arXiv subjects

Elma Dervic

Publications and source records attributed to Elma Dervic.

7 recordsLinked to original sources

arXiv2026

Comorbidity Network Analysis Reveals Diagnostic Disparities Between Austrian and Non-Austrian Inpatients: A Population-Wide Cohort Study

International migrants face well-documented barriers to healthcare access, yet the extent to which these barriers shape patterns of disease co-occurrence remains poorly understood. Drawing on a nationwide dataset of approximately 13 million hospital admissions from around 4 million individuals in Austria (2015-2019), we constructed and compared comorbidity networks between Austrian nationals and non-Austrian migrants, matched 1:1 by age, sex, and time of first hospital admission (272,779 per group). Following matching, metabolic and cardiovascular diagnoses, including type 2 diabetes and myocardial infarction, were more common among non-Austrians, while depression was more common among Austrians. Comorbidity network analysis showed that among all disease pairs that differed significantly between groups, 70% showed stronger co-occurrence in Austrian patients and 30% in non-Austrian patients. Distinct sex-specific patterns appeared: Austrian males showed stronger associations between alcohol use disorder and mental health diagnoses, whereas non-Austrian males more frequently presented with acute somatic conditions. Among non-Austrian women, a pronounced cluster of recurrent depression, somatoform disorders, and dorsalgia was observed. We interpret the disproportionately fewer comorbidity links observed in non-Austrians not as evidence of lower disease burden, but as a likely reflection of structural access barriers, including language differences, cultural factors, and crisis-oriented admission patterns, that prevent comprehensive diagnostic assessment, though a contribution from the healthy migrant effect cannot be excluded. These findings stress the need for culturally aware care strategies and earlier identification of high-risk multimorbidity profiles in migrant populations.

physics.med-ph↗

arXiv2026

Reconstructing temporal multi-relational firm networks at scale using large language models. The case of the semiconductor industry

The semiconductor industry is foundational to modern technology, yet its complex global multi-relational firm network remains poorly understood, posing challenges to scientists, firms, and policymakers. Traditional analysis relies on proprietary databases that are often expensive, incomplete, and slowly updated, limiting their ability to capture rapidly evolving dependencies. Here, we demonstrate that a novel, generalizable methodology combining Large Language Models (LLMs) with open web data can reconstruct this network and its structural dynamics at scale. We identify and classify supply-chain, partnership, and ownership links from 170 million semiconductor firm webpages, yielding a temporal network of over 1,300 linked firms. We validate link-extraction quality (Precision: 0.884; F1-score: 0.784), network overlap and complementarity with a proprietary database, and consistency with aggregate economic data. Our network reveals a temporary 9% decline in edges during the 2022 chip shortage, rapid increases in the centrality of AI supply-chain bottleneck firms such as NVIDIA, and geographic realignment of interfirm relations amid geopolitical turbulence. This generalizable framework overcomes barriers to transparency and provides essential, up-to-date maps for assessing resilience and informing policy across strategically relevant sectors.

physics.soc-ph↗

arXiv2026

Who burdens the welfare state? Migration and ageing in housing, education, and healthcare demand

Political discourse attributes the pressure on European welfare systems to foreign nationals. Yet projections of service demand rarely disaggregate service demand by citizenship status. We develop a structural demographic model and project healthcare, education, and housing demand in Austria through 2050, disaggregated by citizenship status and regions across migration scenarios. We find that migration, ageing, and fertility shape each sector differently. In healthcare, the ageing of Austrian nationals contributes 4.7 times more to demand growth than immigration, with the most acute pressures in rural, low-migration regions. In housing, migration accounts for the entire net growth in demand, concentrated in metropolitan hubs. In education, aggregate demand contracts regardless of migration assumptions, whereas future needs are driven more by the births of foreigners in Austria than by new arrivals. Foreign nationals consume services in proportion to their demographic weight, with deviations explained by age structure rather than over-utilisation. These results show that the drivers of service demand are sector-specific: migration restrictions could ease housing pressure, but would not address ageing-driven healthcare demand and may accelerate contraction in the education system.

