Revista de Biología Tropical ISSN Impreso: 0034-7744 ISSN electrónico: 2215-2075

Current and future ecological niche of Leishmaniasis (Kinetoplastida: Trypanosomatidae) in the Neotropical region
PT 64-3 set 2016
PDF (Español (España))
HTML (Español (España))


nicho ecológico
cambio climático
ecological niche
climate change

How to Cite

Moo-Llanes, D. A. (2016). Current and future ecological niche of Leishmaniasis (Kinetoplastida: Trypanosomatidae) in the Neotropical region. Revista De Biología Tropical, 64(3).


The leishmaniasis is a complex disease system, caused by the protozoan parasite Leishmania and transmitted to humans by the vector Lutzomyia spp. Since it is listed as a neglected disease according to the World Health Organization, the aim of this study was to determine the current and future niche of cutaneous and visceral leishmaniasis in the Neotropical region. We built the ecological niche model (ENM) of cutaneous (N= 2 910 occurrences) and visceral (N= 851 occurrences) leishmaniasis using MaxEnt algorithm. Nine bioclimatic variables (BIO1, BIO4, BIO5, BIO6, BIO7, BIO12, BIO13, BIO14, BIO15 (downloaded from the Worldclim) and disease occurrences data were used for the construction of ENM for three periods (current, 2050 and 2070) and four climate change scenarios (RCP 2.6, 4.5, 6.0 y 8.5). We analyzed the number of pixels occupied, identity niche, modified niche (stable, loss, and gain) and seasonality. Our analyses indicated the expansion for cutaneous leishmaniasis (CL), a comparison for visceral leishmaniasis (VL). We rejected the null hypothesis of niche identity between CL and VL with Hellinger’s index = 0.91 (0.92-0.98) and Schoener’s Index = 0.67 (0.85-1.00) but with an overlap niche of 56.3 %. The differences between the two leishmaniasis types were detected in relation to RCP scenarios and niche shifts (area gained / loss). Seasonality was more important for CL. We provided a current picture of CL and VL distributions and the predicted distributional changes associated to different climate change scenarios for the Neotropical region. We can anticipate that increasing range is likely although it will depend locally on the future trends in weather seasonality.
PDF (Español (España))
HTML (Español (España))


Almeida, A., de Andrade, R., & Werneck, G. L. (2011). Identification of risk areas for visceral leishmaniasis in Teresina, Piaui state, Brazil. American Journal of Tropical Medicine and Hygiene, 84(5), 681-687.

Alvar, J., Vélez, I. D., Bern, C., Herrero, M., Desjeux, P., Cano, J., … the WHO Leishmaniasis Control Team. (2012). Leishmaniasis worldwide and global estimates of its incidence. PLoS ONE, 7(5), e35671.

Anderson, R. P., Lew, D., & Peterson, A. T. (2003). Evaluating predictive models of species’ distributions: criteria for selecting optimal models. Ecological Modelling, 162(3), 211-232.

Araújo, M. B., Thuiller, W., & Pearson, R. G. (2006). Climate warming and the decline of amphibians and reptiles in Europe. Journal of Biogeography, 3, 1712-1728.

Baek, J. H., Lee, J., Lee, H. S., Hyun, Y. K., Cho, C., Kwon, W. T., … Byun, Y. H. (2013). Climate change in the 21st century simulated bye HadGEM-AO under representative concentration pathways. Asia-Pacific Journal of Atmospheric Sciences, 49(5), 603-618.

Barve, N. (2008). Tool for Partial-ROC versión 1. Lawrence, KS, USA: Biodiversity Institute. Retrieved from

Cabaniel, G., Rada, L., Blanco, J. J., Rodríguez-Morales, A. J., & Escalera, J. P. (2005). Impacto de los eventos de El Niño Southern Oscillation (ENSO) sobre la leishmaniosis cutánea en Sucre, Venezuela, a través del uso de información satelital, 1994-2003. Revista Peruana de Medicina Experimental de Salud Pública, 22(1), 32-38. Recuperado de

Caminade, C., Kovats, S., Rocklov, J., Tompkins, A. M., Morse, A. P., Colón-González, F. L., … Lloyd, S. J. (2014). Impact of climate change on global malaria distribution. Proceedings of the National Academy of Sciences of the United States of America, 111(9), 3286-3291.

