RAPID POINT-OF-CARE DETECTION OF SARS-COV-2 BY ALVEO BE.WELL PLATFORM: ANALYTICAL AND CLINICAL EVALUATIONS (preprint)

BACKGROUNDThe pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has had a profound global impact on human health and the economy. Early diagnosis and prompt effective treatment can reduce disease spread. At present, the majority of high-accuracy diagnostic tests for COVID-19 are conducted in specialized laboratories and rely on conventional quantitative real-time polymerase chain reaction (PCR) techniques. This diagnostic approach presents several challenges, including prolonged turnaround times and high costs due to the time and technical skills required to administer test protocols. Our primary aim is to develop a diagnostic platform suitable for use entirely within the point-of-care setting, avoiding the time and resource requirements of standard PCR test processing conducted away from the point-of-care. METHODS AND FINDINGSWe developed the Alveo be.well COVID-19 Test as a diagnostic tool for qualitative detection of SARS-CoV-2 RNA in upper respiratory specimens. This innovative test detects viral RNA from SARS-CoV-2 within an unprocessed nasal specimen through the application of reverse transcription-loop mediated isothermal amplification (RT-LAMP) and electrical impedance measurement. The LAMP test primers are specifically designed to amplify a conserved region in the nucleocapsid gene of SARS-CoV-2 RNA, ensuring detection accuracy. To enhance usability and shelf life at ambient temperature, the primers are embedded within a microfluidic cartridge, along with other required reagents for viral target amplification. This test is designed for point-of-care settings, offering a straightforward and user-friendly process. The test includes: nasal swab sample collection; elution of the sample in a buffer; transfer of the eluted sample into the cartridge; insertion of the cartridge into an analyzer for amplification, and real-time result interpretation. All processing steps, including heating, mixing, amplification, and detection, occur within the cartridge during the test run, making it particularly user-friendly and obviating the need for significant user training. Results are displayed on a mobile smart device within approximately 50 minutes, via the be.well app, facilitating real-time decision-making in the point-of-care environment. Test and result data is also transferred to and stored in the cloud. To evaluate the analytical performance of this platform, we initially assessed the analytical sensitivity and specificity of the Alveo be.well COVID-19 test. We also evaluated the diagnostic performance of the Alveo be.well COVID-19 assay using contrived reference samples. Furthermore, we validated the clinical performance of the Alveo be.well COVID-19 test in different clinical settings in both USA and United Kingdom during the pandemic seasons in 2020 through 2022. Test results from 253 nasal swab samples were compared to a real-time reverse transcription polymerase chain reaction (RT-PCR) reference standard. CONCLUSIONSThe development of the Alveo be.well platform for infectious disease testing, including SARS-CoV-2 diagnosis, represents a significant advancement in portable diagnostic technology, encompassing both nucleic acid amplification and detection technologies. In testing SARS-CoV-2, the system amplifies the nucleic acid target within unprocessed nasal specimens using RT-LAMP chemistry, while concurrently measuring the electrical impedance signal produced during target amplification process, delivering results in under an hour. The system exhibits high analytical specificity and sensitivity, with a limit of detection of as low as 4000 viral genomic copies per milliliter, making it highly effective for detecting the SARS-CoV-2 target. Results derived from clinical validation studies showed 93% sensitivity and 95% specificity when compared to RT-qPCR. This system was demonstrated to be a user-friendly and rapid diagnostic platform with high analytical and clinical specificity and sensitivity for SARS-CoV-2 detection with the potential to facilitate early, fast diagnosis of SARS-CoV-2 to help contain the spread of the disease, particularly in point-of-care settings.

