Clinical pleiomorphism in human leishmaniases, with special mention of asymptomatic infection, Clin. Microbiol. Infect, vol.17, pp.1451-1461, 2011. ,
Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study, Lancet, vol.380, pp.2095-2128, 2010. ,
URL : https://hal.archives-ouvertes.fr/hal-00827612
Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study, Lancet, vol.380, pp.2197-2223, 2010. ,
URL : https://hal.archives-ouvertes.fr/hal-00827610
Complexities of assessing the disease burden attributable to leishmaniasis, PLoS Negl. Trop. Dis, vol.2, p.313, 2008. ,
Leishmaniasis worldwide and global estimates of its incidence, PLoS One, vol.7, p.35671, 2012. ,
Global distribution maps of the leishmaniases, vol.3, p.2851, 2014. ,
The leishmaniasis e-compendium: a geo-referenced bibliographic tool, Trends Parasitol, vol.26, pp.515-516, 2010. ,
Geographical distribution and epidemiological features of Old World cutaneous leishmaniasis foci, based on the isoenzyme analysis of 1048 strains, Trop. Med. Int. Health, vol.14, pp.1071-1085, 2009. ,
Geographical distribution and epidemiological features of Old World Leishmania infantum and Leishmania donovani foci, based on the isoenzyme analysis of 2277 strains, Parasitology, vol.140, pp.423-434, 2013. ,
, WHO. Control of the Leishmaniases. Report of a Meeting of the WHO Expert Committee on the Control of Leishmaniases, pp.22-26, 2010.
ProMED-mail: An early warning system for emerging diseases, Clin. Infect. Dis, vol.39, pp.227-232, 2004. ,
HealthMap: global infectious disease monitoring through automated classification and visualization of internet media reports, J. Am. Med. Inform. Assn, vol.15, pp.150-157, 2008. ,
, The Global Administrative Unit Layers (GAUL): Technical Aspects (Food and Agriculture Organization of the United Nations, 2008.
A global compendium of human dengue virus occurrence, Sci. Data, vol.1, p.140004, 2014. ,
Big data opportunities for global infectious disease surveillance, PLoS Med, vol.10, p.1001413, 2013. ,
The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models, PLoS One, vol.8, p.55158, 2013. ,
Spatial filtering to reduce sampling bias can improve the performance of ecological niche models, Ecol. Model, vol.275, pp.73-77, 2014. ,
Novel methods improve prediction of species' distributions from occurrence data, Ecography, vol.29, pp.129-151, 2006. ,
Exploring the effects of quantity and location of pseudo-absences and sampling biases on the performance of distribution models with limited point occurrence data, J. Nat. Conserv, vol.19, pp.1-7, 2011. ,
Uneven geographies of user-generated information: patterns of increasing informational poverty, Ann. Assoc. Am. Geogr, vol.104, pp.746-764, 2014. ,
Global database of leishmaniasis occurrence locations, Sci. Data, vol.1, p.140036, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-02013788
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