1921
Volume 94, Issue 4
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645

Abstract

Abstract

Cutaneous leishmaniasis is a very complex disease involving multiple factors that limit its emergence and spatial distribution. Prediction of cutaneous leishmaniasis epidemics in Tunisia remains difficult because most of the epidemiological tools used so far are descriptive in nature and mainly focus on a time dimension. The purpose of this work is to predict the potential geographic distribution of and zoonotic cutaneous leishmaniasis caused by in Tunisia using Grinnellian ecological niche modeling. We attempted to assess the importance of environmental factors influencing the potential distribution of and cutaneous leishmaniasis caused by . Vectors were trapped in central Tunisia during the transmission season using CDC light traps (John W. Hock Co., Gainesville, FL). A global positioning system was used to record the geographical coordinates of vector occurrence points and households tested positive for cutaneous leishmaniasis caused by . Nine environmental layers were used as predictor variables to model the geographical distribution and five variables were used to model the potential distribution. Ecological niche modeling was used to relate known species' occurrence points to values of environmental factors for these same points to predict the presence of the species in unsampled regions based on the value of the predictor variables. Rainfall and temperature contributed the most as predictors for sand flies and human case distributions. Ecological niche modeling anticipated the current distribution of with the highest suitability for species occurrence in the central and southeastern part of Tunisian. Furthermore, our study demonstrated that governorates of Gafsa, Sidi Bouzid, and Kairouan are at highest epidemic risk.

[open-access] This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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2017-11-19
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References

