5 papers · 1 filter
Adaptive COVID-19 Trajectory Forecasting Using MAB-Inspired Ensemble Weighting
Hamed Karami, Javier Redondo Anton, Geunsoo Jang +2
Forecasting epidemic trajectories is important for public health decision-making, but no single model is consistently reliable across epidemic phases and forecasting settings. We e…
Parameter uncertainty in dynamical models: a practical identifiability index
Hamed Karami, Alexandra Smirnova, Sunmi Lee +1
Ordinary differential equation models are widely used to describe how complex systems change over time, but reliable conclusions depend on how well their parameters can be estimate…
Comparing Bayesian and Frequentist Inference in Biological Models: A Comparative Analysis of Accuracy, Uncertainty, and Identifiability
Mohammed A. Y. Mohammed, Hamed Karami, Gerardo Chowell
Mathematical models support inference and forecasting in ecology and epidemiology, but results depend on the estimation framework. We compare Bayesian and Frequentist approaches ac…
Comparative study of Bayesian and Frequentist methods for epidemic forecasting: Insights from simulated and historical data
Hamed Karami, Ruiyan Luo, Pejman Sanaei +1
Accurate epidemic forecasting is critical for effective public health interventions. This study compares Bayesian and Frequentist estimation frameworks within deterministic compart…
BayesianFitForecast: A User-Friendly R Toolbox for Parameter Estimation and Forecasting with Ordinary Differential Equations
Hamed Karami, Amanda Bleichrodt, Ruiyan Luo +1
Background: Mathematical models based on ordinary differential equations (ODEs) are essential tools across various scientific disciplines, including biology, ecology, and healthcar…