Effectiveness of the 2023-2024 Omicron XBB.1.5-containing mRNA COVID-19 vaccine (mRNA-1273.815) in preventing COVID-19-related hospitalizations and medical encounters among adults in the United States: An interim analysis (preprint)

Background/ObjectivesCOVID-19 continues to pose a significant burden that impacts public health and the healthcare system as the SARS-CoV-2 virus continues to evolve. Regularly updated vaccines are anticipated to boost waning immunity and provide protection against circulating variants. This study evaluated vaccine effectiveness (VE) of mRNA-1273.815, a 2023-2024 Omicron XBB.1.5-containing mRNA COVID-19 vaccine, at preventing COVID-19-related hospitalizations and any medically attended COVID-19 in adults [≥]18 years, overall, and by age and underlying medical conditions. MethodsThis retrospective cohort study used the Veradigm Network EHR linked to claims data to identify US adults [≥]18 years of age who received the mRNA-1273.815 vaccine (exposed) matched 1:1 to individuals who did not receive a 2023-2024 updated COVID-19 vaccine (unexposed). Patients in the unexposed cohort were randomly matched to eligible mRNA-1273.815 recipients. Inverse probability of treatment weighting was used to adjust for differences between the two cohorts. The exposed cohort was vaccinated between September 12, 2023, and December 15, 2023, and individuals in both cohorts were followed up for COVID-19-related hospitalizations and medically attended COVID-19 until December 31, 2023. A Cox regression model was used to estimate the hazard ratio (HR). VE of the mRNA-1273.815 vaccine in preventing COVID-19-related hospitalizations and any medically attended COVID-19 was estimated as 100*(1-HR). Subgroup analyses were performed for adults [≥]50, adults [≥]65, and individuals with underlying medical conditions associated with severe COVID-19 outcomes. ResultsOverall, 859,335 matched pairs of mRNA-1273.815 recipients and unexposed adults were identified. The mean age was 63 years, and 80% of the study population was [≥]50 years old. 61.5% of the mRNA-1273.815 cohort and 66.4% of the unexposed cohort had an underlying medical condition. Among the overall adult population ([≥]18 years), VE was 60.2% (53.4-66.0%) against COVID-19-related hospitalization and 33.1% (30.2%-35.9%) against medically attended COVID-19 over a median follow-up of 63 (IQR: 44-78) days. VE estimates by age and underlying medical conditions were similar. ConclusionsThese results demonstrate the significant protection provided by mRNA-1273.815 against COVID-19-related hospitalizations and any medically attended COVID-19 in adults 18 years and older, regardless of their vaccination history, and support CDC recommendations for vaccination with the 2023-2024 Omicron XBB.1.5-containing COVID-19 vaccine to prevent COVID-19-related outcomes, including hospitalizations.

Ambiguity in the use of SIR models to fit epidemic incidence data (preprint)

When fitting a multi-parameter model to a data set, computer algorithms may suggest that a range of parameters provide equally reasonable fits, making the parameter estimation difficult. Here, we prove this fact for an SIR model. We say a set of parameter values is a good fit to outbreak data if the solution has the data's three most significant characteristics: the standard deviation, the mean time, and the total number of cases. In our model, in addition to the "basic reproduction number" $R_0$, three other parameters need to be estimated to fit a solution to outbreak data. We will show that those parameters can be chosen so that each gives a linear transformation of a solution's incidence data. As a result, we show that for every choice of $R_0>1$, there is a good fit for each outbreak. We also illustrate our results by providing the least square best fits of the New York City and London data sets of the Omicron variant of COVID-19. Furthermore, we show how versions of the SIR model with $N$ compartments have far more good fits- - indeed a high dimensional set of good fits -- for each target -- showing that more complicated models may have an even greater problem in overparametrizing outbreak characteristics.

