Mathematical modelling of vector-borne diseases and insecticide resistance evolution

• Published in: Journal of Venomous Animals and Toxins including Tropical Diseases
• Main Authors: Maria Laura Gabriel Kuniyoshi, Fernando Luiz Pio dos Santos
• Format: Article in Journal/Newspaper
• Language: English
• Published: SciELO 2017
• Subjects: Epidemiology; Population genetics; Tropical diseases; Insecticides; Theoretical modelling; Numerical simulation; Arctic medicine. Tropical medicine; RC955-962; Toxicology. Poisons; RA1190-1270; Zoology; QL1-991; Arctic
• Online Access: https://doi.org/10.1186/s40409-017-0123-x; https://doaj.org/article/a08c9e814d564a74b70d4d4af7d19296

Abstract Background 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. Methods 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. Results 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. Conclusion 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 ...