physics.soc-ph↗

arXiv2025

Refugees' path to legal stability is long and systematically unequal

Legal systems shape not only the recognition of migrants and refugees but also the pace and stability of their integration. Refugees often shift between multiple legal classifications, a process we refer to as the "legal journey". This journey is frequently prolonged and uncertain. Using a network-based approach, we analyze legal transitions for over 350,000 migrants in Austria (2022 to 2024). Refugees face highly unequal pathways to stability, ranging from two months for Ukrainians to nine months for Syrians and 20 months for Afghans. Women, especially from these regions, are more likely to gain protection; Afghan men wait up to 30 months on average. We also find that those who cross the border without going through official border controls face higher exit rates and lower chances of securing stable status. We show that legal integration is not a uniform process, but one structured by institutional design, procedural entry points, and unequal timelines.

physics.soc-ph↗

arXiv2023

The diaspora model for human migration

Migration's impact spans various social dimensions, including demography, sustainability, politics, economy and gender disparities. Yet, the decision-making process behind migrants choosing their destination remains elusive. Existing models primarily rely on population size and travel distance to explain flow fluctuations, overlooking significant population heterogeneities. Paradoxically, migrants often travel long distances and to smaller destinations if their diaspora is present in those locations. To address this gap, we propose the diaspora model of migration, incorporating intensity (the number of people moving to a country) and assortativity (the destination within the country). Our model considers only the existing diaspora sizes in the destination country, influencing the probability of migrants selecting a specific residence. Despite its simplicity, our model accurately reproduces the observed stable flow and distribution of migration in Austria (postal code level) and US metropolitan areas, yielding precise estimates of migrant inflow at various geographic scales. Given the increase in international migrations due to recent natural and societal crises, this study enlightens our understanding of migration flow heterogeneities, helping design more inclusive, integrated cities.

physics.soc-ph↗

arXiv2022

Stress-testing the Resilience of the Austrian Healthcare System Using Agent-Based Simulation

Patients do not access physicians at random but rather via naturally emerging networks of patient flows between them. As retirements, mass quarantines and absence due to sickness during pandemics, or other shocks thin out these networks, the system might be pushed closer to a tipping point where it loses its ability to deliver care to the population. Here we propose a data-driven framework to quantify the regional resilience to such shocks of primary and secondary care in Austria via an agent-based model. For each region and medical specialty we construct detailed patient-sharing networks from administrative data and stress-test these networks by removing increasing numbers of physicians from the system. This allows us to measure regional resilience indicators describing how many physicians can be removed from a certain area before individual patients won't be treated anymore. We find that such tipping points do indeed exist and that regions and medical specialties differ substantially in their resilience. These systemic differences can be related to indicators for individual physicians by quantifying how much their hypothetical removal would stress the system (risk score) or how much of the stress from the removal of other physicians they would be able to absorb (benefit score). Our stress-testing framework could enable health authorities to rapidly identify bottlenecks in access to care as well as to inspect these naturally emerging physician networks and how potential absences would impact them.

physics.soc-ph↗

arXiv2021

Agent-based simulations for protecting nursing homes with prevention and vaccination strategies

Due to its high lethality amongst the elderly, the safety of nursing homes has been of central importance during the COVID-19 pandemic. With test procedures becoming available at scale, such as antigen or RT-LAMP tests, and increasing availability of vaccinations, nursing homes might be able to safely relax prohibitory measures while controlling the spread of infections (meaning an average of one or less secondary infections per index case). Here, we develop a detailed agent-based epidemiological model for the spread of SARS-CoV-2 in nursing homes to identify optimal prevention strategies. The model is microscopically calibrated to high-resolution data from nursing homes in Austria, including detailed social contact networks and information on past outbreaks. We find that the effectiveness of mitigation testing depends critically on the timespan between test and test result, the detection threshold of the viral load for the test to give a positive result, and the screening frequencies of residents and employees. Under realistic conditions and in absence of an effective vaccine, we find that preventive screening of employees only might be sufficient to control outbreaks in nursing homes, provided that turnover times and detection thresholds of the tests are low enough. If vaccines that are moderately effective against infection and transmission are available, control is achieved if 80% or more of the inhabitants are vaccinated, even if no preventive testing is in place and residents are allowed to have visitors. Since these results strongly depend on vaccine efficacy against infection, retention of testing infrastructures, regular voluntary screening and sequencing of virus genomes is advised to enable early identification of new variants of concern.

physics.soc-ph↗