A decision-theoretic approach towards modelling resilience

Background: ▪ Well-known measures of resilience based on ecosystems modelling. ▪ Some socio-economic conceptualisations but few decision-theoretic formulations to date. Objectives: ▪ To set out a (simple) model of renewable resource use and conceptualise resilience in a rigorous decision-theoretic way. ▪ To derive a model-based measure of resilience and apply it to assess resilience of resource use

A model-based measure for the resilience of resource use under the risk of disruption

While useful conceptualizations and measures have been developed that allow to assess the resilience to shocks of eco systems, socioeconomic systems or individuals, these are often context-specific, somewhat ad-hoc, focused on only certain dimensions of resilience, and not always easy to apply to the assessment of concrete policies. In this paper, we build on a simple yet general model of resource use under the risk of potentially catastrophic disruptions, and derive a rigorous, comprehensive, and policy-oriented measure of socioeconomic resilience. By way of numerical analysis, we illustrate how the measure captures the key aspects of resistance, recovery and robustness; how it embraces current resilience and the continuation resilience following future shocks; and how it can be employed to study the resilience of different harvesting policies both from an ex-ante perspective and following a cascade of shocks

Modeling health shocks

Most of the models on the life-cycle utilization of health care assume that individuals are able to foresee the development of their health perfectly. However, health shocks with significant impact (e.g. severe life-threatening conditions, the onset of chronic disease or accidents) should not be averaged into a mean value, as they have the potential to put the life-course onto a different trajectory. In this paper, we introduce a dynamic optimal control framework incorporating a stochastic health shock with individuals allocating their resources to consumption and different kinds of health care over their life-cycle. We distinguish between general health care and shock specific p revention, a cute and chronic care. This set-up enables us to analyse how the health risk shapes individual behaviour with respect to the different types of health care and how health shocks change the trajectories of consumption and savings. Newly developed transformation techniques allow us to investigate the optimal decisions made in anticipation of a potential health shock and the optimal reaction to all possible shock scenarios. We are able to obtain analytic expressions for the consumption and health care utilization profiles before and after the shock and identify the driving forces. Furthermore, we extend the value of life concept to other aspects of individual health. Finally, we illustrate our findings by calculating a numerical solution calibrated to an individual facing a potential cancer diagnosis in the US

Opening the DICE black-box

Integrated Assessment Models (IAMs) attempt to capture and describe the interactions of (i) human behaviour, (ii) economic activity, and (iii) and climate dynamics and impacts. However, IAMs are often treated as some sort of black-box when calculating solutions

Should the COVID-19 lockdown be relaxed or intensified in case a vaccine becomes available?

Immediately after the start of the COVID-19 pandemic in Early 2020, most affected countries reacted with strict lockdown to limit the spread of the virus. Since that time, the measures were adapted on a short time basis according to certain numbers (i.e., number of infected, utilization of intensive care units). Implementing a long-term optimal strategy was not possible since a forecast when R&D will succeed in developing an effective vaccination was not available. Our paper closes this gap by assuming a stochastic arrival rate of the COVID-19 vaccine with the corresponding change in the optimal policy regarding the accompanying optimal lockdown measures. The first finding is that the lockdown should be intensified after the vaccine approval if the pace of the vaccination campaign is rather slow. Secondly, the anticipation of the vaccination arrival also leads to a stricter lockdown in the period without vaccination. For both findings, an intuitive explanation is offered

Chasing up and locking down the virus: Optimal pandemic interventions within a network

