1. Epidemiology and Global Health
  2. Microbiology and Infectious Disease
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Global distribution maps of the leishmaniases

  1. David M Pigott  Is a corresponding author
  2. Samir Bhatt
  3. Nick Golding
  4. Kirsten A Duda
  5. Katherine E Battle
  6. Oliver J Brady
  7. Jane P Messina
  8. Yves Balard
  9. Patrick Bastien
  10. Francine Pratlong
  11. John S Brownstein
  12. Clark C Freifeld
  13. Sumiko R Mekaru
  14. Peter W Gething
  15. Dylan B George
  16. Monica F Myers
  17. Richard Reithinger
  18. Simon I Hay
  1. University of Oxford, United Kingdom
  2. UFR Médecine, Université Montpellier 1 and UMR ‘MiVEGEC’, CNRS 5290/IRD 224, France
  3. CHRU de Montpellier, Centre National de Référence des Leishmanioses, France
  4. Harvard Medical School, United States
  5. Boston Children's Hospital, United States
  6. Boston University, United States
  7. National Institutes of Health, United States
  8. RTI International, United States
Research Article
Cite this article as: eLife 2014;3:e02851 doi: 10.7554/eLife.02851
4 figures, 2 tables and 1 data set

Figures

Figure 1 with 1 supplement
Reported and predicted distribution of cutaneous leishmaniasis in the New World.

(A) Evidence consensus for presence of the disease ranging from green (complete consensus on the absence: −100%) to purple (complete consensus on the presence of disease: +100%). The blue spots indicate occurrence points or centroids of occurrences within small polygons. (B) Predicted risk of cutaneous leishmaniasis from green (low probability of presence) to purple (high probability of presence).

https://doi.org/10.7554/eLife.02851.003
Figure 1—figure supplement 1
Uncertainty associated with predictions in Figure 1B.

Uncertainty was calculated as the range of the 95% confidence interval in predicted probability of occurrence for each pixel. Regions of highest uncertainty are in dark brown, with blue representing low uncertainty.

https://doi.org/10.7554/eLife.02851.004
Figure 2 with 1 supplement
Reported and predicted distribution of visceral leishmaniasis in the New World.

(A) Evidence consensus for presence of the disease ranging from green (complete consensus on the absence: −100%) to purple (complete consensus on the presence of disease: +100%). The blue spots indicate occurrence points or centroids of occurrences within small polygons. (B) Predicted risk of visceral leishmaniasis from green (low probability of presence) to purple (high probability of presence).

https://doi.org/10.7554/eLife.02851.005
Figure 2—figure supplement 1
Uncertainty associated with predictions in Figure 2B.

Uncertainty was calculated as the range of the 95% confidence interval in predicted probability of occurrence for each pixel. Regions of highest uncertainty are in dark brown, with blue representing low uncertainty.

https://doi.org/10.7554/eLife.02851.006
Figure 3 with 3 supplements
Reported and predicted distribution of cutaneous leishmaniasis in the Old World.

(A) Evidence consensus for presence of the disease ranging from green (complete consensus on the absence: −100%) to purple (complete consensus on the presence of disease: +100%). The blue spots indicate occurrence points or centroids of occurrences within small polygons. (B) Predicted risk of cutaneous leishmaniasis from green (low probability of presence) to purple (high probability of presence).

https://doi.org/10.7554/eLife.02851.007
Figure 3—figure supplement 1
Uncertainty associated with predictions in Figure 3B.

Uncertainty was calculated as the range of the 95% confidence interval in predicted probability of occurrence for each pixel. Regions of highest uncertainty are in dark brown, with blue representing low uncertainty.

https://doi.org/10.7554/eLife.02851.008
Figure 3—figure supplement 2
Reported and predicted distribution of cutaneous leishmaniasis in northeast Africa.

(A) Evidence consensus for presence of the disease ranging from green (complete consensus on the absence: −100%) to purple (complete consensus on the presence of disease: +100%). The blue spots indicate occurrence points or centroids of occurrences within small polygons. (B) Predicted risk of cutaneous leishmaniasis from green (low probability of presence) to purple (high probability of presence).

https://doi.org/10.7554/eLife.02851.009
Figure 3—figure supplement 3
Reported and predicted distribution of cutaneous leishmaniasis across the Near East, including Syria, Iran and Afghanistan.