A Comparative Experimental and Computational Study on the Nature of the Pangolin-CoV and COVID-19 Omicron (preprint)

The relationship between pangolin-CoV and SARS-CoV-2 has been a subject of debate. Further evidence of a special relationship between the two viruses can be found by the fact that all known COVID-19 viruses have abnormally hard outer shell (low M disorder; i.e., low content of intrinsically disordered residues in the membrane (M) protein) that so far was found in CoVs associated with burrowing animals, such as rabbits and pangolins, in which transmission involves virus remaining in buried feces for a long time. While a hard outer shell is necessary for viral survival, a harder inner shell could also help. For this reason, the N disorder range of pangolin-CoVs, not bat-CoVs, more closely matches that of SARS-CoV-2 especially when Omicron is included. The low N disorder (i.e., low content of intrinsically disordered residues in the nucleocapsid (N) protein), first observed in pangolin-CoV-2017 amd later in Omicron, is associated with attenuation according to the Shell-Disorder-Model. Our experimental study revealed that pangolin-CoV-2017 and SARS-CoV-2 Omicron (XBB.1.16 subvariant) show similar attenuations with respect to viral growth and plaque formation. Subtle differences have been observed that are consistent with disorder-centric computational analysis.

Prospective Clinical Surveillance for Severe Acute Respiratory Illness in Kenyan Hospitals during the COVID-19 pandemic (preprint)

There are limited data from sub-Saharan Africa describing the pattern of admissions to public hospitals with severe acute respiratory infections during the COVID-19 pandemic. We conducted a prospective longitudinal hospital-based sentinel surveillance between May 2020 and December 2022 at 16 public hospitals in Kenya. All patients aged above 18 years admitted to adult medical wards in the participating hospitals were included. Demographic and clinical characteristics, COVID-19 infection and vaccination status and outcome data were collected. Of the 52,714 patients included in the study, 18,001 (35%) were admitted with severe acute respiratory illness (SARI). The mean age was 51 years. Patients were equally distributed across sexes. Pneumonia was the most common diagnosis at discharge. Hypertension, HIV and diabetes mellitus were the most common comorbidities. COVID-19 test results were positive in 2,370 (28%) of the 8,517 (47%) patients that underwent testing. Overall inpatient case fatality for SARI was 21% (n=3,828). After adjusting for age, sex and presence of a comorbidity, SARI patients had higher inpatient mortality compared to non-SARI patients regardless of their COVID-19 status (aHR 1.31, 95% CI 1.19 - 1.46). COVID-19 positive SARI patients had a higher inpatient mortality rate compared to their negative counterparts (aHR 1.31, 95% CI 1.12 - 1.54, p value < 0.0001). COVID-19 vaccine effectiveness against mortality due to SARI after adjusting for age, sex and presence of a comorbidity was 34% (95% CI 11% - 51%). We have provided a comprehensive description of the pattern of admissions with respiratory illnesses in Kenyan hospitals during the COVID-19 pandemic period. We have demonstrated the utility of routine surveillance activities within public hospitals in low-income settings which if strengthened can enhance the response to emerging health threats.

Infectious disease surveillance needs for the United States: lessons from COVID-19 (preprint)

The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S., while looking to jurisdictions in the U.S. and beyond to learn lessons about the value of specific data types. In this report, we define the range of decisions for which surveillance data are required, the data elements needed to inform these decisions and to calibrate inputs and outputs of transmission-dynamic models, and the types of data needed to inform decisions by state, territorial, local, and tribal health authorities. We define actions needed to ensure that such data will be available and consider the contribution of such efforts to improving health equity.

The Impact of SIV-Induced Immunodeficiency on Clinical Manifestation, Immune Response, and Viral Dynamics in SARS-CoV-2 Coinfection (preprint)

