Exploring a COVID-19 Endemic Scenario: High-Resolution Agent-Based Modeling of Multiple Variants

Prospective and Longitudinal Analysis of Lymphocyte Subpopulations in SARS-CoV-2 Positive and Negative Pneumonia: Potential Role of Decreased Naïve CD8+ in COVID-19 Patients

Background: During the acute phase of COVID-19, a number of immunological abnormalities have been reported, but few studies longitudinally analyzed the specific subsets of peripheral blood lymphocytes. Methods: In this observational, prospective, and longitudinal study, adult patients developing acute pneumonia during the COVID-19 pandemic have been followed up for 12 months. Peripheral blood lymphocyte subsets were assessed (with a specific focus on the memory markers) at 6 time points after the disease onset until 12 months. Results: A total of 76 patients with acute pneumonia (characterized by a prevalently interstitial pattern of lung inflammation) at the hospital admission (who completed the 12-month follow-up period) were recruited in this study. They were divided into two groups, namely positive (n = 31) and negative (n = 45) patients for the SARS-CoV-2 PCR test. In the acute phase, the general lymphocyte immunophenotyping profile was comparable for most parameters between these groups, except for B cells. When B and T cells were analyzed according to the expression of memory markers, a significant decrease in naïve CD8+ T cells was observed in the SARS-CoV-2-positive pneumonia group during the acute phase. Notably, this aspect was maintained during the follow-up period for at least 9 months. Conclusions: COVID-19 pneumonia seems to be associated with a lower number of naïve CD8+ T cells compared to pneumonia patients negative for this virus. This alteration can persist in the convalescent phase.

TRACE-Omicron: Policy Counterfactuals to Inform Mitigation of COVID-19 Spread in the United States

The Omicron wave was the largest wave of COVID-19 pandemic to date, more than doubling any other in terms of cases and hospitalizations in the United States. In this paper, we present a large-scale agent-based model of policy interventions that could have been implemented to mitigate the Omicron wave. Our model takes into account the behaviors of individuals and their interactions with one another within a nationally representative population, as well as the efficacy of various interventions such as social distancing, mask wearing, testing, tracing, and vaccination. We use the model to simulate the impact of different policy scenarios and evaluate their potential effectiveness in controlling the spread of the virus. Our results suggest the Omicron wave could have been substantially curtailed via a combination of interventions comparable in effectiveness to extreme and unpopular singular measures such as widespread closure of schools and workplaces, and highlight the importance of early and decisive action.