A comparison between a traditional SEIR-SEI epidemiological model and a multi-strain, multi-vector disease spread model

摘要

The spread of infectious diseases is a complex system in which pathogen, vector, and humans interact. Mathematical and simulation modeling has been a commonly applied tool to understand its dynamics. However, due to the trade-off between complexity, time, and accuracy, many assumptions are frequently made. One of the advantages of simulation over mathematical models is that one does not need to know the functional relationships between parameters, as long as one is capable of conceptually modeling the system and validating the model. Nevertheless, disease spread simulation models are usually bounded to single-strain and single-vector scenarios, and human behavior is frequently modeled in a simplistic manner or ignored. Here, we propose an agent-based simulation model where innovative mosquito population control action is considered coupled with multi-strain. The results are compared with a simpler traditional SEIR-SEI model with respect to epidemic outputs (number of individuals infected and duration of epidemics) and model measures (runtime and number of agents/entities). The immediate goal is to show the cost-effect of mimicking the reality more accurately and, in the long term, to improve the knowledge and understanding of disease spread dynamics, and to assist in the decision making process during epidemics.