Persistent and uncontrolled SARS-CoV-2 replication in immunocompromised individuals has been observed and may be a contributing source of novel viral variants that continue to drive the pandemic. Importantly, the effects of immunodeficiency associated with chronic HIV infection on COVID-19 disease and viral persistence have not been directly addressed in a controlled setting. Here we conducted a pilot study wherein two pigtail macaques (PTM) chronically infected with SIVmac239 were exposed to SARS-CoV-2 and monitored for six weeks for clinical disease, viral replication, and viral evolution, and compared to our previously published cohort of SIV-naive PTM infected with SARS-CoV-2. At the time of SARS-CoV-2 infection, one PTM had minimal to no detectable CD4+ T cells in gut, blood, or bronchoalveolar lavage (BAL), while the other PTM harbored a small population of CD4+ T cells in all compartments. Clinical signs were not observed in either PTM; however, the more immunocompromised PTM exhibited a progressive increase in pulmonary infiltrating monocytes throughout SARS-CoV-2 infection. Single-cell RNA sequencing (scRNAseq) of the infiltrating monocytes revealed a less activated/inert phenotype. Neither SIV-infected PTM mounted detectable anti-SARS-CoV-2 T cell responses in blood or BAL, nor anti-SARS-CoV-2 neutralizing antibodies. Interestingly, despite the diminished cellular and humoral immune responses, SARS-CoV-2 viral kinetics and evolution were indistinguishable from SIV-naive PTM in all sampled mucosal sites (nasal, oral, and rectal), with clearance of virus by 3-4 weeks post infection. SIV-induced immunodeficiency significantly impacted immune responses to SARS-CoV-2 but did not alter disease progression, viral kinetics or evolution in the PTM model. SIV-induced immunodeficiency alone may not be sufficient to drive the emergence of novel viral variants.

Understanding COVID-19 testing behaviour in England through a sociodemographic lens (preprint)

BackgroundUnderstanding underlying mechanisms of heterogeneity in test-seeking and reporting behaviour can help to protect the vulnerable and guide equity-driven interventions. Using COVID-19 testing data for England and data from community prevalence surveillance surveys (REACT-1 and ONS-CIS) from October 2020 to March 2022, we investigated the relationship between sociodemographic factors and testing behaviours in England. MethodsWe used mass testing data for lateral flow device (LFD; data for 290 million tests performed and reported) and polymerase chain reaction (PCR) (data for 107 million tests performed and returned from the laboratory) tests made available for the general public, provided by date, self-reported age and ethnicity at lower tier local authority (LTLA) level. Using a mechanistic causal model to debias the PCR testing data, we obtained estimates of weekly SARS-CoV-2 prevalence by self-reported ethnic groups and age groups for LTLAs in England. This approach to debiasing the PCR (or LFD) testing data also estimated a testing bias parameter defined as the odds of testing in infected versus not infected individuals, which would be close to zero if the likelihood of test seeking (or seeking and reporting) was the same regardless of infection status. Using confirmatory PCR data, we estimated false positivity rates, sensitivity, specificity, and the rate of decline in detection probability by PCR by sociodemographic groups. We also estimated the daily incidence allowing us to determine the fraction of cases captured by the testing programme. FindingsFrom March 2021 onwards, individuals in the most deprived regions reported approximately half as many LFD tests per-capita than those in the least deprived areas (Median ratio [Inter quartile range, IQR]: 0{middle dot}50 [0{middle dot}44, 0{middle dot}54]). During October 2020 - June 2021, PCR testing patterns were in the opposite direction (Median ratio [IQR]: 1{middle dot}8 [1{middle dot}7, 1{middle dot}9]). Infection prevalences in Asian or Asian British communities were considerably higher than those of other ethnic groups during the Alpha and Omicron BA.1 waves. Our estimates indicate that the England COVID-19 testing program detected 26% - 40% of all cases (including asymptomatic cases) over the study period with no consistent differences by deprivation levels or ethnic groups. PCR testing biases were generally higher than for LFDs, which was in line with the general policy of symptomatic and asymptomatic use of these tests. During the invasion phases of the Delta and Omicron variants of concern, the PCR testing bias in the most deprived populations was roughly double (ratio: 2{middle dot}2 and 2{middle dot}7 respectively) that in the least. We also determined that ethnic minorities and older individuals were less likely to use confirmatory PCR tests through most of the pandemic and that there was possibly a longer delay in reporting a positive LFD test in the Black populations. InterpretationDifferences in testing behaviours across sociodemographic groups may be reflective of the relatively higher costs of self-isolation to vulnerable populations, differences in test accessibility, digital literacy, and differing perception about the utility of tests and risks posed by infection. Our work shows how mass testing data can be used in conjunction with surveillance surveys to identify gaps in the uptake of public health interventions at fine scale levels and by sociodemographic groups. It provides a framework for monitoring local interventions and yields valuable lessons for policy makers in ensuring an equitable response to future pandemics. FundingUK Health Security Agency.

