Simplified models often rely on several key assumptions to reduce complexity:
1. Homogeneity: Assumes that every individual in the population has an equal chance of interacting with every other individual. 2. Constant Population Size: Assumes that the population size remains constant over the study period, ignoring births and deaths unrelated to the disease. 3. Fixed Transmissibility: Assumes that the probability of disease transmission per contact is constant. 4. Instantaneous Mixing: Assumes that individuals mix uniformly and instantaneously.
These assumptions can be relaxed in more complex models, but doing so often increases the computational and data requirements.
