mlsanityData to 14 Oct 2026

Prediction of COVID-19 Disease Progression in India : Under the Effect of National Lockdown

arXiv 2004.03147 ↗First posted 7 Apr 2020q-bio.PE cs.LGcited by 2

Not on the map. Why?

Abstract (arXiv)

In this policy paper, we implement the epidemiological SIR to estimate the basic reproduction number R0 at national and state level. We also developed the statistical machine learning model to predict the cases ahead of time. Our analysis indicates that the situation of Punjab (R0≈ 16) is not good. It requires immediate aggressive attention. We see the R0 for Madhya Pradesh (3.37) , Maharastra (3.25) and Tamil Nadu (3.09) are more than 3. The R0 of Andhra Pradesh (2.96), Delhi (2.82) and West Bengal (2.77) is more than the India's R0=2.75, as of 04 March, 2020. India's R0=2.75 (as of 04 March, 2020) is very much comparable to Hubei/China at the early disease progression stage. Our analysis indicates that the early disease progression of India is that of similar to China. Therefore, with lockdown in place, India should expect as many as cases if not more like China. If lockdown works, we should expect less than 66,224 cases by May 01,2020. All data and textttR code for this paper is available from urlhttps://github.com/sourish-cmi/Covid19

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Apr 2020.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 1.

2 papers.