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Christine Hedde-von Westernhagen

Publications and source records attributed to Christine Hedde-von Westernhagen.

3 recordsLinked to original sources

Integrating social capital with urban infrastructure networks for more resilient cities

More than half of the world's population now lives in urban environments, which concentrate services and infrastructure to satisfy the material needs of a growing number of inhabitants. The interdependencies between physical infrastructure systems are required for cities to function efficiently, but simultaneously expose cities to new hazards. Failures that emerge from one infrastructure system and cascade through these interdependencies are becoming larger and more frequent due to climate change and growing urban environments. Because of the uneven distribution of resources and basic services, cascade failures often exacerbate pre-existing socioeconomic inequalities. Human communities rely on both social capital and infrastructure services to prepare for, manage, and recover from these challenging scenarios, but the overlap between social and physical infrastructure creates unpredictable feedback dynamics. While prior research has focused on either social capital or physical infrastructure in urban disaster management, an integrative view of these two perspectives is seldom explored. In this paper, the feedback mechanisms between the physical and social layers of different urban designs are identified and analyzed to optimize relief response. Methodologically, we identify cities with high accessibility that have undergone disasters. From these cities, we measure their physical and social resilience indicators before and after disaster as a means to evaluate the impact of accessibility on disaster relief and preparedness. We will supplement this empirical analysis with a simulation that captures a cascade failure/disaster through a multilayer infrastructure and social network model.

physics.soc-ph↗

The Impact of School and Family Networks on COVID-19 Infections Among Dutch Students: A Study Using Population-Level Registry Data

Understanding the impact of different social interactions is key to improving epidemic models. Here, we use extensive registry data -- including PCR test results and population-level networks -- to investigate the impact of school, family, and other social contacts on SARS-CoV-2 transmission in the Netherlands (June 2020--October 2021). We isolate and compare different contexts of potential SARS-CoV-2 transmission by matching pairs of students based on their attendance at the same or different primary school (in 2020) and secondary school (in 2021) and their geographic proximity. We then calculated the probability of temporally associated infections -- i.e. the probability of both students testing positive within a 14-day period. Our results highlight the relative importance of household and family transmission in the spread of SARS-CoV-2 compared to school settings. The probability of temporally associated infections for siblings and parent-child pairs living in the same household was 22.6--23.2\%, and 4.7--7.9\% for family members living in different household. In contrast, the probability of temporally associated infections was 0.52\% for pairs of students living nearby but not attending the same primary or secondary school, 0.66\% for pairs attending different secondary schools but having attended the same primary school, and 1.65\% for pairs attending the same secondary school. Finally, we used multilevel regression analyses to examine how individual, school, and geographic factors contribute to transmission risk. We found that the largest differences in transmission probabilities were due to unobserved individual (60\%) and school-level (35\%) factors. Only a small proportion (3\%) could be attributed to geographic proximity of students or to school size, denomination, or the median income of the school area.

cs.SI↗

Uncovering the Size of the Illegal Corporate Service Provider Industry in the Netherlands: a Network Approach

Economic crimes such as money laundering, terrorism financing, tax evasion or corruption almost invariably involve the use of a corporate entity. Such entities are regularly incorporated and managed by corporate services providers (CSPs). Given this potential for enabling economic crime, the CSP industry in the Netherlands is heavily regulated and CSPs require a license to operate. Operating without a licence is illegal. In this paper, we estimate the size of the illegal CSP sector in the Netherlands. For this, we develop a classification method to detect potentially illegal CSPs based on their similarity with licensed CSPs. Similarity is computed based on their position within the network of directors, companies and addresses, and the characteristics of such entities. We manually annotate a sample of the potential illegal CSPs and estimate that illegal CSPs constitute 31--51\% of the total number of CSPs and manage 19--27\% of all companies managed by CSPs. Our analysis provides a tool to regulators to improve detection and prevention of economic crime, and can be extended to the estimation of other illegal activities.

cs.SI↗