Modelling the economic impact and ripple effects of disease outbreaks

The Coronavirus Disease 2019 (COVID-19) outbreak has had alarming effects on human lives and the economies of affected countries. With the world’s manufacturing hubs experiencing a period of extended factory closures, the economic impact transcends territorial borders via global supply chains. This paper provides a roadmap on how to evaluate the vulnerability that cascades through the supply chain due to a disease outbreak at the firm level, national level, and global scale. The final extent of losses is not yet known, but the development of economic models combined with epidemiological models and network analysis techniques can yield more realistic estimates to select appropriate strategies in a timely manner. © 2020, Springer Nature Singapore Pte Ltd

Rovdjursinventering Järv 2015 : Rovdjursinventering Järv 2015. Järvstammen i Sverige – något minskande

Den senaste populationsberäkningen 2015 visar att järvstammen minskar något. Beräkningen visar att det finns omkring 921 (793–1 142) järvar i Skandinavien varav 585 (481–758) i Sverige. Inventeringarna ger kunskap om rovdjursstammarnas storlek, var de lever och hur stammarna utvecklas över tiden. Bra underlag är nödvändiga för att det ska vara möjligt att bedriva en ansvarsfull och långsiktigt hållbar förvaltning av våra stora rovdjur.

Selection of vaccine strains for serotype O foot-and-mouth disease viruses (2007–2012) circulating in Southeast Asia, East Asia and Far East

Foot-and-mouth disease (FMD) is endemic in Southeast Asia (SEA) and East Asia with circulation of multiple serotypes and multiple genotypes within each serotype of the virus. Although countries like Japan and South Korea in the Far East were free of FMD, in 2010 FMD serotype O (O/Mya-98) outbreaks were recorded and since then South Korea has experienced several FMD outbreaks despite regular vaccination. In this study a total of 85 serotype O FMD viruses (FMDV) isolated from 2007 to 2012 from SEA, East Asia and Far East were characterized by virus neutralisation tests using antisera to four existing (O/HKN/6/83, O/IND/R2/75, O/SKR/2010 and O/PanAsia-2) and one putative (O/MYA/2009) vaccine strains, and by full capsid sequencing. Serological studies revealed broad cross-reactivity with the vaccine strains; O/PanAsia-2 exhibited a good match with 95.3%, O/HKN/6/83 with 91.8%, O/IND/R2/75 with 80%, and the putative strain O/MYA/2009 with 89.4% isolates employed in this study. Similarly O/PanAsia-2 and O/IND/R2/75 vaccines showed a good match with all eight viruses belonging to O-Ind-2001d sublineage whereas the vaccines of O/Mya-98 lineage, O/MYA/2009 and O/SKR/2010 exhibited the lowest match indicating their unsuitability to protect infections from O-Ind-2001d viruses. A Bayesian analysis of the capsid sequence data indicated these circulating viruses (n = 85) to be of either SEA or Middle East-South Asian (ME-SA) topotype. The ME-SA topotype viruses were mainly detected in Lao PDR, Vietnam, Myanmar and Thailand reflecting the trade links with the Indian subcontinent, and also within the SEA countries. Implications of these results in the context of FMD control in SEA and East Asian countries are discussed

Optimization models for financing innovations in green energy technologies

Commercialization of emerging green technologies is essential to improve the sustainability of industrial processes. However, there are risks inherent in funding the development of new technologies that act as a significant barrier to their commercialization. Mathematical models can provide much-needed decision support to allow optimal allocation of funds, while managing the implications of techno-economic risk. The Technology Readiness Level (TRL) scale is a well-established figure of merit approach for quantifying the maturity of stand-alone technologies, while the more recently developed System Readiness Level (SRL) scale is applicable to technology networks with interdependent components. These technology maturity scales are intended mainly to be used for the passive assessment of a given state of technology, but may be incorporated within an optimization model to aid in innovation planning. In this work, two mixed integer linear programming (MILP) models are proposed to optimize strategies for funding innovation. The first model is a bi-objective MILP for optimizing the allocation of funds to a portfolio of independent innovation projects. The model is based on source-sink formulation and uses information on TRL and return on investment (ROI) to determine the best allocation of funds. The second model is a robust MILP that optimizes the allocation of limited project funds in order to maximize the SRL of a system of emerging technologies. This approach accounts for Integration Readiness Level (IRL) among mutually interdependent technologies. Both models are demonstrated with illustrative case studies on biorefinery technologies in order to demonstrate their capabilities. © 2019 Elsevier Lt

A source-sink model for optimum allocation of technology innovation portfolios

Commercialization of emerging green technologies is essential to improving the sustainability of industrial processes. In practice, it is necessary to match funding sources (e.g., research and development grants, venture capital, etc.) with projects at different maturity levels. Because of inherent uncertainties that characterize and evaluate new technologies, the decision-making process is typically fraught with risk, which can be mitigated with the use of systematic decision support methods. In this work, an optimization model is developed for optimal allocation of funds to a portfolio of innovation projects based on the available funds and different levels of technology maturity. The model is based on source-sink formulation typically used in process integration applications. Each source is a fund of known size and can only be used for projects of a specified minimum return on investment (ROI) and minimum technological readiness level (TRL); each project has an estimated cost, TRL and an ROI range across techno-economic risk scenarios. The model is formulated as a bi-objective mixed integer linear programming (MILP) model, using the conservative and optimistic total portfolio ROI as dual objective functions. The methodology is demonstrated using a pedagogical case study. Copyright © 2018, AIDIC Servizi S.r.l

Unified pinch approach for targeting of carbon capture and storage (CCS) systems with multiple time periods and regions

Carbon capture and storage (CCS) is a key technology for the mitigation of industrial carbon dioxide (CO2) emissions. It involves the reduction of emissions from large industrial facilities (i.e., sources) by capturing the CO2 from the exhaust gases and subsequently storing it in appropriate geological storage sites (i.e., sinks) such as depleted oil and/or gas reservoirs, saline aquifers, coal seams and other similar formations. In practice, these sites may not be readily available for storage at the same time or before the sources are operating, which gives rise to a temporal aspect in the planning problem. At the same time, sources and sinks may need to be clustered geographically to minimize the need to transport CO2 over long distances. This work presents an improved pinch analysis based methodology by simultaneously considering injectivity constraint of every sink as well as time of availability of various sources and sinks. Three illustrative case studies are used to demonstrate the applicability of the proposed methodology. The first two case studies illustrate graphical and algebraic variants, while the third case studies shows an extension that involves two distinct geographical regions. (C) 2013 Elsevier Ltd. All rights reserved