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.

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.

Disproportionate impacts of COVID-19 in a large US city.

COVID-19 has disproportionately impacted individuals depending on where they live and work, and based on their race, ethnicity, and socioeconomic status. Studies have documented catastrophic disparities at critical points throughout the pandemic, but have not yet systematically tracked their severity through time. Using anonymized hospitalization data from March 11, 2020 to June 1, 2021 and fine-grain infection hospitalization rates, we estimate the time-varying burden of COVID-19 by age group and ZIP code in Austin, Texas. During this 15-month period, we estimate an overall 23.7% (95% CrI: 22.5-24.8%) infection rate and 29.4% (95% CrI: 28.0-31.0%) case reporting rate. Individuals over 65 were less likely to be infected than younger age groups (11.2% [95% CrI: 10.3-12.0%] vs 25.1% [95% CrI: 23.7-26.4%]), but more likely to be hospitalized (1,965 per 100,000 vs 376 per 100,000) and have their infections reported (53% [95% CrI: 49-57%] vs 28% [95% CrI: 27-30%]). We used a mixed effect poisson regression model to estimate disparities in infection and reporting rates as a function of social vulnerability. We compared ZIP codes ranking in the 75th percentile of vulnerability to those in the 25th percentile, and found that the more vulnerable communities had 2.5 (95% CrI: 2.0-3.0) times the infection rate and only 70% (95% CrI: 60%-82%) the reporting rate compared to the less vulnerable communities. Inequality persisted but declined significantly over the 15-month study period. Our results suggest that further public health efforts are needed to mitigate local COVID-19 disparities and that the CDC's social vulnerability index may serve as a reliable predictor of risk on a local scale when surveillance data are limited.

Real time monitoring of COVID-19 intervention effectiveness through contact tracing data.

Communities worldwide have used vaccines and facemasks to mitigate the COVID-19 pandemic. When an individual opts to vaccinate or wear a mask, they may lower their own risk of becoming infected as well as the risk that they pose to others while infected. The first benefit-reducing susceptibility-has been established across multiple studies, while the second-reducing infectivity-is less well understood. Using a new statistical method, we estimate the efficacy of vaccines and facemasks at reducing both types of risks from contact tracing data collected in an urban setting. We find that vaccination reduced the risk of onward transmission by 40.7% [95% CI 25.8-53.2%] during the Delta wave and 31.0% [95% CI 19.4-40.9%] during the Omicron wave and that mask wearing reduced the risk of infection by 64.2% [95% CI 5.8-77.3%] during the Omicron wave. By harnessing commonly-collected contact tracing data, the approach can broadly provide timely and actionable estimates of intervention efficacy against a rapidly evolving pathogen.

The Effect of Country Economic Institutions and Cultural Values on Government Policy and Societal Compliance in the Covid-19 Pandemic

Using data from 88 countries, we test hypotheses linking a country's economic freedom and cultural values with the propensity and timing of decisions to impose stringent policies to combat the spread of Covid-19, as well as society's compliance with those restrictive measures. Our analysis supports hypotheses that a country's economic freedom and cultural dimensions of individualism and masculinity predict early implementation of stringent policies. After accounting for endogeneity, we find that individualism also helps explain residents' compliance with stringent measures. These findings illustrate how institutions and cultural values influence government policies and societal compliance. © The Author(s) 2023.

Estimating the undetected emergence of COVID-19 in the US.

As SARS-CoV-2 emerged as a global threat in early 2020, China enacted rapid and strict lockdown orders to prevent introductions and suppress transmission. In contrast, the United States federal government did not enact national orders. State and local authorities were left to make rapid decisions based on limited case data and scientific information to protect their communities. To support local decision making in early 2020, we developed a model for estimating the probability of an undetected COVID-19 epidemic (epidemic risk) in each US county based on the epidemiological characteristics of the virus and the number of confirmed and suspected cases. As a retrospective analysis we included county-specific reproduction numbers and found that counties with only a single reported case by March 16, 2020 had a mean epidemic risk of 71% (95% CI: 52-83%), implying COVID-19 was already spreading widely by the first detected case. By that date, 15% of US counties covering 63% of the population had reported at least one case and had epidemic risk greater than 50%. We find that a 10% increase in model estimated epidemic risk for March 16 yields a 0.53 (95% CI: 0.49-0.58) increase in the log odds that the county reported at least two additional cases in the following week. The original epidemic risk estimates made on March 16, 2020 that assumed all counties had an effective reproduction number of 3.0 are highly correlated with our retrospective estimates (r = 0.99; p<0.001) but are less predictive of subsequent case increases (AIC difference of 93.3 and 100% weight in favor of the retrospective risk estimates). Given the low rates of testing and reporting early in the pandemic, taking action upon the detection of just one or a few cases may be prudent.

