MATHEMATICAL MODEL OF DENGUE INFECTION WITH AGE STRUCTURE
Dengue virus infection is still among the leading health problems in many endemic countries, including Indonesia, characterized by its high morbidity and widespread. It is known that the risk factor that influences the transmission intensity varies among the different age groups, which can have i...
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| Format: | Dissertations |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/74981 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Dengue virus infection is still among the leading health problems in many endemic
countries, including Indonesia, characterized by its high morbidity and widespread.
It is known that the risk factor that influences the transmission intensity varies
among the different age groups, which can have implications for dengue control
strategies. This dissertation presents a mathematical model of dengue infection
with a time-dependent infection rate and age structure in the human population.
The population of humans and mosquitoes will be represented by the Susceptible-
Infected-Recovered (SIR) model and the Susceptible-Infected (SI) model, respectively.
A vaccination scenario as a strategy to control dengue infection is also
applied in the model. Dengue case data from populated cities in Indonesia, such
as Semarang City and Bandung City, was used to estimate the constant and timedependent
infection rates. The main indicators can be obtained here to identify
the changes in dengue transmission intensity in each age group, such as the force
of infection (FoI) and reproduction number, both effective and basic reproduction
numbers. Numerical simulation results indicate that the youngster age group is at
high risk for dengue infection. Vaccination in this age group effectively reduced
the number of dengue cases in the studied cities. Therefore, future vaccination
strategies can be prioritized for the youngster to control the spread of dengue
infection.
The presence of early warning for dengue outbreaks can also assist in planning
more effective control strategies. In this study, a cumulative generating operator
is constructed using weekly dengue case data from Palu City to generate dynamic
solutions of a host-vector mathematical model. Based on the calculation of the
correlation over time, the effective reproduction number can be used as an early
warning indicator to predict future trends of dengue incidence. |
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