, plus 14 days. Descriptive analyses were performed and time to Year 2 treatment initiation among those with at least 18 months' follow-up was estimated by vaccination status. Result(s): The survey participation rate in GULF was 87% (91 out of 105) and 19% in LATAM (152 out of 789). In total, 62 (68%) patients in GULF and 144 (95%) in LATAM were fully vaccinated against COVID-19. In both regions, among those with at least 18 months' follow-up (GULF, n=59;LATAM, n=81), all patients initiated Year 2 of treatment with CladT, regardless of vaccination status. In GULF, the mean (standard deviation) time to treatment initiation in Year 2 was 13.8(1.6) months among fully vaccinated patients (44%) and 13.3(3.5) months among those not fully vaccinated (21%). In LATAM, the mean time was 12.8(1.4) months among those fully vaccinated (52%) and 12.4(0.02) months among those not fully vaccinated (1.3%). In each region, only 1 patient initiated Year 2 treatment after at least 18 months from the start of Year 1. Conclusion(s): Most patients were fully vaccinated against COVID-19 in GULF and in LATAM, which was consistent with vaccination coverage and guidelines in both regions. In LATAM, low participation rates might lead to selection bias which limits interpretation of results. In these regions, with limited data, COVID-19 vaccination status did not appear to alter the time of treatment initiation with CladT in Year 2. Almost all patients followed the label recommendations in terms of timing of Year 2 treatment initiation.Copyright © 2022

Comparing the incidence of SARS-CoV-2 across age groups considering sampling biases - use of testing data of autumn 2021 in Belgium.

BACKGROUND: To design efficient mitigation measures against COVID-19, understanding the transmission dynamics between different age groups was crucial. The role of children in the pandemic has been intensely debated and involves both scientific and ethical questions. To design efficient age-targeted non-pharmaceutical interventions (NPI), a good view of the incidence of the different age groups was needed. However, using Belgian testing data to infer real incidence (RI) from observed incidence (OI) or positivity ratio (PR) was not trivial. METHODS: Based on Belgian testing data collected during the Delta wave of Autumn 2021, we compared the use of different estimators of RI and analyzed their effect on comparisons between age groups. RESULTS: We found that the RI estimator's choice strongly influences the comparison between age groups. CONCLUSION: The widespread implementation of testing campaigns using representative population samples could help to avoid pitfalls related to the current testing strategy in Belgium and worldwide. This approach would also allow a better comparison of the data from different countries while reducing biases arising from the specificities of each surveillance system.

Unwarranted Exclusion of Intermediate Lineage A-B SARS-CoV-2 Genomes Is Inconsistent with the Two-Spillover Hypothesis of the Origin of COVID-19

Pekar et al. (2022) propose that SARS-CoV-2 was a zoonotic spillover that first infected humans in the Huanan Seafood Market in Wuhan, China. They propose that there were two separate spillovers of the closely related lineages A and lineage B in a short period of time. The two lineages are differentiated by two SNVs;hence, a single-SNV A-B intermediate must have occurred in an unsampled animal host if the two-spillover hypothesis is correct. Consequently, confirmation of the existence of an intermediate A-B genome from humans would falsify their hypothesis of two spillovers. Pekar et al. identified and excluded 20 A-B intermediate genomes from their analysis. A variety of exclusion criteria were applied, including low read depth and the assertion of repeated erroneous base calls at lineage-defining positions 8782 and 28144. However, data from GISAID show that most of the genomes were sequenced to high average sequencing depth, appearing inconsistent with these criteria. The decision to exclude the majority of genomes was based on personal communications, with raw data unavailable for inspection. Multiple errors, biases, and inconsistencies were observed in the exclusion process. For example, 12 intermediate genomes from one study were excluded;however, 54 other genomes from the same study were included, indicating selection bias. Puzzlingly, two intermediate genomes from Beijing were discarded despite an average sequencing depth of 2175X;however, four genomes from the same sequencing study were included in the analysis. Lastly, we discuss 14 additional possible intermediate genomes not discussed by Pekar et al. and note that genome sequence filtration is inappropriate when considering the presence or absence of a specific SNV pair in an outbreak. Consequently, we find that the exclusion of many of the intermediate genomes is unfounded, leaving the conclusion of two natural zoonoses unsupported.Copyright © 2023 by the authors.

Improving the representativeness of the tribal behavioral risk factor surveillance system through data integration.

