Energy and complexity: new ways forward

The purpose of this paper is to review the application of complexity science methods in understanding energy systems and system change. The challenge of moving to sustainable energy systems which provide secure, affordable and low-carbon energy services requires the application of methods which recognise the complexity of energy systems in relation to social, technological, economic and environmental aspects. Energy systems consist of many actors, interacting through networks, leading to emergent properties and adaptive and learning processes. Insights on these type of phenomena have been investigated in other contexts by complex systems theory. However, these insights are only recently beginning to be applied to understanding energy systems and systems transitions. The paper discusses the aspects of energy systems (in terms of technologies, ecosystems, users, institutions, business models) that lend themselves to the application of complexity science and its characteristics of emergence and coevolution. Complex-systems modelling differs from standard (e.g. economic) modelling and offers capabilities beyond those of conventional models, yet these methods are only beginning to realize anything like their full potential to address the most critical energy challenges. In particular there is significant potential for progress in understanding those challenges that reside at the interface of technology and behaviour. Some of the computational methods that are currently available are reviewed: agent-based and network modelling. The advantages and limitations of these modelling techniques are discussed. Finally, the paper considers the emerging themes of transport, energy behaviour and physical infrastructure systems in recent research from complex-systems energy modelling. Although complexity science is not well understood by practitioners in the energy domain (and is often difficult to communicate), models can be used to aid decision-making at multiple levels e.g. national and local, and to aid understanding and allow decision making. The techniques and tools of complexity science, therefore, offer a powerful means of understanding the complex decision-making processes that are needed to realise a low-carbon energy system. We conclude with recommendations for future areas of research and application

Low carbon infrastructure investment: extending business models for sustainability

Investment in infrastructure is recognized as a key enabler of economic prosperity, but it is also important for addressing social and environmental challenges, including climate change mitigation and addressing fuel poverty. The UK Government Strategy Investing in Britain’s Future argues that significant investment in “resilient, cost effective and sustainable energy supplies” is needed to meet these challenges. However, current methods of assessing the costs and benefits of infrastructure investment, and the subsequent design of business models needed to deliver this investment, often prioritise partial economic gains over social and environmental objectives. This paper extends the business model canvas approach to allow designing business models and evaluation methods that can incorporate social and environmental value streams and propositions as well as economic values in order to facilitate genuinely sustainable infrastructure investment. It demonstrates the usefulness of this extension through two case studies of the development of smart grids for electricity distribution and local heat delivery networks in the UK. Smart grids are essential for maintaining the security and reliability of electricity systems whilst incorporating increasing amounts of low carbon generation in distribution networks. District heat networks can facilitate the efficient supply of low carbon heat. However, both will require significant levels of investment, co-ordination between public, private and regulatory actors, and will deliver a range of economic, social and environmental costs and benefits to these actors. Drawing on empirical interviews with local actors involved in smart grid and heat network developments, and recent work on valuation and business model canvas analysis, the paper challenges the traditional view of a business model as only creating one form of value. Accounting for multiple types of value helps to identify business models that are more likely to achieve the environmental and social goals of infrastructure transformation and opens the door for new actors. Finally, the paper introduces an approach to complex systems modelling of infrastructure investment decisions to take into account the range of actors and the diversity of motivations of these actors

A complexity approach to defining urban energy systems

Urban energy systems have been commonly considered to be socio-technical systems within the boundaries of an urban area. However, recent literature challenges this notion in that it urges researchers to look at the wider interactions and influences of urban energy systems wherein the socio-technical sphere is expanded to political, environmental and economic realms as well. In addition to the inter-sectoral linkages, the diverse agents and multilevel governance trends of energy sustainability in the dynamic environment of cities make the urban energy landscape a complex one. There is a strong case then for establishing a new conceptualisation of urban energy systems that builds upon these contemporary understandings of such systems. We argue that the complex systems approach can be suitable for this. In this paper, we propose a pilot framework for understanding urban energy systems using complex systems theory as an integrating plane. We review the multiple streams of urban energy literature to identify the contemporary discussions and construct this framework that can serve as a common ontological understanding for the different scholarships studying urban energy systems. We conclude the paper by highlighting the ways in which the framework can serve some of the relevant communities

Using a Human Challenge Model of Infection to Measure Vaccine Efficacy: A Randomised, Controlled Trial Comparing the Typhoid Vaccines M01ZH09 with Placebo and Ty21a

