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To investigate population heterogeneity and interaction mechanisms in cross-population transmission dynamics, we develop a community-based SIR (susceptible-infectious-removed) compartmental model applicable to multiple populations. This model is grounded in a heterogeneous network that incorporates both intra-population structural differences and inter-population coupling. Considering the structural characteristics and interactions between the service-providing and the served populations, we introduce multidimensional parameters, including contact preferences, different transmission rates, and recovery rates. The basic reproduction number is obtained analytically through the next-generation matrix method, with the stability of disease-free and endemic equilibria rigorously proved. Agent-based simulations and multi-scenario experiments are conducted to examine how network structure, coupling strength, and population migration mechanisms shape transmission dynamics. Finally, early-stage COVID-19 epidemic data from Hubei Province are used for parameter fitting, and the fitted parameters are employed to validate the Monte Carlo and Mean-field models, demonstrating the high accuracy of the model. This study shows that the coupling of the service population significantly accelerates epidemic transmission. Furthermore, population migration is identified as a transmission accelerator that exhibits a non-monotonic impact on the steady-state infection scale. However, under resource-constrained conditions, prioritizing the improvement of the recovery rate of small-scale service populations can indirectly reduce the final epidemic size in large-scale community populations. This study offers quantitative guidance for designing targeted interventions under multidimensional heterogeneity.<\/jats:p>","DOI":"10.1063\/5.0310925","type":"journal-article","created":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T13:07:48Z","timestamp":1773061668000},"update-policy":"https:\/\/doi.org\/10.1063\/aip-crossmark-policy-page","source":"Crossref","is-referenced-by-count":1,"title":["Dynamics of infectious disease transmission in heterogeneous networks considering population interaction mechanism"],"prefix":"10.1063","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-6195-6572","authenticated-orcid":false,"given":"Junlong","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Transportation Engineering, Chang\u2019an University 1 , Xi\u2019an 710064,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2693-4210","authenticated-orcid":false,"given":"Ziyang","family":"Jin","sequence":"additional","affiliation":[{"name":"School of Transportation Engineering, Chang\u2019an University 1 , Xi\u2019an 710064,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0640-1206","authenticated-orcid":false,"given":"Xueyu","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Northwestern Polytechnical University 2 , Xi\u2019an 710072,","place":["China"]},{"name":"Ministry of Industry and Information Technology Key Laboratory of Industrial Engineering and Intelligent Manufacturing, Northwestern Polytechnical University 3 , Xi\u2019an 710072,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiyong","family":"Yin","sequence":"additional","affiliation":[{"name":"School of Transportation Engineering, Chang\u2019an University 1 , Xi\u2019an 710064,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5122-865X","authenticated-orcid":false,"given":"Ning","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Transportation Engineering, Chang\u2019an University 1 , Xi\u2019an 710064,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"317","published-online":{"date-parts":[[2026,3,9]]},"reference":[{"issue":"9","key":"2026030909074107400_c1","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1038\/s41579-022-00769-y","article-title":"Black death unravelled","volume":"20","year":"2022","journal-title":"Nat. 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