The SIPHER consortium : introducing the new UK hub for systems science in public health and health economic research

The conditions in which we are born, grow, live, work and age are key drivers of health and inequalities in life chances. To maximise health and wellbeing across the whole population, we need well-coordinated action across government sectors, in areas including economic, education, welfare, labour market and housing policy. Current research struggles to offer effective decision support on the cross-sector strategic alignment of policies, and to generate evidence that gives budget holders the confidence to change the way major investment decisions are made. This open letter introduces a new research initiative in this space. The SIPHER (Systems Science in Public Health and Health Economics Research) Consortium brings together a multi-disciplinary group of scientists from across six universities, three government partners at local, regional and national level, and ten practice partner organisations. The Consortium’s vision is a shift from health policy to healthy public policy, where the wellbeing impacts of policies are a core consideration across government sectors. Researchers and policy makers will jointly tackle fundamental questions about: a) the complex causal relationships between upstream policies and wellbeing, economic and equality outcomes; b) the multi-sectoral appraisal of costs and benefits of alternative investment options; c) public values and preferences for different outcomes, and how necessary trade-offs can be negotiated; and d) creating the conditions for intelligence-led adaptive policy design that maximises progress against economic, social and health goals. Whilst our methods will be adaptable across policy topics and jurisdictions, we will initially focus on four policy areas: Inclusive Economic Growth, Adverse Childhood Experiences, Mental Wellbeing and Housing

Uncertainty analysis using Bayesian Model Averaging: a case study of input variables to energy models and inference to associated uncertainties of energy scenarios

Background Energy models are used to illustrate, calculate and evaluate energy futures under given assumptions. The results of energy models are energy scenarios representing uncertain energy futures. Methods The discussed approach for uncertainty quantification and evaluation is based on Bayesian Model Averaging for input variables to quantitative energy models. If the premise is accepted that the energy model results cannot be less uncertain than the input to energy models, the proposed approach provides a lower bound of associated uncertainty. The evaluation of model-based energy scenario uncertainty in terms of input variable uncertainty departing from a probabilistic assessment is discussed. Results The result is an explicit uncertainty quantification for input variables of energy models based on well-established measure and probability theory. The quantification of uncertainty helps assessing the predictive potential of energy scenarios used and allows an evaluation of possible consequences as promoted by energy scenarios in a highly uncertain economic, environmental, political and social target system. Conclusions If societal decisions are vested in computed model results, it is meaningful to accompany these with an uncertainty assessment. Bayesian Model Averaging (BMA) for input variables of energy models could add to the currently limited tools for uncertainty assessment of model-based energy scenarios

Betting is loving and bettors are predators: a conceptual metaphor approach to online sports betting advertising

The legalisation of online gambling in multiple territories has caused a growth in the exposure of consumers to online sports betting (OSB) advertising. While some efforts have been made to understand the visible structure of betting promotional messages, little is known about the latent components of OSB advertisements. The present study sought to address this issue by examining the metaphorical conceptualisation of OSB advertising. A sample of Spanish and British television OSB advertisements from 2014 to 2016 was analysed (N = 133). Following Lakoff and Johnson’s conceptual metaphor theory, four main structural metaphors that shaped how OSB advertising can be understood were identified: betting as (1) an act of love, (2) a market, (3) a sport, and (4) a natural environment. In general, these metaphors, which were found widely across 29 different betting brands, facilitated the perception of bettors as active players, with an executive role in the sport events bet upon, and greater control over bet outcomes

Exploring the Future of Wind-Powered Energy

Although there is a trend towards more sustainable energy system, the future of renewable energies is still deeply uncertain. Among the renewable resources, wind energy is considered to be a promising one. However, in the presence of deep uncertainty, what will be the future of wind-powered energy? Decision making under deep uncertainty for such issues requires an explorative manner. Since predictions under deep uncertainty can be extremely misleading, exploration of plausible futures should be the main approach. In this paper, a new research methodology, Exploratory Modeling and Analysis (EMA), to deal with deep uncertainty will be presented. Three System Dynamics models about Wind-powered energy will be explored using EMA and results of possible policy implementations will be illustrated.Multi Actor SystemsTechnology, Policy and Managemen

The Influenza A(H1N1)v Pandemic: An Exploratory System Dynamics Approach

This paper presents a small exploratory System Dynamics model related to the dynamics of the 2009 flu pandemic, also known as the Mexican flu, swine flu, or A(H1N1)v. The model was developed in May 2009 in order to quickly foster understanding about the possible dynamics of this new flu variant and to perform rough-cut policy explorations. Later, the model was also used to further develop and illustrate the use of Exploratory System Dynamics models as scenario generators for Exploratory Modelling and Analysis. The paper starts with an introduction to, and a description of, the exploratory System Dynamics model, followed by a discussion of plausible behaviours, sensitivity, what-if and policy analyses. The model is subsequently used to illustrate the Exploratory System Dynamics Modelling and Analysis approach: base case behaviours are discussed, followed by sensitivity, what-if and policy analyses. Finally some concluding remarks and policy recommendations are formulated.Multi Actor SystemsTechnology, Policy and Managemen