  1. Alvar J, Vélez ID, Bern C, Herrero M, Desjeux P, Cano J, Jannin J, de Boer M, , 2012. Leishmaniasis worldwide and global estimates of its incidence. PLoS One 7: e35671.[Crossref]
  2. World Health Organization Regional Office for Europe, 2002. Floods: Climate Change and Adaptation Strategies for Human Health. Darmstadt, Germany: Steinkopff Verlag.
  3. Mukhopadhyay J, Braig HR, Rowton ED, Ghosh K, , 2012. Naturally occurring culturable aerobic gut flora of adult Phlebotomus papatasi, vector of Leishmania major in the old world. PLoS One 7: e35748.[Crossref]
  4. Ben Ismail R, Gramiccia M, Gradoni L, Helal H, Ben Rachid MS, , 1987. Isolation of Leishmania major from Phlebotomus papatasi in Tunisia. Trans R Soc Trop Med Hyg 81: 749.[Crossref]
  5. Ben Salah A, Kamarianakis Y, Chlif S, Ben Alaya N, Prastacos P, , 2007. Zoonotic cutaneous leishmaniasis in central Tunisia: spatio-temporal dynamics. Int J Epidemiol 36: 9911000.[Crossref]
  6. Ministry of Health Tunisia, 2013. Annual Report of Activities. Tunis, Tunisia: Ministry of Health Tunisia.
  7. Toumi A, Chlif S, Bettaieb J, Ben Alaya N, Boukthir A, Ahmadi ZE, Ben Salah A, , 2012. Temporal dynamics and impact of climate factors on the incidence of zoonotic cutaneous leishmaniasis in central Tunisia. PLoS Negl Trop Dis 6: e1633.[Crossref]
  8. Patz JA, Hahn MB, , 2013. Climate change and human health: a One Health approach. Curr Top Microbiol Immunol 366: 141171.
  9. Abdel-Dayem MS, Annajar BB, Hanafi HA, Obenauer PJ, , 2012. The potential distribution of Phlebotomus papatasi (Diptera: Psychodidae) in Libya based on ecological niche model. J Med Entomol 49: 739745.[Crossref]
  10. Quintana M, Salomón O, Guerra R, Lizarralde De Grosso M, Fuenzalida A, , 2013. Phlebotominae of epidemiological importance in cutaneous leishmaniasis in northwestern Argentina: risk maps and ecological niche models. Med Vet Entomol 27: 3948.[Crossref]
  11. González C, Wang O, Strutz SE, 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 reservoir species. PLoS Negl Trop Dis 4: e585.[Crossref]
  12. Samy AM, Campbell LP, Peterson AT, , 2014. Leishmaniasis transmission: distribution and coarse-resolution ecology of two vectors and two parasites in Egypt. Rev Soc Bras Med Trop 47: 5762.[Crossref]
  13. ESA, 2009. Global Land Cover. Available at: http://www.esa-landcover-cci.org/?q=node/158.
  14. Croset H, Rioux J-A, Maistre M, Bayar N, , 1978. Les phleìbotomes de Tunisie (Diptera, Phlebotomidae), Mise au point systeìmatique, chronologique er eìthologique. Ann Parasitol Hum Comp 53: 711749.
  15. Lewis DJ, , 1982. A taxonomic review of the genus Phlebotomus (Diptera: Psychodidae). Bull Br Mus (Natural Hist) Entomol 45: 121209.
  16. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A, , 2005. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25: 19651978.[Crossref]
  17. USGS, 1996. Global 30 Arc-Second Elevation Data Set GTOPO30. Reston, VA: USGS.
  18. ESRI, 2012. rcGIS Desktop: Release 10.1. Redlands, CA: Environmental Systems Research Institute.
  19. Rissler LJ, Apodaca JJ, , 2007. Adding more ecology into species delimitation: ecological niche models and phylogeography help define cryptic species in the black salamander (Aneides flavipunctatus). Syst Biol 56: 924942.[Crossref]
  20. Franklin J, , 2009. Mapping species distributions: spatial inference and prediction. J Trop Ecol 1: 320.
  21. Phillips SJ, Dudík M, Schapire RE, , 2004. A maximum entropy approach to species distribution modeling. Proceedings of the Twenty-First International Conference on Machine Learning (ICML) '04. New York, NY: ACM Press, 83.[Crossref]
  22. Phillips SJ, Anderson RP, Schapire RE, , 2006. Maximum entropy modeling of species geographic distributions. Ecol Model 190: 231259.[Crossref]
  23. Phillips SJ, Dudík M, , 2008. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31: 161175.[Crossref]
  24. Elith J, Kearney M, Phillips S, , 2010. The art of modelling range-shifting species. Methods Ecol Evol 1: 330342.[Crossref]
  25. Hosmer DW, Lemeshow S, , 2004. Applied Logistic Regression, 2nd edition. Wiley, New York, NY.
  26. Landis JR, Koch GG, , 1977. The measurement of observer agreement for categorical data. Biometrics 33: 159174.[Crossref]
  27. Ferrier S, Drielsma M, Manion G, Watson G, , 2002. Extended statistical approaches to modelling spatial pattern in biodiversity in northeast New South Wales. II. Community-level modelling. Biodivers Conserv 11: 23092338.[Crossref]
  28. Miller RH, Masuoka P, Klein TA, Kim HC, Somer T, Grieco J, , 2012. Ecological niche modeling to estimate the distribution of Japanese encephalitis virus in Asia. PLoS Negl Trop Dis 6: e1678.[Crossref]
  29. Slater H, Michael E, , 2012. Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling. PLoS One 7: e32202.[Crossref]
  30. Ghawar W, Zaâtour W, Chlif S, Bettaieb J, Chalghaf B, Snoussi MA, Ben Salah A, , 2015. Spatiotemporal dispersal of Meriones shawi estimated by radio-telemetry. Int J Multidiscip Res Dev 2: 211216.
  31. Haouas N, Gorcii M, Chargui N, Aoun K, Bouratbine A, Messaadi Akrout F, Masmoudi A, Zili J, Ben Said M, Pratlong F, Dedet JP, Mezhoud H, Azaiez R, Babba H, , 2007. Leishmaniasis in central and southern Tunisia: current geographical distribution of zymodemes. Parasite 14: 239246.[Crossref]
