Venue:
Year: 2021
Abstract
In a pandemic that affects every aspect of life, how do policy makers make well-informed decisions to effectively mitigate the terrible impacts to life and the society as a whole? The general approach is: there are existing sophisticated and realistic compartmental models (e.g. Ferguson et al.) of how the pandemic spreads. These models have parameters that encapsulate the nature of the virus, and potential actions of the policy makers and private individuals. Thus, varying these parameters we can fit the observed data, and also query tentative policy actions based on the relevant forecasts. This analysis is the basis of informed decision making for the best estimated outcomes, but it remains very much a manual approach. On top of that this is computationally expensive, and requires substantial involvement of the experts. In this preliminary work, we investigate how we can create an interactive tool that exposes compartmental models to experts and policy makers so that they can rapidly investigate future scenarios based on recently observed data.