Predicting Covid-19 Intensive Zones in Delhi Using Neighbourhood Clustering

Abstract

As the world tackles the Covid-19 Pandemic, carefully constructed plans are the need of the hour. Lockdowns are holding back civilians from working and earning a living, and in such a situation, where economies fall and countries will be heading towards recessions, people might be forced to head out and work and live along with the virus. Therefore, mitigation strategies to stop the spread of the virus are an urgent need. This plan shouldn’t be a general one, but should be personalized according to the demographics to be really efficient. To foresee the effects of lifting lock-downs, my research will help people understand which neighbourhoods might see a surge in Covid-19 cases and which ones would show a similar trend. I will be using population density data and location data of popular venues (like popular market places) to estimate the interaction occurring at a particular place. The neighbourhoods will be clustered into groups so that common and effective strategies could be built to handle similar places. I will be focusing on the predictions mainly in my city (Delhi, the capital of India).