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A qualitative model of patterns of resilience and vulnerability in responding to a pandemic outbreak with system dynamics

Kontogiannis Thomas

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/54B536DD-AE1F-49AE-860B-3EFC8DD97692
Έτος 2021
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
Άδεια Χρήσης
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Βιβλιογραφική Αναφορά T. Kontogiannis, “A qualitative model of patterns of resilience and vulnerability in responding to a pandemic outbreak with system dynamics,” Saf. Sci., vol. 134, Feb. 2021, doi: 10.1016/j.ssci.2020.105077. https://doi.org/10.1016/j.ssci.2020.105077
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Περίληψη

Covid-19 has revealed the fragility of healthcare, government, social support and economic systems. The complexity of interactions and the tight coupling of these systems have become evident during the spread of the disease and the evolution of policies that produced unintended migrating effects. Striving for efficiency most systems have abandoned resilience principles against disturbances. In this article, systemic risk is viewed within a system dynamics framework complemented by a resilience perspective in anticipating threats and making provisions for resources, responding in the face of uncertainty and foreseeing side-effects, monitoring critical indicators to assess progress and learning by doing. Earlier system dynamics models focused on the epidemiological micro-level, hence, losing sight of the wider social and the economic landscape that affect the control of the disease. This article expands this model-based approach by looking into the capacity of the healthcare to pace with the surge of patients, the role of governments in mobilizing individuals and organizations, the diffusion of risk information to the general public and so on. The relationships between the healthcare, government, social support and economic systems are presented with the use of system archetypes and leverage points for overcoming bottlenecks. Finally, the archetypes are assembled into an overall causal loop diagram that has implications for policies and behavioral patterns.

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