Potential impact of annual vaccination with reformulated COVID-19 vaccines: lessons from the U.S. COVID-19 Scenario Modeling Hub (preprint)

ImportanceCOVID-19 continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. ObjectiveTo project COVID-19 hospitalizations and deaths from April 2023-April 2025 under two plausible assumptions about immune escape (20% per year and 50% per year) and three possible CDC recommendations for the use of annually reformulated vaccines (no vaccine recommendation, vaccination for those aged 65+, vaccination for all eligible groups). DesignThe COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023-April 15, 2025 under six scenarios representing the intersection of considered levels of immune escape and vaccination. State and national projections from eight modeling teams were ensembled to produce projections for each scenario. SettingThe entire United States. ParticipantsNone. ExposureAnnually reformulated vaccines assumed to be 65% effective against strains circulating on June 15 of each year and to become available on September 1. Age and state specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. Main outcomes and measuresEnsemble estimates of weekly and cumulative COVID-19 hospitalizations and deaths. Expected relative and absolute reductions in hospitalizations and deaths due to vaccination over the projection period. ResultsFrom April 15, 2023-April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November-January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% PI: 1,438,000-4,270,000) hospitalizations and 209,000 (90% PI: 139,000-461,000) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% CI: 104,000-355,000) fewer hospitalizations and 33,000 (95% CI: 12,000-54,000) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000-598,000) fewer hospitalizations and 49,000 (95% CI: 29,000-69,000) fewer deaths. Conclusion and RelevanceCOVID-19 is projected to be a significant public health threat over the coming two years. Broad vaccination has the potential to substantially reduce the burden of this disease. Key pointsO_ST_ABSQuestionC_ST_ABSWhat is the likely impact of COVID-19 from April 2023-April 2025 and to what extent can vaccination reduce hospitalizations and deaths? FindingsUnder plausible assumptions about viral evolution and waning immunity, COVID-19 will likely cause annual epidemics peaking in November-January over the two-year projection period. Though significant, hospitalizations and deaths are unlikely to reach levels seen in previous winters. The projected health impacts of COVID-19 are reduced by 10-20% through moderate use of reformulated vaccines. MeaningCOVID-19 is projected to remain a significant public health threat. Annual vaccination can reduce morbidity, mortality, and strain on health systems.

Postacute Sequelae SARS-CoV-2 Infection by Vaccination Status: A Six-Month Latent Class Analysis (preprint)

Symptoms post- SARS-CoV-2 infection may persist for months and cause significant impairment and impact to quality of life. Acute symptoms of SARS-CoV-2 infection are well studied, yet data on clusters of symptoms over time, or postacute sequelae of SARS-CoV-2 infection (PASC), are limited. We aim to characterize PASC phenotypes by identifying symptom clusters over a six-month period following infection in individuals vaccinated (boosted and not) and those unvaccinated. Subjects with [≥]1 self-reported symptom and positive RT-PCR for SARS-CoV-2 at CVS Health US test sites were recruited between January and April 2022. Patient-reported outcomes symptoms, heath-related quality of life (QoL), work productivity and activity impairment (WPAI) were captured at 1 month, 3 months, and 6 months post-acute infection. Logistic regression and latent class analysis (LCA) were performed on 20 symptoms using baseline socio-demographic, clinical characteristics, and vaccination status as well as EQ-5and WPAI results as covariables. Subjects with more symptoms were associated with lower health-related quality of life, and worse WPAI scores. LCA identified three phenotypes that are primarily differentiated by number of symptoms. These three phenotypes remained consistent across time periods. Vaccinated individuals were more likely to be in the low symptom burden latent classes at all time points compared to unvaccinated individuals.

Impact of bivalent BA.4/5 BNT162b2 COVID-19 vaccine on acute symptoms, quality of life, work productivity and activity levels among symptomatic US adults testing positive for SARS-CoV-2 at a national retail pharmacy (preprint)

