From Correlation to Causation through stories and math

Correlation and causation are two concepts that people often mixup in their minds. I must admit that I myself have been guilty about this, and it unlikely that I would ever entirely grow out of it as it is wired deeply into our psychology. Let me use this article to briefly emphasise what the concepts of correlation and causation means, some interesting stories that have emerged from people misunderstanding these concepts and an algorithm that attempts to find causal relationship using correlation information. Here is a story that I heard a professor of mine, Prof. Dr. Ernst-Jan Camiel Wit, tell us during a lecture. There was a school that was involved in a study to see if providing free mid-day meals to students, which they could choose to be subscribed to this or not. At the end of the study, both the students who subscribed to it and did not where tested for different health indicators. It was observed that the students who chose to have meals from the programme had poorer health

Regarding a Covid-19 related project that I worked on a few months ago

A little over a year ago, I had written a blog post in this blog titled "COVID-19 Disease Spreading Simulation". That was something that I worked on in a very short time frame. A few months after that, during a conversation with an old professor of mine, Dr. Jimson Mathew, we discussed modifying it further to create something really interesting. We started working on creating "A Framework for COVID-19 Cure or Vaccine Distribution Modeling, Analysis and Decision Making" in October 2020 and finished creating it and drafting a research paper about it in the first week of November 2020. We had submitted this to the Journal of Simulation, but the reviewers rejected the paper citing more information recently. Of course, we will be editing the paper and re-submitting it; however, I thought it would be better if I uploaded the project in the public domain so that anyone who would like to use it can do the same without having to wait.

I have made this available on GitHub. The following are respectively the links to the source code and the hosted version. (You may have to zoom out a bit to see the entire grid structure)

What we have created here is a framework where you can define region boundaries and their permeability, and have people as actors being generated in the scene. There are hyperparameters to determine the number of people in a region, the number of people who are initially sick, the point in simulation from which vaccines and/or medicines get distributed, and its frequency and quantity as well. People can easily tweak the JSON file that is loaded in the webpage to have different layouts and different hyperparameters.

To generate the aforementioned JSON file, I used a script to do the same. I wanted to generate a hexagonal grid (honeycomb), as I was inspired by central place theory. Central place theory is an economic theory that attempts to explain the different hierarchies of human settlements across an ideal homogeneous landscape.

For the sake of simplicity in capturing the data, I have added UI buttons to take a screenshot as well as export simulation data that is captured over time. There are buttons to pause and play the simulation as well.

In the folder named 'resultsAndAnalysis', I have added in all the simulation data that we exported using the button that I stated above for various hyperparameters that we designed. The corresponding JSON files for the hyperparameters are also available in the folders.

I hope someone who is looking for something like this will find it useful.

Update from November 2023:

I just submitted a preprint to ArXiv describing this project. Check it out!


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