BACKGROUND: Previous literature showed significant health disparities between Native American population and other populations such as Non-Hispanic White. Most existing studies for Native American Health were based on non-probability samples which suffer with selection bias. In this paper, we are the first to evaluate the effectiveness of data integration methods, including calibration and sequential mass imputation, to improve the representativeness of the Tribal Behavioral Risk Factor Surveillance System (TBRFSS) in terms of reducing the biases of the raw estimates. METHODS: We evaluated the benefits of our proposed data integration methods, including calibration and sequential mass imputation, by using the 2019 TBRFSS and the 2018 and 2019 Behavioral Risk Factor Surveillance System (BRFSS). We combined the data from the 2018 and 2019 BRFSS by composite weighting. Demographic variables and general health variables were used as predictors for data integration. The following health-related variables were used for evaluation in terms of biases: Smoking status, Arthritis status, Cardiovascular Disease status, Chronic Obstructive Pulmonary Disease status, Asthma status, Cancer status, Stroke status, Diabetes status, and Health Coverage status. RESULTS: For most health-related variables, data integration methods showed smaller biases compared with unadjusted TBRFSS estimates. After calibration, the demographic and general health variables benchmarked with those for the BRFSS. CONCLUSION: Data integration procedures, including calibration and sequential mass imputation methods, hold promise for improving the representativeness of the TBRFSS.

Research strategies in treatment of hypertension: value of retrospective real-life data.

This review will discuss the limitations of data collected by RCTs in relation to their applicability to daily life clinical management. It will then argue that these limitations are only partially overcome by modifications of RCT design and conduction (e.g. 'pragmatic trials') while being substantially attenuated by real-life-derived research, which can fill many gaps left by trial-collected evidence and have thus an important complementary value. The focus will be on the real-life research approach based on the retrospective analysis of the now widely available healthcare utilization databases (formerly known as administrative databases), which will be discussed in detail for their multiple advantages as well as challenges. Emphasis will be given to the potential of these databases to provide low-cost information over long periods on many different healthcare issues, drug therapies in particular, from the general population to clinically important subgroups, including (i) prognostic aspects of treatments implemented at the medical practice level via hospitalization and fatality data and (ii) medical practice-related phenomena such as low treatment adherence and therapeutic inertia (unsatisfactorily evaluated by RCTs). It will also be mentioned that thanks to the current availability of these data in electronic format, results can be obtained quickly, helping timely decisions under emergencies. The potential shortcomings of this approach (confounding by indication, misclassification, and selection bias) will also be discussed along with their possible minimization by suitable analytic means. Finally, examples of the contributions of studies on hypertension and other cardiovascular risk factors will be offered based on retrospective healthcare utilization databases that have provided information on real-life cardiovascular treatments unavailable via RCTs.

Incidence of COVID-19 hospitalization in patients with psoriasis taking systemic immunomodulators

Background: Current research on COVID-19-related outcomes in patients with psoriasis, particularly regarding influence of treatments, are subject to lack of comparator group, selection bias, and insufficient statistical power.1 Accordingly, it remains uncertain whether immunomodulatory treatments for psoriasis enhance or decrease the risk of severe COVID-19-related outcomes, including hospitalization. Objective(s): To compare the risk of COVID-19-related hospitalization according to immunomodulator treatment type in patients with psoriasis Methods: Retrospective cohort study of the Explorys database in the United States between March 1st, 2020 and December 31st, 2020. Psoriasis diagnosis was defined by at least 2 ICD-9 or ICD-10 diagnosis codes prior to March 1st, 2020. Drug exposure was classified as biologic or traditional immunosuppressive (methotrexate, cyclosporine, apremilast) treatment based on prescription order in the 3 months preceding March 1st, 2020. Biologic treatments included TNFalpha, IL-12/IL-23, IL-17A, IL-23 and JAK inhibitors. The primary outcome was defined as hospital admission with diagnosis of COVID-19 or positive lab test occurring between admission and discharge date. Propensity score weighting was used to compare COVID-19-related hospitalization between treatment groups, adjusting for comorbidities and demographic characteristics. Result(s): A total of 51,606 psoriasis patients aged 18-88 were included. Crude cumulative incidence of COVID-19 hospitalization per 1,000 psoriasis patients was 3.4 in the biologic group (9/2,669), 9.5 in the traditional immunosuppressive group (15/1,585), and 3.9 in those receiving neither drug class (184/47,352). Incidence was 4.7 (6/1,282) and 14 (13/898) per 1,000 patients among those receiving TNF-alpha inhibitors and methotrexate, respectively. After propensity-score weighting, risk of COVID-19-related hospitalization for patients receiving any biologic was lower than that of patients receiving traditional immunosuppressives (RR 0.39, 95% CI 0.16, 0.92), and those receiving neither drug class (RR 0.66, 95% CI 0.32, 1.34). TNF-alpha inhibitor use was associated with lower risk of hospitalization relative to methotrexate use (adjusted RR 0.39, 95% CI 0.14, 1.06). Adjusted relative risk of hospitalization for methotrexate users relative to those receiving neither drug class was 2.78 (95% CI 1.47, 5.26). Conclusion(s): During the first wave of the pandemic in 2020, psoriasis patients using biologics were at lower risk of COVID-19-related hospitalization compared to those using traditional immunosuppressives, particularly methotrexate. Methotrexate use was associated with a substantial increase in risk of hospitalization relative to those who did not receive systemic treatments.