Cárdenas, R., Sandoval, C. M., Rodríguez-Morales, A. J., & Franco-Paredes, C. (2006). Impact of climate variability in the occurrence of leishmaniasis in northeastern Colombia. American Journal of Tropical Medicine and Hygiene, 75(2), 273-277. Retrieved from

Carneiro, D., Bavia, M. E., Rocha, W., Tavares, A., Cardim, L., & Alemayehu, B. (2007). Application of spatio-temporal scan statistics for the detection of areas with increased risk for American visceral leishmaniasis in the state of Bahia, Brazil. Geospatial Health, 2(1), 113-126.

Carrada-Figueroa, G., Leal-Ascencio, V. J., Jiménez-Sastré, A., & López-Álvarez, J. (2014). Transmission of cutaneous leishmaniasis associated with cacao (Theobroma cacao) plantations in Tabasco. Gaceta Médica de México, 150, 494-502.

Chaves, L. F., & Pascual, M. (2007). Climate cycle and forecasts of cutaneous leishmaniasis, a nonstationary vector-borne disease. PLoS Medicine, 4(3), e123.

Chaves, L. F., Calzada, J. E., Valderrama, A., & Saldaña, A. (2014). Cutaneous leishmaniasis and sand fly fluctuations are associated with El Niño in Panamá. PLoS Neglected Tropical Diseases, 8(10), e3210.

Chelbi, I., Kaabi, B., Bejaoui, M., Derbali, M., & Zhioua, E. (2009). Spatial correlation between Phlebotomus papatasi Scopoli (Diptera: Psychodidae) and incidence of zoonotic cutaneous leishmaniasis in Tunisia. Journal of Medical Entomology, 46(2), 400-402.

Feijó, V. A., Paes, L. R., Dias, R. A., Amaku, M., Ferreira, J. S., dos Santos, R. B., & Ferreira, F. (2012). Space-time cluster analysis of America visceral leishmaniasis in Bauru, Sao Paulo State, Brazil. Caderno do Saúde Pública, 28(10), 1949-1964.

García, R. A., Araújo, M. B., Burgess, N. D., Foden, W. B., Gutsche, A., Rahbek, C., & Cabeza, M. (2014). Matching species traits to projected threats and opportunities from climate change. Journal of Biogeography, 41, 724-735.

González, C., Wang, O., Strutz, S. E., González-Salazar, C., Sánchez-Cordero, V., & Sarkar, S. (2010). Climate change and risk of leishmaniasis in North America: Predictions from ecological niche models of vector and reservoirs species. PLoS Neglected Tropical Diseases, 4(1), e585.

Harris, R. M., Grose, M. R., Lee, G., Bindoff, N. L., Porfirio, L. L., & Fox-Hughes, P. (2014). Climate projections for ecologist. WIREs Climate change, 5, 621-237.

Ikeda, D. H., Grady, K. C., Shuster, S. M., & Whitham, T. G. (2014). Incorporating climate change and exotic species into forecasts of Riparian Forest Distribution. PLoS ONE, 9(9), e107037.

IPCC-Intergovernmental Panel on Climate Change (2007). Cambio climático 2007. Informe de síntesis. Contribución de los grupos de trabajo I, II, III al Cuarto Informe de evaluación del Grupo Intergubernamental de Expertos sobre el cambio climático. Ginebra, Suiza.

IPCC-Intergovernmental Panel on Climate Change. (2013). Climate change 2013: The physical science basis. Contributions of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. United Kingdom and New York: Cambridge University Press.

King, R. J., Campbell-Lendrum, D. H., & Davies C. R. (2004). Predicting geographic variation in cutaneous leishmaniasis, Colombia. Emerging Infectious Diseases, 10(4), 598-607.

