We have previously implemented a SIR infection model and its possible effect on the Catalan Health System. Given the current situation of health alarm, we would like to contribute to the general understanding, debate and research using computational models.
In order to do this, we would like to ask the DTIC community help in adapting it to the current epidemic and in creating a collaborative environment where other researchers (and or general public) could intervene.
- Do not harm – Simulations and models are difficult to validate and could be used to create panic or unnecessary alarm. How to use those tools without harming?
- Why do we do this – What good could we do with this? Maybe get some additional insights that are not possible with global models that only consider aggregated data?
- Scenarios - Which scenario are we more interested in?
Code is available on bitbucket here
Data is pooled from the Catalan health system observatory, automatically analyzed and consolidated using an online pipeline and stored in a local db that the models can access.
Agent based simulations implementing the SIR infection model are run on the cluster and results are visualized on a map using cartodb software.
For the IPER project, we started implementing the following architecture which could be useful as well.
- Upper Row: We start with data processing that will be used to create predictive models and to estimate the parameters for massive scale agent-based simulations. The information produced so far will be compressed using manifold learning techniques to reduce visualization burden and explosive dimensionality problems. This output will feed the policy optimization part of the framework.
- Lower Row: We will maintain and act on several different event sequences at once (timeline diagram). And show the results using powerful, interactive spatial representations.