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Estimating Population Burden of Stroke with an Agent-Based Model

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Advances in Social Simulation (ESSA 2023)

Part of the book series: Springer Proceedings in Complexity ((SPCOM))

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Abstract

Stroke is one of the leading causes of death and disability worldwide but it is believed to be highly preventable. The majority of stroke prevention focuses on targeting high-risk individuals but its is important to understand how the targeting of high-risk individuals might impact the overall societal burden of stroke. We propose using an agent-based model that follows agents through their pre-stroke and stroke journey to assess the impacts of different interventions at the population level. We present a case study looking at the impacts of agents being informed of their stroke risk at certain ages and those agents taking measure to reduce their risk. The results of our study show that if agents are aware of their risk and act accordingly we see a significant reduction in strokes and population DALYs. The case study highlights the importance of individuals understanding their own stroke risk for stroke prevention and the usefulness of agent-based models in assessing the impact of stroke interventions.

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Notes

  1. 1.

    The modified Rankin Scale is a clinical scale for assessing neurological disability. It ranges from 0 (no symptoms) to 6 (dead).

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Acknowledgements

This manuscript was prepared using FRAMCOHORT, GEN3, and FRAMOFFSPRING research materials obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center and does not necessarily reflect the opinions or views of the FRAMCOHORT, GEN3, FRAMOFFSPRING, or the NHLBI.

The Irish Longitudinal study on Ageing (TILDA)” and also ISSDA, in the following way: “Accessed via the Irish Social Science Data Archive—www.ucd.ie/issda.

Funding

This work was partly supported by the PRECISE4Q project funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 777107, the STRATIF-AI project funded by EU’s Horizon Europe research and innovation programme under grant agreement No. 101080875 and by the ADAPT Centre for Digital Content Technology funded under the SFI Research Centres Programme (Grant 13/RC/2106_P2) and was co-funded under the European Regional Development Funds.

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Authors and Affiliations

  1. Technological University Dublin, Dublin, Ireland

    Elizabeth Hunter

  2. Trinity College Dublin, Dublin, Ireland

    John D. Kelleher

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  1. Elizabeth Hunter
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  2. John D. Kelleher
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Correspondence to Elizabeth Hunter .

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Editors and Affiliations

  1. MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK

    Corinna Elsenbroich

  2. Department of Computer & Systems Sciences, Stockholm University, Kista, Stockholms Län, Sweden

    Harko Verhagen

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Hunter, E., Kelleher, J.D. (2024). Estimating Population Burden of Stroke with an Agent-Based Model. In: Elsenbroich, C., Verhagen, H. (eds) Advances in Social Simulation. ESSA 2023. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-031-57785-7_2

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