{"title":"大流行防备和通过气溶胶传播的空气传播疾病新模式的发展","authors":"Aleck H. Alexopoulos","doi":"10.1016/j.biosystems.2025.105532","DOIUrl":null,"url":null,"abstract":"<div><div>Currently most computational models for airborne disease transmission in epidemics and pandemics are based on the Susceptible-Infected-Recovered, SIR, family of models. Although these models are suitable for describing diseases transmitting by direct contact, e.g., face-to-face coughing, they are less suitable for diseases transmitted by aerosols. In this study a general mathematical formulation for aerosol and direct transmission of an airborne infective agent is described. The formulation utilizes a multivariate population balance equation, PBE, framework that considers not just infected individuals but also infected indoor spaces. These PBEs are significantly more complex than SIR models and require simplifications to reduced models suitable for computational simulations. In this study two levels of reduced models are presented including univariate PBEs and compartment population level descriptions. It is shown how the SIR model can be extracted but also how the simplest possible aerosol SIR model, A-SIR, can be determined. The SIR and A-SIR models are compared for different scenarios and are shown to present significantly different dynamics and outcomes. Finally, the PBE approach appears to avoid many of the shortcomings of the SIR models noted in the literature and enables integration with other modeling approaches.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"255 ","pages":"Article 105532"},"PeriodicalIF":1.9000,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pandemic preparedness and new model developments for airborne diseases transmitting via aerosols\",\"authors\":\"Aleck H. Alexopoulos\",\"doi\":\"10.1016/j.biosystems.2025.105532\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Currently most computational models for airborne disease transmission in epidemics and pandemics are based on the Susceptible-Infected-Recovered, SIR, family of models. Although these models are suitable for describing diseases transmitting by direct contact, e.g., face-to-face coughing, they are less suitable for diseases transmitted by aerosols. In this study a general mathematical formulation for aerosol and direct transmission of an airborne infective agent is described. The formulation utilizes a multivariate population balance equation, PBE, framework that considers not just infected individuals but also infected indoor spaces. These PBEs are significantly more complex than SIR models and require simplifications to reduced models suitable for computational simulations. In this study two levels of reduced models are presented including univariate PBEs and compartment population level descriptions. It is shown how the SIR model can be extracted but also how the simplest possible aerosol SIR model, A-SIR, can be determined. The SIR and A-SIR models are compared for different scenarios and are shown to present significantly different dynamics and outcomes. Finally, the PBE approach appears to avoid many of the shortcomings of the SIR models noted in the literature and enables integration with other modeling approaches.</div></div>\",\"PeriodicalId\":50730,\"journal\":{\"name\":\"Biosystems\",\"volume\":\"255 \",\"pages\":\"Article 105532\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2025-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biosystems\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S030326472500142X\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosystems","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S030326472500142X","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
Pandemic preparedness and new model developments for airborne diseases transmitting via aerosols
Currently most computational models for airborne disease transmission in epidemics and pandemics are based on the Susceptible-Infected-Recovered, SIR, family of models. Although these models are suitable for describing diseases transmitting by direct contact, e.g., face-to-face coughing, they are less suitable for diseases transmitted by aerosols. In this study a general mathematical formulation for aerosol and direct transmission of an airborne infective agent is described. The formulation utilizes a multivariate population balance equation, PBE, framework that considers not just infected individuals but also infected indoor spaces. These PBEs are significantly more complex than SIR models and require simplifications to reduced models suitable for computational simulations. In this study two levels of reduced models are presented including univariate PBEs and compartment population level descriptions. It is shown how the SIR model can be extracted but also how the simplest possible aerosol SIR model, A-SIR, can be determined. The SIR and A-SIR models are compared for different scenarios and are shown to present significantly different dynamics and outcomes. Finally, the PBE approach appears to avoid many of the shortcomings of the SIR models noted in the literature and enables integration with other modeling approaches.
期刊介绍:
BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.