COVID-19 Test Allocation Strategy to Mitigate SARS-CoV-2 Infections across School Districts.

In response to COVID-19, schools across the United States closed in early 2020; many did not fully reopen until late 2021. Although regular testing of asymptomatic students, teachers, and staff can reduce transmission risks, few school systems consistently used proactive testing to safeguard return to classrooms. Socioeconomically diverse public school districts might vary testing levels across campuses to ensure fair, effective use of limited resources. We describe a test allocation approach to reduce overall infections and disparities across school districts. Using a model of SARS-CoV-2 transmission in schools fit to data from a large metropolitan school district in Texas, we reduced incidence between the highest and lowest risk schools from a 5.6-fold difference under proportional test allocation to 1.8-fold difference under our optimized test allocation. This approach provides a roadmap to help school districts deploy proactive testing and mitigate risks of future SARS-CoV-2 variants and other pathogen threats.

The risk of SARS-CoV-2 Omicron variant emergence in low and middle-income countries (LMICs).

We estimated the probability of undetected emergence of the SARS-CoV-2 Omicron variant in 25 low and middle-income countries (LMICs) prior to December 5, 2021. In nine countries, the risk exceeds 50 %; in Turkey, Pakistan and the Philippines, it exceeds 99 %. Risks are generally lower in the Americas than Europe or Asia.

Interpreting discordant SARS-CoV-2 diagnostic test results (preprint)

We introduce a model to interpret discordant SARS-CoV-2 test results and estimate that an individual receiving a positive rapid antigen test followed by a negative Nucleic Acid Amplification Test had only a 12-24% chance of being infected in the United States from March 2020 to May 2022.

Instruments Assessing Cognitive Impairment in Survivors of Critical Illness and Reporting of Race Norms: A Systematic Review.

To conduct a systematic review to summarize cognitive instruments being used in long-term outcome studies of survivors of adult critical illness, as well as evaluate whether these measures are reported as using patient demographic norms, specifically race norms. DATA SOURCES: A comprehensive search was conducted in PubMed (National Center for Biotechnology Information), Excerpta Medica dataBASE (Ovid), Psychological Information Database (ProQuest), and Web of Science (Clarivate) for English language studies published since 2002. STUDY SELECTION: Studies were eligible if the population included adult ICU survivors assessed for postdischarge cognitive outcomes. DATA EXTRACTION: Two independent reviewers screened abstracts, examined full text, and extracted data from all eligible articles. DATA SYNTHESIS: A total of 98 articles (55 unique cohorts: 22 general ICU, 14 Acute respiratory distress syndrome/Acute respiratory failure/Sepsis, 19 COVID-19 and other subpopulations) were eligible for data extraction and synthesis. Among general ICU survivors, the majority of studies (n = 15, 68%) assessed cognition using multiple instruments, of which the most common was the Mini-Mental State Examination. Only nine of the 22 studies (41%) explicitly reported using patient demographic norms for scoring neuropsychological cognitive tests. Of the nine, all reported using age as a norming characteristic, education was reported in eight (89%), sex/gender was reported in five (55%), and race/ethnicity was reported in three (33%). Among Acute respiratory distress syndrome/Acute respiratory failure/Sepsis survivors, norming characteristics were reported in only four (28%) of the 14 studies, of which all reported using age and none reported using race/ethnicity. CONCLUSIONS: Less than half of the studies measuring cognitive outcomes in ICU survivors reported the use of norming characteristics. There is substantial heterogeneity in how studies reported the use of cognitive instruments, and hence, the prevalence of the use of patient norms may be underestimated. These findings are important in the development of appropriate standards for use and reporting of neuropsychological tests among ICU survivors.

Disproportionate impacts of COVID-19 in a large US city (preprint)

COVID-19 has disproportionately impacted individuals depending on where they live and work, and based on their race, ethnicity, and socioeconomic status. Studies have documented catastrophic disparities at critical points throughout the pandemic, but have not yet systematically tracked their severity through time. Using anonymized hospitalization data from March 11, 2020 to June 1, 2021, we estimate the time-varying burden of COVID-19 by age group and ZIP code in Austin, Texas. During this 15-month period, we estimate an overall 16.9% (95% CrI: 16.1-17.8%) infection rate and 34.1% (95% CrI: 32.4-35.8%) case reporting rate. Individuals over 65 were less likely to be infected than younger age groups (8.0% [95% CrI: 7.5-8.6%] vs 18.1% [95% CrI: 17.2-19.2%]), but more likely to be hospitalized (1,381 per 100,000 vs 319 per 100,000) and have their infections reported (51% [95% CrI: 48-55%] vs 33% [95% CrI: 31-35%]). Children under 18, who make up 20.3% of the local population, accounted for only 5.5% (95% CrI: 3.8-7.7%) of all infections between March 1 and May 1, 2020 compared with 20.4% (95% CrI: 17.3-23.9%) between December 1, 2020 and February 1, 2021. We compared ZIP codes ranking in the 75th percentile of vulnerability to those in the 25th percentile, and found that the more vulnerable communities had 2.5 (95% CrI: 2.0-3.0) times the infection rate and only 70% (95% CrI: 61%-82%) the reporting rate compared to the less vulnerable communities. Inequality persisted but declined significantly over the 15-month study period. For example, the ratio in infection rates between the more and less vulnerable communities declined from 12.3 (95% CrI: 8.8-17.1) to 4.0 (95% CrI: 3.0-5.3) to 2.7 (95% CrI: 2.0-3.6), from April to August to December of 2020, respectively. Our results suggest that public health efforts to mitigate COVID-19 disparities were only partially effective and that the CDC's social vulnerability index may serve as a reliable predictor of risk on a local scale when surveillance data are limited.

The ongoing impact of the Covid-19 pandemic on endometriosis patients: A survey of 1,089 UK patients.

Background: The impact of Covid-19 on endometriosis patients is under-researched. Endometriosis has significant psychosocial effects on patients. Moreover, the mainstay of diagnosis and treatment of endometriosis is elective surgery, impacted as a result of healthcare strain. Objective: To better understand the effect of the Covid-19 pandemic on endometriosis patients. Materials and Methods: An online survey sent to adult UK endometriosis patients between 27th August and 15th September 2021. The study received HRA and HCRW research ethic committee approval. Main outcome measures: Effects of the Covid-19 pandemic on endometriosis symptoms and surgery. Results: We received 1,089 survey responses. Respondents had a median age of 34, and 82.0% of respondents were white British. 18.8% of respondents reported a previous positive Covid-19 PCR test. 84.6% of patients had been double vaccinated at time of response. 20 patients reported Covid-related hospital admission, with 1 requiring intubation. Large numbers of patients (31.4-55.2%) reported worsening of endometriosis symptoms during the pandemic. 69.2% of respondents reported worsening of associated mental health symptoms. Whilst 44% of respondents had elective endometriosis surgery planned, the majority of operations were disrupted, and 18.7% of total respondents did not have a new surgery date. Conclusions: More research and support are needed for endometriosis patients as they wait longer for surgery. A holistic approach, encompassing mental health needs, may be particularly beneficial for patients. What is new?: This is the first survey examining the effects of Covid-19 on endometriosis patients including data beyond January 2021.

A post-COVID strategy for event planners

The authors propose a strategy to help event planners pivot and adjust to the post-COVID world. This involves the use of social media and sales force automation (SFA). The authors explain how both of these can be accomplished in a low cost, easy to learn and use manner by adopting LinkedIn. The authors also present three tools that will help the event planner assess if they and their personnel are ready to make such a change. The authors conclude with a set of managerial imperatives that include not only how to be proactive and competitive but also the operational adjustments that will be necessary for the mode of operation, the reach of the planner, how online presence and content will drive awareness, the role and definition of personnel, how client relationships are conducted, and how the different facets of the event itself will change.

The effectiveness of COVID-19 testing and contact tracing in a US city.

Although testing, contact tracing, and case isolation programs can mitigate COVID-19 transmission and allow the relaxation of social distancing measures, few countries worldwide have succeeded in scaling such efforts to levels that suppress spread. The efficacy of test-trace-isolate likely depends on the speed and extent of follow-up and the prevalence of SARS-CoV-2 in the community. Here, we use a granular model of COVID-19 transmission to estimate the public health impacts of test-trace-isolate programs across a range of programmatic and epidemiological scenarios, based on testing and contact tracing data collected on a university campus and surrounding community in Austin, TX, between October 1, 2020, and January 1, 2021. The median time between specimen collection from a symptomatic case and quarantine of a traced contact was 2 days (interquartile range [IQR]: 2 to 3) on campus and 5 days (IQR: 3 to 8) in the community. Assuming a reproduction number of 1.2, we found that detection of 40% of all symptomatic cases followed by isolation is expected to avert 39% (IQR: 30% to 45%) of COVID-19 cases. Contact tracing is expected to increase the cases averted to 53% (IQR: 42% to 58%) or 40% (32% to 47%), assuming the 2- and 5-day delays estimated on campus and in the community, respectively. In a tracing-accelerated scenario, in which 75% of contacts are notified the day after specimen collection, cases averted increase to 68% (IQR: 55% to 72%). An accelerated contact tracing program leveraging rapid testing and electronic reporting of test results can significantly curtail local COVID-19 transmission.

