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Mathematical modelling of vector-borne diseases and insecticide resistance evolution

Overview of attention for article published in Journal of Venomous Animals and Toxins including Tropical Diseases, July 2017
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Article details
Title
Mathematical modelling of vector-borne diseases and insecticide resistance evolution
Published in
Journal of Venomous Animals and Toxins including Tropical Diseases, July 2017
DOI 10.1186/s40409-017-0123-x
Pubmed ID
Authors
Abstract

Vector-borne diseases are important public health issues and, consequently, in silico models that simulate them can be useful. The susceptible-infected-recovered (SIR) model simulates the population dynamics of an epidemic and can be easily adapted to vector-borne diseases, whereas the Hardy-Weinberg model simulates allele frequencies and can be used to study insecticide resistance evolution. The aim of the present study is to develop a coupled system that unifies both models, therefore enabling the analysis of the effects of vector population genetics on the population dynamics of an epidemic. Our model consists of an ordinary differential equation system. We considered the populations of susceptible, infected and recovered humans, as well as susceptible and infected vectors. Concerning these vectors, we considered a pair of alleles, with complete dominance interaction that determined the rate of mortality induced by insecticides. Thus, we were able to separate the vectors according to the genotype. We performed three numerical simulations of the model. In simulation one, both alleles conferred the same mortality rate values, therefore there was no resistant strain. In simulations two and three, the recessive and dominant alleles, respectively, conferred a lower mortality. Our numerical results show that the genetic composition of the vector population affects the dynamics of human diseases. We found that the absolute number of vectors and the proportion of infected vectors are smaller when there is no resistant strain, whilst the ratio of infected people is larger in the presence of insecticide-resistant vectors. The dynamics observed for infected humans in all simulations has a very similar shape to real epidemiological data. The population genetics of vectors can affect epidemiological dynamics, and the presence of insecticide-resistant strains can increase the number of infected people. Based on the present results, the model is a basis for development of other models and for investigating population dynamics.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 7 15%
Student > Master 7 15%
Student > Ph. D. Student 5 11%
Researcher 4 9%
Lecturer 3 6%
Other 2 4%
Unknown 19 40%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 11%
Agricultural and Biological Sciences 5 11%
Mathematics 3 6%
Computer Science 3 6%
Veterinary Science and Veterinary Medicine 2 4%
Other 7 15%
Unknown 22 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 July 2017.
All research outputs
#19,159,670
of 27,788,586 outputs
Outputs from Journal of Venomous Animals and Toxins including Tropical Diseases
#312
of 516 outputs
Outputs of similar age
#216,444
of 333,524 outputs
Outputs of similar age from Journal of Venomous Animals and Toxins including Tropical Diseases
#7
of 9 outputs
Altmetric has tracked 27,788,586 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 516 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 333,524 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.