During the COVID-19 pandemic countries invested significant amounts of resources into its containment. In early stages of the pandemic most of the (nonpharmaceutical) interventions can be classified into two groups: (i) testing and identification of infected individuals, (ii) social distancing measures to reduce the transmission probabilities. Furthermore, both groups of measures may, in principle, be targeted at certain subgroups of a networked population. To study such a problem, we propose an extension of the SIR model with additional compartments for quarantine and different courses of the disease across several network nodes. We develop the structure of the optimal allocation and study a numerical example of three symmetric regions that are subject to an asymmetric progression of the disease (starting from an initial hotspot). Key findings include that (i) for our calibrations policies are chosen in a “flattening-the-curve,” avoiding hospital congestion; (ii) policies shift from containing spillovers from the hotspot initially to establishing a symmetric pattern of the disease; and (iii) testing that can be effectively targeted allows to reduce substantially the duration of the disease, hospital congestion and the total cost, both in terms of lives lost and economic costs

Optimization in age-structured dynamic economic models

Age structured optimal control models experience increasing applications in various research fields including e.g., demography, economics, operations research, epidemiology environmental economics. In this paper we present the mathematical theory and potential applications of age-structured optimal control models. We first state the general form of the problem and present the necessary optimality conditions. To illustrate the mathematical theory we introduce a toy model on air pollution, where consumption induces pollution which in turn negatively effects utility, fertility and mortality. We solve the model analytically and present numerical simulations. The potential of age-structure to solve non-standard optimal control models is demonstrated by considering optimal control models with random switches or time-lags and delays

Arabidopsis RCD1 coordinates chloroplast and mitochondrial functions through interaction with ANAC transcription factors

Reactive oxygen species (ROS)-dependent signaling pathways from chloroplasts and mitochondria merge at the nuclear protein RADICAL-INDUCED CELL DEATH1 (RCD1). RCD1 interacts in vivo and suppresses the activity of the transcription factors ANAC013 and ANAC017, which mediate a ROS-related retrograde signal originating from mitochondrial complex III. Inactivation of RCD1 leads to increased expression of mitochondrial dysfunction stimulon (MDS) genes regulated by ANAC013 and ANAC017. Accumulating MDS gene products, including alternative oxidases (AOXs), affect redox status of the chloroplasts, leading to changes in chloroplast ROS processing and increased protection of photosynthetic apparatus. ROS alter the abundance, thiol redox state and oligomerization of the RCD1 protein in vivo, providing feedback control on its function. RCD1-dependent regulation is linked to chloroplast signaling by 3'-phosphoadenosine 5'-phosphate (PAP). Thus, RCD1 integrates organellar signaling from chloroplasts and mitochondria to establish transcriptional control over the metabolic processes in both organelles.Peer reviewe

Immunolocalization of dually phosphorylated MAPKs in dividing root meristem cells of Vicia faba, Pisum sativum, Lupinus luteus and Lycopersicon esculentum

Key message In plants, phosphorylated MAPKs display constitutive nuclear localization; however, not all studied plant species show co-localization of activated MAPKs to mitotic microtubules. Abstract The mitogen-activated protein kinase (MAPK) signaling pathway is involved not only in the cellular response to biotic and abiotic stress but also in the regulation of cell cycle and plant development. The role of MAPKs in the formation of a mitotic spindle has been widely studied and the MAPK signaling pathway was found to be indispensable for the unperturbed course of cell division. Here we show cellular localization of activated MAPKs (dually phosphorylated at their TXY motifs) in both interphase and mitotic root meristem cells of Lupinus luteus, Pisum sativum, Vicia faba (Fabaceae) and Lycopersicon esculentum (Solanaceae). Nuclear localization of activated MAPKs has been found in all species. Colocalization of these kinases to mitotic microtubules was most evident in L. esculentum, while only about 50 % of mitotic cells in the root meristems of P. sativum and V. faba displayed activated MAPKs localized to microtubules during mitosis. Unexpectedly, no evident immunofluorescence signals at spindle microtubules and phragmoplast were noted in L. luteus. Considering immunocytochemical analyses and studies on the impact of FR180204 (an inhibitor of animal ERK1/2) on mitotic cells, we hypothesize that MAPKs may not play prominent role in the regulation of microtubule dynamics in all plant species