Fig 1.
Human-mosquito transmission dynamics of dengue fever.
Fig 2.
Compartmental model structure for dengue transmission dynamics.
Table 1.
Description of epidemiological parameters in the compartmental model.
Fig 3.
In S1 Fig, we provide an illustration of the complete neural network model, including the input, hidden, and output layers.
Fig 4.
Selected calibration and projection dengue outbreaks from city data.
Fig 5.
Selected calibration and projection dengue outbreaks from country data.
Fig 6.
NPC vs MCMC accuracy and processing time on city data.
Table 2.
Comparison of NPC and MCMC: MSE and processing time on city data.
Fig 7.
Comparison of NPC and MCMC accuracy for infectious (Hi) and cumulative infectious () compartments on city data.
Fig 8.
Comparison of NPC and MCMC for marginal posterior densities of ECM parameter set on city data.
The plot shows marginal posterior distributions for parameters in α after calibration in Bello, Iquitos, and San Juan. The x-axis gives parameter values and the y-axis gives posterior density. Narrow, sharp peaks indicate higher certainty, while broader shapes indicate greater uncertainty. Comparing these distributions across NPC and MCMC highlights differences in parameter uncertainty and estimation values.
Fig 9.
Sensitivity and uncertainty analysis for basic reproductive number on city data.
Fig 10.
NPC vs MCMC accuracy and processing time on country data.
Table 3.
Comparison of NPC and MCMC: MSE and Processing Time on Country Data
Fig 11.
Comparison of NPC and MCMC accuracy for infectious (Hi) and cumulative infectious () compartments on country data.
Fig 12.
Comparison of NPC and MCMC for marginal posterior densities of ECM parameter set on country data.
The plot shows marginal posterior distributions for parameters in α after calibration in Vietnam, the Philippines, and Cambodia. The x-axis gives parameter values and the y-axis gives posterior density. Narrow, sharp peaks indicate higher certainty, while broader shapes indicate greater uncertainty. Comparing these distributions across NPC and MCMC highlights differences in parameter uncertainty and estimation values.
Fig 13.
Sensitivity and uncertainty analysis for basic reproductive number on country data.