BackgroundEvidence on the impact of COVID-19 vaccination on symptoms, Health-Related Quality of Life (HRQoL), Work Productivity and Activity Impairment (WPAI) is scarce. We analyzed associations between bivalent BA.4/5 BNT162b2 and these patient-reported outcomes (PROs). MethodsSymptomatic US adults who tested positive for SARS-CoV-2 were recruited between 03/02-05/18/2023. PROs were assessed using a CDC-based symptom questionnaire, EQ-5D-5L, WPAI-GH, and PROMIS Fatigue, from pre-COVID to Week 4 following infection. Multivariable analysis using mixed models for repeated measures was conducted, adjusting for several covariates. ResultsThe study included 641 participants: 314 vaccinated with bivalent BA.4/5 BNT162b2 and 327 unvaccinated/not up-to-date. Mean (SD) age was 46.5 years (15.9), 71.2% were female, 44.2% reported prior infection, 25.7% had [≥]1 comorbidity. The BA.4/5 BNT162b2 cohort reported fewer acute symptoms through Week 4, especially systemic and respiratory symptoms. All PROs were adversely affected, especially at Week 1; however, at that time point, the bivalent BA.4/5 BNT162b2 cohort reported better work performance, driven by less absenteeism, and fewer work hours lost. No significant differences were observed for HRQoL. ConclusionsCOVID-19 negatively impacted patient outcomes. Compared with unvaccinated/not up-to-date participants, those vaccinated with bivalent BA.4/5 BNT162b2 reported fewer and less persistent symptoms and improved work performance. Clinicaltrials.gov NCT05160636

Informing pandemic response in the face of uncertainty. An evaluation of the U.S. COVID-19 Scenario Modeling Hub (preprint)

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make 6-month ahead projections of the number of SARS-CoV-2 cases, hospitalizations and deaths. The SMH released nearly 1.8 million national and state-level projections between February 2021 and November 2022. SMH performance varied widely as a function of both scenario validity and model calibration. Scenario assumptions were periodically invalidated by the arrival of unanticipated SARS-CoV-2 variants, but SMH still provided projections on average 22 weeks before changes in assumptions (such as virus transmissibility) invalidated scenarios and their corresponding projections. During these periods, before emergence of a novel variant, a linear opinion pool ensemble of contributed models was consistently more reliable than any single model, and projection interval coverage was near target levels for the most plausible scenarios (e.g., 79% coverage for 95% projection interval). SMH projections were used operationally to guide planning and policy at different stages of the pandemic, illustrating the value of the hub approach for long-term scenario projections.

Adherence to Psychotropic Medication Before and During COVID-19: A Population-Wide Retrospective Observational Study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic and associated public health measures have shifted the way people access health care. We aimed to study the effects of the COVID-19 pandemic on psychotropic medication adherence. METHODS: A retrospective cohort study using administrative data from the Manitoba Centre for Health Policy Manitoba Population Research Data Repository was conducted. Outpatients who received at least 1 prescription for an antidepressant, antipsychotic, anxiolytic/sedative-hypnotic, cannabinoid, lithium, or stimulants from 2015 to 2020 in Manitoba, Canada, were included. Adherence was measured using the proportion of individuals with a mean possession ratio of ≥0.8 over each quarter. Each quarter of 2020 after COVID-19-related health measures were implemented was compared with the expected trend using autoregression models for time series data plus indicator variables. Odds ratio of drug discontinuation among those previously adherent in 2020 was compared with each respective quarter of 2019. RESULTS: There were 1,394,885 individuals in the study population in the first quarter of 2020 (mean [SD] age, 38.9 [23.4] years; 50.3% female), with 36.1% having a psychiatric diagnosis in the preceding 5 years. Compared with the expected trend, increases in the proportions of individuals adherent to antidepressants and stimulants were observed in the fourth quarter (October-December) of 2020 (both P < 0.001). Increases in the proportions of individuals with anxiolytic and cannabinoid adherence were observed in the third quarter (July-September) of 2020 (both P < 0.05), whereas a decrease was seen with stimulants in the same quarter ( P < 0.0001). No significant changes were observed for antipsychotics. All drug classes except lithium had decreases in drug discontinuation in previously adherent patients during the pandemic compared with 2019. CONCLUSIONS: Improved adherence to most psychotropic medications in the 9 months after public health restrictions were enacted was observed. Patients who were already adherent to their psychotropic medications were less likely to discontinue them during the pandemic.

