Prediction and mathematical analysis of the outbreak of coronavirus (COVID-19) in Bangladesh

Shahrear, Pabel; Rahman, Shahedur; Nahid, Mahadi Hasan

doi:10.1016/j.rinam.2021.100145

Cited by 17 publications

(9 citation statements)

References 27 publications

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“…In terms of recovered cases, the number of recovered people has increased since October 2021 ( Figure 3 ). A previous study in Bangladesh by applying the SEQIRP model (modified SIR model) observed that, after 400 days (April 2021), the actual recovery rate was increasing, with a value of roughly 0.56 [ 47 ].…”

Section: Resultsmentioning

confidence: 99%

Prediction of COVID-19 Pandemic in Bangladesh: Dual Application of Susceptible-Infective-Recovered (SIR) and Machine Learning Approach

Haq

Hossain

Saleheen

et al. 2022

Interdisciplinary Perspectives on Infectious Diseases

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The outbreak of COVID-19 is a global problem today, and, to reduce infectious cases and increase recovered cases, it is relevant to estimate the future movement and pattern of the disease. To identify the hotspot for COVID-19 in Bangladesh, we performed a cluster analysis based on the hierarchical k-means approach. A well-known epidemiological model named “susceptible-infectious-recovered (SIR)” and an additive regression model named “Facebook PROPHET Procedure” were used to predict the future direction of COVID-19 using data from IEDCR. Here we compare the results of the optimized SIR model and a well-known machine learning algorithm (PROPHET algorithm) for the forecasting trend of the COVID-19 pandemic. The result of the cluster analysis demonstrates that Dhaka city is now a hotspot for the COVID-19 pandemic. The basic reproduction ratio value was 2.1, which indicates that the infection rate would be greater than the recovery rate. In terms of the SIR model, the result showed that the virus might be slightly under control only after August 2022. Furthermore, the PROPHET algorithm observed an altered result from SIR, implying that all confirmed, death, and recovered cases in Bangladesh are increasing on a daily basis. As a result, it appears that the PROPHET algorithm is appropriate for pandemic data with a growing trend. Based on the findings, the study recommended that the pandemic is not under control and ensured that if Bangladesh continues the current pattern of infectious rate, the spread of the pandemic in Bangladesh next year will increase.

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Section: Resultsmentioning

confidence: 99%

Prediction of COVID-19 Pandemic in Bangladesh: Dual Application of Susceptible-Infective-Recovered (SIR) and Machine Learning Approach

Haq

Hossain

Saleheen

et al. 2022

Interdisciplinary Perspectives on Infectious Diseases

View full text Add to dashboard Cite

show abstract

“…Parsamanesh and Erfanian [ 20 ] looked at the global dynamics of a model with a standard incidence rate and immunization approach. Shahrear et al [ 21 ] have predicted and mathematically analyzed the COVID-19 outbreak in Bangladeshi scenario, and Maugeri et al [ 22 ] have analyzed the transmission of the COVID-19 pandemic in Saudi Arabia and Indonesia. By eliciting behavioural reactions in the community, Saha et al [ 23 ] explored an epidemic model of the COVID-19 outbreak.…”

Section: Introductionmentioning

confidence: 99%

Global Stability Analysis and Parameter Estimation for a Diphtheria Model: A Case Study of an Epidemic in Rohingya Refugee Camp in Bangladesh

Islam

Ahmed

Rahman

et al. 2022

Computational and Mathematical Methods in Medicine

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In this article, we have developed a deterministic Susceptible-Latent-Infectious-Recovered (SLIR) model for diphtheria outbreaks. Here, we have studied a case of the diphtheria outbreak in the Rohingya refugee camp in Bangladesh to trace the disease dynamics and find out the peak value of the infection. Both analytical and numerical investigations have been performed on the model to find several remarkable behaviors like the positive and bounded solution, basic reproductive ratio, and equilibria such as disease extinction equilibrium and disease persistence equilibrium which are characterized depending on the basic reproductive ratio and global stability of the model using Lyapunov function for both equilibria. Parameter estimation has been performed to determine the values of the parameter from the daily case data using numerical technique and determined the value of the basic reproductive number for the outbreak as R 0 = 5.86 .

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“…Dauda et al [ 3 ] on the other hand focused on Plateau State with emphasis on statistical analysis of lockdown, locus of control and state anxiety among residents. Furthermore, while some studies focused on hybrid fractional order, fractional optimal control and stochastic models [ 13 – 16 ], some other recent studies predicted outbreak of coronavirus and assessment of control measures as well as Neyman–Scott point process model for COVID-19 both within and across international borders [ 17 – 20 ]. However, from the foregoing researches and other previously published works [ 21 – 27 ], there has not been any published research to date which has considered a mathematical model approach for the transmission dynamics of the spread of COVID-19 in Plateau State Nigeria.…”

Section: Introductionmentioning

confidence: 99%

Mathematical model of the spread of COVID-19 in Plateau State, Nigeria

Adedire

Ndam

2022

J Egypt Math Soc

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In this research, a mathematical model consisting of non-pharmaceutical control measures is formulated. The developed model helps to examine the transmission of COVID-19 infection in Plateau State, Nigeria, using face masks$$c_{f}$$cfand social distancing$$c_{d}$$cdas control measures. Data used for the simulation of the developed model were obtained from Nigeria Centre for Disease Control which was fitted to the system of ordinary differential equations using nonlinear least squares method. Results at baseline values$$c_{f} = 0.1$$cf=0.1and$$c_{d} = 0.2$$cd=0.2of control measures indicate 2.3 estimation as basic reproduction number which suggests that COVID-19 in Plateau State tends towards endemic state. However, above about 40% in the use of face masks in the population and corresponding above 50% adherence to social distancing could as well bring down the basic reproduction number to a value below 1 necessary for disease eradication. The results at baseline values further indicate that the peak of the COVID-19 had been reached in less than 250 days from the first detection date after about 476,455 undetected asymptomatic individuals, 92,168 undetected symptomatic individuals and 83,801 detected quarantined individuals have been fully infectious. Therefore, the policymakers in Plateau State have the possibility of eradicating the disease with further strict non-pharmaceutical control measures provided that the present conditions of analysis remain fairly the same.

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Prediction and mathematical analysis of the outbreak of coronavirus (COVID-19) in Bangladesh

Cited by 17 publications

References 27 publications

Prediction of COVID-19 Pandemic in Bangladesh: Dual Application of Susceptible-Infective-Recovered (SIR) and Machine Learning Approach

Prediction of COVID-19 Pandemic in Bangladesh: Dual Application of Susceptible-Infective-Recovered (SIR) and Machine Learning Approach

Global Stability Analysis and Parameter Estimation for a Diphtheria Model: A Case Study of an Epidemic in Rohingya Refugee Camp in Bangladesh

Mathematical model of the spread of COVID-19 in Plateau State, Nigeria

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