Introduction/ Motivation: As the number of cases in different countries continues to fluctuate in an errant manner, changing rules and regulations have made travelers confused and skeptical whether to travel to a particular country or not. Our project aims to simplify and alleviate a prospective traveler concerns by providing a travel score. Analyzing the current number of cases and the status of vaccine distribution in the country the person plans to visit. Our project aims to provide a concise score which can act as a metric to decide whether a destination is safe to travel to or not.
Abstract/Solution:
- We plan to refine data from various real time COVID datasets which are publicly available to get valuable insights to the current COVID situation.
- These insights will be used to create a numerical score for a travel destination.
- This score can be further enhanced by the vaccination status of the destination.
Approach:
- Input: Travel destination entered by a user (City/State/Country)
- Process: The factors taken into consideration to calculate the score are:
- No. of cases in the that particular area.
- No. of people vaccinated in that area.
- Population size and density of that area.
- Output: Percentage score showing how safe that destination is.
Personas: Our target audience would be uncertain travelers, who cannot decide whether a particular destination is COVID safe or not.
Datasets:
- https://www.kaggle.com/gpreda/covid-world-vaccination-progress
- https://www.kaggle.com/imdevskp/corona-virus-report?select=country_wise_latest.csv
Top 20 Recommended Safe Countries based on Predicted Score
Top 20 Active cases on that date
Training Algorithms Considered
K-means : Groups similar data into clusters
Linear Regression
Logistic regression