Epidemiological models often rely on several key assumptions:
1. Homogeneous Mixing: This assumption posits that every individual in the population has an equal chance of coming into contact with any other individual. While this simplifies the model, real-world populations often have structured interactions based on geography, social networks, and behavior.
2. Constant Population Size: Many models assume a closed population with no births, deaths, immigration, or emigration. This can be a significant limitation in long-term studies where demographic changes are inevitable.
3.
Fixed Infectious Period: Models like the
SIR model assume a constant infectious period for all individuals. However, the infectious period can vary significantly between individuals and diseases.
4. Instantaneous Mixing: This assumption implies that individuals mix and potentially spread the disease instantaneously, which overlooks the temporal dynamics of disease transmission.
5. No Latency Period: Some models assume that individuals become infectious immediately after being exposed, ignoring the incubation period characteristic of many diseases.
