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1. Awareness-driven behavior changes can shift the shape of epidemics away from peaks and toward plateaus, shoulders, and oscillations

   https://doi.org/10.1073/pnas.2009911117  

   Weitz, Joshua S.; Park, Sang Woo; Eksin, Ceyhun; Dushoff, Jonathan (December 2020, Proceedings of the National Academy of Sciences)

   null (Ed.)

   The COVID-19 pandemic has caused more than 1,000,000 reported deaths globally, of which more than 200,000 have been reported in the United States as of October 1, 2020. Public health interventions have had significant impacts in reducing transmission and in averting even more deaths. Nonetheless, in many jurisdictions, the decline of cases and fatalities after apparent epidemic peaks has not been rapid. Instead, the asymmetric decline in cases appears, in most cases, to be consistent with plateau- or shoulder-like phenomena—a qualitative observation reinforced by a symmetry analysis of US state-level fatality data. Here we explore a model of fatality-driven awareness in which individual protective measures increase with death rates. In this model, fast increases to the peak are often followed by plateaus, shoulders, and lag-driven oscillations. The asymmetric shape of model-predicted incidence and fatality curves is consistent with observations from many jurisdictions. Yet, in contrast to model predictions, we find that population-level mobility metrics usually increased from low levels before fatalities reached an initial peak. We show that incorporating fatigue and long-term behavior change can reconcile the apparent premature relaxation of mobility reductions and help understand when post-peak dynamics are likely to lead to a resurgence of cases. 

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2. Governance structure affects transboundary disease management under alternative objectives

   https://doi.org/10.1186/s12889-021-11797-3  

   Blackwood, Julie C.; Malakhov, Mykhaylo M.; Duan, Junyan; Pellett, Jordan J.; Phadke, Ishan S.; Lenhart, Suzanne; Sims, Charles; Shea, Katriona (October 2021, BMC Public Health)

   Abstract BackgroundThe development of public health policy is inextricably linked with governance structure. In our increasingly globalized world, human migration and infectious diseases often span multiple administrative jurisdictions that might have different systems of government and divergent management objectives. However, few studies have considered how the allocation of regulatory authority among jurisdictions can affect disease management outcomes. MethodsHere we evaluate the relative merits of decentralized and centralized management by developing and numerically analyzing a two-jurisdictionSIRSmodel that explicitly incorporates migration. In our model, managers choose between vaccination, isolation, medication, border closure, and a travel ban on infected individuals while aiming to minimize either the number of cases or the number of deaths. ResultsWe consider a variety of scenarios and show how optimal strategies differ for decentralized and centralized management levels. We demonstrate that policies formed in the best interest of individual jurisdictions may not achieve global objectives, and identify situations where locally applied interventions can lead to an overall increase in the numbers of cases and deaths. ConclusionsOur approach underscores the importance of tailoring disease management plans to existing regulatory structures as part of an evidence-based decision framework. Most importantly, we demonstrate that there needs to be a greater consideration of the degree to which governance structure impacts disease outcomes. 

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3. PUBLIC TRUST AND BIOTECH INNOVATION: A THEORY OF TRUSTWORTHY REGULATION OF (SCARY!) TECHNOLOGY

   https://doi.org/10.1017/S0265052522000036  

   Wolf, Clark (January 2021, Social Philosophy and Policy)

   Abstract Regulatory agencies aim to protect the public by moderating risks associated with innovation, but a good regulatory regime should also promote justified public trust. After introducing the USDA 2020 SECURE Rule for regulation of biotech innovation as a case study, this essay develops a theory of justified public trust in regulation. On the theory advanced here, to be trustworthy, a regulatory regime must (1) fairly and effectively manage risk, must be (2) “science based” in the relevant sense, and must in addition be (3) truthful, (4) transparent, and (5) responsive to public input. Evaluated with these norms, the USDA SECURE Rule is shown to be deeply flawed, since it fails appropriately to manage risk, and similarly fails to satisfy other normative requirements for justified trust. The argument identifies ways in which the SECURE Rule itself might be improved, but more broadly provides a normative framework for the evaluation of trustworthy regulatory policy-making. 

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4. Re-ranking via Metric Fusion for Object Retrieval and Person Re-identification.

   Bai, Song; Tang, Peng; Torr, Philip; Latecki, Longin Jan (June 2019, IEEE Conference on Computer Vision and Pattern Recognition)

   This work studies the unsupervised re-ranking procedure for object retrieval and person re-identification with a specific concentration on an ensemble of multiple metrics (or similarities). While the re-ranking step is involved by running a diffusion process on the underlying data manifolds, thefusionstepcanleveragethecomplementarityofmultiple metrics. We give a comprehensive summary of existing fusion with diffusion strategies, and systematically analyze their pros and cons. Based on the analysis, we propose a unified yet robust algorithm which inherits their advantages and discards their disadvantages. Hence, we call it Unified Ensemble Diffusion (UED). More interestingly, we derive that the inherited properties indeed stem from a theoretical framework, where the relevant works can be elegantly summarized as special cases of UED by imposing additional constraints on the objective function and varying the solver of similarity propagation. Extensive experiments with 3D shape retrieval, image retrieval and person re-identification demonstrate that the proposed framework outperforms the state of the arts, and at the same time suggest that re-ranking via metric fusion is a promising tool to further improve the retrieval performance of existing algorithms. 

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5. Evolutionary Origins of the Oligodendrocyte Cell Type and Adaptive Myelination

   https://doi.org/10.3389/fnins.2021.757360  

   Hines, Jacob H. (December 2021, Frontiers in Neuroscience)

   Oligodendrocytes are multifunctional central nervous system (CNS) glia that are essential for neural function in gnathostomes. The evolutionary origins and specializations of the oligodendrocyte cell type are among the many remaining mysteries in glial biology and neuroscience. The role of oligodendrocytes as CNS myelinating glia is well established, but recent studies demonstrate that oligodendrocytes also participate in several myelin-independent aspects of CNS development, function, and maintenance. Furthermore, many recent studies have collectively advanced our understanding of myelin plasticity, and it is now clear that experience-dependent adaptations to myelination are an additional form of neural plasticity. These observations beg the questions of when and for which functions the ancestral oligodendrocyte cell type emerged, when primitive oligodendrocytes evolved new functionalities, and the genetic changes responsible for these evolutionary innovations. Here, I review recent findings and propose working models addressing the origins and evolution of the oligodendrocyte cell type and adaptive myelination. The core gene regulatory network (GRN) specifying the oligodendrocyte cell type is also reviewed as a means to probe the existence of oligodendrocytes in basal vertebrates and chordate invertebrates. 

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