"Gauging the Potential for Social Unrest"

It stands to reason that social unrest does not erupt out of the blue. Although there are a great many reasons why social dismay might descend into social disorder, only few yardsticks or indices can plausibly be used to gauge the potential for social unrest (PSU). If policy makers want to undertake public action to prevent social dismay escalating into social disruption, they obviously need to draw on practical sensors. This paper assesses critically the adequacy of two such measures, the polarization (P) index, and the total relative deprivation (TRD) index. The paper proposes a tentative guide to selecting between these two measures. A review of three stylized scenarios suggests that, where income redistributions reduce the number of distinct income groups, and when each group is characterized by a strong sense of within-group identity, the P index surpasses the TRD index as a basis for predicting PSU. When the within-group identification is weak, however, it is better to use the TRD index to predict PSU.Social dismay; Potential for social unrest; Polarization; Total relative deprivation; Policy choice

Job Selection in a Network of Autonomous UAVs for Delivery of Goods

This article analyzes two classes of job selection policies that control how a network of autonomous aerial vehicles delivers goods from depots to customers. Customer requests (jobs) occur according to a spatio-temporal stochastic process not known by the system. If job selection uses a policy in which the first job (FJ) is served first, the system may collapse to instability by removing just one vehicle. Policies that serve the nearest job (NJ) first show such threshold behavior only in some settings and can be implemented in a distributed manner. The timing of job selection has significant impact on delivery time and stability for NJ while it has no impact for FJ. Based on these findings we introduce a methodological approach for decision-making support to set up and operate such a system, taking into account the trade-off between monetary cost and service quality. In particular, we compute a lower bound for the infrastructure expenditure required to achieve a certain expected delivery time. The approach includes three time horizons: long-term decisions on the number of depots to deploy in the service area, mid-term decisions on the number of vehicles to use, and short-term decisions on the policy to operate the vehicles

Why resilience in health care systems is more than coping with disasters: implications for health care policy

Health care systems need to be resilient to deal with disasters like the global spread of the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) on top of serving the changing needs of a multi-morbid, ageing and often dispersed population. This paper identifies, discusses and augments critical dimensions of resilience retrieved from the academic literature. It pulls together an integrated concept of resilience characterised by organisational capabilities. Our concept does not focus on the micro-level like most resilience literature in health care but addresses the system level with many stakeholders involved. Distinguishing exogenous shocks to the health care system into adverse events and planned innovations provides the basis for our conclusions and insights. It becomes apparent only when dealing with planned interventions that transformative capabilities are indispensable to cope with sudden increases in health care pressures. Due to the current focus on absorptive and adaptive resilience, organisations over-rely on management capabilities that cannot generate a lasting increase in functionality. Therefore, reducing the resilience discussion to bouncing back from adverse events could deceive organisations into cultivating a suboptimal mix of organisational capabilities lacking transformative capabilities, which pave the way for a structural change that aims at a sustainably higher functionality

Modeling disease progression and treatment pathways for depression jointly using agent based modeling and system dynamics

Introduction: Depression is a common mental health condition that affects millions of people worldwide. Care pathways for depression are complex and the demand across different parts of the healthcare system is often uncertain and not entirely understood. Clinical progression with depression can be equally complex and relates to whether or not a patient is seeking care, the care pathway they are on, and the ability for timely access to healthcare services. Considering both pathways and progression for depression are however rarely studied together in the literature. Methods: This paper presents a hybrid simulation modeling framework that is uniquely able to capture both disease progression, using Agent Based Modeling, and related care pathways, using a System Dynamics. The two simulation paradigms within the framework are connected to run synchronously to investigate the impact of depression progression on healthcare services and, conversely, how any limitations in access to services may impact clinical progression. The use of the developed framework is illustrated by parametrising it with published clinical data and local service level data from Wales, UK. Results and discussion: The framework is able to quantify demand, service capacities and costs across all care pathways for a range of different scenarios. These include those for varying service coverage and provision, such as the cost-effectiveness of treating patients more quickly in community settings to reduce patient progression to more severe states of depression, and thus reducing the costs and utilization of more expensive specialist settings

Still looking in the wrong place: literature-based evidence of why patients really attend an emergency department

Presenting complaints at an Emergency Department (ED) that could (and should) have been seen in primary care are discussed in the literature as ‘inappropriate use’ of hospital-based emergency services. These medically inappropriate requests are perceived as a threat to service quality, implying more costs than necessary. Using Systems Thinking/Dynamics, this paper introduces an evidence-based framework to explain why people increasingly attend an ED instead of a primary-care-based emergency facility, with patient demographics (age and deprivation), signposting sources and patients' perceptions (reflecting latent needs) identified as the main determinates of ED use. The framework makes explicit the endogenous dynamics of referral, service choice and service reputation (where expectations and confirming experiences are recursively shaped over time). The work can be employed at the strategic level as a framework to inform attendance management when evaluating or altering the healthcare system. This is achieved by presenting how the healthcare system responds to patient encounters and how patient behaviour adapts in response. At the operational level, the presented framework enables modellers and healthcare planners to develop hospital-based and primary-care-based emergency care interventions with empathy and compassion for patients. We highlight opportunities for future work as the healthcare system is complex and requires more in-depth exploration/modelling to complete the picture

