State-by-state influenza outbreaks and oversee: A Markov chain study of California and North Carolina, USA.

ABSTRACT: Influenza, a significant public health concern, spreads rapidly and causes seasonal epidemics and pandemics. Mathematical models are essential tools for devising effective strategies to combat this pandemic. Various models have been utilized to study influenza's transmission dynamics and control measures. This paper presents the SEIRS (Susceptible-Exposed-Infectious-Recovered-Susceptible) model to analyze the disease's transmission dynamics. The model analyzes real data from California and North Carolina to assess trends, identify key factors, and project the nationwide spread of the disease. Subsequently, we calculate the basic reproduction number ([Formula: see text]) using the next-generation matrix method. Sensitivity analysis using Latin Hypercube Sampling (LHS) has been conducted to

SUBMITTER: Akhi AA 

PROVIDER: S-EPMC12445519 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature