Omicron Subvariants: Clinical, Laboratory, and Cell Culture Characterization

BackgroundThe variant of concern, Omicron, has become the sole circulating SARS-CoV-2 variant for the past several months. Omicron subvariants BA.1, BA.2, BA.3, BA.4, and BA.5 evolved over the time, with BA.1 causing the largest wave of infections globally in December 2021- January 2022. In this study, we compare the clinical outcomes in patients infected with different Omicron subvariants and compare the relative viral loads, and recovery of infectious virus from upper respiratory specimens. MethodsSARS-CoV-2 positive remnant clinical specimens, diagnosed at the Johns Hopkins Microbiology Laboratory between December 2021 and July 2022, were used for whole genome sequencing. The clinical outcomes of infections with Omicron subvariants were compared to infections with BA.1. Cycle threshold values (Ct) and the recovery of infectious virus on VeroTMPRSS2 cell line from clinical specimens were compared. ResultsThe BA.1 was associated with the largest increase in SARS-CoV-2 positivity rate and COVID-19 related hospitalizations at the Johns Hopkins system. After a peak in January cases fell in the spring, but the emergence of BA.2.12.1 followed by BA.5 in May 2022 led to an increase in case positivity and admissions. BA.1 infections had a lower mean Ct when compared to other Omicron subvariants. BA.5 samples had a greater likelihood of having infectious virus at Ct values less than 20. ConclusionsOmicron subvariants continue to associate with a relatively high positivity and admissions. The BA.5 infections are more while BA.2 infections are less likely to have infectious virus, suggesting potential differences in infectibility during the Omicron waves. FundingCenters for Disease Control and Prevention contract 75D30121C11061, NIH/NIAID Center of Excellence in Influenza Research and Surveillance contract HHS N2772201400007C, Johns Hopkins University, Maryland department of health, and The Modeling Infectious Diseases in Healthcare Network (MInD) under awards U01CK000589.

A Quick Displacement of the SARS-CoV-2 variant Delta with Omicron: Unprecedented Spike in COVID-19 Cases Associated with Fewer Admissions and Comparable Upper Respiratory Viral Loads

BackgroundThe increase in SARS-CoV-2 infections in December 2021 in the United States was driven primarily by the Omicron variant which largely displaced the Delta over a three week span. Outcomes from infection with the Omicron remain uncertain. We evaluate whether clinical outcomes and viral loads differ between Delta and Omicron infections during the period when both variants were co-circulating. MethodsRemnant clinical specimens from patients that tested positive for SARS-CoV-2 after standard of care testing between the last week of November and the end of December 2021were used for whole viral genome sequencing. Cycle threshold values (Ct) for viral RNA, the presence of infectious virus, and levels of respiratory IgG were measured, and clinical outcomes were obtained. Differences in each measure were compared between variants stratified by vaccination status. ResultsThe Omicron variant displaced the Delta during the study period and constituted 95% of the circulating lineages by the end of December 2021. Patients with Omicron infections (N= 1121) were more likely to be vaccinated compared to patients with Delta (N = 910), but were less likely to be admitted, require ICU level care, or succumb to infection regardless of vaccination status. There was no significant difference in Ct values based on the lineage regardless of the vaccination status. Recovery of infectious virus in cell culture was reduced in boosted patients compared to fully vaccinated without a booster and unvaccinated when infected with the Delta lineage. However, in patients with Omicron infections, recovery of infectious virus was not affected by vaccination. ConclusionsOmicron infections of vaccinated individuals are expected, yet admissions are less frequent. Admitted patients might develop severe disease comparable to Delta. Efforts for reducing the Omicron transmission are required as even though the admission risk is lower, the numbers of infections continue to be high. Research in context Evidence before this studyThe unprecedented increase in COVID-19 cases in the month of December 2021, associated with the displacement of the Delta variant with the Omicron, triggered a lot of concerns. An understanding of the disease severity associated with infections with Omicron is essential as well as the virological determinants that contributed to its widespread predominance. We searched PubMed for articles published up to January 23, 2022, using the search terms ("Omicron") AND ("Disease severity") as well as ("Omicron") AND ("Viral load") And/ or ("Cell culture"). Our search yielded 3 main studies that directly assessed the omicrons clinical severity in South Africa, its infectious viral load compared to Delta, and the dynamics of viral RNA shedding. In South Africa, compared to Delta, Omicron infected patients showed a significant reduction in severe disease. In this study, Omicron and non-Omicron variants were characterized based on S gene target failure using the TaqPath COVID-19 PCR (Thermo Fisher Scientific). In the study from Switzerland that assessed the infectious viral load in Omicron versus Delta, the authors analyzed only 18 Omicron samples that were all from vaccinated individuals to show that compared to Delta, Omicron had equivalent infectious viral titers. The third study that assessed the Omicron viral dynamics showed that the peak viral RNA in Omicron infections is lower than Delta. No published studies assessed the clinical discrepancies of Omicron and Delta infected patients from the US, nor comprehensively assessed, by viral load and cell culture studies, the characteristics of both variants stratified by vaccination status. Added value of this studyTo the best of our knowledge, this is the only study to date to compare the clinical characteristics and outcomes after infection with the Omicron variant compared to Delta in the US using variants characterized by whole genome sequencing and a selective time frame when both variant co-circulated. It is also the first study to stratify the analysis based on the vaccination status and to compare fully vaccinated patients who didnt receive a booster vaccination to patients who received a booster vaccination. In addition, we provide a unique viral RNA and infectious virus load analyses to compare Delta and Omicron samples from unvaccinated, fully vaccinated, and patients with booster vaccination. Implications of all the available evidenceOmicron associated with a significant increase in infections in fully and booster vaccinated individuals but with less admissions and ICU level care. Admitted patients showed similar requirements for supplemental oxygen and ICU level care when compared to Delta admitted patients. Viral loads were similar in samples from Omicron and Delta infected patients regardless of the vaccination status. The recovery of infectious virus on cell culture was reduced in samples from patients infected with Delta who received a booster dose, but this was not the case with Omicron. The recovery of infectious virus was equivalent in Omicron infected unvaccinated, fully vaccinated, and samples from patients who received booster vaccination. FundingNIH/NIAID Center of Excellence in Influenza Research and Surveillance contract HHS N2772201400007C, Johns Hopkins University, Maryland department of health, Centers for Disease Control and Prevention contract 75D30121C11061.

COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support

Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.

Investigating the effects of absolute humidity and human encounters on transmission of COVID-19 in the United States

BackgroundMounting evidence suggests that the primary mode of transmission of SARS-CoV-2 is aerosolized transmission from close contact with infected individuals. Even though transmission is a direct result of human encounters, environmental conditions, such as lower humidity, may enhance aerosolized transmission risks similar to other respiratory viruses such as influenza. MethodsWe utilized dynamic time warping to cluster all 3,137 counties in the United States based on temporal data on absolute humidity from March 10 to September 29, 2020. We then used a multivariate generalized additive model (GAM) combining data on human mobility derived from mobile phone data with humidity data to identify the potential effect of absolute humidity and mobility on new daily cases of COVID-19 while considering the temporal differences between seasons. ResultsThe clustering analysis found ten groups of counties with similar humidity levels. We found a significant negative effect between increasing humidity and new cases of COVID-19 in most regions, particularly in the period from March to July. The effect was greater in regions with generally lower humidity in the Western, Midwest, and Northeast regions of the US. In the two regions with the largest effect, a 1 g/m3 increase of absolute humidity resulted in a 0.21 and 0.15 decrease in cases. The effect of mobility on cases was positive and significant across all regions in the July-Sept time period, though the relationship in some regions was more mixed in the March to June period. ConclusionsWe found that increasing humidity played an important role in falling cases in the spring, while increasing mobility in the summer contributed more significantly to increases in the summer. Our findings suggest that, similar to other respiratory viruses, the decreasing humidity in the winter is likely to lead to an increase in COVID-19 cases. Furthermore, the fact that mobility data were positively correlated suggests that efforts to counteract the rise in cases due to falling humidity can be effective in limiting the burden of the pandemic.

Modeling COVID-19 Transmission in Africa: Country-wise Projections of Total and Severe Infections Under Different Lockdown Scenarios

ObjectivesAs of August 24th 2020, there have been 1,084,904 confirmed cases of SARS-CoV-2 and 24,683 deaths across the African continent. Despite relatively lower numbers of cases initially, many African countries are now experiencing an exponential increase in case numbers. Estimates of the progression of disease and potential impact of different interventions are needed to inform policy making decisions. Herein, we model the possible trajectory of SARS-CoV-2 in 52 African countries under different intervention scenarios. DesignWe developed a compartmental model of SARS-CoV-2 transmission to estimate the COVID-19 case burden for all African countries while considering four scenarios: no intervention, moderate lockdown, hard lockdown, and hard lockdown with continued restrictions once lockdown is lifted. We further analyzed the potential impact of COVID-19 on vulnerable populations affected by HIV/AIDS and TB. ResultsIn the absence of an intervention, the most populous countries had the highest peaks in active projected number of infections with Nigeria having an estimated 645,081 severe infections. The scenario with a hard lockdown and continued post-lockdown interventions to reduce transmission was the most efficacious strategy for delaying the time to the peak and reducing the number of cases. In South Africa projected peak severe infections increase from 162,977 to 203,261, when vulnerable populations with HIV/AIDS and TB are included in the analysis. ConclusionThe COVID-19 pandemic is rapidly spreading across the African continent. Estimates of the potential impact of interventions and burden of disease are essential for policy makers to make evidence-based decisions on the distribution of limited resources and to balance the economic costs of interventions with the potential for saving lives. ARTICLE SUMMARY Strengths and limitations of this studyO_LIThough the rapid spread of SARS-CoV-2 through China, Europe and the United States has been well-studied, leading to a detailed understanding of its biology and epidemiology, the population and resources for combatting the spread of the disease in Africa greatly differ to those areas and require models specific to this context. C_LIO_LIFew models that provide estimates for policymakers, donors, and aid organizations focused on Africa to plan an effective response to the pandemic threat that optimizes the use of limited resources. C_LIO_LIThis is a compartmental model and as such has inherent weaknesses; including the possible overestimation of the number of infections as it is assumed people are well mixed, despite many social, physical and geographical barriers to mixing within countries. C_LIO_LIPeaks in transmission are likely to occur at different times in different regions, with multiple epicenters. C_LIO_LIThis model is not stochastic and case data are modeled from the first twenty or more cases, each behaving as an average case; in reality, there are no average cases; some individuals are likely to have many contacts, causing multiple infections, and others to have very few. C_LI