A Monte Carlo simulation model for evaluating the effectiveness of Interventions along the ‘Diabesity’ pathway

The prevalence of obesity has increased worldwide in the past 50 years, reaching pandemic levels (Blüher, 2019). In this paper, we report on the development of an intervention evaluation model and risk assessment tool that has been developed for an Adult Weight Management Service (AWMS) within the U.K.’s National Health Service (NHS). The tool uses Monte Carlo simulation to predict the progress of morbidity and mortality in individual AWMS patients for up to 25 years, with and without intervention. Running the tool on a sample of AWMS patients with known weight loss outcomes indicates that interventions can be evaluated in terms of risk assessment of developing obesity-related health conditions such as diabetes

MultiDark-Galaxies: data release and first results

We present the public release of the MultiDark-Galaxies: three distinct galaxy catalogues derived from one of the Planck cosmology MULTIDARK simulations (i.e. MDPL2, with a volume of (1 h-1 Gpc)3 and mass resolution of 1.5 × 109 h-1 M⊙) by applying the semi-analytic models GALACTICUS, SAG, and SAGE to it. We compare the three models and their conformity with observational data for a selection of fundamental properties of galaxies like stellar mass function, star formation rate, cold gas fractions, and metallicities - noting that they sometimes perform differently reflecting model designs and calibrations. We have further selected galaxy subsamples of the catalogues by number densities in stellar mass, cold gas mass, and star formation rate in order to study the clustering statistics of galaxies. We show that despite different treatment of orphan galaxies, i.e. galaxies that lost their dark-matter host halo due to the finite-mass resolution of the N-body simulation or tidal stripping, the clustering signal is comparable, and reproduces the observations in all three models - in particular when selecting samples based upon stellar mass. Our catalogues provide a powerful tool to study galaxy formation within a volume comparable to those probed by ongoing and future photometric and redshift surveys. All model data consisting of a range of galaxy properties - including broad-band SDSS magnitudes - are publicly available.Facultad de Ciencias Astronómicas y GeofísicasInstituto de Astrofísica de La Plat

MultiDark-Galaxies: data release and first results

We present the public release of the MultiDark-Galaxies: three distinct galaxy catalogues derived from one of the Planck cosmology MULTIDARK simulations (i.e. MDPL2, with a volume of (1 h-1 Gpc)3 and mass resolution of 1.5 × 109 h-1 M⊙) by applying the semi-analytic models GALACTICUS, SAG, and SAGE to it. We compare the three models and their conformity with observational data for a selection of fundamental properties of galaxies like stellar mass function, star formation rate, cold gas fractions, and metallicities - noting that they sometimes perform differently reflecting model designs and calibrations. We have further selected galaxy subsamples of the catalogues by number densities in stellar mass, cold gas mass, and star formation rate in order to study the clustering statistics of galaxies. We show that despite different treatment of orphan galaxies, i.e. galaxies that lost their dark-matter host halo due to the finite-mass resolution of the N-body simulation or tidal stripping, the clustering signal is comparable, and reproduces the observations in all three models - in particular when selecting samples based upon stellar mass. Our catalogues provide a powerful tool to study galaxy formation within a volume comparable to those probed by ongoing and future photometric and redshift surveys. All model data consisting of a range of galaxy properties - including broad-band SDSS magnitudes - are publicly available.Facultad de Ciencias Astronómicas y GeofísicasInstituto de Astrofísica de La Plat

MultiDark-Galaxies: data release and first results

We present the public release of the MultiDark-Galaxies: three distinct galaxy catalogues derived from one of the Planck cosmology MULTIDARK simulations (i.e. MDPL2, with a volume of (1 h-1 Gpc)3 and mass resolution of 1.5 × 109 h-1 M⊙) by applying the semi-analytic models GALACTICUS, SAG, and SAGE to it. We compare the three models and their conformity with observational data for a selection of fundamental properties of galaxies like stellar mass function, star formation rate, cold gas fractions, and metallicities - noting that they sometimes perform differently reflecting model designs and calibrations. We have further selected galaxy subsamples of the catalogues by number densities in stellar mass, cold gas mass, and star formation rate in order to study the clustering statistics of galaxies. We show that despite different treatment of orphan galaxies, i.e. galaxies that lost their dark-matter host halo due to the finite-mass resolution of the N-body simulation or tidal stripping, the clustering signal is comparable, and reproduces the observations in all three models - in particular when selecting samples based upon stellar mass. Our catalogues provide a powerful tool to study galaxy formation within a volume comparable to those probed by ongoing and future photometric and redshift surveys. All model data consisting of a range of galaxy properties - including broad-band SDSS magnitudes - are publicly available.Facultad de Ciencias Astronómicas y GeofísicasInstituto de Astrofísica de La Plat