COVID-19 Trend and Forecast in India: A Joinpoint Regression Analysis
Chaurasia, A. R.
Show abstract
This paper analyses the trend in daily reported confirmed cases of COVID-19 in India using joinpoint regression analysis. The analysis reveals that there has been little impact of the nation-wide lockdown and subsequent extension on the progress of the COVID-19 pandemic in the country and there is no empirical evidence to suggest that relaxations under the third and the fourth phase of the lockdown have resulted in a spike in the reported confirmed cases. The analysis also suggests that if the current trend continues, in the immediate future, then the daily reported confirmed cases of COVID-19 in the country is likely to increase to 21 thousand by 15 June 2020 whereas the total number of confirmed cases of COVID-19 will increase to around 422 thousand. The analysis calls for a population-wide testing approach to check the increase in the reported confirmed cases of COVID-19.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Estimating the parameters of SIR model of COVID-19 cases in India during lock down periods 96%
- Covid-19: analysis of a modified SEIR model, a comparison of different intervention strategies and projections for India 95%
- An Epidemic Model SIPHERD and its application for prediction of the spread of COVID-19 infection in India 94%
Similar papers in this journal
Similar papers in this journal
- Management of mild COVID-19: Policy implications of initial experience in India 93%
- Serological prevalence of SARS-CoV-2 antibody among children and young age (between age 2-17 years) group in India: An interim result from a large multi-centric population-based seroepidemiological study 93%
- Experience from a COVID-19 screening centre of a tertiary care institution: A retrospective hospital-based study 92%
Similar papers in this journal
- A new, simple method of describing COVID-19 trajectory and dynamics in any country based on Johnson Cumulative Distribution Function fitting 93%
- Several countries in one: a mathematical modeling analysis for COVID-19 in inner Brazil 93%
- Spatial variation in the non-use of modern contraception and its predictors in Bangladesh 91%
Similar papers in this journal
- Decentralisation of the compliance of anti-tobacco law in India: The case of higher educational institutions in New Delhi, India 91%
- Comparative study between first and second wave of COVID-19 deaths in India - a single center study 91%
- Second wave of the Covid-19 pandemic in Delhi, India: high seroprevalence not a deterrent? 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.