Sequence Proven Reinfections with SARS-CoV-2 at a Large Academic Center (preprint)

Increased reinfection rates with SARS-CoV-2 have recently been reported, with some locations basing reinfection on a second positive PCR test at least 90 days after initial infection. We investigated sequencing and clinical data on the 750 patients (920 samples) we identified with these criteria. The median time between tests was 377 days, and 724 (79%) of the post 90-day positives were collected after the emergence of the Omicron variant in November 2021. Successful sequencing occurred in 127 of 231 attempted samples, spiked during the Omicron surge and showed higher median days from initial infection compared to failed sequences (median 398 days compared to 276 days, p<0.0005). A total of 122 (98%) patients showed evidence of reinfection, 45 of which had sequence proven reinfection and 77 had inferred reinfections (later sequence showed a clade that was not circulating when the patient was initially infected). Children accounted for only 4% of reinfections. 43 (96%) of 45 infections with sequence proven reinfection were caused by the Omicron variant, 41 (91%) were symptomatic, 32 (71%), were vaccinated prior to the second infection, and 6 (13%) were Immunosuppressed. Only 2 (4%) were hospitalized, and both had underlying conditions.

Infection with the SARS-CoV-2 Delta Variant is Associated with Higher Infectious Virus Loads Compared to the Alpha Variant in both Unvaccinated and Vaccinated Individuals (preprint)

BackgroundThe emerging SARS-CoV-2 variant of concern (VOC) B.1.6.17.2 (Delta) quickly displaced the B.1.1.7 (Alpha) and is associated with increases in COVID-19 cases nationally. The Delta variant has been associated with greater transmissibility and higher viral RNA loads in both unvaccinated and fully vaccinated individuals. Data is lacking regarding the infectious virus load in Delta infected individuals and how that compares to individuals infected with other SARS-CoV-2 lineages. MethodsWhole genome sequencing of 2,785 clinical isolates was used to characterize the prevalence of SARS-CoV-2 lineages circulating in the National Capital Region between January and July 2021. Clinical chart reviews were performed for the Delta, Alpha, and B.1.2 (a control predominant lineage prior to both VOCs) variants to evaluate disease severity and outcome and Cycle threshold values (Cts) were compared. The presence of infectious virus was determined using Vero-TMPRSS2 cells and anti-SARS-CoV-2 IgG levels were determined from upper respiratory specimen. An analysis of infection in unvaccinated and fully vaccinated populations was performed. ResultsThe Delta variant displaced the Alpha variant to constitute 88.2% of the circulating lineages in the National Capital Region by July, 2021. The Delta variant associated with increased breakthrough infections in fully vaccinated individuals that were mostly symptomatic when compared to the Alpha breakthrough infections, though it is important to note there was a significantly longer period of time between vaccination and infection with Delta infections. The recovery of infectious virus on cell culture was significantly higher with the Delta variant compared to Alpha in both vaccinated and unvaccinated groups. The impact of vaccination on reducing the recovery of infectious virus from clinical samples was only observed with Alpha variant infections but was strongly associated with low localized SARS-CoV-2 IgG for both variants. A comparison of Ct values showed a significant decrease in the Delta compared to Alpha with no significant differences between unvaccinated and vaccinated groups. ConclusionsOur data indicate that the Delta variant is associated with increased infectious virus loads when compared to the Alpha variant and decreased upper respiratory antiviral IgG levels. Measures to reduce transmission in addition to increasing vaccinations rates have to be implemented to reduce Delta variant spread. 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.

Sex and gender differences in COVID testing, hospital admission, presentation, and drivers of severe outcomes in the DC/Maryland region (preprint)

Background. Rates of severe illness and mortality from SARS-CoV-2 are greater for males, but the mechanisms for this difference are unclear. Understanding the differences in outcomes between males and females across the age spectrum will guide both public health and biomedical interventions. Methods. Retrospective cohort analysis of SARS-CoV-2 testing and admission data in a health system. Patient-level data were assessed with descriptive statistics and logistic regression modeling was used to identify features associated with increased male risk of severe outcomes. Results. In 213,175 SARS-CoV-2 tests, despite similar positivity rates (8.2%F vs 8.9%M), males were more frequently hospitalized (28%F vs 33%M). Of 2,626 hospitalized individuals, females had less severe presenting respiratory parameters and males had more fever. Comorbidity burden was similar, but with differences in specific conditions. Medications relevant for SARS-CoV-2 were used at similar frequency except tocilizumab (M>F). Males had higher inflammatory lab values. In a logistic regression model, male sex was associated with a higher risk of severe outcomes at 24 hours (odds ratio (OR) 3.01, 95%CI 1.75, 5.18) and at peak status (OR 2.58, 95%CI 1.78,3.74) among 18-49 year-olds. Block-wise addition of potential explanatory variables demonstrated that only the inflammatory labs substantially modified the OR associated with male sex across all ages. Conclusion. Higher levels of clinical inflammatory labs are the only features that are associated with the heightened risk of severe outcomes and death for males in COVID-19.

Explaining the Bomb-Like Dynamics of COVID-19 with Modeling and the Implications for Policy (preprint)

Using a Bayesian approach to epidemiological compartmental modeling, we demonstrate the bomb-like behavior of exponential growth in COVID-19 cases can be explained by transmission of asymptomatic and mild cases that are typically unreported at the beginning of pandemic events due to lower prevalence of testing. We studied the exponential phase of the pandemic in Italy, Spain, and South Korea, and found the R0 to be 2.56 (95% CrI, 2.41-2.71), 3.23 (95% CrI, 3.06-3.4), and 2.36 (95% CrI, 2.22-2.5) if we use Bayesian priors that assume a large portion of cases are not detected. Weaker priors regarding the detection rate resulted in R0 values of 9.22 (95% CrI, 9.01-9.43), 9.14 (95% CrI, 8.99-9.29), and 8.06 (95% CrI, 7.82-8.3) and assumes nearly 90% of infected patients are identified. Given the mounting evidence that potentially large fractions of the population are asymptomatic, the weaker priors that generate the high R0 values to fit the data required assumptions about the epidemiology of COVID-19 that do not fit with the biology, particularly regarding the timeframe that people remain infectious. Our results suggest that models of transmission assuming a relatively lower R0 value that do not consider a large number of asymptomatic cases can result in misunderstanding of the underlying dynamics, leading to poor policy decisions and outcomes.