Modelling of reproduction number for COVID-19 in India and high incidence states

Abstract

Background: Since the onset of the COVID-19 in China, forecasting and projections of the epidemic based on epidemiological models have been in the centre stage. Researchers have used various models to predict the maximum extent of the number of cases and the time of peak. This yielded varying numbers. This paper aims to estimate the effective reproduction number (R) for COVID-19 over time using incident number of cases that are reported by the government. Methods: Exponential Growth method to estimate basic reproduction rate R 0 , and Time dependent method to calculate the effective reproduction number (dynamic) were used. "R0" package in R software was used to estimate these statistics. Results: The basic reproduction number (R 0 ) for India was estimated at 1.

Random forest regression analysis on combined role of meteorological indicators in disease dissemination in an Indian city: A case study of New Delhi

“…The behavior of the epidemic curve shall be further understood using the measures of viral transmission such as the attack rate and basic reproduction number (R 0 ) as shown in Fig. 1 b–d ( Marimuthu et al, 2020 ; Nikbakht et al, 2019 ). The basic reproduction number represents the number of secondary infections caused by an infected person during the course of a contagious disease.…”

Analysis of key factors of a SARS-CoV-2 vaccination program: A mathematical modeling approach

“…The aim is to test the impact of the inoculation rate and efficacy of the vaccine under two different SARS-CoV-2 virus transmission rate scenarios. As it has been mentioned before, there are a lot of uncertainties in the transmission rates for different regions and they vary over the time depending on official and unofficial non-pharmaceutical interventions [40, 55, 85, 93, 120, 25, 75]. However, the approach used here allows us to understand the impact of inoculation rate and vaccine efficacy under two different transmission of the SARS-CoV-2 virus environments.…”

“…Thus, we construct a mathematical model taking into account asymptomatic people, which have been missed in other studies. In addition, we will study scenarios with different SARS-CoV-2 virus transmission rates, which results in different effective reproduction numbers R t of COVID-19 [75, 85, 14, 25].…”

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“…Due to inadequate testing, data limitations, and prejudiced reporting may be the barriers to estimate a precise and representative R0 value of Bangladesh. However, the calculated R0 value in India is 1.379 (range: 1.29 to 1.45) 10 , which may resemble the approximate R0 value of Bangladesh. Therefore, the threshold percentage may be assumed as 22 to 31% of the total population required to achieve indirect protection through natural herd immunity in Bangladesh.…”