Transition Probability Density Function for Number of Infections in a Population Satisfying a Stochastic SIS-Epidemic Model
Related Event
Title
Event type
ConferenceDate
04/02/2021 - 04/03/2021Location
Abstract
By assuming a certain population is randomly fluctuating and subject to a continuous spectrum of disturbances at a given time, we derive and analyze the time-dependent probability density function (PDF) for the number of susceptible and infected individuals at a given time in a stochastic Susceptible-Infective-Susceptible (SIS) epidemic model with vital dynamics. The PDF is obtained for the case where fluctuation is present in the transmission and recovery rates of the disease. With the PDF, the closed-form expression for the mean number of infections at each given time is obtained. The effect of noise, together with the effect of changes in epidemiological parameters on the distribution are investigated. Properties of the distribution, namely, the time-dependent mean, variance, skewness, and kurtosis are obtained and analyzed. The correctness of the work done is verified and validated using population and published parameters.
Publication Information
Output type
Original language
English (US)Pages from-to (Number of pages)
Pages 111-139 (29 pages)Publication milestones
- Published - 2024
Publication status
Publisher
SpringerPublication series
- Publication series name: Springer Proceedings in Mathematics and Statistics
ISSN (Print): 2194-1009
ISSN (Electronic): 2194-1017
Volume: 472
ISBN (Print)
9783031697098Publication IDs
- Scopus: 85210151371
- ORCID: /0000-0002-8360-9094/work/174020024
Host publication title
Applied Mathematical Analysis and Computations II - 1st SGMCHost publication editors
- Divine Wanduku
- Shijun Zheng
- Zhan Chen
- Andrew Sills
- Haomin Zhou
- Ephraim Agyingi
