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Understanding transmissibility patterns of Chagas disease through complex vector–host networks

Published online by Cambridge University Press:  12 January 2017

LAURA RENGIFO-CORREA ,
CHRISTOPHER R. STEPHENS ,
JUAN J. MORRONE ,
JUAN LUIS TÉLLEZ-RENDÓN  and
CONSTANTINO GONZÁLEZ-SALAZAR Open the ORCID record for CONSTANTINO GONZÁLEZ-SALAZAR [Opens in a new window]
LAURA RENGIFO-CORREA
Affiliation:
Museo de Zoología ‘Alfonso L. Herrera’, Departamento de Biología Evolutiva, Facultad de Ciencias, Universidad Nacional Autónoma de México, 04510 Mexico City, Mexico
CHRISTOPHER R. STEPHENS*
Affiliation:
C3 – Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, 04510 Mexico City, Mexico Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, 04510 Mexico City, Mexico
JUAN J. MORRONE
Affiliation:
Museo de Zoología ‘Alfonso L. Herrera’, Departamento de Biología Evolutiva, Facultad de Ciencias, Universidad Nacional Autónoma de México, 04510 Mexico City, Mexico
JUAN LUIS TÉLLEZ-RENDÓN
Affiliation:
Instituto de Diagnóstico y Referencia Epidemiológicos (INDRE), 01480 Mexico City, Mexico
CONSTANTINO GONZÁLEZ-SALAZAR
Affiliation:
C3 – Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, 04510 Mexico City, Mexico
*
*Corresponding author: C3 – Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México (UNAM), 04510 Mexico City, Mexico. E-mail: stephens@nucleares.unam.mx
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Summary

Chagas disease is one of the most important vector-borne zoonotic diseases in Latin America. Control strategies could be improved if transmissibility patterns of its aetiologic agent, Trypanosoma cruzi, were better understood. To understand transmissibility patterns of Chagas disease in Mexico, we inferred potential vectors and hosts of T. cruzi from geographic distributions of nine species of Triatominae and 396 wild mammal species, respectively. The most probable vectors and hosts of T. cruzi were represented in a Complex Inference Network, from which we formulated a predictive model and several associated hypotheses about the ecological epidemiology of Chagas disease. We compiled a list of confirmed mammal hosts to test our hypotheses. Our tests allowed us to predict the most important potential hosts of T. cruzi and to validate the model showing that the confirmed hosts were those predicted to be the most important hosts. We were also able to predict differences in the transmissibility of T. cruzi among triatomine species from spatial data. We hope our findings help drive efforts for future experimental studies.

Keywords

Trypanosoma cruzipotential hostsspatial data miningecological epidemiology
Type
Research Article
Information
Parasitology , Volume 144 , Issue 6 , May 2017 , pp. 760 - 772
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Copyright
Copyright © Cambridge University Press 2017 

