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Estimation of the Impact of COVID-19 Pandemic Lockdowns on Breast Cancer Deaths and Costs in Poland Using Markovian Monte Carlo Simulation

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Computational Science – ICCS 2023 (ICCS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14075))

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Abstract

This study examines the effect of COVID-19 pandemic and associated lockdowns on access to crucial diagnostic procedures for breast cancer patients, including screenings and treatments. To quantify the impact of the lockdowns on patient outcomes and cost, the study employs a mathematical model of breast cancer progression. The model includes ten different states that represent various stages of health and disease, along with the four different stages of cancer that can be diagnosed or undiagnosed. The study employs a natural history stochastic model to simulate the progression of breast cancer in patients. The model includes transition probabilities between states, estimated using both literature and empirical data. The study utilized a Markov Chain Monte Carlo simulation to model the natural history of each simulated patient over a seven-year period from 2019 to 2025. The simulation was repeated 100 times to estimate the variance in outcome variables. The study found that the COVID-19 pandemic and associated lockdowns caused a significant increase in breast cancer costs, with an average rise of 172.5 million PLN (95% CI [82.4, 262.6]) and an additional 1005 breast cancer deaths (95% CI [426, 1584]) in Poland during the simulated period. While these results are preliminary, they highlight the potential harmful impact of lockdowns on breast cancer treatment outcomes and costs.

M. Dul and M. K. Grzeszczyk —Authors contributed equally.

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Acknowledgements

This publication is partly supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement Sano No. 857533 and the International Research Agendas programme of the Foundation for Polish Science, co-financed by the European Union under the European Regional Development Fund. We would like to thank Tadeusz Satława, Katarzyna Tabor, Karolina Tkaczuk, and Maja Więckiewicz from Sano for help and their initial contribution in the development of the model.

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Authors and Affiliations

  1. Sano Centre for Computational Medicine, Cracow, Poland

    Magdalena Dul & Michal K. Grzeszczyk

  2. Warsaw School of Economics, Warsaw, Poland

    Magdalena Dul & Ewelina Nojszewska

  3. Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Arkadiusz Sitek

Authors
  1. Magdalena Dul
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  2. Michal K. Grzeszczyk
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  3. Ewelina Nojszewska
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  4. Arkadiusz Sitek
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Corresponding author

Correspondence to Michal K. Grzeszczyk .

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Editors and Affiliations

  1. Czech Technical University in Prague, Prague, Czech Republic

    Jiří Mikyška

  2. University of Amsterdam, Amsterdam, The Netherlands

    Clélia de Mulatier

  3. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  4. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  5. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  6. University of Amsterdam, Amsterdam, The Netherlands

    Peter M.A. Sloot

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Dul, M., Grzeszczyk, M.K., Nojszewska, E., Sitek, A. (2023). Estimation of the Impact of COVID-19 Pandemic Lockdowns on Breast Cancer Deaths and Costs in Poland Using Markovian Monte Carlo Simulation. In: Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 14075. Springer, Cham. https://doi.org/10.1007/978-3-031-36024-4_10

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  • DOI: https://doi.org/10.1007/978-3-031-36024-4_10

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