2021
DOI: 10.18280/ria.350202
|View full text |Cite
|
Sign up to set email alerts
|

Forecasting the Spread of COVID-19 Pandemic with Prophet

Abstract: COVID-19 pandemic shook the whole world with its brutality, and the spread has been still rising on a daily basis, causing many nations to suffer seriously. This paper presents a medical stance on research studies of COVID-19, wherein we estimated a time-series data-based statistical model using prophet to comprehend the trend of the current pandemic in the coming future after July 29, 2020 by using data at a global level. Prophet is an open-source framework discovered by the Data Science team at Facebook for … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
4
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 6 publications
(4 citation statements)
references
References 7 publications
0
4
0
Order By: Relevance
“…The finding of this study is consistent with an earlier study conducted in three countries, namely, Australia, Italy, and the UK, and indicates that the growth rate of confirmed cases will increase in the next year [ 48 ]. Another similar study conducted by Mahanty and team members observed that India, USA, and Brazil's growth rate of confirmed cases is increasing day by day, and the rate tends to be exponential [ 49 ]. In contrast, Hossain et al [ 50 ] showed that confirmed cases in Bangladesh gradually decreased for the next 40 days.…”
Section: Resultsmentioning
confidence: 99%
“…The finding of this study is consistent with an earlier study conducted in three countries, namely, Australia, Italy, and the UK, and indicates that the growth rate of confirmed cases will increase in the next year [ 48 ]. Another similar study conducted by Mahanty and team members observed that India, USA, and Brazil's growth rate of confirmed cases is increasing day by day, and the rate tends to be exponential [ 49 ]. In contrast, Hossain et al [ 50 ] showed that confirmed cases in Bangladesh gradually decreased for the next 40 days.…”
Section: Resultsmentioning
confidence: 99%
“…It's an additive regression model with trends like a piecewise linear growth curve or a logistic growth curve. It recognizes changes in patterns in real time by identifying data change points [17].…”
Section: Fb-prophet Methodmentioning
confidence: 99%
“…FB Prophet is adept at managing time series data characterized by significant seasonal fluctuations and a substantial historical data span. Notably, the Prophet model effectively manages outliers, even in scenarios involving missing data or shifts in trends [51] , [52] . The effective application of a Prophet model necessitates the variables y (target) and ds (Date Time) in the time series.…”
Section: Methodsmentioning
confidence: 99%