| The countries with the largest infectious diseases burden tend to also be the least resourceful. Consequently, public health authorities in those countries need adequate predictive approaches, i.e. early warning-systems, to reduce the burden of infectious diseases whilst minimizing excessive budgetary costs. However, the analytical, parametric treatment and prediction models for even the simplest infectious disease transmission system are often too complex to be widely useful because of. Furthermore, the operation and optimization of early-warning systems frequently require a level of expertise unusually found in the poorest and most burdened countries. Therefore, this dissertation entertains different approaches to infectious diseases prediction and early-warning systems. Here, non-parametric early-warning methods from econometrics and engineering are co-opted and put in the service of public health. |
