EconPapers    
Economics at your fingertips  
 

On the quick estimation of probability of recovery from COVID-19 during first wave of epidemic in India: a logistic regression approach

Joshi Hemlata (), Azarudheen S. (), Nagaraja M. S. () and Chandraketu Singh ()
Additional contact information
Joshi Hemlata: , CHRIST (Deemed to be University), Bangalore, India .
Azarudheen S.: , CHRIST (Deemed to be University), Bangalore, India .
Nagaraja M. S.: , CHRIST (Deemed to be University), Bangalore, India .
Chandraketu Singh: , CHRIST (Deemed to be University), Bangalore, India .

Statistics in Transition New Series, 2022, vol. 23, issue 2, 197-208

Abstract: The COVID-19 pandemic has recently become a threat all across the globe with the rising cases every day and many countries experiencing its outbreak. According to the WHO, the virus is capable of spreading at an exponential rate across countries, and India is now one of the worst-affected country in the world. Researchers all around the world are racing to come up with a cure or treatment for COVID-19, and this is creating extreme pressure on the policy makers and epidemiologists. However, in India the recovery rate has been far better than in other countries, and is steadily improving. Still in such a difficult situation with no effective medicine, it is essential to know if a patient with the COVID-19 is going to recover or die. To meet this end, a model has been developed in this article to estimate the probability of a recovery of a patient based on the demographic characteristics. The study used data published by the Ministry of Health and Family Welfare of India for the empirical analysis.

Keywords: COVID-19; epidemic; coronavirus disease; recovery estimation; logistic regression; logit analysis (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/stattrans-2022-0024 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:23:y:2022:i:2:p:197-208:n:12

DOI: 10.2478/stattrans-2022-0024

Access Statistics for this article

Statistics in Transition New Series is currently edited by Włodzimierz Okrasa

More articles in Statistics in Transition New Series from Statistics Poland
Bibliographic data for series maintained by Peter Golla ().

 
Page updated 2025-03-20
Handle: RePEc:vrs:stintr:v:23:y:2022:i:2:p:197-208:n:12