| Issue |
E3S Web Conf.
Volume 371, 2023
International Scientific Conference “Fundamental and Applied Scientific Research in the Development of Agriculture in the Far East” (AFE-2022)
|
|
|---|---|---|
| Article Number | 01053 | |
| Number of page(s) | 8 | |
| Section | Smart Farming and Precision Agriculture | |
| DOI | https://doi.org/10.1051/e3sconf/202337101053 | |
| Published online | 28 February 2023 | |
System-Dynamic simulation of the Cholera spread
1 Don State Technical University, 344003 Rostov-on-Don, Russia
2 Rostov-on-Don Research Anti-Plague Institute, 344002 Rostov-on-Don, Russia
* Corresponding author: anisimovagalina@mail.ru
One of the frequently used modern epidemiological methods is the simulation of disease spread. We used AnyLogic simulation. System-dynamic model is presented here. It may be used for strategic modelling of the epidemiological situation and reflects the global trends. During the model construction, we take into account the specific cholera features, such as the pathways of infection transmission, the course duration and the duration of the incubation (latent) period, the possibility of vaccination, etc. Different cholera strains correspond to different parameter values. Anylogic makes it possible to visualize the epidemic spread in movement at various values of the model parameters and it looks like cartoon. It also gives the possibility to select and clarify the parameter values. For convenience, when building the model, we used sliders. They help in the selection of parameters to change quickly the values of the model parameters, including the effect of vaccination on the process of the disease spread. We were able to compare the results obtained by simulating the disease spread with specific data on real cholera spread. Our results of the study indicate that the used model can be effectively applied for forecasting. By analyzing the results of modeling with varying parameters, it is possible to predict the dynamics of the cholera spread.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.