UPM Institutional Repository

Stochastic SIS modelling: coinfection of two pathogens in two-host communities


Citation

Abdullahi, Auwal and Shohaimi, Shamarina and Kilicman, Adem and Ibrahim, Mohd Hafiz and Salari, Nader (2020) Stochastic SIS modelling: coinfection of two pathogens in two-host communities. Entropy, 22 (1). art. no. 54. pp. 1-12. ISSN 1099-4300

Abstract

A pathogen can infect multiple hosts. For example, zoonotic diseases like rabies often colonize both humans and animals. Meanwhile, a single host can sometimes be infected with many pathogens, such as malaria and meningitis. Therefore, we studied two susceptible classes S1(t) and S2(t) , each of which can be infected when interacting with two different infectious groups I1(t) and I2(t) . The stochastic models were formulated through the continuous time Markov chain (CTMC) along with their deterministic analogues. The statistics for the developed model were studied using the multi-type branching process. Since each epidemic class was assumed to transmit only its own type of pathogen, two reproduction numbers were obtained, in addition to the probability-generating functions of offspring. Thus, these, together with the mean number of infections, were used to estimate the probability of extinction. The initial population of infectious classes can influence their probability of extinction. Understanding the disease extinctions and outbreaks could result in rapid intervention by the management for effective control measures.


Download File

[img] Text
38195.pdf
Restricted to Repository staff only

Download (834kB)

Additional Metadata

Item Type: Article
Divisions: Faculty of Science
Institute for Mathematical Research
DOI Number: https://doi.org/10.3390/e22010054
Publisher: MDPI
Keywords: Branching process; Continuous time Markov chain; Epidemic extinction; Gillespie algorithm; Basic reproduction number; Stochastic differential equation
Depositing User: Nabilah Mustapa
Date Deposited: 04 May 2020 15:51
Last Modified: 04 May 2020 15:51
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/e22010054
URI: http://psasir.upm.edu.my/id/eprint/38195
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item