TY - GEN
T1 - Using the SVIRS model to understand the prevention strategy for influenza with vaccination
AU - Husnulkhotimah, H.
AU - Rusin, R.
AU - Aldila, D.
N1 - Funding Information:
The authors thank the reviewer for their valuable comments. This research is funded by Universitas Indonesia with PUTI SAINTEKES grant scheme, 2020 (ID Number: NKB-2387/UN2.RST/HKP.05.00/2020).
Publisher Copyright:
© 2021 Author(s).
PY - 2021/7/23
Y1 - 2021/7/23
N2 - Influenza is an infectious disease that can threaten the lives of people at high risk of complications. As vaccines are expected to strongly aid the prevention of diseases such as influenza and COVID-19, this research discusses how a modification of the well-known Susceptible-Vaccinated-Infected-Recovered-Susceptible (SVIRS) model can help prevent these diseases. This study involves employing a combination of vaccination and social distancing as a means of preventing these diseases. The SVIRS model divides the human population into four subpopulations:, those susceptible to influenza, vaccinated, infected, and recovered from influenza. Subpopulations of people who have been given the vaccine are also assumed to be susceptible to influenza, owing to the imperfect effectiveness of the vaccine. Also, since immunity to the disease is not life-long, there is a possibility that recovered individuals may get re-infected. Analytical studies of the nondimensionalization process and the existence and stability of the equilibrium points were carried out on the model, using the bifurcation analysis. Finally, a few numerical simulations were carried out using several scenarios of vaccination and social distancing strategies. Our model indicated the possibility of backward bifurcation at R0 = 1. Based on the analytical studies, R0 gave an insight to determine the best strategy that can be used to prevent the spread of influenza among the population.
AB - Influenza is an infectious disease that can threaten the lives of people at high risk of complications. As vaccines are expected to strongly aid the prevention of diseases such as influenza and COVID-19, this research discusses how a modification of the well-known Susceptible-Vaccinated-Infected-Recovered-Susceptible (SVIRS) model can help prevent these diseases. This study involves employing a combination of vaccination and social distancing as a means of preventing these diseases. The SVIRS model divides the human population into four subpopulations:, those susceptible to influenza, vaccinated, infected, and recovered from influenza. Subpopulations of people who have been given the vaccine are also assumed to be susceptible to influenza, owing to the imperfect effectiveness of the vaccine. Also, since immunity to the disease is not life-long, there is a possibility that recovered individuals may get re-infected. Analytical studies of the nondimensionalization process and the existence and stability of the equilibrium points were carried out on the model, using the bifurcation analysis. Finally, a few numerical simulations were carried out using several scenarios of vaccination and social distancing strategies. Our model indicated the possibility of backward bifurcation at R0 = 1. Based on the analytical studies, R0 gave an insight to determine the best strategy that can be used to prevent the spread of influenza among the population.
KW - basic reproduction number
KW - bifurcation
KW - Influenza
KW - Mathematical model
UR - http://www.scopus.com/inward/record.url?scp=85112042558&partnerID=8YFLogxK
U2 - 10.1063/5.0058692
DO - 10.1063/5.0058692
M3 - Conference contribution
AN - SCOPUS:85112042558
T3 - AIP Conference Proceedings
BT - Proceedings of the 6th International Symposium on Current Progress in Mathematics and Sciences 2020, ISCPMS 2020
A2 - Ivandini, Tribidasari A.
A2 - Churchill, David G.
A2 - Lee, Youngil
A2 - Alias, Yatimah Binti
A2 - Margules, Chris
PB - American Institute of Physics Inc.
T2 - 6th International Symposium on Current Progress in Mathematics and Sciences 2020, ISCPMS 2020
Y2 - 27 October 2020 through 28 October 2020
ER -