The Concerted Run on the DSB Bank: An Exploratory System Dynamics Approach

In this paper, an Exploratory System Dynamics model of a concerted run is first of all presented. The immediate cause for modelling a concerted bank run was the mediatised call for a run on the DSB bank. This Exploratory System Dynamics model was developed the morning of the call for the bank run, before the start of the ensuing bank crisis, in order to quickly foster understanding of possible dynamic behaviours of ‘concerted’ bank runs and to perform rough-cut policy/strategy analyses. The model is subsequently used to illustrate the combination of Exploratory System Dynamics modelling and Exploratory Modelling and Analysis, or Exploratory System Dynamics Modelling and Analysis. The paper starts with a short overview of the DSB Bank crisis, the description of the exploratory System Dynamics model and some quick exploratory analyses. The model is then used as a scenario generator for Exploratory System Dynamics Modelling and Analysis in order to analyse and deal with deep uncertainties surrounding the issue and its modelling (parameters and functions). The paper ends with some applied conclusions and policy recommendations, methodological conclusions, and venues for future work.Multi Actor SystemsTechnology, Policy and Managemen

Test anxiety, coping strategies, and perceived health in a group of high school students: A Turkish sample

A group of high school juniors and a group of high school seniors in Izmir, Turkey completed measures of test anxiety, coping skills, and perceived health status both before and after a major exam period. Students with high test anxiety used less effective coping mechanisms and tended to have poorer perceptions of their health. Prior to the exams, juniors displayed higher test anxiety and used less effective coping mechanisms than seniors. After the exam periods, improvements were seen for both age groups on perceived health, but scores of younger students remained significantly higher than scores of seniors on one of the key measures of test anxiety. Results of the study lend support to those of previous studies done in other cultural contexts, and Findings have implications for the development of interventions designed to help students cope with stress

Exploring carbon futures in the EU power sector: Using Exploratory System Dynamics Modelling and Analysis to explore policy regimes under deep uncertainty

The European Emissions Trading Scheme (ETS) in combination with other renewable electricity (RES-E) support schemes such as (premium) feed-in tariffs or tradable green certificates do not guarantee a carbon neutral power sector in 2050. This paper shows that many plausible futures of high carbon emissions exist when no substantial efficiency measures are taken in high growth futures. Using System Dynamics (SD) in combination with Exploratory Modelling and Analysis (EMA), it seems that the main European energy policies might result in high levels of carbon abatement but have very limited guarantees whatsoever. There are potential ‘free lunches’ for policy makers to reduce carbon emissions but these will probably not suffice when ambition levels remain high. This paper sheds new light on the path to find policy synergies for the European electricity sector with the aim to rule out lurking catastrophic futures of high carbon emissions combined with high costs for society.Multi Actor SystemsTechnology, Policy and Managemen

Optimal Adaptive Policymaking under Deep Uncertainty? Yes we can!

Uncertainty manifests itself in almost every aspect of decision making. Adaptive and flexible policy design becomes crucial under uncertainty. An adaptive policy is designed to be flexible and can be adapted over time to changing circumstances and unforeseeable surprises. A crucial part of an adaptive policy is the monitoring system and associated pre-specified actions to be taken in response to how the future unfolds. However, the adaptive policymaking literature remains silent on how to design this monitoring system and how to specify appropriate values that will trigger the pre-specified responses. These trigger values have to be chosen such that the resulting adaptive plan is robust and flexible to surprises in the future. Actions should be neither triggered too early nor too late. One possible family of techniques for specifying triggers is optimization. Trigger values would then be the values that maximize the extent of goal achievement across a large ensemble of scenarios. This ensemble of scenarios is generated using Exploratory Modeling and Analysis. In this paper, we show how optimization can be useful for the specification of trigger values. A Genetic Algorithm is used because of its flexibility and efficiency in complex and irregular solution spaces. The proposed approach is illustrated for the transitions of the energy system towards a more sustainable functioning which requires effective dynamic adaptive policy design. The main aim of this paper is to show the contribution of optimization for adaptive policy design.Multi Actor SystemsTechnology, Policy and Managemen

Adaptive policymaking under deep uncertainty: Optimal preparedness for the next pandemic

The recent flu pandemic in 2009 caused a panic about the possible consequences due to deep uncertainty about an unknown virus. Overstock of vaccines or unnecessary social measures to be taken were all due to uncertainty. However, what should be the necessary actions to take in such deeply uncertain situation where there is no or very little information available? For uncertain and complex future, adaptivity and flexibility should be the main aim for designing robust policies. Here, we propose an iterative approach for designing adaptive and robust policies in the presence of deep uncertainty. A crucial part of this approach is the use of monitoring systems that provide the adaptivity and flexibility of the policy design. In the monitoring system, signposts to track specific information are defined. Specific values of these signposts are called triggers and they are triggered when pre-specified conditions occur in the system. The specification of trigger values is crucial for the policy performance but has not been studied in depth. Here, we use robust optimization to optimize the trigger values. This paper shows that our proposed approach with robust optimization improves policy design in deeply uncertain and complex situations where very little information is available.Multi Actor SystemsTechnology, Policy and Managemen