Fig 1.
Conceptual representation of the two model types.
The equation-based model (SEIRS) is structured as a finite-state machine in which population subsets mass-transition between states based on probabilities. The agent-based model (ABM) is structured as layered complex networks in which individuals transition between states based on local interactions.
Fig 2.
Visual representation of the agent-based implementation of the diffusion model at two different time steps.
The color of each cell (shades of green) represents the level of information present in that specific area, while agents are depicted by arrows in a visual representation that shows both the position and the current orientation: orange susceptible, magenta infected, blue recovered, and violet exposed.
Table 1.
Comparison of characteristics between the EBM, simple ABM, and enhanced ABM for infodemic modeling.
Fig 3.
Example of matching outcomes for the SEIRS model, ABM (left) vs. EBM (right), ,
,
,
(means and deviations for 1000 runs of the ABM).
Fig 4.
Example of non-matching outcomes for the SEIRS model, ABM (left) vs. EBM (right), ,
,
,
(means and deviations for 1000 runs of the ABM).
Table 2.
Cumulative results for intermodel equivalence across parameter variations: with a step of 0.1, resulting in 10 experiments for SI, 100 SIS and SIR, 1000 SIRS and SEIR, 10000 SEIRS. Case II configuration. Notations: NRMSE normalized root mean of square error, ρ Pearson’s correlation coefficient, SD standard deviation, ABM agent-based model, EBM equation-based model, S susceptible, E exposed, I infected, R recovered.
Fig 5.
Intermodel equivalence outcomes for the SIS and SI models (result exemplification), where NRMSE is the normalized root mean of square error, ρ is Pearson’s correlation coefficient, β is the infection rate, and γ is the recovery rate.
Case I configuration.
Fig 6.
Effect of homophily on the ABM model outcomes with ,
(total
agents): simple model large variant (left) and enhanced model (right) for 1000 runs (means and deviation).
Fig 7.
Results of the SIS model fitting against the real world data for the enhanced ABM (,
) averaged over 100 runs (variance 5498.17) and for the EBM (
,
).
Fig 8.
Enhanced ABM outputs fitted against real world data, compared with the simple ABM and the EBM outputs obtained using the same parameters (where applicable).
,
. Both ABM outputs are averaged over 100 runs and have a variance of 5498.17 for the enhanced and 1577.25 for the simple versions.
Table 3.
Outcome measures (Pearson correlation coefficient ρ and normalized root mean of squared error NRMSE) comparing the real-world data with the outputs of the enhanced ABM, simple ABM and EBM, simulated with the parameters ,
, resulted from the enhanced ABM fitting procedure.
Notations: ABM agent-based model, EBM equation-based model.