Challenges of COVID-19 Case Forecasting in the US, 2020-2021 (preprint)

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naive baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making. Author SummaryAs SARS-CoV-2 began to spread throughout the world in early 2020, modelers played a critical role in predicting how the epidemic could take shape. Short-term forecasts of epidemic outcomes (for example, infections, cases, hospitalizations, or deaths) provided useful information to support pandemic planning, resource allocation, and intervention. Yet, infectious disease forecasting is still a nascent science, and the reliability of different types of forecasts is unclear. We retrospectively evaluated COVID-19 case forecasts, which were often unreliable. For example, forecasts did not anticipate the speed of increase in cases in early winter 2020. This analysis provides insights on specific problems that could be addressed in future research to improve forecasts and their use. Identifying the strengths and weaknesses of forecasts is critical to improving forecasting for current and future public health responses.

Covid-19 CSR Activation by Malaysian Companies: Evidence from Online News

The novel Coronavirus (Covid-19) has badly affected individuals and organizations all around the globe. There are many efforts undertaken by organizations to assist governments in combating the pandemic. This include spending funds to curb the Coronavirus which is the corporate social responsibility (CSR) activities. This paper aims to investigate the extent of CSR activation by Malaysian companies in battling the Covid-19 pandemic via content analysis of online news during the implementation of the Movement Control Order by the government using the legitimacy theory and coercive isomorphism under the umbrella of institutional theory. The analysis includes the examination of online news which was captured from a Google search from a period 18 March to 17 May 2020. There were 95 online news captured during the period. The results found out that the types of CSR activation were classified into: monetary, non-monetary and both. It is also found that the CSR activation reported on online news is part of the companies' legitimation strategies in addition to the on-going business's marketing strategies. Several implications and limitations are also provided in this paper. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Sustainable Teaching: Teacher Readiness for Online Teaching Working from Home

The COVID-19 pandemic has prompted a shift to online education, and work from home is becoming the new normal for teachers. Key areas of interest in this context are teacher readiness, online teaching, and working from home. Through a rigorous literature survey, this paper identifies gaps, looks for possibilities, and identifies factors affecting teacher readiness, online teaching, and working from home for online teachers. Five main areas for intervention are identified: keeping online audience attention, technology and preliminary infrastructure, social and emotional factors of online teachers, learner readiness, and effective management. The future course of research is also discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Barriers and solutions to developing and maintaining research networks during a pandemic: An example from the iELEVATE perinatal network.

Introduction: To improve maternal health outcomes, increased diversity is needed among pregnant people in research studies and community surveillance. To expand the pool, we sought to develop a network encompassing academic and community obstetrics clinics. Typical challenges in developing a network include site identification, contracting, onboarding sites, staff engagement, participant recruitment, funding, and institutional review board approvals. While not insurmountable, these challenges became magnified as we built a research network during a global pandemic. Our objective is to describe the framework utilized to resolve pandemic-related issues. Methods: We developed a framework for site-specific adaptation of the generalized study protocol. Twice monthly video meetings were held between the lead academic sites to identify local challenges and to generate ideas for solutions. We identified site and participant recruitment challenges and then implemented solutions tailored to the local workflow. These solutions included the use of an electronic consent and videoconferences with local clinic leadership and staff. The processes for network development and maintenance changed to address issues related to the COVID-19 pandemic. However, aspects of the sample processing/storage and data collection elements were held constant between sites. Results: Adapting our consenting approach enabled maintaining study enrollment during the pandemic. The pandemic amplified issues related to contracting, onboarding, and IRB approval. Maintaining continuity in sample management and clinical data collection allowed for pooling of information between sites. Conclusions: Adaptability is key to maintaining network sites. Rapidly changing guidelines for beginning and continuing research during the pandemic required frequent intra- and inter-institutional communication to navigate.

COVID-19 vaccine hesitancy among non-refugees and refugees in Kenya.

