Search arXivSearch

arXiv · 2601.08754

Evolving spatiotemporal patterns and urban scaling of deaths from external causes

Abstract

Urban scaling theory posits that urban indicators follow power-law relations with population, yet the evolution of these patterns - and the role of regional differences in settings marked by social inequalities and unplanned urbanization - remains poorly understood. Here, we analyze nearly three decades of mortality data from Brazilian cities to investigate the scaling of external causes of death: homicides, suicides, and accidents. Using a hierarchical Bayesian framework and spatial correlation analysis, we find that these mortality indicators exhibit distinct, regionally heterogeneous scaling trajectories. Homicide mortality has significantly attenuated its typical superlinear scaling with increased spatial clustering, suggesting a redistribution of violence to smaller cities and intensified intercity interactions, possibly linked to the consolidation of organized crime. Suicide mortality, usually sublinear, has trended upward, implying a weakening of urban agglomerations' protective effect. Accident mortality remains superlinear, with transport fatalities scaling nearly proportionally, and non-transport accidents becoming superlinear. The scaling changes for suicides and accidents coincide with less correlated and stable spatial patterns, suggesting that the underlying processes predominantly operate within city boundaries. Finally, while scaling exponents have evolved more homogeneously across Brazilian states, scale-adjusted mortality remains highly heterogeneous, indicating that fundamental processes govern scaling laws, whereas state-specific factors drive scale-adjusted metrics.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Cesar I. N. Sampaio Filho, Humberto A. Carmona, Antonio S. Lima Neto, Monica V. Prates, Haroldo V. Ribeiro, Marcia C. Castro, Jose S. Andrade Jr. 2026-01-13. Evolving spatiotemporal patterns and urban scaling of deaths from external causes. https://doi.org/10.1038/s41598-025-31970-7

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Self-Reference in Large Language Models: The Introspection Threshold for Recursive Self-Improvement

The pursuit of self-evolving AI raises a critical question: when is autonomous self-improvement sustainable rather than degenerative? Drawing an analogy to von Neumann's complexity threshold for self-reproducing automata, we argue that sustainable recursive self-improvement in Large Language Models (LLMs) requires a functional analogue: introspection -- the system's capacity to simulate its own operations and target modifications. Grounded in Kleene's Second Recursion Theorem, we demonstrate the theoretical existence of such introspective programs. However, an empirical review reveals that while current LLMs exhibit quasi-introspection (e.g., partial metacognition), they fall short of true introspection due to structural bottlenecks: a lack of complete self-access, the feedforward nature of the Transformer, and computational class constraints that prevent fixed-point iteration. We conclude by outlining architectural paths to cross this complexity threshold and discussing the associated safety implications.

physics.soc-ph

Multilayer Analysis of the Global Trade Network

Global trade is more than a single network of aggregate flows. Beneath the observable exchange of products among economies lies a complex multilayer structure, formed by thousands of product-specific trade relationships that differ in their similarity, interdependence, and temporal evolution. Using the CEPII's BACI database, which records bilateral product-level trade flows between economies, we represent the global trade network from 1995 to 2024 as a temporal multilayer network, with economies as nodes and directed weighted trade flows as edges. To investigate product-level organisation and cross-layer similarity, temporal structural change, and the structural role of individual economies, we introduce a random-walk-based similarity measure that provides a unified framework for comparing weighted and directed trade layers. Our results show that the global trade network remains relatively stable over short periods but undergoes gradual structural change over longer timescales. We also find that similarity-based product communities only partially align with the official product taxonomy, indicating that products assigned to the same official category do not necessarily exhibit similar trade-network structures. Finally, we show that an economy's structural influence is not always determined by its trade volume. These results highlight the value of multilayer network analysis for revealing patterns in global trade that remain hidden at the aggregate level.

physics.soc-ph

Detectability limits of scaling laws

Power law scaling relations between size and output are central to quantitative theories of cities, organisms, and other complex systems. Competing theories predict scaling exponents that differ by small fractions, but there is no existing theory for verifying whether a given dataset can even distinguish exponents at the required resolution to address such discrepancies. Here we derive a resolution limit for scaling exponents, giving the smallest exponent difference that any method of analysis can detect. We find that the Hurst exponents governing the evolution of systems' sizes and deviations from the scaling law determine how long a record of growing systems must be before it can separate competing scaling theories. Empirical results suggest that many available data panels are insufficient for reliable scaling model selection.

physics.soc-ph