Hemlata Joshi, S. Azarudheen, M. Nagaraja, Singh Chandraketu
{"title":"On the quick estimation of probability of recovery from COVID-19 during first wave of epidemic in India: a logistic regression approach","authors":"Hemlata Joshi, S. Azarudheen, M. Nagaraja, Singh Chandraketu","doi":"10.2478/stattrans-2022-0024","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":37985,"journal":{"name":"Statistics in Transition","volume":"23 1","pages":"197 - 208"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics in Transition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/stattrans-2022-0024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 1
Abstract
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.
期刊介绍：
Statistics in Transition (SiT) is an international journal published jointly by the Polish Statistical Association (PTS) and the Central Statistical Office of Poland (CSO/GUS), which sponsors this publication. Launched in 1993, it was issued twice a year until 2006; since then it appears - under a slightly changed title, Statistics in Transition new series - three times a year; and after 2013 as a regular quarterly journal." The journal provides a forum for exchange of ideas and experience amongst members of international community of statisticians, data producers and users, including researchers, teachers, policy makers and the general public. Its initially dominating focus on statistical issues pertinent to transition from centrally planned to a market-oriented economy has gradually been extended to embracing statistical problems related to development and modernization of the system of public (official) statistics, in general.
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