Factors associated with COVID-19 vaccine hesitancy (which we define as refusal to be vaccinated when asked, resulting in delayed or non- vaccination) are poorly studied in sub-Saharan Africa and among refugees, particularly in Kenya. Using survey data from wave five (March to June 2021) of the Kenya Rapid Response Phone Survey (RRPS), a household survey representative of the population of Kenya, we estimated the self-reported rates and factors associated with vaccine hesitancy among non-refugees and refugees in Kenya. Non-refugee households were recruited through sampling of the 2015/16 Kenya Household Budget Survey and random digit dialing. Refugee households were recruited through random sampling of registered refugees. Binary response questions on misinformation and information were transformed into a scale. We performed a weighted (to be representative of the overall population of Kenya) multivariable logistic regression including interactions for refugee status, with the main outcome being if the respondent self-reported that they would not take the COVID-19 vaccine if available at no cost. We calculated the marginal effects of the various factors in the model. The weighted univariate analysis estimated that 18.0% of non-refugees and 7.0% of refugees surveyed in Kenya would not take the COVID-19 vaccine if offered at no cost. Adjusted, refugee status was associated with a -13.1[95%CI:-17.5,-8.7] percentage point difference (ppd) in vaccine hesitancy. For the both refugees and non-refugees, having education beyond the primary level, having symptoms of COVID-19, avoiding handshakes, and washing hands more often were also associated with a reduction in vaccine hesitancy. Also for both, having used the internet in the past three months was associated with a 8.1[1.4,14.7] ppd increase in vaccine hesitancy; and disagreeing that the government could be trusted in responding to COVID-19 was associated with a 25.9[14.2,37.5]ppd increase in vaccine hesitancy. There were significant interactions between refugee status and some variables (geography, food security, trust in the Kenyan government's response to COVID-19, knowing somebody with COVID-19, internet use, and TV ownership). These relationships between refugee status and certain variables suggest that programming between refugees and non-refugees be differentiated and specific to the contextual needs of each group.

Virtually the Same? Evaluating the Effectiveness of Remote Undergraduate Research Experiences.

In-person undergraduate research experiences (UREs) promote students' integration into careers in life science research. In 2020, the COVID-19 pandemic prompted institutions hosting summer URE programs to offer them remotely, raising questions about whether undergraduates who participate in remote research can experience scientific integration and whether they might perceive doing research less favorably (i.e., not beneficial or too costly). To address these questions, we examined indicators of scientific integration and perceptions of the benefits and costs of doing research among students who participated in remote life science URE programs in Summer 2020. We found that students experienced gains in scientific self-efficacy pre- to post-URE, similar to results reported for in-person UREs. We also found that students experienced gains in scientific identity, graduate and career intentions, and perceptions of the benefits of doing research only if they started their remote UREs at lower levels on these variables. Collectively, students did not change in their perceptions of the costs of doing research despite the challenges of working remotely. Yet students who started with low cost perceptions increased in these perceptions. These findings indicate that remote UREs can support students' self-efficacy development, but may otherwise be limited in their potential to promote scientific integration.

Education and Rehabilitation of Incarcerated Youth during COVID-19: Views of State-Level Administrators

The present study addresses the complexities of providing education and rehabilitation to incarcerated youth during the COVID-19 crisis. A total of three state-level administrators, one supervisor for juvenile residential services health care, and one medical director of state detention centers from three states completed a survey focusing on the key domains of education, physical safety, mental health support, social support, support for physical health, and information sharing. With each domain, respondents were queried on the adequacy and basis of policies, as well as monitoring of compliance with policies and barriers to compliance. The state officials then each participated in two 45-minute interviews. Results indicate that the survey respondents found policies to be adequate across domains. Interview findings yielded across-state themes of learned capability and collaboration and/or cooperation. Additional results, as well as implications for research and practices, are discussed.

Assessing the impact of non-pharmaceutical interventions on SARS-CoV-2 transmission in Switzerland.

