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Volume 28, Number 4—April 2022
Research

Mapping the Risk for West Nile Virus Transmission, Africa

José-María García-CarrascoComments to Author , Antonio-Román Muñoz, Jesús Olivero, Marina Segura, and Raimundo Real
Author affiliations: University of Malaga, Malaga, Spain (J.-M. García-Carrasco, A.-R. Muñoz, J. Olivero, R. Real); Ministry of Health, Consumption, and Social Welfare, Malaga (M. Segura)

Main Article

Table

Predictor variables included in reservoir, vector, and dead-end host West Nile fever models for Africa*

Variable Reservoir
Vector
Dead-end host
B Wald B Wald B Wald
Climatic
Minimum temperature of the coldest month
(−) 1.16 × 10−2
9.65






Ecosystemic
Distance to Ramsar sites (−) 0.96 8.52 (−) 0.54 6.49 (−) 0.68 13.59
Vegetation on flooded soil
(+) 5.39
4.51






Human
Cropland and vegetation (+) 2.78 6.27
% Of irrigation areas (+) 0.04 5.06
Chicken density (+) 1.00 × 10−5 13.71 (+) 1.60 × 10−5 27.15 (+) 1.20 × 10−5 13.49
Cattle density (+) 1.78 × 10−5 4.32
Population density (+) 1.10 × 10−3 7.11
Distance to railway (−) 3.00 × 10−3 4.60

*Signs in parentheses indicate positive/negative relationships between favorability and variables. B is the coefficient multiplying the variable values in the logit of the multivariate logistic regression. The Wald parameter quantifies the relevance of every variable in the model. Variable abbreviations are given in Appendix 1 Table 1.

Main Article

Page created: January 27, 2022
Page updated: March 19, 2022
Page reviewed: March 19, 2022
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