The COVID-19 outbreak gave rise to an unprecedented production of models and studies aimed at understanding the pandemic, predicting its evolution and designing measures to reduce its spread.The aim of this project is to show how a simple SIR model was used to make quick predictions for New Jersey in early March 2020 and call for action based on data from China and Italy. Now different viruses manifest with different characteristics and public response to these characteristics can be drastically different. Therefore A more refined model, which accounts for the parameters social distancing, testing, contact tracing and quarantining, is then proposed to identify containment measures to minimize the economic cost of the pandemic.
This model was programmed using AMPL (a mathematical programming language) in which we use optimization techniques and data from throughout New Jersey, split into three regions, to minimize the economic costs of the aforementioned parameters. For visualization and plotting we use Matlab to plot our results. Our paper can be found here
