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.Integrative Biolog

Bone marrow-based homeostatic proliferation of mature T cells in nonhuman primates: implications for AIDS pathogenesis

Bone marrow (BM) is the key hematopoietic organ in mammals and is involved in the homeostatic proliferation of memory CD8(+) T cells. Here we expanded on our previous observation that BM is a preferential site for T-cell proliferation in simian immunodeficiency virus (SIV)-infected sooty mangabeys (SMs) that do not progress to AIDS despite high viremia. We found high levels of mature T-cell proliferation, involving both naive and memory cells, in healthy SMs and rhesus macaques (RMs). In addition, we observed in both species that lineage-specific, BM-based T-cell proliferation follows antibody-mediated in vivo CD4(+) or CD8(+) T-cell depletion, thus indicating a role for the BM in maintaining T-cell homeostasis under depleting circumstances. We also observed that, in SIV-infected SMs, but not RMs, the level of proliferation of BM-based CD4(+) T cells is higher than that of circulating CD4(+) T cells. Interestingly, limited BM-based CD4(+) T-cell proliferation was found in SIV-infected SMs with low CD4(+) T-cell counts, suggesting a regenerative failure in these animals. Collectively, these results indicate that BM is involved in maintaining T-cell homeostasis in primates and suggest a role for BM-based CD4(+) T-cell proliferation in determining the benign nature of natural SIV infection of SMs

Lineage-specific T-cell reconstitution following in vivo CD4+ and CD8+ lymphocyte depletion in nonhuman primates

Many features of T-cell homeostasis in primates are still unclear, thus limiting our understanding of AIDS pathogenesis, in which T-cell homeostasis is lost. Here, we performed experiments of in vivo CD4+ or CD8+ lymphocyte depletion in 2 nonhuman primate species, rhesus macaques (RMs) and sooty mangabeys (SMs). Whereas RMs develop AIDS after infection with simian immunodeficiency virus (SIV), SIV-infected SMs are typically AIDS-resistant. We found that, in both species, most CD4+ or CD8+ T cells in blood and lymph nodes were depleted after treatment with their respective antibodies. These CD4+ and CD8+ lymphocyte depletions were followed by a largely lineage-specific CD4+ and CD8+ T-cell proliferation, involving mainly memory T cells, which correlated with interleukin-7 plasma levels. Interestingly, SMs showed a faster repopulation of naive CD4+ T cells than RMs. In addition, in both species CD8+ T-cell repopulation was faster than that of CD4+ T cells, with CD8+ T cells reconstituting a normal pool within 60 days and CD4+ T cells remaining below baseline levels up to day 180 after depletion. While this study revealed subtle differences in CD4+ T-cell repopulation in an AIDS-sensitive versus an AIDS-resistant species, such differences may have particular relevance in the presence of active SIV repli cation, where CD4+ T-cell destruction is chronic

Multiple models for outbreak decision support in the face of uncertainty

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020

Multiple models for outbreak decision support in the face of uncertainty.

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020