Using SPI-Hub™ to Promote the Key Role of Prepublishing in Healthcare.

With the need to quickly advance knowledge dissemination in rapid-paced fields, and more recently in response to the urgency of the COVID-19 pandemic, prepublishing has been brought to the forefront. SPI-Hub™, a publicly available journal selection decision support tool, is being strategically enhanced to address prospective authors' critical needs in navigating and selecting the most appropriate preprint or traditional publication venue.

SARS-CoV-2 Brain Regional Detection, Histopathology, Gene Expression, and Immunomodulatory Changes in Decedents with COVID-19.

Brains of 42 COVID-19 decedents and 107 non-COVID-19 controls were studied. RT-PCR screening of 16 regions from 20 COVID-19 autopsies found SARS-CoV-2 E gene viral sequences in 7 regions (2.5% of 320 samples), concentrated in 4/20 subjects (20%). Additional screening of olfactory bulb (OB), amygdala (AMY) and entorhinal area for E, N1, N2, RNA-dependent RNA polymerase, and S gene sequences detected one or more of these in OB in 8/21 subjects (38%). It is uncertain whether these RNA sequences represent viable virus. Significant histopathology was limited to 2/42 cases (4.8%), one with a large acute cerebral infarct and one with hemorrhagic encephalitis. Case-control RNAseq in OB and AMY found more than 5000 and 700 differentially expressed genes, respectively, unrelated to RT-PCR results; these involved immune response, neuronal constituents, and olfactory/taste receptor genes. Olfactory marker protein-1 reduction indicated COVID-19-related loss of OB olfactory mucosa afferents. Iba-1-immunoreactive microglia had reduced area fractions in cerebellar cortex and AMY, and cytokine arrays showed generalized downregulation in AMY and upregulation in blood serum in COVID-19 cases. Although OB is a major brain portal for SARS-CoV-2, COVID-19 brain changes are more likely due to blood-borne immune mediators and trans-synaptic gene expression changes arising from OB deafferentation.

Projecting the Combined Health Care Burden of Seasonal Influenza and COVID-19 in the 2020-2021 Season.

Background. In mid-2020, there was significant concern that the overlapping 2020-2021 influenza season and COVID-19 pandemic would overwhelm already stressed health care systems in the Northern Hemisphere, particularly if influenza immunization rates were low. Methods. Using a mathematical susceptible-exposed-infected-recovered (SEIR) compartmental model incorporating the age-specific viral transmission rates and disease severity of Austin, Texas, a large metropolitan region, we projected the incidence and health care burden for both COVID-19 and influenza across observed levels of SARS-CoV-2 transmission and influenza immunization rates for the 2020-2021 season. We then retrospectively compared scenario projections made in August 2020 with observed trends through June 2021. Results. Across all scenarios, we projected that the COVID-19 burden would dwarf that of influenza. In all but our lowest transmission scenarios, intensive care units were overwhelmed by COVID-19 patients, with the levels of influenza immunization having little impact on health care capacity needs. Consistent with our projections, sustained nonpharmaceutical interventions (NPIs) in Austin prevented COVID-19 from overwhelming health care systems and almost completely suppressed influenza during the 2020-2021 respiratory virus season. Limitations. The model assumed no cross-immunity between SARS-CoV-2 and influenza, which might reduce the burden or slow the transmission of 1 or both viruses. Conclusion. Before the widespread rollout of the SARS-CoV-2 vaccine, COVID-19 was projected to cause an order of magnitude more hospitalizations than seasonal influenza because of its higher transmissibility and severity. Consistent with predictions assuming strong NPIs, COVID-19 strained but did not overwhelm local health care systems in Austin, while the influenza burden was negligible. Implications. Nonspecific NPI efforts can dramatically reduce seasonal influenza burden and preserve health care capacity during respiratory virus season. Highlights: As the COVID-19 pandemic threatened lives worldwide, the Northern Hemisphere braced for a potential "twindemic" of seasonal influenza and COVID-19.Using a validated mathematical model of influenza and SARS-CoV-2 co-circulation in a large US city, we projected the impact of COVID-19-driven nonpharmaceutical interventions combined with influenza vaccination on health care capacity during the 2020-2021 respiratory virus season.We describe analyses conducted during summer 2020 to help US cities prepare for the 2020-2021 influenza season and provide a retrospective evaluation of the initial projections.