Comparison of COVID-19 and Influenza-Related Outcomes in the United States during Fall-Winter 2022-2023 (preprint)

Background: Three years into the pandemic, SARS-COV-2 remains a significant burden in comparison to other respiratory illnesses; however, many of the monitoring tools available during the early phase of the COVID-19 pandemic have been phased out, making it more difficult to track the current burden of outpatient medical encounters and hospitalizations, especially for at-risk groups. The objective of this analysis was to characterize the frequency and severity of medically-attended COVID-19 and influenza during peak influenza activity in the pediatric (0-17), adult (18-64), and older adult (65+) populations and characterize the prevalence of underlying medical conditions among patients hospitalized with COVID-19. Methods: This was a cross-sectional analysis of individuals in the Veradigm Health Insights EHR Database linked to Komodo claims data with a medical encounter of claim between October 1, 2022, and March 31, 2023. We captured age, sex, and underlying medical conditions associated with higher risk for severe COVID-19 during a 12-month baseline period. We identified patients with medical encounters with a diagnosis of COVID-19 or influenza between October 1, 2022, and March 31, 2023, and stratified them into 5 mutually exclusive categories based on the highest level of care received with that diagnosis during the season (intensive care unit [ICU] > hospitalization without ICU > emergency department > urgent care > other outpatient). Results: Among the 23,526,196 individuals in the dataset, 5.0% had a COVID-19-related medical encounter, and 3.0% had an influenza-related medical encounter during the 6 month observation period. The incidence of hospitalizations with a COVID-19 diagnosis was 4.6 times higher than the incidence of hospitalizations with an influenza diagnosis. Hospitalizations with COVID-19 were higher in all age groups. Nearly all adults hospitalized with COVID-19 had at least one underlying medical condition, but 25.8% of 0-5-year-olds and 18.3% of 6-17-year-olds had no underlying medical conditions. Conclusions: COVID-19 continues to place a heavy burden on the United States healthcare system and was associated with more medical encounters in all age groups, including hospitalizations, than influenza during a 6-month period that included the 2022-2023 peak influenza activity.

Comparative Effectiveness of the Bivalent (Original/Omicron BA.4/BA.5) mRNA COVID-19 Vaccines mRNA-1273.222 and BNT162b2 Bivalent in Adults in the United States (preprint)

Background: The emergence of Omicron variants coincided with declining vaccine-induced protection against SARS-CoV-2 infection and other COVID-19-related outcomes. Two bivalent mRNA vaccines, mRNA-1273.222 (Moderna) and BNT162b2 Bivalent (Pfizer-BioNTech) were developed to provide greater protection against the predominate circulating variants by including the mRNA that encodes both the ancestral (original) strain and BA.4/BA.5. We estimated their relative vaccine effectiveness (rVE) in preventing COVID-19-related outcomes in the US. Methods: We conducted a retrospective cohort study using a US nationwide dataset linking primary care electronic health records (EHR) and pharmacy/medical claims data. The adult study population (aged >18 years) received either mRNA-1273.222 or BNT162b2 Bivalent vaccination between August 31, 2022, and February 28, 2023. We used a propensity score weighting based on the inverse probability of treatment to adjust for the baseline differences in age, sex, race, ethnicity, geographic region, vaccination week, and health status between groups. Outcomes evaluated were rVE of the two bivalent mRNA vaccines against COVID-19-related hospitalizations (primary outcome) and outpatient visits (secondary). We weighted the vaccine groups prior to analysis and estimated adjusted hazard ratios (HR) using multivariable Cox regression models. We calculated rVE as (1-HR) X 100. Results: We evaluated outcomes for 1,034,538 mRNA-1273.222 and 1,670,666 BNT162b2 Bivalent vaccine recipients. The adjusted rVE of mRNA-1273.222 versus BNT162b2 Bivalent vaccines against COVID-19-related hospitalization was 9.8% (95% confidence interval: 2.6% --16.4%). The adjusted rVE against COVID-19-related outpatient visits was 5.1% (95% CI: 3.2% --6.9%). When evaluated by age group, the incremental relative effectiveness was greater. Among adults [≥]65, rVE against COVID-19-related hospitalizations and outpatient visits was 13.5% (95% CI: 5.5% -- 20.8%) and 10.7% (8.2% -- 13.1%), respectively. Conclusion: We found greater effectiveness of mRNA-1273.222 compared with the BNT162b2 Bivalent vaccine in preventing COVID-19-related hospitalizations and outpatient visits, with increased benefits in older adults

