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COVID-19 Pandemic Outbreak in the Subcontinent: A Data Driven Analysis.

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The COVID-19 pandemic is spreading rapidly in Bangladesh, India, and Pakistan. This study estimates reproduction numbers using various models, indicating continued transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Keywords:
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Area of Science:

  • Epidemiology
  • Infectious Disease Modeling

Background:

  • The COVID-19 pandemic, caused by SARS-CoV-2, emerged in late 2019 and poses a critical global health threat.
  • South Asian countries like Bangladesh, India, and Pakistan are projected to be severely affected.
  • Predicting disease trends is crucial for implementing effective control strategies.

Purpose of the Study:

  • To estimate the reproduction number of COVID-19 in Bangladesh, India, and Pakistan.
  • To assess the spread rate of SARS-CoV-2 in the subcontinent.
  • To evaluate the fitness of various epidemiological models for predicting COVID-19 trends.

Main Methods:

  • Utilized publicly available epidemiological data from Bangladesh, India, and Pakistan.
  • Employed multiple mathematical models including Susceptible Infection Recovery (SIR), Exponential Growth (EG), Sequential Bayesian (SB), Maximum Likelihood (ML), and Time Dependent (TD).
  • Estimated reproduction numbers and analyzed model performance against the data.

Main Results:

  • Reproduction numbers estimated by all models were consistently above 1.2.
  • This indicates a sustained and gradual spread of COVID-19 within the studied regions.
  • Model fitness varied, suggesting different predictive accuracies for each approach.

Conclusions:

  • COVID-19 continues to spread progressively in Bangladesh, India, and Pakistan.
  • Accurate estimation of reproduction numbers is vital for public health interventions.
  • Further research into model selection and data accuracy is warranted for precise forecasting.