Real-time pandemic surveillance using hospital admissions and mobility data.

Forecasting the burden of COVID-19 has been impeded by limitations in data, with case reporting biased by testing practices, death counts lagging far behind infections, and hospital census reflecting time-varying patient access, admission criteria, and demographics. Here, we show that hospital admissions coupled with mobility data can reliably predict severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission rates and healthcare demand. Using a forecasting model that has guided mitigation policies in Austin, TX, we estimate that the local reproduction number had an initial 7-d average of 5.8 (95% credible interval [CrI]: 3.6 to 7.9) and reached a low of 0.65 (95% CrI: 0.52 to 0.77) after the summer 2020 surge. Estimated case detection rates ranged from 17.2% (95% CrI: 11.8 to 22.1%) at the outset to a high of 70% (95% CrI: 64 to 80%) in January 2021, and infection prevalence remained above 0.1% between April 2020 and March 1, 2021, peaking at 0.8% (0.7-0.9%) in early January 2021. As precautionary behaviors increased safety in public spaces, the relationship between mobility and transmission weakened. We estimate that mobility-associated transmission was 62% (95% CrI: 52 to 68%) lower in February 2021 compared to March 2020. In a retrospective comparison, the 95% CrIs of our 1, 2, and 3 wk ahead forecasts contained 93.6%, 89.9%, and 87.7% of reported data, respectively. Developed by a task force including scientists, public health officials, policy makers, and hospital executives, this model can reliably project COVID-19 healthcare needs in US cities.

Deafferentation of Olfactory Bulb in Subjects Dying with COVID-19 (preprint)

There have been clinical descriptions of diverse neurological effects in COVID-19 disease, involving up to 36% of patients. It appears likely that most of these are not caused by viral brain invasion but by systemic accompaniments of critical illness such as coagulopathy, deleteriously upregulated immune response, autoimmune mechanisms, hypoxia or multiorgan failure. Anosmia or hyposmia is present in a majority of COVID-19 patients, and there is early and severe involvement of the nasopharyngeal mucosa and olfactory epithelium. Preliminary studies by our group have found massive gene expression changes in olfactory bulb, but the magnitude of these changes are not different between subjects with detectable versus non-detectable olfactory bulb SARS-CoV-2 RNA. As spontaneous discharge of olfactory epithelial afferents dictates intra-olfactory bulb neurophysiological activity and connectivity, we hypothesized that olfactory bulb deafferentation during COVID-19 is responsible for a large fraction of our observed olfactory bulb transcriptional changes. As the olfactory marker protein (OMP-1) is a specific marker of olfactory epithelial afferents to the olfactory bulb and is severely depleted in animal model lesions of olfactory epithelium, we quantified OMP-1-immunoreactivity in the olfactory bulb of subjects dying with or without COVID-19. Additionally, we quantified olfactory bulb tyrosine hydroxylase (TH), which is often also reduced after olfactory epithelium lesions, and SNAP-25, a pan-synaptic marker. COVID-19 cases (n = 18) were generally elderly and were not significantly different in age or gender distribution from the non-COVID-19 cases (n = 28). Both COVID-19 and non-COVID-19 cases had a wide range of neuropathological diagnoses. The area occupied by OMP-1 immunoreactivity in COVID-19 cases was significantly less, about 60% of that in control cases but amongst subjects with COVID-19, there was no significant difference between OBT-SARS-CoV-2-PCR-positive and negative cases. There were no significant group differences for TH or SNAP-25, supporting a selective effect for OMP-1. We suggest that olfactory dysfunction, and some of the COVID-19-associated transcriptional changes that we have reported for the olfactory bulb and amygdala, may be due to olfactory bulb deafferentation and subsequent transsynaptic effects. Additionally, animal models of olfactory bulb deafferentation or bulbectomy indicate a possibility for widespread changes in interconnected brain regions, providing a possible substrate for diverse post-acute COVID-19 neurological sequelae.

Real-Time Projections of SARS-CoV-2 B.1.1.7 Variant in a University Setting, Texas, USA.

We used the incidence of spike gene target failures identified during PCR testing to provide an early projection of the prevalence of severe acute respiratory syndrome coronavirus 2 variant B.1.1.7 in a university setting in Texas, USA, before sequencing results were available. Findings from a more recent evaluation validated those early projections.