Mathematical models for epidemic spread play a crucial role in understanding and predicting the behavior of infectious diseases. These models provide valuable insights into how diseases propagate through populations, helping public health officials and policymakers make informed decisions to control outbreaks. With advancements in computational techniques and predictive analytics, researchers can now simulate and analyze epidemic dynamics with greater accuracy and detail. This article explores the various mathematical models used to study epidemic spread, their computational insights, and the role of predictive analytics in managing public health crises.
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Journal of Applied & Computational Mathematics received 1282 citations as per Google Scholar report
