id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-148145-qg5623s7	Singh, Bikash Chandra	COVID-19 Pandemic Outbreak in the Subcontinent: A data-driven analysis	2020-08-22		.txt	text/plain	5832	338	56	More specifically, we use various models (for example, susceptible infection recovery (SIR), exponential growth (EG), sequential Bayesian (SB), maximum likelihood (ML) and time dependent (TD)) to estimate the reproduction numbers and observe the model fitness in the corresponding data set. Since the governments of different countries have responded to the COVID-19 pandemic seriously, it is important that the researchers estimate: (i) the pandemic regionally based on the basic reproduction number, (ii) the arrival of the peak time, and forecast the time course of the epidemic by analyzing the data on the total number of infected cases, (iii) the total number of confirmed cases, (iv) the total number of deaths, and (v) the total number of cases recovered, etc. In this study, we use SIR, EG, SB, ML and TD models to analyze data to determine the reproduction number and pre-dict the epidemic trend of COVID-19 in Bangladesh, India and Pakistan.	./cache/cord-148145-qg5623s7.txt	./txt/cord-148145-qg5623s7.txt