Computational models that matter during a global pandemic outbreak: A call to action

The COVID-19 pandemic is causing a dramatic loss of lives worldwide, challenging the sustainability of our health care systems, threatening economic meltdown, and putting pressure on the mental health of individuals (due to social distancing and lock-down measures). The pandemic is also posing severe challenges to the scientific community, with scholars under pressure to respond to policymakers’ demands for advice despite the absence of adequate, trusted data. Understanding the pandemic requires fine-grained data representing specific local conditions and the social reactions of individuals. While experts have built simulation models to estimate disease trajectories that may be enough to guide decision-makers to formulate policy measures to limit the epidemic, they do not cover the full behavioural and social complexity of societies under pandemic crisis. Modelling that has such a large potential impact upon people’s lives is a great responsibility. This paper calls on the scientific community to improve the transparency, access, and rigour of their models. It also calls on stakeholders to improve the rapidity with which data from trusted sources are released to the community (in a fully responsible manner). Responding to the pandemic is a stress test of our collaborative capacity and the social/economic value of research

Greenhouse gas calculator for electricity and heat from biomass

Industrial Ecolog

Climate adaptation of interconnected infrastructures: a framework for supporting governance

Infrastructures are critical for human society, but vulnerable to climate change. The current body of research on infrastructure adaptation does not adequately account for the interconnectedness of infrastructures, both internally and with one another. We take a step toward addressing this gap through the introduction of a framework for infrastructure adaptation that conceptualizes infrastructures as complex socio-technical “systems of systems” embedded in a changing natural environment. We demonstrate the use of this framework by structuring potential climate change impacts and identifying adaptation options for a preliminary set of cases—road, electricity and drinking water infrastructures. By helping to clarify the relationships between impacts at different levels, we find that the framework facilitates the identification of key nodes in the web of possible impacts and helps in the identification of particularly nocuous weather conditions. We also explore how the framework may be applied more comprehensively to facilitate adaptation governance. We suggest that it may help to ensure that the mental models of stakeholders and the quantitative models of researchers incorporate the essential aspects of interacting climate and infrastructure systems. Further research is necessary to test the framework in these contexts and to determine when and where its application may be most beneficial.Infrastructure Networks Climate Adaptation and Hotspots. Knowledge for Climate Progra

Fc engineered ACE2-Fc is a potent multifunctional agent targeting SARS-CoV2

Joining a function-enhanced Fc-portion of human IgG to the SARS-CoV-2 entry receptor ACE2 produces an antiviral decoy with strain transcending virus neutralizing activity. SARS-CoV-2 neutralization and Fc-effector functions of ACE2-Fc decoy proteins, formatted with or without the ACE2 collectrin domain, were optimized by Fc-modification. The different Fc-modifications resulted in distinct effects on neutralization and effector functions. H429Y, a point mutation outside the binding sites for FcγRs or complement caused non-covalent oligomerization of the ACE2-Fc decoy proteins, abrogated FcγR interaction and enhanced SARS-CoV-2 neutralization. Another Fc mutation, H429F did not improve virus neutralization but resulted in increased C5b-C9 fixation and transformed ACE2-Fc to a potent mediator of complement-dependent cytotoxicity (CDC) against SARS-CoV-2 spike (S) expressing cells. Furthermore, modification of the Fc-glycan enhanced cell activation via FcγRIIIa. These different immune profiles demonstrate the capacity of Fc-based agents to be engineered to optimize different mechanisms of protection for SARS-CoV-2 and potentially other viral pathogens

Social simulation comparison in arbitrary problem domains: first steps towards a more principled approach

We outline a simulation development process, backed by a software framework, which focuses on developing and using a partial conceptual model as a ‘lens’ to compare and possibly re-implement existing models in a chosen problem domain (as well as to design new models). To make this feasible for existing models of arbitrary structure and background social theory, we construct our (partial) conceptual model in a way that acknowledges that it is a base representation which any individual model will typically add detail to, and abstract away from, in various ways which we argue can be formalised. A given model’s design is fitted to the conceptual model to capture how its structural architecture (and selected aspects of the system’s state and driving processes) map to the conceptual model. This fit can be used to produce incomplete skeleton code which can then be extended to produce a simulation. Along the way, we discuss how the field of robust decision-making provides a useful context for this, and how it differs from other approaches. This is inevitably a preliminary approach to a broad and difficult problem, so we end by discussing some of the main issues and what might be needed next

Multi-model ecologies for shaping future energy systems:Design patterns and development paths

As energy systems grow more complex, modeling efforts spanning multiple scales, disciplines and perspectives are essential. Improved methods are needed to guide the development of not just individual models, but also multi-model ecologies - systems of interacting models. Currently there is a lack of knowledge concerning how multi-model ecologies can and should be designed to facilitate adequate understanding of energy system complexity and its consequences. Via an analysis of twelve multi-model initiatives both within and outside the energy domain, this paper elucidates possible design patterns and development paths for multi-model ecologies. The results highlight two broad paths to developing energy system multi-model ecologies, one prioritizing interoperability and the other prioritizing diversity. The former path facilitates the efficient development of models spanning multiple scales and (to a degree) disciplines, and can ease systematic testing of assumptions. The latter is suited to bridging traditional disciplines and perspectives and advancing knowledge within the interstices of different knowledge communities. It is furthermore suggested that a combination of diversity, connectivity and hierarchy in multi-model ecology composition is central to enabling the development of complex webs of models capable of addressing the complexity of real-world energy systems