👉 Mathematics plays a crucial role in understanding viral dynamics, particularly in modeling the spread and impact of viral infections. Key concepts include exponential growth models to describe how quickly a virus can spread in a population, where the rate of infection is proportional to the number of infected individuals. Logistic growth models are also used to account for the carrying capacity of the environment, reflecting how factors like immunity and resource limitations slow down infection rates. Additionally, compartmental models, such as the SIR (Susceptible-Infected-Recovered) model, divide the population into different states to simulate the progression of an outbreak and predict the effects of interventions like vaccination or social distancing. These mathematical frameworks help researchers and public health officials make informed decisions to control viral spread and mitigate outbreaks.
