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Abstract
In this paper, we will start off by introducing the classical Ross-Macdonald model for vector-borne diseases which we use to describe the transmission of dengue between humans and Aedes mosquitoes in Shah Alam, which is a city and the state capital of Selangor, Malaysia. We will focus on analysing the effect of using the Mosquito Home System (MHS), which is an example of an autodissemination trap, in reducing the number of dengue cases by changing the Ross-Macdonald model. By using the national dengue data from Malaysia, we are able to estimate , which represents the initial growth rate of the dengue epidemic, and this allows us to estimate the number of mosquitoes in Malaysia. A mathematical expression is also constructed which allows us to estimate the potential number of breeding sites of Aedes mosquitoes. By using the data available from the MHS trial carried out in Section 15 of Shah Alam, we included the potential effect of the MHS into the dengue model and thus modelled the impact MHS has on the spread of dengue within the trial area. We then extended our results to analyse the effect of the MHSs on reducing the number of dengue cases in the whole of Malaysia. A new model was constructed with a basic reproduction number, R0,MalaMHS, which allows us to identify the required MHSs coverage needed to achieve extinction in Malaysia. Numerical simulations and tables of results were also produced to illustrate our results.
Original language | English |
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Article number | 1923479 |
Number of pages | 15 |
Journal | Computational and Mathematical Methods in Medicine |
Volume | 2019 |
DOIs | |
Publication status | Published - 4 Aug 2019 |
Keywords
- Dengue
- auto-dissemination trap
- mosquito home system
- ordinary differential equations
- delayed model
- Aedes mosquitoes
- numerical simulations
- Malaysia
- Sah Alam
- extinction
- basic reporduction number
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- 1 Finished
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EPSRC Institutional Sponsorship: Global Challenges Research Fund (GCRF) / R160677-105
EPSRC (Engineering and Physical Sciences Research Council)
1/06/16 → 31/03/17
Project: Research - Internally Allocated