Simulation-based assessment of digital twin systems for immunisation
BackgroundThis paper presents the application of simulation to assess the functionality of a proposed Digital Twin (DT) architecture for immunisation services in primary healthcare centres. The solution is based on Industry 4.0 concepts and technologies, such as IoT, machine learning, and cloud comp...
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Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Digital Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2025.1603550/full |
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| author | Leonardo de Oliveira El-Warrak Claudio Miceli de Farias Victor Hugo Dias Macedo De Azevedo Costa |
| author_facet | Leonardo de Oliveira El-Warrak Claudio Miceli de Farias Victor Hugo Dias Macedo De Azevedo Costa |
| author_sort | Leonardo de Oliveira El-Warrak |
| collection | DOAJ |
| description | BackgroundThis paper presents the application of simulation to assess the functionality of a proposed Digital Twin (DT) architecture for immunisation services in primary healthcare centres. The solution is based on Industry 4.0 concepts and technologies, such as IoT, machine learning, and cloud computing, and adheres to the ISO 23247 standard.MethodsThe system modelling is carried out using the Unified Modelling Language (UML) to define the workflows and processes involved, including vaccine storage temperature monitoring and population vaccination status tracking. The proposed architecture is structured into four domains: observable elements/entities, data collection and device control, digital twin platform, and user domain. To validate the system's performance and feasibility, simulations are conducted using SimPy, enabling the evaluation of its response under various operational scenarios.ResultsThe system facilitates the storage, monitoring, and visualisation of data related to the thermal conditions of ice-lined refrigerators (ILR) and thermal boxes. Additionally, it analyses patient vaccination coverage based on the official immunisation schedule. The key benefits include optimising vaccine storage conditions, reducing dose wastage, continuously monitoring immunisation coverage, and supporting strategic vaccination planning.ConclusionThe paper discusses the future impacts of this approach on immunisation management and its scalability for diverse public health contexts. By leveraging advanced technologies and simulation, this digital twin framework aims to improve the performance and overall impact of immunization services. |
| format | Article |
| id | doaj-art-df974554783f4cb5a0681f4dcc919ecd |
| institution | Kabale University |
| issn | 2673-253X |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Digital Health |
| spelling | doaj-art-df974554783f4cb5a0681f4dcc919ecd2025-08-22T05:26:46ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2025-08-01710.3389/fdgth.2025.16035501603550Simulation-based assessment of digital twin systems for immunisationLeonardo de Oliveira El-Warrak0Claudio Miceli de Farias1Victor Hugo Dias Macedo De Azevedo Costa2COPPE - Graduate School and Research in Engineering, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, BrazilCOPPE - Graduate School and Research in Engineering, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, BrazilFEN - Graduate School in Engineering, State University of Rio de Janeiro (UERJ), Rio de Janeiro, BrazilBackgroundThis paper presents the application of simulation to assess the functionality of a proposed Digital Twin (DT) architecture for immunisation services in primary healthcare centres. The solution is based on Industry 4.0 concepts and technologies, such as IoT, machine learning, and cloud computing, and adheres to the ISO 23247 standard.MethodsThe system modelling is carried out using the Unified Modelling Language (UML) to define the workflows and processes involved, including vaccine storage temperature monitoring and population vaccination status tracking. The proposed architecture is structured into four domains: observable elements/entities, data collection and device control, digital twin platform, and user domain. To validate the system's performance and feasibility, simulations are conducted using SimPy, enabling the evaluation of its response under various operational scenarios.ResultsThe system facilitates the storage, monitoring, and visualisation of data related to the thermal conditions of ice-lined refrigerators (ILR) and thermal boxes. Additionally, it analyses patient vaccination coverage based on the official immunisation schedule. The key benefits include optimising vaccine storage conditions, reducing dose wastage, continuously monitoring immunisation coverage, and supporting strategic vaccination planning.ConclusionThe paper discusses the future impacts of this approach on immunisation management and its scalability for diverse public health contexts. By leveraging advanced technologies and simulation, this digital twin framework aims to improve the performance and overall impact of immunization services.https://www.frontiersin.org/articles/10.3389/fdgth.2025.1603550/fullimmunisationdigital twinvaccinesTwinVaxsimulationIoT |
| spellingShingle | Leonardo de Oliveira El-Warrak Claudio Miceli de Farias Victor Hugo Dias Macedo De Azevedo Costa Simulation-based assessment of digital twin systems for immunisation Frontiers in Digital Health immunisation digital twin vaccines TwinVax simulation IoT |
| title | Simulation-based assessment of digital twin systems for immunisation |
| title_full | Simulation-based assessment of digital twin systems for immunisation |
| title_fullStr | Simulation-based assessment of digital twin systems for immunisation |
| title_full_unstemmed | Simulation-based assessment of digital twin systems for immunisation |
| title_short | Simulation-based assessment of digital twin systems for immunisation |
| title_sort | simulation based assessment of digital twin systems for immunisation |
| topic | immunisation digital twin vaccines TwinVax simulation IoT |
| url | https://www.frontiersin.org/articles/10.3389/fdgth.2025.1603550/full |
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