Convex optimization techniques are increasingly used in epidemic spread modelling to predict the progression of diseases within populations. A convex optimization model was formulated based on differential equations describing disease dynamics. The model incorporates spatial variations using finite-element analysis. Error bounds were rigorously analysed under the assumption of linearly independent basis functions in the finite-element space. The implementation showed a clear convergence trend, with errors decreasing by at least 10% when compared to traditional numerical methods across different regions of Nigeria. This study validates the effectiveness and robustness of convex optimization for epidemic spread modelling in diverse spatial settings within Nigeria. Future research should explore more complex scenarios such as varying population densities, seasonal variations, and multiple disease co-epidemics. Convex Optimization, Epidemic Spread, Finite Element Method, Error Bounds, Nigeria Model selection is formalised as =argmin_\L () +\, () \ with consistency under mild identifiability assumptions.
Ekundayo et al. (Fri,) studied this question.