Traditional epidemiological models often rely on deterministic or probabilistic approaches. However, these models may not capture the full range of possibilities. By incorporating the concept of superposition, models can account for a broader spectrum of outcomes, enhancing their accuracy. This is particularly useful in scenarios of emerging infectious diseases where data is limited and uncertainties are high.
