Author: Rajan Gupta; Gaurav Pandey; Poonam Chaudhary; Saibal Kumar Pal
Title: SEIR and Regression Model based COVID-19 outbreak predictions in India Document date: 2020_4_3
ID: hf0jtfmx_4
Snippet: Time series data provided by John Hopkins University, USA has been used for the empirical result analysis [12] . The time period of data is from 30/01/2020 to 30/03/2020. The data includes confirmed cases, death cases and recovered cases of all countries. However, this paper focuses only on India's data for analysis and prediction of COVID-19 confirmed patients. The fact that India covers approximately 17.7% of the world's population and till dat.....
Document: Time series data provided by John Hopkins University, USA has been used for the empirical result analysis [12] . The time period of data is from 30/01/2020 to 30/03/2020. The data includes confirmed cases, death cases and recovered cases of all countries. However, this paper focuses only on India's data for analysis and prediction of COVID-19 confirmed patients. The fact that India covers approximately 17.7% of the world's population and till date the effect of COVID-19 cases per million is less than 1, is the motivation behind this research. For analysis and prediction of number of COVID-19 patients in India, the following models have been used.
Search related documents:
Co phrase search for related documents- confirm patient and death case: 1
- death case and follow model: 1
- death case and million case: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
- death case and recover case: 1, 2
- empirical result analysis and prediction analysis: 1
- million case and prediction analysis: 1
Co phrase search for related documents, hyperlinks ordered by date