(A) Evidence consensus for presence of the disease ranging from green (complete consensus on the absence: −100%) to purple (complete consensus on the presence of disease: +100%). The blue spots indicate occurrence points or centroids of occurrences within small polygons. (B) Predicted risk of cutaneous leishmaniasis from green (low probability of presence) to purple (high probability of presence).

https://doi.org/10.7554/eLife.02851.010
Figure 4 with 4 supplements
Reported and predicted distribution of visceral leishmaniasis in the Old World.

(A) Evidence consensus for presence of the disease ranging from green (complete consensus on the absence: −100%) to purple (complete consensus on the presence of disease: +100%). The blue spots indicate occurrence points or centroids of occurrences within small polygons. (B) Predicted risk of visceral leishmaniasis from green (low probability of presence) to purple (high probability of presence).

https://doi.org/10.7554/eLife.02851.011
Figure 4—figure supplement 1
Uncertainty associated with predictions in Figure 4B.

Uncertainty was calculated as the range of the 95% confidence interval in predicted probability of occurrence for each pixel. Regions of highest uncertainty are in dark brown, with blue representing low uncertainty.

https://doi.org/10.7554/eLife.02851.012
Figure 4—figure supplement 2
Reported and predicted distribution of visceral leishmaniasis in northeast Africa.

(A) Evidence consensus for presence of the disease ranging from green (complete consensus on the absence: −100%) to purple (complete consensus on the presence of disease: +100%). The blue spots indicate occurrence points or centroids of occurrences within small polygons. (B) Predicted risk of visceral leishmaniasis from green (low probability of presence) to purple (high probability of presence).

https://doi.org/10.7554/eLife.02851.013
Figure 4—figure supplement 3
Reported and predicted distribution of visceral leishmaniasis in the Indian subcontinent.

(A) Evidence consensus for presence of the disease ranging from green (complete consensus on the absence: −100%) to purple (complete consensus on the presence of disease: +100%). The blue spots indicate occurrence points or centroids of occurrences within small polygons. (B) Predicted risk of visceral leishmaniasis from green (low probability of presence) to purple (high probability of presence).

https://doi.org/10.7554/eLife.02851.014
Figure 4—figure supplement 4
Population at risk estimates for leishmaniasis.

Four scatterplots showing the relationship between non-zero estimated mean annual incidence (Alvar et al., 2012) and estimated population at risk derived from the cartographic approach for (A) New World cutaneous leishmaniasis, (B) New World visceral leishmaniasis, (C) Old World cutaneous leishmaniasis, and (D) Old World visceral leishmaniasis. For each country the bars represent the annual incidence estimate range.

https://doi.org/10.7554/eLife.02851.015

Tables

Table 1

Origin and spatial resolution of leishmaniasis occurrence data

https://doi.org/10.7554/eLife.02851.016
Origin and resolution of occurrence data
Point dataProvince level dataDistrict level dataTotal
Cutaneous leishmaniasis
 Literature368087912205779
 CNR-L5314731609
 HealthMap3131
 GenBank617
 Total424892612526426
Visceral leishmaniasis
 Literature3050150010685618
 CNR-L4292429482
 HealthMap32133
 GenBank314
 Total3514152510986137
  1. Each cell gives the number of occurrence records added to the data set by considering each additional datasource after removing duplicate records. Occurrence records are separated by spatial resolution—whether they are recorded as points (typically representing settlements) or as province level (admin 1) or district level (admin 2) data.

Table 2

Mean relative contribution of predictor variables to the ensemble BRT models of CL and VL in both the Old and New World

https://doi.org/10.7554/eLife.02851.017
Top predictors of CLRelative contributionTop predictors of VLRelative contribution
Old world
 Peri-urban extents47.34Peri-urban extents51.50
 Minimum LST18.36Urban extents17.38
 Urban extents9.01Maximum NDVI7.87
 G-Econ7.33Minimum LST5.87
 Minimum Precipitation4.95Maximum Precipitation4.00
New World
 Maximum LST36.91Peri-urban extents25.90
 Peri-urban extents18.61Urban extents21.24
 Maximum precipitation12.06Mean LST9.18
 Minimum precipitation6.21Mean NDVI7.83
 Minimum LST4.39Maximum LST6.40
  1. LST = Land Surface Temperature, G-Econ = Geographically based Economic data, NDVI = Normalised Difference Vegetation Index.

Data availability

The following data sets were generated
  1. 1

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