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Undocumented migrants often experience how their spatial vulnerability continues across their life trajectories through different forms of displacements in the form of forced migration, being at risk of deportation and being victims of gentrification or policies that make it difficult to find a stable housing situation. Drawing on ethnographic fieldwork in Sweden and the UK, the paper shows how weak the position of undocumented migrants is on the housing market through recently established policies in the UK which criminalizes the letting of housing to undocumented migrants and the practice of sharing address information between the social services and the border police in Sweden. This intervention argues that these policies that construct spatial vulnerabilities locally are connected to national and transnational policies of displacement globally and suggest that "displaceability", the potential of being displaced, is a strategy for governing vulnerable groups at every scale where governing takes place. Consequently, this intervention suggests that displaceability can help us capture the universal, interconnected experience of spatial vulnerability shared by many differently positioned groups in the world who are susceptible to forced mobility or removal. [ABSTRACT FROM AUTHOR]

Analyzing the COVID-19 pandemic is a critical factor in developing effective policies to deal with similar challenges in the future. However, many parameters (e.g., the actual number of infected people, the effectiveness of vaccination) are still subject to considerable debate because they are unobservable. To model a pandemic and estimate unobserved parameters, researchers use compartmental models. Most often, in such models, the transition rates are considered as constants, which allows simulating only one epidemiological wave. However, multiple waves have been reported for COVID-19 caused by different strains of the virus. This paper presents an approach based on the reconstruction of real distributions of transition rates using genetic algorithms, which makes it possible to create a model that describes several pandemic peaks. The model is fitted on registered COVID-19 cases in four countries with different pandemic control strategies (Germany, Sweden, UK, and US). Mean absolute percentage error (MAPE) was chosen as the objective function, the MAPE values of 2.168%, 2.096%, 1.208% and 1.703% were achieved for the listed countries, respectively. Simulation results are consistent with the empirical statistics of medical studies, which confirms the quality of the model. In addition to observables such as registered infected, the output of the model contains variables that cannot be measured directly. Among them are the proportion of the population protected by vaccines, the size of the exposed compartment, and the number of unregistered cases of COVID-19. According to the results, at the peak of the pandemic, between 14% (Sweden) and 25% (the UK) of the population were infected. At the same time, the number of unregistered cases exceeds the number of registered cases by 17 and 3.4 times, respectively. The average duration of the vaccine induced immune period is shorter than claimed by vaccine manufacturers, and the effectiveness of vaccination has declined sharply since the appearance of the Delta and Omicron strains. However, on average, vaccination reduces the risk of infection by about 65–70%. [ABSTRACT FROM AUTHOR]

Addmaster has been acquired by Sweden-based company Polygiene, making it a dominant player in the supply of antimicrobial solutions for both soft and hard surfaces. The acquisition will allow both companies to offer the market a comprehensive solution of antimicrobial functions, with Polygiene offering textiles while UK firm Addmaster's Biomaster brand offers solutions for polymers, paints, coatings and paper. [ABSTRACT FROM AUTHOR]

The methods used to define functional regions for public statistics and policy purposes need to establish several parameter values. This is typically achieved using expert knowledge based on qualitative judgements and lengthy consultations with local stakeholders. We propose to support this process by using an optimization algorithm to calibrate any regionalization method by identifying the parameter values that produce the best regionalization for a given quantitative indicator. The approach is exemplified by using a grid search and a genetic algorithm to configure the official methods employed in the UK and Sweden for the definition of their respective official concepts of local labour markets. [ABSTRACT FROM AUTHOR]