Table 1.
ENM features by studies in the systematic review of ecological niche modeling applied to vector-borne and zoonotic infectious diseases emergence.
| Step | Prominent ENM features | Description | % Of studies |
|---|---|---|---|
| 1 | Data approach | Presence-absence | 2% |
| Presence-background | 84% | ||
| Presence-only | 14% | ||
| Predictor selection | |||
| Vegetation | 36% | ||
| 2 | Environmental | Land cover types | 43% |
| Climate (temperature, precipitation) | 89% | ||
| Soil | 21% | ||
| Human social | Primarily population density and land use | 13% | |
| Algorithm applied | |||
| 3 | Machine learning | Maxent | 55% |
| GARP | 22% | ||
| Statistical algorithm | Generalized linear models, boosted regression tress | 3% | |
| Mixed Methods | Maxent or GARP and boosted regression trees | 20% | |
| Model selection | |||
| 4 | Jackknife | Commonly used with maxent algorithm | 38% |
| Best Subset | Commonly used with GARP algorithm | 23% | |
| Other | Chi-squared, bootstrap, etc. used with statistical algorithms | 39% | |
| 5 | Model validation | Area under the curve (AUC-ROC) | 56% |
| Partial area under the curve (pAUC) | 13% | ||
| Other | 31% | ||
| 6 | Uncertainty estimation | Sensitivity analysis | 7% |