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Covid-19 Analysis and Prediction - A Case Study using Machine Learning


It's a Machine learning project where I have analyzed the current situation of Covid-19 of India with respect to the world and predicted the cases and outcomes of the analysis.

Contents of the Project :

Introduction

  • Heatmap of the confirmed cases, recovered cases and death cases
  • How many countries were effected by the virus?
  • Percentage of confirmed cases per country
  • Top 5 countries having most number of confirmed cases

China : The first epicenter of the pandemic

  • Curve of total number of confirmed, recovered and death cases
  • Confirmed cases increased per day stats
  • Death cases increased per day stats
  • Hubei Province

World : Excluding China

  • Per day stats
  • Curve of total number of confirmed, recovered and death cases
  • Confirmed cases increased per day stats
  • Death cases increased per day stats

Italy : The 2nd Epicenter

  • Per day stats
  • Curve of total number of confirmed, recovered and death cases
  • Confirmed cases increased per day stats
  • Death cases increased per day stats

USA : The 3rd Epicenter

  • Per day stats
  • Curve of total number of confirmed, recovered and death cases
  • Confirmed cases increased per day stats
  • Death cases increased per day stats

South Korea : The most successful country against Covid-19

  • Per day stats
  • Curve of total number of confirmed, recovered and death cases
  • Confirmed cases increased per day stats
  • Death cases increased per day stats

United Kingdom : Recovered from Covid-19 or, not?

  • Per day stats
  • Curve of total number of confirmed, recovered and death cases
  • Confirmed cases increased per day stats
  • Death cases increased per day stats

Does Germany defeat Covid-19 like the UK did?

  • Per day stats
  • Curve of total number of confirmed, recovered and death cases
  • Confirmed cases increased per day stats
  • Death cases increased per day stats

Does The Tech country Japan, overcome the situation?

  • Per day stats
  • Curve of total number of confirmed, recovered and death cases
  • Confirmed cases increased per day stats
  • Death cases increased per day stats

Australia : How did they manage?

  • Per day stats
  • Curve of total number of confirmed, recovered and death cases
  • Confirmed cases increased per day stats
  • Death cases increased per day stats

LOCKDOWN : The Saviour or, not?

  • China
  • Italy
  • USA
  • Germany
  • united Kingdom
  • Australia
  • Japan

India : the fastest growing epicenter

  • Per day stats
  • Curve of total number of confirmed, recovered and death cases
  • Confirmed cases increased per day stats
  • Death cases increased per day stats
  • Lockdown of India

Statewise Analysis of India :

  • Statewise Tree Map
  • Male or, Female, which community is more affected?
  • Which age group is more effected?
  • Statewise Recovery rate and Death rate
  • Total Tested v/s Positive cases : analysis
  • State v/s Testing labs
  • Health facility condition analysis statewise
  • State v/s Hospital Beds

Prediction for India

  • Prediction of the growth rate in the upcoming months
  • Requirement of hospital beds v/s Confirmed cases
  • When the states will be running out of hospital beds?
  • How many beds we required to prevent the crisis (Statewise analysis)

Conclusion

N.B.: This project is based on the data provided till 15th November, 2020


✔Contributors of this Research Work


Abhishek Sharma

Ishita Pahari

Udayan Misra

Digbijoy Dasgupta

Shreya Bose

Raktim Karmakar

📜Conference Participated with this Research Work

 

📝Publication

 

Sharma A. et al. (2022) Covid-19—Analysis and Prediction—A Case Study Using Machine Learning. In: Tavares J.M.R.S., Dutta P., Dutta S., Samanta D. (eds) Cyber Intelligence and Information Retrieval. Lecture Notes in Networks and Systems, vol 291. Springer, Singapore. https://doi.org/10.1007/978-981-16-4284-5_31

◆ ISBN : 978-981-16-4283-8 ◆ DOI : 10.1007/978-981-16-4284-5 ◆ eBook ISBN : 978-981-16-4284-5 ◆ Series ISSN : 2367-3370


© 2021 Abhishek Sharma

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