Understanding COVID-19 Vaccine Effectiveness against Death Using a Novel Measure: COVID Excess Mortality Percentage.

COVID-19 vaccines have saved millions of lives; however, understanding the long-term effectiveness of these vaccines is imperative to developing recommendations for booster doses and other precautions. Comparisons of mortality rates between more and less vaccinated groups may be misleading due to selection bias, as these groups may differ in underlying health status. We studied all adult deaths during the period of 1 April 2021-30 June 2022 in Milwaukee County, Wisconsin, linked to vaccination records, and we used mortality from other natural causes to proxy for underlying health. We report relative COVID-19 mortality risk (RMR) for those vaccinated with two and three doses versus the unvaccinated, using a novel outcome measure that controls for selection effects. This measure, COVID Excess Mortality Percentage (CEMP), uses the non-COVID natural mortality rate (Non-COVID-NMR) as a measure of population risk of COVID mortality without vaccination. We validate this measure during the pre-vaccine period (Pearson correlation coefficient = 0.97) and demonstrate that selection effects are large, with non-COVID-NMRs for two-dose vaccinees often less than half those for the unvaccinated, and non-COVID NMRs often still lower for three-dose (booster) recipients. Progressive waning of two-dose effectiveness is observed, with an RMR of 10.6% for two-dose vaccinees aged 60+ versus the unvaccinated during April-June 2021, rising steadily to 36.2% during the Omicron period (January-June, 2022). A booster dose reduced RMR to 9.5% and 10.8% for ages 60+ during the two periods when boosters were available (October-December, 2021; January-June, 2022). Boosters thus provide important additional protection against mortality.

Exploring the impact of selection bias in observational studies of COVID-19: a simulation study.

BACKGROUND: Non-random selection of analytic subsamples could introduce selection bias in observational studies. We explored the potential presence and impact of selection in studies of SARS-CoV-2 infection and COVID-19 prognosis. METHODS: We tested the association of a broad range of characteristics with selection into COVID-19 analytic subsamples in the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank (UKB). We then conducted empirical analyses and simulations to explore the potential presence, direction and magnitude of bias due to this selection (relative to our defined UK-based adult target populations) when estimating the association of body mass index (BMI) with SARS-CoV-2 infection and death-with-COVID-19. RESULTS: In both cohorts, a broad range of characteristics was related to selection, sometimes in opposite directions (e.g. more-educated people were more likely to have data on SARS-CoV-2 infection in ALSPAC, but less likely in UKB). Higher BMI was associated with higher odds of SARS-CoV-2 infection and death-with-COVID-19. We found non-negligible bias in many simulated scenarios. CONCLUSIONS: Analyses using COVID-19 self-reported or national registry data may be biased due to selection. The magnitude and direction of this bias depend on the outcome definition, the true effect of the risk factor and the assumed selection mechanism; these are likely to differ between studies with different target populations. Bias due to sample selection is a key concern in COVID-19 research based on national registry data, especially as countries end free mass testing. The framework we have used can be applied by other researchers assessing the extent to which their results may be biased for their research question of interest.

Comparative hospitalization risk for SARS-CoV-2 Omicron and Delta variant infections, by variant predominance periods and patient-level sequencing results, New York City, August 2021-January 2022.

