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Modelling the influence of host community composition in a sylvatic Trypanosoma cruzi system

Published online by Cambridge University Press:  13 July 2017

DIANA ERAZO
Affiliation:
BIOMAC-Mathematical and Computational Biology, Universidad de los Andes, Cra 1 este # 19 a-40, Bogota, Colombia
JUAN CORDOVEZ
Affiliation:
BIOMAC-Mathematical and Computational Biology, Universidad de los Andes, Cra 1 este # 19 a-40, Bogota, Colombia
CAROLINA CABRERA
Affiliation:
Department of Pathology, School of Veterinary Medicine, The University of Georgia, 501 DW Brooks Drive, Athens, GA 30602, USA
JOSE E. CALZADA
Affiliation:
Department of Parasitology, Instituto Conmemorativo Gorgas de Estudios de la Salud, Apartado Postal 0816-02593, Panama City, Panama
AZAEL SALDAÑA
Affiliation:
Department of Parasitology, Instituto Conmemorativo Gorgas de Estudios de la Salud, Apartado Postal 0816-02593, Panama City, Panama
NICOLE L. GOTTDENKER*
Affiliation:
Department of Pathology, School of Veterinary Medicine, The University of Georgia, 501 DW Brooks Drive, Athens, GA 30602, USA
*
*Corresponding author: Department of Pathology, School of Veterinary Medicine, The University of Georgia, 501 DW Brooks Drive, Athens, GA 30602, USA. E-mail: gottdenk@gmail.com

Summary

Species composition of wild reservoir hosts can influence the transmission and maintenance of multi-host vector borne pathogens. The ‘pace of life’ hypothesis proposes that the life history strategy of reservoir hosts can influence pathogen transmission of vector borne generalist pathogens. We use empirical data to parameterize a mathematical model that investigates the impacts of host life history traits on vector transmission dynamics of the vector-borne multi-host parasite Trypanosoma cruzi in habitats characterized by different degrees of deforestation and varying host community structure. The model considers susceptible and infected vector and host populations. When comparing the proportion of vectors infected with T. cruzi predicted by the model with empirical data, we found a trend of increasing vector infection as anthropogenic landscape disturbance increases for both data and model output. The model's vector infection rates were significantly lower than empirical results, but when incorporating host congenital transmission in the model, vector infection approaches field data. We conclude that intervened habitats associated with r-selected host species communities predict higher proportions of infected vectors.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2017 

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References

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