Following the rapid dissemination of COVID-19 cases in Switzerland, large-scale non-pharmaceutical interventions (NPIs) were implemented by the cantons and the federal government between 28 February and 20 March 2020. Estimates of the impact of these interventions on SARS-CoV-2 transmission are critical for decision making in this and future outbreaks. We here aim to assess the impact of these NPIs on disease transmission by estimating changes in the basic reproduction number (R0) at national and cantonal levels in relation to the timing of these NPIs. We estimated the time-varying R0 nationally and in eleven cantons by fitting a stochastic transmission model explicitly simulating within-hospital dynamics. We used individual-level data from more than 1000 hospitalised patients in Switzerland and public daily reports of hospitalisations and deaths. We estimated the national R0 to be 2.8 (95% confidence interval 2.1–3.8) at the beginning of the epidemic. Starting from around 7 March, we found a strong reduction in time-varying R0 with a 86% median decrease (95% quantile range [QR] 79–90%) to a value of 0.40 (95% QR 0.3–0.58) in the period of 29 March to 5 April. At the cantonal level, R0 decreased over the course of the epidemic between 53% and 92%. Reductions in time-varying R0 were synchronous with changes in mobility patterns as estimated through smartphone activity, which started before the official implementation of NPIs. We inferred that most of the reduction of transmission is attributable to behavioural changes as opposed to natural immunity, the latter accounting for only about 4% of the total reduction in effective transmission. As Switzerland considers relaxing some of the restrictions of social mixing, current estimates of time-varying R0 well below one are promising. However, as of 24 April 2020, at least 96% (95% QR 95.7–96.4%) of the Swiss population remains susceptible to SARS-CoV-2. These results warrant a cautious relaxation of social distance practices and close monitoring of changes in both the basic and effective reproduction numbers.

COVID-19 vaccine hesitancy among non-refugees and refugees in Kenya

Factors associated with COVID-19 vaccine hesitancy (which we define as refusal to be vaccinated when asked, resulting in delayed or non- vaccination) are poorly studied in sub-Saharan Africa and among refugees, particularly in Kenya. Using survey data from wave five (March to June 2021) of the Kenya Rapid Response Phone Survey (RRPS), a household survey representative of the population of Kenya, we estimated the self-reported rates and factors associated with vaccine hesitancy among non-refugees and refugees in Kenya. Non-refugee households were recruited through sampling of the 2015/16 Kenya Household Budget Survey and random digit dialing. Refugee households were recruited through random sampling of registered refugees. Binary response questions on misinformation and information were transformed into a scale. We performed a weighted (to be representative of the overall population of Kenya) multivariable logistic regression including interactions for refugee status, with the main outcome being if the respondent self-reported that they would not take the COVID-19 vaccine if available at no cost. We calculated the marginal effects of the various factors in the model. The weighted univariate analysis estimated that 18.0% of non-refugees and 7.0% of refugees surveyed in Kenya would not take the COVID-19 vaccine if offered at no cost. Adjusted, refugee status was associated with a -13.1[95%CI:-17.5,-8.7] percentage point difference (ppd) in vaccine hesitancy. For the both refugees and non-refugees, having education beyond the primary level, having symptoms of COVID-19, avoiding handshakes, and washing hands more often were also associated with a reduction in vaccine hesitancy. Also for both, having used the internet in the past three months was associated with a 8.1[1.4,14.7] ppd increase in vaccine hesitancy;and disagreeing that the government could be trusted in responding to COVID-19 was associated with a 25.9[14.2,37.5]ppd increase in vaccine hesitancy. There were significant interactions between refugee status and some variables (geography, food security, trust in the Kenyan government's response to COVID-19, knowing somebody with COVID-19, internet use, and TV ownership). These relationships between refugee status and certain variables suggest that programming between refugees and non-refugees be differentiated and specific to the contextual needs of each group.

Factors associated with an increase in tobacco use and alcohol drinking during the COVID-19 pandemic: A cross-sectional study of data from 105 countries.

