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Abstract
In this paper we have adapted a delayed dengue model to Zika. By assuming that the epidemic starts by a single infected individual entering a disease-free population at some initial time t0 we have used the least squares parameter estimation technique in R to estimate the initial time t0 using observed Zika data from Brazil as well as the transmission probabilities of Zika in Brazil between humans and mosquitoes and vice-versa. Different values of Aedes aegypti (A. aegypti) biting rate are used throughout the paper.
We have estimated the value of the basic reproduction number for Zika in Brazil and calculated the expected number of cases of microcephaly in newborns as a result of women infected with Zika during pregnancy. We started off with a non-age-structured model then introduced age-structure into the model.
However in reality seasonality, in particular temperature and rainfall, have a great impact on the population size of A. aegypti. Hence we repeat both the non-age-structured and age-structured analyses introducing seasonality into the A. aegypti birth function to model the effect of these environmental factors.
We have estimated the value of the basic reproduction number for Zika in Brazil and calculated the expected number of cases of microcephaly in newborns as a result of women infected with Zika during pregnancy. We started off with a non-age-structured model then introduced age-structure into the model.
However in reality seasonality, in particular temperature and rainfall, have a great impact on the population size of A. aegypti. Hence we repeat both the non-age-structured and age-structured analyses introducing seasonality into the A. aegypti birth function to model the effect of these environmental factors.
Original language | English |
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Pages (from-to) | 8217–8242 |
Number of pages | 26 |
Journal | Mathematical Biosciences and Engineering |
Volume | 16 |
Issue number | 6 |
DOIs | |
Publication status | Published - 16 Sept 2019 |
Keywords
- Zika virus
- microcephaly
- dengue
- aedes aegypti
- parameter estimation
- least square estimation
- ordinary differential equations
- partial differential equations
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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