Longitudinal study of perceived gendered differences of entrepreneurial program participants

Entrepreneurial pursuits have historically encountered gender bias in many forms. The stereotypes associated with successful entrepreneurs combined with the upsurge in participation by women in entrepreneurship over recent years have sparked greater interest and research into its gendered differences. Using surveys to gauge the perception of knowledge and experience in entrepreneurship, we assess longitudinally over the last 5 years, differences in responses from men and women in an accelerator program at New York University, dubbed the ‘Startup Sprint' program. Significant trends in confidence relating to STEM entrepreneurship knowledge and experience are tracked with notably lower average ratings for women. Halfway through the study, the COVID-19 pandemic occurred bringing with it external stressors and a transformation of learning and working environments. Considering the stressors of the COVID-19 pandemic and the transition to a remote educational environment, we analyze our survey results to better understand the impact of these changes on the gendered perceptions of entrepreneurship. Supplementary Information The online version contains supplementary material available at 10.1007/s41959-023-00095-1.

Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study.

OBJECTIVES: We sought to 1) identify long COVID phenotypes based on patient reported outcome measures (PROMs) and 2) determine whether the phenotypes were associated with quality of life (QoL) and/or lung function. METHODS: This was a longitudinal cohort study of hospitalized and non-hospitalized patients from March 2020 to January 2022 that was conducted across 4 Post-COVID Recovery Clinics in British Columbia, Canada. Latent class analysis was used to identify long COVID phenotypes using baseline PROMs (fatigue, dyspnea, cough, anxiety, depression, and post-traumatic stress disorder). We then explored the association between the phenotypes and QoL (using the EuroQoL 5 dimensions visual analogue scale [EQ5D VAS]) and lung function (using the diffusing capacity of the lung for carbon monoxide [DLCO]). RESULTS: There were 1,344 patients enrolled in the study (mean age 51 ±15 years; 780 [58%] were females; 769 (57%) were of a non-White race). Three distinct long COVID phenotypes were identified: Class 1) fatigue and dyspnea, Class 2) anxiety and depression, and Class 3) fatigue, dyspnea, anxiety, and depression. Class 3 had a significantly lower EQ5D VAS at 3 (50±19) and 6 months (54 ± 22) compared to Classes 1 and 2 (p<0.001). The EQ5D VAS significantly improved between 3 and 6 months for Class 1 (median difference of 6.0 [95% CI, 4.0 to 8.0]) and Class 3 (median difference of 5.0 [95% CI, 0 to 8.5]). There were no differences in DLCO between the classes. CONCLUSIONS: There were 3 distinct long COVID phenotypes with different outcomes in QoL between 3 and 6 months after symptom onset. These phenotypes suggest that long COVID is a heterogeneous condition with distinct subpopulations who may have different outcomes and warrant tailored therapeutic approaches.

Structural and computational design of a SARS-CoV-2 spike antigen with improved expression and immunogenicity.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern challenge the efficacy of approved vaccines, emphasizing the need for updated spike antigens. Here, we use an evolutionary-based design aimed at boosting protein expression levels of S-2P and improving immunogenic outcomes in mice. Thirty-six prototype antigens were generated in silico and 15 were produced for biochemical analysis. S2D14, which contains 20 computationally designed mutations within the S2 domain and a rationally engineered D614G mutation in the SD2 domain, has an ~11-fold increase in protein yield and retains RBD antigenicity. Cryo-electron microscopy structures reveal a mixture of populations in various RBD conformational states. Vaccination of mice with adjuvanted S2D14 elicited higher cross-neutralizing antibody titers than adjuvanted S-2P against the SARS-CoV-2 Wuhan strain and four variants of concern. S2D14 may be a useful scaffold or tool for the design of future coronavirus vaccines, and the approaches used for the design of S2D14 may be broadly applicable to streamline vaccine discovery.

