BRIEF RESEARCH REPORT article
Front. Epidemiol.
Sec. Epidemiology of Chronic Diseases and Prevention
Volume 5 - 2025 | doi: 10.3389/fepid.2025.1577333
Complex Interrelationships Among Respiratory Diseases and Chronic Multimorbidity: A Longitudinal Network Analysis and Implications for Future Viral Respiratory Pandemic Preparedness
Provisionally accepted
Daniel E Zoughbie1
Kyongsik Yun2*- 1University of California, Berkeley, Berkeley, California, United States
- 2California Institute of Technology, Pasadena, United States
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Respiratory diseases, such as asthma, chronic obstructive pulmonary disease (COPD), pneumonia, and acute respiratory failure, impose a substantial burden on global health, particularly when coupled with chronic systemic conditions. This study drew on over 82 million healthcare claims from the Comprehensive Health Care Information System (CHIS) between 2020 and 2024 to investigate the interrelationship between respiratory and systemic disorders. A disease co-occurrence matrix was constructed by counting overlapping ICD-10 codes in individual patient timelines, followed by Spearman's rank-order correlation analyses to identify significant associations, with false discovery rate corrections. The resulting undirected network revealed central roles for COPD (J44.9) and asthma (J45.909), which frequently co-occurred with metabolic (E11.9, E78.5), cardiovascular (I10), and mental health conditions (F32.9, F41.9). The longitudinal assessment indicated notable reductions in chronic disease management during 2022, consistent with the heightened pressures of the COVID-19 pandemic, although service utilization rebounded in 2023. These findings underscore the complexity of multimorbidity and highlight the importance of integrated strategies that address both respiratory and systemic conditions, ultimately strengthening healthcare systems against future viral respiratory pandemics.
Keywords: Network analysis, respiratory comorbidities, Healthcare claims data, ICD-10 co-occurrence, Chronic Disease
Received: 27 Feb 2025; Accepted: 26 May 2025.
Copyright: © 2025 Zoughbie and Yun. 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: Kyongsik Yun, California Institute of Technology, Pasadena, United States
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