Loureiro Nathalia A, Neto Camilo R, Sutton Jack, Perc Matjaž, Ribeiro Haroldo V
Complex Systems Modeling Program, School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, Brazil.
College of Science and Engineering, University of Derby, Markeaton Street, DE22 3AW, Derby, United Kingdom.
Sci Rep. 2025 Jan 2;15(1):498. doi: 10.1038/s41598-024-84252-z.
Inter-city interactions are critical for the transmission of infectious diseases, yet their effects on the scaling of disease cases remain largely underexplored. Here, we use the commuting network as a proxy for inter-city interactions, integrating it with a general scaling framework to describe the incidence of seven infectious diseases across Brazilian cities as a function of population size and the number of commuters. Our models significantly outperform traditional urban scaling approaches, revealing that the relationship between disease cases and a combination of population and commuters varies across diseases and is influenced by both factors. Although most cities exhibit a less-than-proportional increase in disease cases with changes in population and commuters, more-than-proportional responses are also observed across all diseases. Notably, in some small and isolated cities, proportional rises in population and commuters correlate with a reduction in disease cases. These findings suggest that such towns may experience improved health outcomes and socioeconomic conditions as they grow and become more connected. However, as growth and connectivity continue, these gains diminish, eventually giving way to challenges typical of larger urban areas - such as socioeconomic inequality and overcrowding - that facilitate the spread of infectious diseases. Our study underscores the interconnected roles of population size and commuter dynamics in disease incidence while highlighting that changes in population size exert a greater influence on disease cases than variations in the number of commuters.
城市间的相互作用对传染病传播至关重要，但其对疾病病例规模的影响在很大程度上仍未得到充分探索。在此，我们以通勤网络作为城市间相互作用的代理指标，将其与一个通用的规模框架相结合，以描述巴西各城市七种传染病的发病率与人口规模和通勤者数量之间的函数关系。我们的模型显著优于传统的城市规模分析方法，揭示了疾病病例与人口和通勤者组合之间的关系因疾病而异，且受到这两个因素的影响。尽管大多数城市的疾病病例随人口和通勤者的变化呈现出低于比例的增长，但在所有疾病中也都观察到了高于比例的反应。值得注意的是，在一些小型孤立城市，人口和通勤者的成比例增长与疾病病例的减少相关。这些发现表明，随着这些城镇的发展和联系日益紧密，其健康状况和社会经济条件可能会得到改善。然而，随着增长和连通性的持续，这些益处会逐渐减少，最终让位于大城市典型的挑战——如社会经济不平等和过度拥挤——这些因素会促进传染病的传播。我们的研究强调了人口规模和通勤者动态在疾病发病率中的相互关联作用，同时突出了人口规模变化对疾病病例的影响大于通勤者数量的变化。
