Nyabadza, F.; Mushanyu, J.; Mbogo, R.; Muchatibaya, G. Modelling the Influence of Dynamic Social Processes on COVID-19 Infection Dynamics. Mathematics2023, 11, 963.
Nyabadza, F.; Mushanyu, J.; Mbogo, R.; Muchatibaya, G. Modelling the Influence of Dynamic Social Processes on COVID-19 Infection Dynamics. Mathematics 2023, 11, 963.
Nyabadza, F.; Mushanyu, J.; Mbogo, R.; Muchatibaya, G. Modelling the Influence of Dynamic Social Processes on COVID-19 Infection Dynamics. Mathematics2023, 11, 963.
Nyabadza, F.; Mushanyu, J.; Mbogo, R.; Muchatibaya, G. Modelling the Influence of Dynamic Social Processes on COVID-19 Infection Dynamics. Mathematics 2023, 11, 963.
Abstract
Human behaviour was tipped as the mainstay in the control of further SARS-CoV-2 (COVID-19) spread especially after the lifting of restrictions by many countries. Countries in which restrictions were lifted soon after the first wave, had subsequent waves of the COVID-19 infections and it remains to be seen whether there will be more waves. In this paper, we formulate a deterministic model for COVID-19 incorporating dynamic non-pharmaceutical interventions, dubbed social dynamics. The model steady states are determined and their stability analysed. Numerical simulations are carried out to determine the pack of various parameters that influence the social dynamics. In South Africa, the first wave was the only wave in which the only interventions rested solely on human behavior. The model is thus fitted to COVID-19 data on the first wave in South Africa. The results presented in this paper have implications on the trajectory of the pandemic in the presence of changing social processes.
Keywords
COVID-19; mathematical modelling; stability; dynamic social processes; simulations
Subject
Computer Science and Mathematics, Applied Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