Background Typhoid persists as a major cause of global morbidity. While several licensed vaccines to prevent typhoid are available, they are of only moderate efficacy and unsuitable for use in children less than two years of age. Development of new efficacious vaccines is complicated by the human host-restriction of Salmonella enterica serovar Typhi (S. Typhi) and lack of clear correlates of protection. In this study, we aimed to evaluate the protective efficacy of a single dose of the oral vaccine candidate, M01ZH09, in susceptible volunteers by direct typhoid challenge. Methods and Findings We performed a randomised, double-blind, placebo-controlled trial in healthy adult participants at a single centre in Oxford (UK). Participants were allocated to receive one dose of double-blinded M01ZH09 or placebo or 3-doses of open-label Ty21a. Twenty-eight days after vaccination, participants were challenged with 104CFU S. Typhi Quailes strain. The efficacy of M01ZH09 compared with placebo (primary outcome) was assessed as the percentage of participants reaching pre-defined endpoints constituting typhoid diagnosis (fever and/or bacteraemia) during the 14 days after challenge. Ninety-nine participants were randomised to receive M01ZH09 (n = 33), placebo (n = 33) or 3-doses of Ty21a (n = 33). After challenge, typhoid was diagnosed in 18/31 (58.1% [95% CI 39.1 to 75.5]) M01ZH09, 20/30 (66.7% [47.2 to 87.2]) placebo, and 13/30 (43.3% [25.5 to 62.6]) Ty21a vaccine recipients. Vaccine efficacy (VE) for one dose of M01ZH09 was 13% [95% CI -29 to 41] and 35% [-5 to 60] for 3-doses of Ty21a. Retrospective multivariable analyses demonstrated that pre-existing anti-Vi antibody significantly reduced susceptibility to infection after challenge; a 1 log increase in anti-Vi IgG resulting in a 71% decrease in the hazard ratio of typhoid diagnosis ([95% CI 30 to 88%], p = 0.006) during the 14 day challenge period. Limitations to the study included the requirement to limit the challenge period prior to treatment to 2 weeks, the intensity of the study procedures and the high challenge dose used resulting in a stringent model. Conclusions Despite successfully demonstrating the use of a human challenge study to directly evaluate vaccine efficacy, a single-dose M01ZH09 failed to demonstrate significant protection after challenge with virulent Salmonella Typhi in this model. Anti-Vi antibody detected prior to vaccination played a major role in outcome after challenge

Marine and urban tropospheric chemistry

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

British Association of Dermatologists guidelines for biologic therapy for psoriasis 2017

The overall aim of the guideline is to provide evidence-based recommendations on the use of biologic therapies (adalimumab, etanercept, infliximab, ixekizumab, secukinumab and ustekinumab) in adults, children and young people for the treatment of psoriasis; consideration is given to the specific needs of people with psoriasis and psoriatic arthritis. Biologic therapies have now been in use for over 10 years, and with accrued patient-years exposure and clinical experience, many areas that were covered in previous versions of the guideline are now part of the Summary of Product Characteristics (SPC) and/or routine care so that specific recommendations are redundant (see Toolkit A: Summary of licensed indications and posology for biologic therapy, in Supporting information 2). Therefore, in this update we focus on areas where there has been a major change in the evidence base or clinical practice, where practice is very varied and/or where clear consensus or guidelines are lacking (see section 3.1 in Supporting information 1)

Families as Partners in Hospital Error and Adverse Event Surveillance

ImportanceMedical errors and adverse events (AEs) are common among hospitalized children. While clinician reports are the foundation of operational hospital safety surveillance and a key component of multifaceted research surveillance, patient and family reports are not routinely gathered. We hypothesized that a novel family-reporting mechanism would improve incident detection.ObjectiveTo compare error and AE rates (1) gathered systematically with vs without family reporting, (2) reported by families vs clinicians, and (3) reported by families vs hospital incident reports.Design, setting, and participantsWe conducted a prospective cohort study including the parents/caregivers of 989 hospitalized patients 17 years and younger (total 3902 patient-days) and their clinicians from December 2014 to July 2015 in 4 US pediatric centers. Clinician abstractors identified potential errors and AEs by reviewing medical records, hospital incident reports, and clinician reports as well as weekly and discharge Family Safety Interviews (FSIs). Two physicians reviewed and independently categorized all incidents, rating severity and preventability (agreement, 68%-90%; κ, 0.50-0.68). Discordant categorizations were reconciled. Rates were generated using Poisson regression estimated via generalized estimating equations to account for repeated measures on the same patient.Main outcomes and measuresError and AE rates.ResultsOverall, 746 parents/caregivers consented for the study. Of these, 717 completed FSIs. Their median (interquartile range) age was 32.5 (26-40) years; 380 (53.0%) were nonwhite, 566 (78.9%) were female, 603 (84.1%) were English speaking, and 380 (53.0%) had attended college. Of 717 parents/caregivers completing FSIs, 185 (25.8%) reported a total of 255 incidents, which were classified as 132 safety concerns (51.8%), 102 nonsafety-related quality concerns (40.0%), and 21 other concerns (8.2%). These included 22 preventable AEs (8.6%), 17 nonharmful medical errors (6.7%), and 11 nonpreventable AEs (4.3%) on the study unit. In total, 179 errors and 113 AEs were identified from all sources. Family reports included 8 otherwise unidentified AEs, including 7 preventable AEs. Error rates with family reporting (45.9 per 1000 patient-days) were 1.2-fold (95% CI, 1.1-1.2) higher than rates without family reporting (39.7 per 1000 patient-days). Adverse event rates with family reporting (28.7 per 1000 patient-days) were 1.1-fold (95% CI, 1.0-1.2; P = .006) higher than rates without (26.1 per 1000 patient-days). Families and clinicians reported similar rates of errors (10.0 vs 12.8 per 1000 patient-days; relative rate, 0.8; 95% CI, .5-1.2) and AEs (8.5 vs 6.2 per 1000 patient-days; relative rate, 1.4; 95% CI, 0.8-2.2). Family-reported error rates were 5.0-fold (95% CI, 1.9-13.0) higher and AE rates 2.9-fold (95% CI, 1.2-6.7) higher than hospital incident report rates.Conclusions and relevanceFamilies provide unique information about hospital safety and should be included in hospital safety surveillance in order to facilitate better design and assessment of interventions to improve safety