Improved clinical outcomes in response to a 12-week blended digital and community-based long-COVID-19 rehabilitation programme.

Introduction: Two million people in the UK are experiencing long COVID (LC), which necessitates effective and scalable interventions to manage this condition. This study provides the first results from a scalable rehabilitation programme for participants presenting with LC. Methods: 601 adult participants with symptoms of LC completed the Nuffield Health COVID-19 Rehabilitation Programme between February 2021 and March 2022 and provided written informed consent for the inclusion of outcomes data in external publications. The 12-week programme included three exercise sessions per week consisting of aerobic and strength-based exercises, and stability and mobility activities. The first 6 weeks of the programme were conducted remotely, whereas the second 6 weeks incorporated face-to-face rehabilitation sessions in a community setting. A weekly telephone call with a rehabilitation specialist was also provided to support queries and advise on exercise selection, symptom management and emotional wellbeing. Results: The 12-week rehabilitation programme significantly improved Dyspnea-12 (D-12), Duke Activity Status Index (DASI), World Health Orginaisation-5 (WHO-5) and EQ-5D-5L utility scores (all p < 0.001), with the 95% confidence intervals (CI) for the improvement in each of these outcomes exceeding the minimum clinically important difference (MCID) for each measure (mean change [CI]: D-12: -3.4 [-3.9, -2.9]; DASI: 9.2 [8.2, 10.1]; WHO-5: 20.3 [18.6, 22.0]; EQ-5D-5L utility: 0.11 [0.10, 0.13]). Significant improvements exceeding the MCID were also observed for sit-to-stand test results (4.1 [3.5, 4.6]). On completion of the rehabilitation programme, participants also reported significantly fewer GP consultations (p < 0.001), sick days (p = 0.003) and outpatient visits (p = 0.007) during the previous 3 months compared with baseline. Discussion: The blended and community design of this rehabilitation model makes it scalable and meets the urgent need for an effective intervention to support patients experiencing LC. This rehabilitation model is well placed to support the NHS (and other healthcare systems worldwide) in its aim of controlling the impacts of COVID-19 and delivering on its long-term plan. Clinical trial registration: https://www.isrctn.com/ISRCTN14707226, identifier 14707226.

Alternative epidemic indicators for COVID-19 in three settings with incomplete death registration systems.

Not all COVID-19 deaths are officially reported, and particularly in low-income and humanitarian settings, the magnitude of reporting gaps remains sparsely characterized. Alternative data sources, including burial site worker reports, satellite imagery of cemeteries, and social media-conducted surveys of infection may offer solutions. By merging these data with independently conducted, representative serological studies within a mathematical modeling framework, we aim to better understand the range of underreporting using examples from three major cities: Addis Ababa (Ethiopia), Aden (Yemen), and Khartoum (Sudan) during 2020. We estimate that 69 to 100%, 0.8 to 8.0%, and 3.0 to 6.0% of COVID-19 deaths were reported in each setting, respectively. In future epidemics, and in settings where vital registration systems are limited, using multiple alternative data sources could provide critically needed, improved estimates of epidemic impact. However, ultimately, these systems are needed to ensure that, in contrast to COVID-19, the impact of future pandemics or other drivers of mortality is reported and understood worldwide.

COVID-19 Bivalent Booster Vaccination Coverage and Intent to Receive Booster Vaccination Among Adolescents and Adults - United States, November-December 2022.

