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ORIGINAL RESEARCH article

Front. Public Health

Sec. Environmental Health and Exposome

This article is part of the Research TopicHuman Health Affected by Changing Ecological Environment in the Rapid UrbanizationView all 14 articles

The Health Cost of Urbanization: Identification and Ranking of Influencing Factors of Class A and B Infectious Diseases Based on Machine Learning

Provisionally accepted
  • 1Tsinghua University, Beijing, China
  • 2Renmin University of China, Beijing, Beijing Municipality, China
  • 3Southwestern University of Finance and Economics, Chengdu, Sichuan Province, China

The final, formatted version of the article will be published soon.

Aims: Rapid urbanization concentrates population and economic activity, potentially accelerating infectious disease transmission and pollution exposure, while improved infrastructure, healthcare, and protective behaviors can mitigate risks. Using the incidence of Class A/B infectious diseases as a sentinel of public health, this study identifies and prioritizes key determinants during 2008–2022 to inform evidence-based policymaking and address system gaps. Methods: Using provincial-level data from mainland China (2008–2022), this study systematically applied multiple machine learning methods, including Random Forest, Gradient Boosting Tree, and XGBoost, to evaluate the impacts of over ten indicators across economic, demographic, land use, and social dimensions on the Incidence Rate of Class A and B Infectious Diseases per 100,000 Population. Results: (1) Social factors account for 46.7%, constituting the most significant determinant, succeeded by land use, population, and economic dimensions. (2) Public transportation, urban water supply coverage, healthcare expenditure, and the spatial distribution of healthcare resources exert direct effects on residents' health outcomes and the accessibility of public health services. (3) Regarding land use, effective urban planning—reflected in indicators such as the green coverage rate of built-up areas and the per capita area of paved roads—plays a crucial role in promoting public health, accounting for 17.4% on average, whereas inadequate land-use management often precipitates health risks. (4) Population dynamics, encompassing demographic restructuring, agglomeration, and education levels, simultaneously generate advantages and challenges. (5) Economic factors, including industrial pollution control, industrial upgrading (ratio of tertiary to secondary industry value-added), international trade, and income levels, manifest dual effects: advancing health improvements while engendering environmental degradation and cross-border health risks. (6) The health implications of rapid urbanization display regional disparity: social factors(60.2%) predominate in eastern China, economic factors(63.2%) in central China, and land use factors(54.2%) in western regions. Conclusion: During rapid urbanization, governments must prioritize timely enhancements to public health services, rational land use planning, and protection of vulnerable populations. Emphasizing the quality of economic development and fostering synergies between industrial upgrading and environmental governance will improve public health outcomes.

Keywords: Public health1, infectious diseases2, urbanization3, machine learning4, influencing factors5

Received: 23 Apr 2025; Accepted: 17 Nov 2025.

Copyright: © 2025 Wang, Zhu and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Boyi Zhu, annyzby@163.com

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