COVID-19 in India: State-wise Analysis and Prediction

Abstract

Coronavirus disease 2019 (COVID-19), a highly infectious disease, was first detected in Wuhan, China, in December 2019. The disease has spread to 212 countries and territories around the world and infected (confirmed) more than three million people. In India, the disease was first detected on 30 January 2020 in Kerala in a student who returned from Wuhan. The total (cumulative) number of confirmed infected people is more than 37000 till now across India (3 May 2020). Most of the research and newspaper articles focus on the number of infected people in the entire country. However, given the size and diversity of India, it may be a good idea to look at the spread of the disease in each state separately, along with the entire country. For example, currently, Maharashtra has more than 10000 confirmed cumulative infected cases, whereas West Bengal has less than 800 confirmed infected cases (1 May 2020). The approaches to address the pandemic in the two states must be different due to limited resources. In this article, we will focus the infected people in each state (restricting to only those states with enough data for prediction) and build three growth models to predict infected people for that state in the next 30 days. The impact of preventive measures on daily infected-rate is discussed for each state.

COVID-19 Pandemic and City-Level Nitrogen Dioxide (NO2) Reduction for Urban Centres of India

“…As of May 18, 2020, the world has recorded 53, 70,375 cases and 3, 44,454 deaths with the highest mortality in the USA; India has witnessed a total of 96,192 cases and 3039 fatalities (WHO 2020 ). Preliminary analysis reveals that the transmission rate for India is 1.7 (where the value is ranging from 1.5 to 3.5 worldwide) (Ghosh et al 2020 ). The respiratory illness symptoms and mortality due to prolonged exposure to gaseous pollutants like nitrogen dioxide (NO 2 ), sulphur dioxide (SO 2 ), particulate matter (PM), carbon monoxide (CO), etc., have been reported earlier in India and around the world in several studies (Abbey et al 1995 ; Abbey and Burchette 1996 ; Balakrishnan et al 2019 ; Beeson et al 1998 ; David et al 2019 ; Faustini et al 2014 ; He et al 2020 ; Liu et al 2013 ; Ogen 2020 ; Siddique et al 2011 ).…”

Epidemiological Transition of Covid-19 in India from Higher to Lower HDI States and Territories: Implications for Prevention and Control

“…23 A number of studies have predicted the burden of covid--19 infection in India using various modeling techniques, e.g. Bhardwaj, Ghosh et al 26,27 These studies focus on extent of the disease and date/s of epidemic ascent and descent. However, modeling techniques of a novel epidemic are not always accurate.…”

“…We have focused on sociological aspects of the disease and show that the epidemic is still in evolution and till the time it matures into low HDI states, it is unlikely to terminate soon ( Figure 3). However, although we have used raw data available from a non--profit website, 16 there are certain differences with the official government data used by others, 26,27 and the prediction may not be accurate.…”

Fine-tuned Forecasting Techniques for COVID-19 Prediction in India

“…[3] performed a simulation study of situation COVID-19 at the very initial stage of pandemics, a model of susceptibleinfectious-recovered-dead (SIRD) was used. Ghosh et al [4] used a pandemic model of Susceptible Infectious Susceptible (SIS) to forecast spread of the COVID-19 in India.…”