  32. Ben Abda I, Aoun K, Ben Alaya N, Bousslimi N, Mokni M, Bouratbine A, , 2009. Current epidemiological, clinical and parasitological data concerning cutaneous leishmaniasis in Tunisia. Rev Tunisienne d'Infectiologie 2: 3136.
  33. Chelbi I, Kaabi B, Béjaoui M, Derbali M, Zhioua E, , 2009. Spatial correlation between Phlebotomus papatasi Scopoli (Diptera: Psychodidae) and incidence of zoonotic cutaneous leishmaniasis in Tunisia. J Med Entomol 46: 400402.[Crossref]
  34. Killick-Kendrick R, , 1990. Phlebotomine vectors of the leishmaniases: a review. Med Vet Entomol 4: 124.[Crossref]
  35. Claborn DM, , 2010. The biology and control of leishmaniasis vectors. J Glob Infect Dis 2: 127134.[Crossref]
  36. El-Shazly MM, Soliman MM, Zayed A, , 2012. Seasonal abundance, number of annual generations, and effect of an entomopathogenic fungus on Phlebotomus papatasi (Diptera: Psychodidae). Environ Entomol 41: 1119.[Crossref]
  37. Guzmán H, Tesh RB, , 2000. Effects of temperature and diet on the growth and longevity of phlebotomine sand flies (Diptera: Psychodidae). Biomedica 20: 190199.[Crossref]
  38. Theodor O, , 2009. Observations on the hibernation of Phlebotomus papatasi (Dipt.). Bull Entomol Res 25: 459.[Crossref]
  39. Singh R, Lal S, Saxena VK, , 2008. Breeding ecology of visceral leishmaniasis vector sand fly in Bihar State of India. Acta Trop 107: 117120.[Crossref]
  40. Feliciangeli MD, , 2004. Natural breeding places of phlebotomine sand flies. Med Vet Entomol 18: 7180.[Crossref]
  41. Feliciangeli MD, Rabinovich J, , 1998. Abundance of Lutzomyia ovallesi but not Lu. gomezi (Diptera: Psychodidae) correlated with cutaneous leishmaniasis incidence in north-central Venezuela. Med Vet Entomol 12: 121131.[Crossref]
  42. Elnaiem D-EA, Schorscher J, Bendall A, Obsomer V, Osman ME, Mekkawi AM, Connor SJ, Ashford RW, Thomson MC, , 2003. Risk mapping of visceral leishmaniasis: the role of local variation in rainfall and altitude on the presence and incidence of kala-azar in eastern Sudan. Am J Trop Med Hyg 68: 1017.
  43. Barata RA, da Silva JCF, da Costa RT, Fortes-Dias CL, da Silva JC, de Paula EV, Prata A, Monteiro EM, Dias ES, , 2004. Phlebotomine sand flies in Porteirinha, an area of American visceral leishmaniasis transmission in the State of Minas Gerais, Brazil. Mem Inst Oswaldo Cruz 99: 481487.[Crossref]
  44. Gálvez R, Descalzo MA, Miró G, Jiménez MI, Martín O, Dos Santos-Brandao F, Guerrero I, Cubero E, Molina R, , 2010. Seasonal trends and spatial relations between environmental/meteorological factors and leishmaniosis sand fly vector abundances in Central Spain. Acta Trop 115: 95102.[Crossref]
  45. 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. Geospat Health 5: 7177.[Crossref]
  46. Fathy FM, El-Kasah F, El-Ahwal AM, , 2009. Emerging cutaneous leishmaniasis in Sirte-Libya: epidemiology, recognition and management. J Egypt Soc Parasitol 39: 881905.
  47. Bhunia GS, Kesari S, Jeyaram A, Kumar V, Das P, , 2010. Influence of topography on the endemicity of Kala-azar: a study based on remote sensing and geographical information system. Geospat Health 4: 155165.[Crossref]
  48. Kassem HA, Siri J, Kamal HA, Wilson ML, , 2012. Environmental factors underlying spatial patterns of sand flies (Diptera: Psychodidae) associated with leishmaniasis in southern Sinai, Egypt. Acta Trop 123: 815.[Crossref]
  49. Belen A, Alten B, , 2011. Seasonal dynamics and altitudinal distributions of sand fly (Diptera: Psychodidae) populations in a cutaneous leishmaniasis endemic area of the Cukurova region of Turkey. J Vector Ecol 36 (Suppl 1): S87S94.[Crossref]
  50. Boussaa S, Neffa M, Pesson B, Boumezzough A, , 2010. Phlebotomine sand flies (Diptera: Psychodidae) of southern Morocco: results of entomological surveys along the Marrakech-Ouarzazat and Marrakech-Azilal roads. Ann Trop Med Parasitol 104: 163170.[Crossref]
  51. Adegboye OA, Kotze D, , 2012. Disease mapping of leishmaniasis outbreak in Afghanistan: spatial hierarchical Bayesian analysis. Asian Pacific J Trop Dis 2: 253259.[Crossref]
  52. Simsek FM, Alten B, Caglar SS, Ozbel Y, Aytekin AM, Kaynas S, Belen A, Kasap OE, Yaman M, Rastgeldi S, , 2007. Distribution and altitudinal structuring of phlebotomine sand flies (Diptera: Psychodidae) in southern Anatolia, Turkey: their relation to human cutaneous leishmaniasis. J Vector Ecol 32: 269279.[Crossref]
  53. Barry RG, , 2012. Recent advances in mountain climate research. Theor Appl Climatol 110: 549553.[Crossref]
  54. Jiménez-Valverde A, , 2012. Insights into the area under the receiver operating characteristic curve (AUC) as a discrimination measure in species distribution modelling. Glob Ecol Biogeogr 21: 498507.[Crossref]
  55. Lobo JM, Jiménez-valverde A, Real R, , 2008. AUC: a misleading measure of the performance of predictive distribution models. Glob Ecol Biogeogr 17: 145151.[Crossref]
  56. Peterson AT, Papeş M, Soberón J, , 2008. Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecol Model 213: 6372.[Crossref]
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Supplementary Data

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  • Received : 10 May 2015
  • Accepted : 02 Dec 2015

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