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References

REFERENCES

Abad-Franch, F., Diotaiuti, L., Gurgel-Gonçalves, R. and Gürtler, R. E. (2013). Certifying the interruption of Chagas disease transmission by native vectors: cui bono? Memórias do Instituto Oswaldo Cruz 108, 251–254.Google Scholar
Bargues, M. D., Klisiowicz, D. R., Gonzalez-Candelas, F., Ramsey, J. M., Monroy, C., Ponce, C., Salazar-Schettino, P. M., Panzera, F., Abad-Franch, F., Sousa, O. E., Schofield, C. J., Dujardin, J. P., Guhl, F. and Mas-Coma, S. (2008). Phylogeography and genetic variation of Triatoma dimidiata, the main Chagas disease vector in Central America, and its position within the genus Triatoma . PLoS Neglected Tropical Diseases 2, e233.CrossRefGoogle ScholarPubMed
Berzunza-Cruz, M., Rodríguez-Moreno, Á., Gutiérrez-Granados, G., González-Salazar, C., Stephens, C. R., Hidalgo-Mihart, M., Marina, C. F., Rebollar-Téllez, E., Bailón-Martínez, D., Balcells, C., Ibarra-Cerdeña, C. N., Sánchez-Cordero, V. and Becker, I. (2015). Leishmania (L.) mexicana infected bats in Mexico: novel potential reservoirs. PLoS Neglected Tropical Diseases 9, 1–15.Google Scholar
Bosseno, M. F., Barnabé, C., Ramirez, M. J., Kengne, P., Guerrero, S., Lozano, F., Ezequiel, K., Gastélum, M. and Brenière, S. F. (2009). Wild ecotopes and food habits of Triatoma longipennis infected by Trypanosoma cruzi lineages I and II in Mexico. The American Journal of Tropical Medicine and Hygiene 80, 988–991.Google Scholar
Ceballos, G. and Arroyo-Cabrales, J. (2012). Lista actualizada de los mamíferos de México 2012. Revista Mexicana de Mastozoología, Nueva época 2, 28–80.Google Scholar
Dorn, P., Monroy, C. and Curtis, A. (2007). Triatoma dimidiata (Latreille, 1811): a review of its diversity across its geographic range and the relationship among populations. Infection, Genetics and Evolution 7, 343–352.Google Scholar
Dorn, P. L., Calderón, C., Melgar, S., Moguel, B., Solorzano, E., Dumonteil, E., Rodas, A., Rua, N., Garnica, R. and Monroy, C. (2009). Two distinct Triatoma dimidiata (Latreille, 1811) taxa are found in sympatry in Guatemala and Mexico. PLoS Neglected Tropical Diseases 3, e393.Google Scholar
González-Salazar, C. and Stephens, C. (2012). Constructing ecological networks: a tool to infer risk of transmission and dispersal of Leishmaniasis. Zoonoses and Public Health 59, 179–193.Google Scholar
González-Salazar, C., Stephens, C. and Marquet, P. A. (2013). Comparing the relative contributions of biotic and abiotic factors as mediators of species’ distributions. Ecological Modelling 248, 57–70.CrossRefGoogle Scholar
González-Salazar, C., Martínez-Meyer, E. and López-Santiago, G. (2014). A hierarchical classification of trophic guilds for North American birds and Mammals. Revista Mexicana de Biodiversidad 85, 931–941.Google Scholar
Graham, C. H., Ferrier, S., Huettman, F., Moritz, C. and Peterson, A. T. (2004). New developments in museum-based informatics and applications in biodiversity analysis. Trends in Ecology and Evolution 19, 497–503.Google Scholar
Herrera-Aguilar, M., Be-Barragán, L. A., Ramirez-Sierra, M. J., Tripet, F., Dorn, P. and Dumonteil, E. (2009). Identification of a large hybrid zone between sympatric sibling species of Triatoma dimidiata in the Yucatán Peninsula, Mexico, and its epidemiological importance. Infection, Genetics and Evolution 9, 1345–1351.Google Scholar
Jansen, A. M., and Roque, A. R. L. (2010). Domestic and wild mammalian reservoirs. In American Trypanosomiasis Chagas Disease. One Hundred Years of Research (ed. Telleria, J. and Tibayrenc, M.), pp. 249–276. Elsevier, Amsterdam.Google Scholar
Jansen, A. M., Xavier, S. C. C. and Roque, A. R. L. (2015). The multiple and complex and changeable scenarios of the Trypanosoma cruzi transmission cycle in the sylvatic environment. Acta Tropica 151, 1–15.Google Scholar
Lent, H. and Wygodzinsky, P. (1979). Revision of the Triatominae (Hemiptera, Reduviidae) and their significance as vectors of Chagas disease. Bulletin of the American Museum of Natural History 163, 123–520.Google Scholar
Martínez-Ibarra, J. A. and Novelo-López, M. (2004). Blood meals to molt, feeding time and postfeeding defecation delay of Meccus pallidipennis (Stål, 1872) (Hemiptera: Reduviidae) under laboratory conditions. Folia Entomologica Mexicana 43, 313–319.Google Scholar
