Memory usage is critical in epidemiology for several reasons: 1. Large Datasets: Epidemiologists often work with extensive datasets that include patient information, disease incidence, geographic data, and more. Efficient memory management ensures that these datasets can be processed and analyzed without overwhelming computational resources. 2. Complex Models: Epidemiological models, such as agent-based models and compartmental models, require significant memory to simulate disease spread and intervention scenarios accurately. 3. Real-Time Analysis: During outbreaks, real-time data analysis is essential. Efficient memory usage ensures that data can be processed quickly to inform timely public health decisions.
