Predicting Spread, Recovery and Death Due to COVID-19 using a Time-Series Model (Prophet)

Abstract

The world is facing its biggest challenge since
1920 due to spread of COVID-19 virus. Identified in China in
December 2019, the virus has spread more than 200 countries
in the world. Scientists have named the virus as Novel Corona
Virus (belongs to SARS group virus). The virus has caused
severe disruption to our world. Educational institutions, financial
Services, government services and many other sectors are badly
affected by this virus. More importantly, the virus has caused
a massive amount of human deaths around the world and
still its infecting people every day. Scientist around the world
are trying to find a solution to stop the COVID-19. Their
solutions include identifying possible effective vaccine, computer
aided modelling to see the pattern of spread etc. Using Machine
Learning techniques, it is possible to forecast the spread, death,
and recovery due to COVID-19. In this article, we have shown a
machine learning model named as Prophet Time Series Analysis
to forecast the spread, death, and recovery in different countries.
Wetrain the model using the available historical data on COVID
19 from John Hopkins University’s COVID-19 site. Then we
forecast spread, death, and recovery for seven days using a well
known forecasting model called Prophet. This interval can be
increased to see the effect of COVID-19. We chose 145 days of
historical data to train the model then we predict effect for seven
days (15 June 2020 to 22 June 2020). To verify out result, we
compare the predicted value with actual value of spread, death
and recovery. The model provides accuracy over 92% in all the
cases. Our model can be used to identify the effect of COVID-19
in any countries in the world. The system is developed using
Python language and visualization is also possible interactively.
By using our system, it will be possible to observe the effect of
spread, death and recovery for any countries for any period of
time.