COVID-19 vaccine booster doses are safe and maintain protection after receipt of a primary vaccination series and reduce the risk for serious COVID-19-related outcomes, including emergency department visits, hospitalization, and death (1,2). CDC recommended an updated (bivalent) booster for adolescents aged 12-17 years and adults aged ≥18 years on September 1, 2022 (3). The bivalent booster is formulated to protect against the Omicron BA.4 and BA.5 subvariants of SARS-CoV-2 as well as the original (ancestral) strain (3). Based on data collected during October 30-December 31, 2022, from the National Immunization Survey-Child COVID Module (NIS-CCM) (4), among all adolescents aged 12-17 years who completed a primary series, 18.5% had received a bivalent booster dose, 52.0% had not yet received a bivalent booster but had parents open to booster vaccination for their child, 15.1% had not received a bivalent booster and had parents who were unsure about getting a booster vaccination for their child, and 14.4% had parents who were reluctant to seek booster vaccination for their child. Based on data collected during October 30-December 31, 2022, from the National Immunization Survey-Adult COVID Module (NIS-ACM) (4), 27.1% of adults who had completed a COVID-19 primary series had received a bivalent booster, 39.4% had not yet received a bivalent booster but were open to receiving booster vaccination, 12.4% had not yet received a bivalent booster and were unsure about getting a booster vaccination, and 21.1% were reluctant to receive a booster. Adolescents and adults in rural areas had a much lower primary series completion rate and up-to-date vaccination coverage. Bivalent booster coverage was lower among non-Hispanic Black or African American (Black) and Hispanic or Latino (Hispanic) adolescents and adults compared with non-Hispanic White (White) adolescents and adults. Among adults who were open to receiving booster vaccination, 58.9% reported not having received a provider recommendation for booster vaccination, 16.9% had safety concerns, and 4.4% reported difficulty getting a booster vaccine. Among adolescents with parents who were open to getting a booster vaccination for their child, 32.4% had not received a provider recommendation for any COVID-19 vaccination, and 11.8% had parents who reported safety concerns. Although bivalent booster vaccination coverage among adults differed by factors such as income, health insurance status, and social vulnerability index (SVI), these factors were not associated with differences in reluctance to seek booster vaccination. Health care provider recommendations for COVID-19 vaccination; dissemination of information by trusted messengers about the continued risk for COVID-19-related illness and the benefits and safety of bivalent booster vaccination; and reducing barriers to vaccination could improve COVID-19 bivalent booster coverage among adolescents and adults.

Points of entry dynamics: understanding the cross-border threats for Ebola virus disease and COVID-19 in Ghana using a logic model approach.

Background: The influx of people across the national borders of Ghana has been of interest and concern in the public health and national security community in recent times due to the low capacity for the prevention and management of epidemics and other public health risks. Although the international health regulations (IHR) stipulate core public health capacities for designated border facilities such as international airports, seaports, and ground crossings, contextual factors that influence the attainment of effective public health measures and response capabilities remain understudied. Objective: This study aims to assess the relationship between contextual factors and COVID-19 procurement to help strengthen infrastructure resources for points of entry (PoE) public health surveillance functions, thereby eliminating gaps in the design, implementation, monitoring, and evaluation of pandemic-related interventions in Ghana. Methods: This study employed a mixed-methods design, where quantitative variables were examined for relationships and effect size interactions using multiple linear regression techniques and the wild bootstrap technique. Country-level data was sourced from multiple publicly available sources using the social-ecological framework, logic model, and IHR capacity monitoring framework. The qualitative portion included triangulation with an expert panel to determine areas of convergence and divergence. Results: The most general findings were that laboratory capacity and Kotoka International Airport testing center positively predicted COVID-19 procurement, and public health response and airline boarding rule negatively predicted COVID-19 procurement. Conclusion: Contextual understanding of the COVID-19 pandemic and Ebola epidemic is vital for strengthening PoE mitigation measures and preventing disease importation.

The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data (preprint)

Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Public access to the training methodology for these solutions remains absent. This study implements the Type Three (T3) challenge format, which allows for training solutions on private data and guarantees reusable training methodologies. With T3, challenge organizers train a codebase provided by the participants on sequestered training data. T3 was implemented in the STOIC2021 challenge, with the goal of predicting from a computed tomography (CT) scan whether subjects had a severe COVID-19 infection, defined as intubation or death within one month. STOIC2021 consisted of a Qualification phase, where participants developed challenge solutions using 2000 publicly available CT scans, and a Final phase, where participants submitted their training methodologies with which solutions were trained on CT scans of 9724 subjects. The organizers successfully trained six of the eight Final phase submissions. The submitted codebases for training and running inference were released publicly. The winning solution obtained an area under the receiver operating characteristic curve for discerning between severe and non-severe COVID-19 of 0.815. The Final phase solutions of all finalists improved upon their Qualification phase solutions.HSUXJM-TNZF9CHSUXJM-TNZF9C

Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients.

