id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-270519-orh8fd1c	Oliveira, A. C. S. d.	Bayesian modeling of COVID-19 cases with a correction to account for under-reported cases	2020-05-25		.txt	text/plain	4263	231	55	To address these issues, we introduce a Bayesian approach to the SIR model with correction for under-reporting in the analysis of COVID-19 cases in Brazil. The proposed model was enforced to obtain estimates of important quantities such as the reproductive rate and the average infection period, along with the more likely date when the pandemic peak may occur. Focusing on the modeling and estimating, aiming to preview the behavior and the speed of the COVID-19 growth, this paper presents an approach to address the problem of under-registration of COVID-19 cases in Brazil, proposing methodologies to work on the inaccuracy of the official reported cases. The model was estimated considering COVID-19 data in Brazil, assuming a reporting rate between 0.05 and 1.00, varying every 0.05. The simulation study revealed that the parameters estimates from the SIR model and the peak estimate which is a concern of several researchers and health authorities are sensitive to reporting rates.	./cache/cord-270519-orh8fd1c.txt	./txt/cord-270519-orh8fd1c.txt