Mollalo, A., Alimohammadi, A., Shirzadi, M. R., & Malek, M. R. (2015). Geographic information system-based analysis of the spatial and spatio-temporal distribution of zoonotic cutaneous leishmaniasis in Golestan Province, Nort-East of Iran. Zoonoses Public Health, 62(1), 18-28. doi:10.1111/zph.12109

Moo-Llanes, D. A., Ibarra-Cerdeña, C. N., Rebollar-Téllez, E. A., Ibáñez-Bernal, S., González, C., & Ramsey, J. M. (2013). Current and future niche of North and Central American sand flies (Diptera: Psychodidae) in climate change scenarios. PLoS Neglected Tropical Diseases, 7(9), e2421.

Nieto, P., Malone, J. B., & Bavia, M. E. (2006). Ecological niche modeling for visceral leishmaniasis in the state of Bahia, Brazil, using genetic algorithm for rule-set prediction and growing degree day-water budget analysis. Geospatial Health, 1(1), 115-126.

Peterson, A. T., & Shaw, J. J. (2003). Lutzomyia vectors for cutaneous leishmaniasis in Southern Brazil: ecological niche models, predicted geographic distributions, and climate change effects. International Journal of Parasitology, 33(9), 919-931.

Peterson, A. T., Papes, M., & Soberón, J. (2008). Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecological Modelling, 213(1), 63-72.

Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3-4), 231-259.

Piggot, D. M., Bhatt, S., Golding, N., Duda, K. A., Battle, K. E., Brady, O. J., … Hay, S. I. (2014a). Global distributions maps of the leishmaniases. eLife 3, e02851.

Pigott, D. M., Golding, N., Messina, J. P., Battle, K. E., Duda, K. A., Balard, Y., … Hay, S. I. (2014b). Global database of leishmaniasis occurrence locations, 1960-2012. Scientific Data, 1, 140036.

Rajabi, M., Mansourian, A., Pilesjo, P., & Bazmani, A. (2014). Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks: a case study in north-western Iran. Geospatial Health, 9(1), 179-191.

Ramsey, J. M., Moo-Llanes, D. A., Danis-Lozano, R., Pinto-Castillo, J. F., Ibarra-Cerdeña, C. N., & Casas-Martinez, M. (2013). Peligro de exposición actual y futuro para Dengue, Chagas, leishmaniasis y Paludismo en México. México: CONACyT / SEMARNAT-0108158. Recuperado de

Salahi-Moghaddam, A., Mohebali, M., Moshfae, A., Habibi, M., & Zarei, Z. (2010). Ecological study and risk mapping of visceral leishmaniasis in an endemic area of Iran based on a geographical information systems approach. Geospatial Health, 5(1), 71-77.

Samy, A. M., Campbell, L. P., & Peterson, A. T. (2014). Leishmaniasis transmission: distribution and coarse-resolution ecology of two vectors and two parasites in Egypt. Revista da Sociedade Brasileira de Medicina Tropical, 47(1), 57-62.

Saupe, E. E., Hendricks, J. R., Peterson, A. T., & Lieberman, B. S. (2014). Climate change and marine molluscs of the western North Atlantic: future prospects and perils. Journal of Biogeography, 41, 1352-1366.

Seid, A., Gadisa, E., Tsegaw, T., Abera, A., Teshome, A., Mulugeta, A., Herrero, M., … Aseffa, A. (2014). Risk map for cutaneous leishmaniasis in Ethiopia based on environmental factors as revealed by geographical information systems and statistics. Geospatial Health, 8(2), 377-387.

Shrestha, U. B., & Bawa, K. S. (2014). Impact of climate change on potential distribution of Chinese Caterpillar Fungus (Ophiocordyceps sinensis) in Nepal Himalaya. PLoS ONE, 9(9), e106405.

Triviño, M., Cabeza, M., Thuiller, W., Hickler, T., & Araújo, M. B. (2013). Risk assessment for Iberian birds under global change. Biological Conservation, 168, 192-200.

Warren, D., Glor, R., & Turelli, M. (2010). ENMtools: a toolbox for comparative studies of environmental niche models. Ecography, 33, 607-611.

WHO-World Health Organization. (2010). Control of the leishmaniasis. Geneva, Switzerland: World Health Organization Technical Report.



Download data is not yet available.