Simulation modelling reproduces the behaviour of a system using a mathematical model. It is used to explore and gain new insights into systems too complex for analytical solutions — and many biological systems are complex. Simulation models are established tools in physics, climatology, chemistry, biology, economics, the social sciences and engineering; their further use in medical research, and specifically for vector-borne diseases, is highly valuable.
Example: mosquito vectors of Rift Valley fever
In Mweya et al. (2014, PLoS ONE), time-varying distributed delays and multi-way functional responses were used to simulate the development stages of mosquito vectors and their hosts, and the interactions between them, built in C++ with the open-source Universal Simulator. Floodwater Aedes and Culex populations fluctuated with temperature and water level, controlled by the availability of hosts for blood feeding. Infection entered the system through floodwater Aedes, and Culex amplified it. The simulated mosquito population showed an unusual increase between December 1997 and January 1998 — the period of the Rift Valley fever outbreak in Ngorongoro District.
The model has since been re-implemented as open Python software, rvf-vector-model, which drives the RVF Early Warning Platform.