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J. Ehigie

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Open access 2026

Neural ordinary differential equations for parameter estimation, simulation and forecasting of infectious disease dynamics: Applications to HIV/AIDS and malaria models

The results demonstrate that the Neural ODE framework effectively learns disease transmission patterns, accurately captures the progression of compartmental dynamics, estimates key epidemiological parameters, and produces reliable forecasts from both observed and numerically generated data.

F. C. Ndubuogaranya, J. Ehigie, S. Okunuga · 0 citations

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