Monteiro, F. A., Peretolchina, T., Lazoski, C., Harris, K., Dotson, E. M., Abad-Franch, F., Tamayo, E., Pennington, P. M., Monroy, C., Cordon-Rosales, C., Salazar-Schettino, P. M., Gómez-Palacio, A., Grijalva, M. J., Beard, C. B. and Marcet, P. L. (2013). Phylogeographic pattern and extensive mitocondrial DNA divergence disclose a species complex within the Chagas disease vector Triatoma dimidiata . PLoS ONE 8, e70974.Google Scholar
Morrone, J. J. (2009). Evolutionary Biogeography: an Integrative Approach with Case Studies. Columbia University Press, New York.Google Scholar
Mota, J., Chacon, J. C., Gutierrez, A., Sanchez-Cordero, V., Wirtz, R., Ordoñez, R., Panzera, F. and Ramsey, J. M. (2007). Identification of Chagas disease vector blood meal source using a multiplex cytochrome b PCR assay. Vector Borne Zoonotic Disease 7, 617–627.Google Scholar
Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., D'Amico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P. and Kassem, K. R. (2001). Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51, 933–938.Google Scholar
Ponder, W. F., Carter, G. A., Flemons, P. and Chapman, R. R. (2001). Evaluation of museum collection data for use in biodiversity assessment. Conservation Biology 15, 648–657.Google Scholar
Ramsey, J. M., Gutierrez-Cabrera, A. E., Salgado-Ramírez, L., Peterson, T. A., Sanchez-Cordero, V. and Ibarra-Cerdeña, C. N. (2012). Ecological connectivity of Trypanosoma cruzi reservoirs and Triatoma pallidipennis in an anthropogenic landscape with endemic Chagas disease. PLoS ONE 7, e46013.Google Scholar
Ramsey, J. M., Peterson, A. T., Carmona-Castro, O., Moo-Llanes, D. A., Nakazawa, Y., Butrick, M., Tun-Ku, E., Cruz-Félix, K. and Ibarra-Cerdeña, C. N. (2015). Atlas of Mexican Triatominae (Reduviidae: Hemiptera) and vector transmission of Chagas disease. Memórias do Instituto Oswaldo Cruz 110, 339–352.Google Scholar
Rodrigues-Coura, J. (2013). Chagas disease: control, elimination and eradication. Is it possible? Memórias do Instituto Oswaldo Cruz 108, 962–967.Google Scholar
Salazar-Schettino, P. M., Arteaga, I. H. and Cabrera, M. (2005). Tres especies de triatominos y su importancia como vectores de Trypanosoma cruzi en México. Medicina Buenos Aires 65, 63–69.Google Scholar
Sierra, R. and Stephens, C. R. (2012). Exploratory analysis of the interrelations between co-located Boolean spatial features using network graphs. International Journal of Geographical Information Science 26, 441–468.Google Scholar
Stephens, C. R., Heau, J. G., González, C., Ibarra-Cerdeña, C., Sánchez-Cordero, V. and González-Salazar, C. (2009). Using biotic interaction networks for prediction in biodiversity and emerging diseases. PLoS ONE 4, e5725.Google Scholar
Stephens, C. R., González-Salazar, C., Sánchez-Cordero, V., Becker, I., Rebollar-Tellez, E., Rodríguez-Moreno, Á., Berzunza-Cruz, M., Domingo Balcells, C., Gutiérrez-Granados, G., Hidalgo-Mihart, M., Ibarra-Cerdeña, C. N., Ibarra López, P., Iñiguez Dávalos, L. I. and Ramírez Martínez, M. M. (2016). Can you judge a disease host by the company it keeps? Predicting disease hosts and their relative importance: a case study for Leishmaniasis. PLoS Neglected Tropical Diseases 10, 1–21.Google Scholar
Varela, S., Anderson, R. P., García-Valdés, R. and Fernández-González, F. (2014). Environmental filters reduce the effects of sampling bias and improve predictions of ecological niche models. Ecography 37, 1084–1091.Google Scholar
Villalobos, G., Martínez-Hernández, F., de la Torre, P., Laclette, J. P. and Espinoza, B. (2011). Entomological indices, feeding sources, and molecular identification of Triatoma phyllosoma (Hemiptera: Reduviidae) one of the main vectors of Chagas disease in the Istmo de Tehuantepec, Oaxaca, Mexico. The American Journal of Tropical Medicine and Hygiene 85, 490–497.Google Scholar
World Health Organization (2015). Chagas Disease in Latin America: an Epidemiological Update Based on 2010 Estimates . WHO Weekly Epidemiological Record 90. World Health Organization, Geneva, Switzerland.Google Scholar
Yañez-Arenas, C., Guevara, R., Martínez-Meyer, E., Mandujano, S. and Lobo, J. M. (2014). Predicting species’ abundances from occurrence data: effects of sample size and bias. Ecological Modelling 294, 36–41.Google Scholar
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