INTRODUCTION: The COVID-19 pandemic has inevitably led to monumental challenges, and alcohol drinking and tobacco use have unlikely been spared. This cross-sectional survey reports on factors associated with an increase in alcohol drinking and tobacco use during the COVID-19 pandemic. METHODS: An online survey conducted in 2020, generated data from 14899 adults residing in 105 countries. Dependent variables were changes in alcohol drinking and tobacco use. Independent variables were age, sex, education level, job loss, lost or reduced wages, investment/retirement benefits, interrupted substance addiction care, and income level of the countries. Multilevel logistic regression analysis was computed to explore the associations between dependent and independent variables in adjusted models using the backward stepwise method. The probability of including or excluding a covariate was set at p(in)<0.05 and p(out)>0.1, respectively. RESULTS: Of the regular alcohol consumers (N=4401), 22.9% reported an increase in their alcohol drinking. Of the regular tobacco users (N=2718), 31% reported an increase in their tobacco use. Job loss (Alcohol: AOR=1.26; Tobacco: AOR=1.32) and lost/reduced wages (Alcohol: AOR=1.52; Tobacco: AOR=1.52) were associated with higher odds of increased alcohol drinking and tobacco use. Many interruptions to addiction care (AOR=1.75) were associated with higher odds of increased alcohol drinking. Whereas no interruption to addiction care was associated with lower odds of increased alcohol drinking (AOR=0.77). Also, none (AOR=0.66) or some (AOR=0.70) interruptions to addiction care were associated with lower odds of increased tobacco use. CONCLUSIONS: This global survey alludes to the unintended consequences of the current COVID-19 pandemic on alcohol drinking and tobacco use. It is critical that the strategies for emergency responses should include support to ameliorate the impact of financial distress and disruption in substance dependence treatment services.

Impact of COVID-19 and effects of booster vaccination with BNT162b2 on six-month long COVID symptoms, quality of life, work productivity and activity impairment during Omicron (preprint)

Background: Longitudinal estimates of long COVID burden during Omicron remain limited. This study characterized long-term impacts of COVID-19 and booster vaccination on symptoms, Health-Related Quality of Life (HRQoL), and Work Productivity Activity Impairment (WPAI). Methods: Outpatients with [≥]1 self-reported symptom and positive SARS-CoV-2 test at CVS Health United States test sites were recruited between 01/31-04/30/2022. Symptoms,EQ-5D and WPAI were collected via online surveys until 6 months following infection. Both observed and model-based estimates were analyzed. Effect sizes based on Cohen's d quantified the magnitude of outcome changes over time, within and between vaccination groups. Mixed models for repeated measures were conducted for multivariable analyses, adjusting for covariates. Logistic regression assessed odds ratio (OR) of long COVID between vaccination groups. Results: At long COVID start (Week 4), 328 participants included 87 (27%) Boosted with BNT162b2, 86 (26%) with a BNT162b2 primary series (Primed), and 155 (47%) Unvaccinated. Mean age was 42.0 years, 73.8% were female, 26.5% had [≥]1 comorbidity, 36.9% prior infection, and 39.6% reported [≥]3 symptoms (mean: 3.1 symptoms). At Month 6, among 260 participants, Boosted reported a mean of 1.1 symptoms versus 3.4 and 2.8 in Unvaccinated and Primed, respectively (p<0.001). Boosted had reduced risks of [≥]3 symptoms versus Unvaccinated (observed: OR 0.22, 95% CI, 0.10-0.47, p<0.001; model-based: OR: 0.36, 95% CI, 0.15-0.87, p=0.019) and Primed (observed: OR 0.29, 95% CI, 0.13-0.67, p=0.003; model-based: OR 0.59, 95% CI, 0.21-1.65, p=0.459). Results were consistent using [≥]2 symptoms. Regarding HRQoL, among those with long COVID, Boosted had higher EQ-5D Utility Index (UI) than Unvaccinated (observed: 0.922 versus 0.731, p=0.014; model-based: 0.910 versus 0.758, p-value=0.038) and Primed (0.922 versus 0.648, p=0.014; model-based: 0.910 versus 0.708, p-value=0.008). Observed and model-based estimates for EQ-VAS and UI among Boosted were comparable with pre-COVID since Month 3. Subjects vaccinated generally reported better WPAI scores Conclusions: Long COVID negatively impacted HRQoL and WPAI. The BNT162b2 booster could have a beneficial effect in reducing the risk and burden of long COVID. Boosted participants reported fewer and less durable symptoms, which contributed to improve HRQoL and maintain WPAI levels. Limitations included self-reported data and small sample size for WPAI.