A Statistical Approach To Analyse Infectivity Of Pre-Symptomatic Sars-Cov-2 Carriers Against Testing Delays

  • Shrabani Mallick, Biru Rajak2, Kushwaha, Ashish Kumar Verma
Keywords: SARS-CoV2, symptomatic, pre-symptomatic, logistic regression, Series Interval

Abstract

One of the biggest times trial, COVID-19 that has affected the entire human race, is caused by severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2). Amidst a lot of research going on with regards to the prediction on growth and transmission through Symptomatic carriers of the virus, the vulnerability of the spread of11 infection by pre-symptomatic carriers of SARS-COV-2 is also a matter of grave concern. Pre-Symptomatic carriers either don’t realize that they are potential suspects of the virus or ignore the significance of otherwise mild symptoms resulting in delayed medical diagnosis and testing. The proposed work presents an analysis of clinical characteristics of 450 contacts who had onset of very low to mild COVID-19 symptoms with varying delays in exposure to medical care facilities for testing or treatment. The results show that 20% of the subjects were pre-symptomatic and establishes that the pre-symptomatic cases where the first medical intervention was delayed with a delay factor greater than the Series Interval were responsible for spreading 61% of the total infection.

Published
2021-07-19
How to Cite
Kushwaha, Ashish Kumar Verma, S. M. B. R. (2021). A Statistical Approach To Analyse Infectivity Of Pre-Symptomatic Sars-Cov-2 Carriers Against Testing Delays. Design Engineering, 3791- 3802. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/2808
Section
Articles