The IMPACC cohort, composed of >1,000 hospitalized COVID-19 participants, contains five illness trajectory groups (TGs) during acute infection (first 28 days), ranging from milder (TG1-3) to more severe disease course (TG4) and death (TG5). Here, we report deep immunophenotyping, profiling of >15,000 longitudinal blood and nasal samples from 540 participants of the IMPACC cohort, using 14 distinct assays. These unbiased analyses identify cellular and molecular signatures present within 72 h of hospital admission that distinguish moderate from severe and fatal COVID-19 disease. Importantly, cellular and molecular states also distinguish participants with more severe disease that recover or stabilize within 28 days from those that progress to fatal outcomes (TG4 vs. TG5). Furthermore, our longitudinal design reveals that these biologic states display distinct temporal patterns associated with clinical outcomes. Characterizing host immune responses in relation to heterogeneity in disease course may inform clinical prognosis and opportunities for intervention.

Disproportionality analysis of adverse neurological and psychiatric reactions with the ChAdOx1 (Oxford-AstraZeneca) and BNT162b2 (Pfizer-BioNTech) COVID-19 vaccines in the United Kingdom.

BACKGROUND: Information on neurological and psychiatric adverse events following immunization (AEFIs) with COVID-19 vaccines is limited. RESEARCH DESIGN & METHODS: We examined and compared neurological and psychiatric AEFIS reports related to BNT162b2 (Pfizer-BioNTech) and ChAdOx1 (Oxford-AstraZeneca) COVID-19 vaccines and recorded in the United Kingdom Medicines and Healthcare products Regulatory Agency between 9 December 2020 and 30 June 2021. RESULTS: As of 30 June 2021, 46.1 million doses of ChAdOx1 and 30.3 million doses of BNT162b2 had been administered. The most frequently reported AEFI was headache with 1,686 and 575 cases per million doses of ChAdOx1 and BNT162b2, respectively. AEFIs more frequently reported after CHAdOx1 compared with BNT162b2 vaccination were Guillain-Barré syndrome (OR, 95% CI = 2.53, 1.82-3.51), freezing (6.66, 3.12-14.22), cluster headache (1.53, 1.28-1.84), migraine (1.23,1.17-1.30), postural dizziness (1.24,1.13-1.37), tremor (2.86, 2.68-3.05), headache (1.40, 1.38-1.43), paresthesia (1.11, 1.06-1.16), delirium (1.85, 1.45-2.36), hallucination (2.20, 1.82-2.66), poor quality sleep (1.53, 1.26-1.85), and nervousness (1.54, 1.26-1.89) Reactions less frequently reported with ChAdOx1 than with BNT162b2 were Bell's palsy (0.47, 0.41-0.55), anosmia (0.58, 0.47-0.71), facial paralysis (0.35, 0.29-0.41), dysgeusia (0.68, 0.62-0.73), presyncope (0.48, 0.42-0.55), syncope (0.63, 0.58-0.67), and anxiety (0.75 (0.67-0.85). CONCLUSION: Neurological and psychiatric AEFIs were relatively infrequent, but each vaccine was associated with a distinctive toxic profile.

We examined reports on adverse neurological and psychiatric effects following immunization with BNT162b2 (Pfizer-BioNTech) and ChAdOx1 (Oxford-AstraZeneca) for COVID-19 to the United Kingdom Medicines and Healthcare products Regulatory Agency between 9 December 2020 and 30 June 2021. Adverse effects following immunization (AEFIs) were relatively infrequent. Compared to BNT162b2, Guillain-Barré syndrome, freezing phenomenon, cluster headache, migraine, postural dizziness, tremor, headache, paresthesia, delirium, hallucination, poor quality sleep, and nervousness were more frequently reported for ChAdOx1. Reactions less frequently reported for ChAdOx1 than for BNT162b2 were Bell's palsy, anosmia, facial paralysis, dysgeusia, presyncope, syncope, and anxiety.