{"title":"卫生机构内部能力建设和外包给学术界或产业界:建立有效传染病模型的考虑因素。","authors":"Rachael Pung, Adam J Kucharski","doi":"10.1016/j.epidem.2024.100802","DOIUrl":null,"url":null,"abstract":"<p><p>Infectious disease models provide a systematic way to estimate crucial features of epidemic dynamics and explore different transmission and control scenarios. Given the importance of model-based analysis in managing public health crises, there has been an increase in post-pandemic creation of both academia-driven modelling centres, hubs and consortiums and government-driven public health agencies with in-house modelling units or teams. However, in the past, the delineation of roles and responsibilities between government- and academia-led modelling groups has often been unclear. Who should perform which tasks and when? This ambiguity can increase the risk of duplicated work or unaddressed gaps in analysis. It also raises questions about the sustainability of modelling capacity for addressing routine operational analytical needs while also developing new approaches that can be tailored for emergencies. In the sections below, we discuss factors that could inform decisions about where to locate infectious disease modelling activity. Rather than giving a fixed set of rules, we outlined key considerations and trade-offs that could be taken into account to enable academic and government modelling activities to complement each other effectively, which can in turn be refined as new public health crises emerge in future.</p>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":" ","pages":"100802"},"PeriodicalIF":3.0000,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Building in-house capabilities in health agencies and outsourcing to academia or industry: Considerations for effective infectious disease modelling.\",\"authors\":\"Rachael Pung, Adam J Kucharski\",\"doi\":\"10.1016/j.epidem.2024.100802\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Infectious disease models provide a systematic way to estimate crucial features of epidemic dynamics and explore different transmission and control scenarios. Given the importance of model-based analysis in managing public health crises, there has been an increase in post-pandemic creation of both academia-driven modelling centres, hubs and consortiums and government-driven public health agencies with in-house modelling units or teams. However, in the past, the delineation of roles and responsibilities between government- and academia-led modelling groups has often been unclear. Who should perform which tasks and when? This ambiguity can increase the risk of duplicated work or unaddressed gaps in analysis. It also raises questions about the sustainability of modelling capacity for addressing routine operational analytical needs while also developing new approaches that can be tailored for emergencies. In the sections below, we discuss factors that could inform decisions about where to locate infectious disease modelling activity. Rather than giving a fixed set of rules, we outlined key considerations and trade-offs that could be taken into account to enable academic and government modelling activities to complement each other effectively, which can in turn be refined as new public health crises emerge in future.</p>\",\"PeriodicalId\":49206,\"journal\":{\"name\":\"Epidemics\",\"volume\":\" \",\"pages\":\"100802\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Epidemics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.epidem.2024.100802\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epidemics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.epidem.2024.100802","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
Building in-house capabilities in health agencies and outsourcing to academia or industry: Considerations for effective infectious disease modelling.
Infectious disease models provide a systematic way to estimate crucial features of epidemic dynamics and explore different transmission and control scenarios. Given the importance of model-based analysis in managing public health crises, there has been an increase in post-pandemic creation of both academia-driven modelling centres, hubs and consortiums and government-driven public health agencies with in-house modelling units or teams. However, in the past, the delineation of roles and responsibilities between government- and academia-led modelling groups has often been unclear. Who should perform which tasks and when? This ambiguity can increase the risk of duplicated work or unaddressed gaps in analysis. It also raises questions about the sustainability of modelling capacity for addressing routine operational analytical needs while also developing new approaches that can be tailored for emergencies. In the sections below, we discuss factors that could inform decisions about where to locate infectious disease modelling activity. Rather than giving a fixed set of rules, we outlined key considerations and trade-offs that could be taken into account to enable academic and government modelling activities to complement each other effectively, which can in turn be refined as new public health crises emerge in future.
期刊介绍:
Epidemics publishes papers on infectious disease dynamics in the broadest sense. Its scope covers both within-host dynamics of infectious agents and dynamics at the population level, particularly the interaction between the two. Areas of emphasis include: spread, transmission, persistence, implications and population dynamics of infectious diseases; population and public health as well as policy aspects of control and prevention; dynamics at the individual level; interaction with the environment, ecology and evolution of infectious diseases, as well as population genetics of infectious agents.