Sanusi, U.; Abdulfatah, S.; Sani, S. Managing Infectious Diseases Under Quiescence. Preprints2023, 2023121159. https://doi.org/10.20944/preprints202312.1159.v1
APA Style
Sanusi, U., Abdulfatah, S., & Sani, S. (2023). Managing Infectious Diseases Under Quiescence. Preprints. https://doi.org/10.20944/preprints202312.1159.v1
Chicago/Turabian Style
Sanusi, U., Saratu Abdulfatah and Sulaiman Sani. 2023 "Managing Infectious Diseases Under Quiescence" Preprints. https://doi.org/10.20944/preprints202312.1159.v1
Abstract
In this work, quiescence is added to the Susceptible-Infectious-Recovered (SIR) model with demography. In order to investigate consequences of quiescence in the infection process in more depth, we use stochastic simulations on the stochastic version of model that we built. This method provides a more accurate picture of the dynamics of infectious diseases by taking into consideration the inherent randomness in the disease processes. We examine the effects of quiescence on the number of infected people using simulations. The results, presented in histograms depicting the distribution of infected individuals, reveal a notable trend: the mean number of infected individuals is higher when quiescence is incorporated into the dynamics. These finding emphasizes the dynamic influence of quiescence on infectious disease spread. The higher mean number of infections during periods of quiescence highlights the need for public health strategies that are flexible enough to focused interventions during these times to reduce the possibility of an increase in infections.
Keywords
Parasite quiescence; Managing; Model; stochasticity; Public Health; Prevention
Subject
Computer Science and Mathematics, Mathematical and Computational Biology
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.
