Table 1 Risk factors and fuzzy membership functions used to create risk maps
From: A multi-criteria decision analysis approach to assessing malaria risk in northern South America
Data | Source | Factor | Control points | Fuzzy function | Rationale |
|---|---|---|---|---|---|
Deforestation | Global Forest change [54] | Distance (km) | 0, 5 | Linear ↓ | Vectors are found within 5 km of deforested areas |
Elevation | SRTM 90 m | Elevation (m) | 500, 1800 | J-shaped ↓ | Exposure to vectors decrease above 500 m and is non-existent above 1800 m |
Population | LandScan | Population density | 2, 50, 100, 150 | Sigmoidal ↑↓ | Populations between 2 and 150/km2 are sufficient for malaria transmission |
Precipitation | WorldClim | Precipitation (mm) | 0, 80 | Linear ↑ | Precipitation of 80 mm is suitable for vectors for stable transmission to occur [43] |
Roads | DCW | Distance (km) | 0, 5 | Linear ↓ | Transmission occurs within 5 km of roads where blood meals are available |
Temperature | WorldClim | Temperature °C | 18, 22, 32, 40 | Sigmoidal ↑↓ | Sporogony starts at 18 °C and is completed at 22 °C, vector survival decreases above 32 °C and death occurs at 40 °C [43] |
TWI | SRTM 90 m | Soil Saturation (%) | 0, 5 | Linear ↑ | An area requires about 5 % water saturation to serve as breeding site |
Urban areas | DeLorme, Inc. | Distance (km) | 1, 10, 20, 30 | Sigmoidal ↑↓ | Vectors are absent in urban areas but found in the urban periphery |
Wetlands | WWF | Distance (km) | 0, 3 | Linear ↓ | Vectors are found within 3 km of wetlands |