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Dynamics of COVID‐19: Exploring Behavioral Responsiveness

Ali N. Mashayekhi et al.

System Dynamics Review2025https://doi.org/10.1002/sdr.70006article
AJG 2
Weight
0.41

What the paper says

In March 2020, our team initiated a modeling effort whose purposes were to create semantically rich stories about the COVID‐19 pandemic aimed at the public, and to create teaching materials for students of system dynamics. The present paper documents the technical details of the models that have supported that work. To achieve this, the final model is presented in eight layers that present a disaggregated structural description of the many ways that a population reacts to the pandemic. As a secondary purpose, we explore how the disaggregated view of population responsiveness, coupled with a parameter sensitivity analysis, can create a more robust description of “behavioral responsiveness,” a key factor driving a hundredfold variability in cumulative deaths per capita that was seen across societies in the pandemic.

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https://doi.org/https://doi.org/10.1002/sdr.70006

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@article{ali2025,
  title        = {{Dynamics of COVID‐19: Exploring Behavioral Responsiveness}},
  author       = {Ali N. Mashayekhi et al.},
  journal      = {System Dynamics Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1002/sdr.70006},
}

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Dynamics of COVID‐19: Exploring Behavioral Responsiveness

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.