关于印度第一波疫情期间COVID-19恢复概率的快速估计:逻辑回归方法

Q4 Mathematics

Statistics in Transition Pub Date : 2022-06-01 DOI:10.2478/stattrans-2022-0024

Hemlata Joshi, S. Azarudheen, M. Nagaraja, Singh Chandraketu

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引用次数: 1

摘要

最近，COVID-19大流行已成为全球范围内的威胁，病例每天都在上升，许多国家都出现了疫情。据世界卫生组织称，这种病毒能够以指数速度在各国传播，印度现在是世界上受影响最严重的国家之一。世界各地的研究人员都在竞相提出COVID-19的治愈或治疗方法，这给政策制定者和流行病学家带来了极大的压力。然而，印度的回收率远远好于其他国家，并且正在稳步提高。在没有有效药物的情况下，仍然处于这种困难的情况下，了解COVID-19患者是会康复还是会死亡至关重要。为了达到这一目的，本文开发了一个模型来估计基于人口统计学特征的患者康复的概率。本研究使用印度卫生和家庭福利部公布的数据进行实证分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

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

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.

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来源期刊

Statistics in Transition Decision Sciences-Statistics, Probability and Uncertainty

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

9 weeks

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.