Data-driven modelling and prediction of COVID-19 infection in India and correlation analysis of the virus transmission with socio-economic factors.

ABSTRACT:

Aims

The current study attempts to model the COVID-19 outbreak in India, USA, China, Japan, Italy, Iran, Canada and Germany. The interactions of coronavirus transmission with socio-economic factors in India using the multivariate approach were also investigated.

Methods

Actual cumulative infected population data from 15 February to May 15, 2020 was used for determination of parameters of a nested exponential statistical model, which were further employed for the prediction of infection. Correlation and Principal component analysis provided the relationships of coronavirus spread with socio-economic factors of different states of India using the Rstudio software.

Results

Cumulative infection and spreadability rate predicted by the model was in good agreement with the a

SUBMITTER: Kumar A 

PROVIDER: S-EPMC7347321 | biostudies-literature | 2020 Sep - Oct

REPOSITORIES: biostudies-literature