Predicting the Spread of a Disease with Machine Learning Algorithms!

The process of identifying, assessing, and managing people who have been exposed to a disease to prevent transmission.
People who may have been exposed to the virus from affected countries/people are to be traced and monitored for certain number of days.

This works for any person who had contact with patients under treatment for suspected, probable or confirmed case of that certain disease. Generally, Any person who provided care for the patient suspected or confirmed with the disease, including a health care worker or family member.

Contact tracing is a key component of a public health response to infectious disease outbreaks. The purpose of this guidance is to reinforce the place of community engagement and participation in the contact tracing process. The guidance and related products articulate best practice principles for community engagement and how they can be operationalized as part of any community-centred contact tracing strategy

---

In this Machine Learning project of mine, what i did was :

• Taken the dataset and checked for Null Values

• Did Exploratory Data Analysis and Visualized the Considerable Factors

• and Finded the correlation

For Training my model, i used : DBSCAN Clustering

DBSCAN is an Unsupervised Machine Learning Technique. By which, we will be able to Cluster the Data Points Precisely. It also helps to detect the noise in Dataset.

• Showed the clusters predicted by my model.

• And hence, Plotted the spread of disease using contact tracing curve.

• Finally, Predicted and showed the infected person through spreading.