COVID-19 Pandemic Outbreak in the Subcontinent: A data-driven analysis
- URL: http://arxiv.org/abs/2008.09803v1
- Date: Sat, 22 Aug 2020 10:40:17 GMT
- Title: COVID-19 Pandemic Outbreak in the Subcontinent: A data-driven analysis
- Authors: Bikash Chandra Singh, Zulfikar Alom, Mohammad Muntasir Rahman, Mrinal
Kanti Baowaly, Mohammad Abdul Azim
- Abstract summary: COVID-19 virus emerged in late December 2019 in Wuhan city, Hubei, China.
Numerous studies claim that the subcontinent could remain in the worst affected region by the COVID-19.
This paper uses publicly available epidemiological data of Bangladesh, India, and Pakistan to estimate the reproduction numbers.
- Score: 0.8057708414390126
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Human civilization is experiencing a critical situation that presents itself
for a new coronavirus disease 2019 (COVID-19). This virus emerged in late
December 2019 in Wuhan city, Hubei, China. The grim fact of COVID-19 is, it is
highly contagious in nature, therefore, spreads rapidly all over the world and
causes severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Responding
to the severity of COVID-19 research community directs the attention to the
analysis of COVID-19, to diminish its antagonistic impact towards society.
Numerous studies claim that the subcontinent, i.e., Bangladesh, India, and
Pakistan, could remain in the worst affected region by the COVID-19. In order
to prevent the spread of COVID-19, it is important to predict the trend of
COVID-19 beforehand the planning of effective control strategies.
Fundamentally, the idea is to dependably estimate the reproduction number to
judge the spread rate of COVID-19 in a particular region. Consequently, this
paper uses publicly available epidemiological data of Bangladesh, India, and
Pakistan to estimate the reproduction numbers. 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. Experimental results show that the
reproduction numbers produced by these models are greater than 1.2
(approximately) indicates that COVID-19 is gradually spreading in the
subcontinent.
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