{"title":"基于个体因素的西安市新冠肺炎疫情影响及病原疾病风险模拟模型研究","authors":"Wen Dong, Henan Yao, Wei-Na Wang","doi":"10.3389/fcimb.2025.1547601","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Since the first discovery and reporting of the COVID - 19 pandemic towards the end of 2019, the virus has rapidly propagated across the world. This has led to a remarkable spike in the number of infections. Even now, doubt lingers over whether it has completely disappeared. Moreover, the issue of restoring normal life while ensuring safety continues to be a crucial challenge that public health agencies and people globally are eager to tackle.</p><p><strong>Methods: </strong>To thoroughly understand the epidemic's outbreak and transmission traits and formulate timely prevention measures to fully safeguard human lives and property, this paper presents an agent - based model incorporating individual - level factors.</p><p><strong>Results: </strong>The model designates Xi'an-where a characteristic disease outbreak occurred-as the research area. The simulation results demonstrate substantial consistency with official records, effectively validating the model's applicability, adaptability, and generalizability. This validated capacity enables accurate prediction of epidemic trends and comprehensive assessment of disease risks.</p><p><strong>Discussion: </strong>From late 2021 to early 2022, it employs a one - to - one population simulation approach and simulates epidemic impacts and disease risks. Initially, using building statistical data in the study area, the model reconstructs the local real - world geographical environment. Leveraging data from the seventh national population census, it also replicates the study area's population characteristics. Next, the model takes into account population mobility, contact tracing, patient treatment, and the diagnostic burden of COVID - 19 - like influenza symptoms. It integrates epidemic transmission impact parameters into the model framework. Eventually, the model's results are compared with official data for validation, and it's applied to hypothetical scenarios. It provides scientific theoretical tools to support the implementation of government - driven prevention and control measures. Additionally, it facilitates the adjustment of individual behavioral guidelines, promoting more effective epidemic management.</p>","PeriodicalId":12458,"journal":{"name":"Frontiers in Cellular and Infection Microbiology","volume":"15 ","pages":"1547601"},"PeriodicalIF":4.6000,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12106320/pdf/","citationCount":"0","resultStr":"{\"title\":\"Study on the impact of COVID-19 epidemic and agent disease risk simulation model based on individual factors in Xi'an City.\",\"authors\":\"Wen Dong, Henan Yao, Wei-Na Wang\",\"doi\":\"10.3389/fcimb.2025.1547601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Since the first discovery and reporting of the COVID - 19 pandemic towards the end of 2019, the virus has rapidly propagated across the world. This has led to a remarkable spike in the number of infections. Even now, doubt lingers over whether it has completely disappeared. Moreover, the issue of restoring normal life while ensuring safety continues to be a crucial challenge that public health agencies and people globally are eager to tackle.</p><p><strong>Methods: </strong>To thoroughly understand the epidemic's outbreak and transmission traits and formulate timely prevention measures to fully safeguard human lives and property, this paper presents an agent - based model incorporating individual - level factors.</p><p><strong>Results: </strong>The model designates Xi'an-where a characteristic disease outbreak occurred-as the research area. The simulation results demonstrate substantial consistency with official records, effectively validating the model's applicability, adaptability, and generalizability. This validated capacity enables accurate prediction of epidemic trends and comprehensive assessment of disease risks.</p><p><strong>Discussion: </strong>From late 2021 to early 2022, it employs a one - to - one population simulation approach and simulates epidemic impacts and disease risks. Initially, using building statistical data in the study area, the model reconstructs the local real - world geographical environment. Leveraging data from the seventh national population census, it also replicates the study area's population characteristics. Next, the model takes into account population mobility, contact tracing, patient treatment, and the diagnostic burden of COVID - 19 - like influenza symptoms. It integrates epidemic transmission impact parameters into the model framework. Eventually, the model's results are compared with official data for validation, and it's applied to hypothetical scenarios. It provides scientific theoretical tools to support the implementation of government - driven prevention and control measures. Additionally, it facilitates the adjustment of individual behavioral guidelines, promoting more effective epidemic management.</p>\",\"PeriodicalId\":12458,\"journal\":{\"name\":\"Frontiers in Cellular and Infection Microbiology\",\"volume\":\"15 \",\"pages\":\"1547601\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-05-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12106320/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Cellular and Infection Microbiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3389/fcimb.2025.1547601\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Cellular and Infection Microbiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fcimb.2025.1547601","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
Study on the impact of COVID-19 epidemic and agent disease risk simulation model based on individual factors in Xi'an City.
Introduction: Since the first discovery and reporting of the COVID - 19 pandemic towards the end of 2019, the virus has rapidly propagated across the world. This has led to a remarkable spike in the number of infections. Even now, doubt lingers over whether it has completely disappeared. Moreover, the issue of restoring normal life while ensuring safety continues to be a crucial challenge that public health agencies and people globally are eager to tackle.
Methods: To thoroughly understand the epidemic's outbreak and transmission traits and formulate timely prevention measures to fully safeguard human lives and property, this paper presents an agent - based model incorporating individual - level factors.
Results: The model designates Xi'an-where a characteristic disease outbreak occurred-as the research area. The simulation results demonstrate substantial consistency with official records, effectively validating the model's applicability, adaptability, and generalizability. This validated capacity enables accurate prediction of epidemic trends and comprehensive assessment of disease risks.
Discussion: From late 2021 to early 2022, it employs a one - to - one population simulation approach and simulates epidemic impacts and disease risks. Initially, using building statistical data in the study area, the model reconstructs the local real - world geographical environment. Leveraging data from the seventh national population census, it also replicates the study area's population characteristics. Next, the model takes into account population mobility, contact tracing, patient treatment, and the diagnostic burden of COVID - 19 - like influenza symptoms. It integrates epidemic transmission impact parameters into the model framework. Eventually, the model's results are compared with official data for validation, and it's applied to hypothetical scenarios. It provides scientific theoretical tools to support the implementation of government - driven prevention and control measures. Additionally, it facilitates the adjustment of individual behavioral guidelines, promoting more effective epidemic management.
期刊介绍:
Frontiers in Cellular and Infection Microbiology is a leading specialty journal, publishing rigorously peer-reviewed research across all pathogenic microorganisms and their interaction with their hosts. Chief Editor Yousef Abu Kwaik, University of Louisville is supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide.
Frontiers in Cellular and Infection Microbiology includes research on bacteria, fungi, parasites, viruses, endosymbionts, prions and all microbial pathogens as well as the microbiota and its effect on health and disease in various hosts. The research approaches include molecular microbiology, cellular microbiology, gene regulation, proteomics, signal transduction, pathogenic evolution, genomics, structural biology, and virulence factors as well as model hosts. Areas of research to counteract infectious agents by the host include the host innate and adaptive immune responses as well as metabolic restrictions to various pathogenic microorganisms, vaccine design and development against various pathogenic microorganisms, and the mechanisms of antibiotic resistance and its countermeasures.