TY - GEN
T1 - Mathematical analysis of a tuberculosis transmission model with vaccination in an age structured population
AU - Chasanah, S. L.
AU - Aldila, D.
AU - Tasman, H.
N1 - Funding Information:
This research was financially supported by Universitas Indonesia, with PITTA research grant scheme 2018 (Number ID: 2252/UN2.R3.1/HKP.05.00/2018).
Publisher Copyright:
© 2019 Author(s).
PY - 2019/3/22
Y1 - 2019/3/22
N2 -
This article presents a mathematical model of Tuberculosis (TB) transmission considering BCG vaccination in an age- structured population. We used several strategies to simulate the TB dynamic and evaluate the potential impact on active TB. We developed a deterministic compartmental model where the population was distributed into seven compartments, i.e., susceptible individuals that can be vaccinated (S
1
) and can't be vaccinated (S
2
), vaccinated (V), slow (L) and fast (E) exposed, infectious (I), and recovery (R). The mathematical model analysis was done by determining the equilibrium points, the Basic Reproduction Number (R
0
) of the model, and analysing the stability of the equilibrium point. Some numeric interpretations were given by sensitivity vaccination parameters and percentage vaccine protection to the value of R
0
and autonomous model simulations. We find that to reach TB free condition is not enough by maximising one of the vaccination parameters for newborn, adults or percentage vaccine protection. We also find that vaccination into the adult population is more effective to suppress TB spread rather than newborn.
AB -
This article presents a mathematical model of Tuberculosis (TB) transmission considering BCG vaccination in an age- structured population. We used several strategies to simulate the TB dynamic and evaluate the potential impact on active TB. We developed a deterministic compartmental model where the population was distributed into seven compartments, i.e., susceptible individuals that can be vaccinated (S
1
) and can't be vaccinated (S
2
), vaccinated (V), slow (L) and fast (E) exposed, infectious (I), and recovery (R). The mathematical model analysis was done by determining the equilibrium points, the Basic Reproduction Number (R
0
) of the model, and analysing the stability of the equilibrium point. Some numeric interpretations were given by sensitivity vaccination parameters and percentage vaccine protection to the value of R
0
and autonomous model simulations. We find that to reach TB free condition is not enough by maximising one of the vaccination parameters for newborn, adults or percentage vaccine protection. We also find that vaccination into the adult population is more effective to suppress TB spread rather than newborn.
UR - http://www.scopus.com/inward/record.url?scp=85063865556&partnerID=8YFLogxK
U2 - 10.1063/1.5094282
DO - 10.1063/1.5094282
M3 - Conference contribution
AN - SCOPUS:85063865556
T3 - AIP Conference Proceedings
BT - Proceedings of the Symposium on BioMathematics, SYMOMATH 2018
A2 - Handari, Bevina Desjwiandra
A2 - Seno, Hiromi
A2 - Tasman, Hengki
PB - American Institute of Physics Inc.
T2 - International Symposium on BioMathematics 2018, SYMOMATH 2018
Y2 - 31 August 2018 through 2 September 2018
ER -
