Application of a second-order stochastic optimization algorithm for fitting stochastic epidemiological models

Epidemiological models have tremendous potential to forecast disease burden and quantify the impact of interventions. Detailed models are increasingly popular, however these models tend to be stochastic and very costly to evaluate. Fortunately, readily available high-performance cloud computing now means that these models can be evaluated many times in… CONTINUE READING

2 Figures & Tables