BACKGROUND: Comparing disease severity between SARS-CoV-2 variants among populations with varied vaccination and infection histories can help characterize emerging variants and support healthcare system preparedness. METHODS: We compared COVID-19 hospitalization risk among New York City residents with positive laboratory-based SARS-CoV-2 tests when ≥98% of sequencing results were Delta (August-November 2021) or Omicron (BA.1 and sublineages, January 2022). A secondary analysis defined variant exposure using patient-level sequencing results during July 2021-January 2022, comprising 1-18% of weekly confirmed cases. RESULTS: Hospitalization risk was lower among patients testing positive when Omicron (16,025/488,053, 3.3%) than when Delta predominated (8268/158,799, 5.2%). In multivariable analysis adjusting for demographic characteristics and prior diagnosis and vaccination status, patients testing positive when Omicron predominated, compared with Delta, had 0.72 (95% CI: 0.63, 0.82) times the hospitalization risk. In a secondary analysis of patients with sequencing results, hospitalization risk was similar among patients infected with Omicron (2042/29,866, 6.8%), compared with Delta (1780/25,272, 7.0%), and higher among the subset who received two mRNA vaccine doses (adjusted relative risk 1.64; 95% CI: 1.44, 1.87). CONCLUSIONS: Hospitalization risk was lower among patients testing positive when Omicron predominated, compared with Delta. This finding persisted after adjusting for prior diagnosis and vaccination status, suggesting intrinsic virologic properties, not population-based immunity, explained the lower severity. Secondary analyses demonstrated collider bias from the sequencing sampling frame changing over time in ways associated with disease severity. Representative data collection is necessary to avoid bias when comparing disease severity between previously dominant and newly emerging variants.

Evaluation of the representativeness of data in the COVID-19 Registry Japan during the first six waves of the epidemic.

The COVID-19 Registry Japan (COVIREGI-JP), a registry of patients hospitalized with coronavirus disease (COVID-19), contains the largest national COVID-19 inpatient population. Since COVIREGI-JP invites voluntary participation by facilities, selection bias is inevitable. The current study examined the representativeness of COVIREGI-JP data in comparison to open-source national data. The number of infections and deaths among hospitalized COVID-19 patients in COVIREGI-JP were compared to those in national data recorded during the six waves of the COVID-19 epidemic until March 6, 2022. During the period studied, patients in COVIREGI-JP represented 1% of the total COVID-19 cases according to national data; the proportion was high during the first wave (32.7%) and tended to decrease, especially after the fourth wave. The overall proportion of patients from each region varied from 0.8% to 2.5%, but case fatality rates in COVIREGI-JP tended to be higher than those in the national data, with the exception of a few waves, in several regions. The difference was smallest during the first wave. Although COVIREGI-JP consistently registered cases from all regions of the country, the proportion tended to decline after the beginning of the epidemic. Given the epidemiological persistence and the ever-changing epidemiology of COVID-19, continued case registration and data utilization in COVIREGI-JP is desirable, although selection bias in COVIREGI-JP registration of cases should be carefully interpreted.

How well do covariates perform when adjusting for sampling bias in online COVID-19 research? Insights from multiverse analyses.

COVID-19 research has relied heavily on convenience-based samples, which-though often necessary-are susceptible to important sampling biases. We begin with a theoretical overview and introduction to the dynamics that underlie sampling bias. We then empirically examine sampling bias in online COVID-19 surveys and evaluate the degree to which common statistical adjustments for demographic covariates successfully attenuate such bias. This registered study analysed responses to identical questions from three convenience and three largely representative samples (total N = 13,731) collected online in Canada within the International COVID-19 Awareness and Responses Evaluation Study ( www.icarestudy.com ). We compared samples on 11 behavioural and psychological outcomes (e.g., adherence to COVID-19 prevention measures, vaccine intentions) across three time points and employed multiverse-style analyses to examine how 512 combinations of demographic covariates (e.g., sex, age, education, income, ethnicity) impacted sampling discrepancies on these outcomes. Significant discrepancies emerged between samples on 73% of outcomes. Participants in the convenience samples held more positive thoughts towards and engaged in more COVID-19 prevention behaviours. Covariates attenuated sampling differences in only 55% of cases and increased differences in 45%. No covariate performed reliably well. Our results suggest that online convenience samples may display more positive dispositions towards COVID-19 prevention behaviours being studied than would samples drawn using more representative means. Adjusting results for demographic covariates frequently increased rather than decreased bias, suggesting that researchers should be cautious when interpreting adjusted findings. Using multiverse-style analyses as extended sensitivity analyses is recommended.