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Table 9 Predicting Anopheles presence compared to random using GLM

From: Identifying malaria vector breeding habitats with remote sensing data and terrain-based landscape indices in Zambia

Model

Data Source

Variable

Odds Ratio

P > |z|

95% CI Lower

95% CI Upper

LandSat-SRTM

SRTM

slope

0.47

0.005

0.27

0.80

 

SRTM

TPI500

0.58

<0.001

0.47

0.71

 

SRTM

TWI

1.36

0.002

1.05

1.76

 

SRTM

TPI2000

0.94

0.03

0.88

0.99

LandSat-ASTER

LandSat

3:1

2.40e - 06

<0.001

3.15e - 09

0.002

 

ASTER

TPI2000

0.95

<0.001

0.92

0.97

 

LandSat

2:4

316321.9

0.007

30.83

3.25e + 09

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International Journal of Health Geographics

ISSN: 1476-072X