Volume 28, Number 7—July 2022
Research
Effect of Agroecosystems on Seroprevalence of St. Louis Encephalitis and West Nile Viruses in Birds, La Pampa, Argentina, 2017–2019
Ana P. Mansilla, Juan M. Grande, and Adrián Diaz
Table 4
Models for SLEV seroprevalence based on the generated hypotheses ranked by their AIC scores in study of effect of agroecosystems on seroprevalence of SLEV and WNV in birds, La Pampa, Argentina, 2017–2019*
| Model | Variables of the model | k | AICc | ∆AICc | wi |
|---|---|---|---|---|---|
| GLMM3 | Agricultural area | 3 | 388.819 | 0.000 | 0.441 |
| GLMM8 | Distance to water body + agricultural area | 4 | 390.198 | 1.379 | 0.221 |
| GLMM7 | Agricultural area + dove abundance | 4 | 390.244 | 1.425 | 0.216 |
| GLMM5 | Dove abundance | 3 | 391.421 | 2.602 | 0.120 |
| GLMM2 | Distance to water body | 3 | 401.845 | 13.026 | 0.001 |
| GLMM1 | Null model | 2 | 408.710 | 19.892 | 0.000 |
| GLMM6 | Sparrow abundance | 3 | 410.216 | 21.397 | 0.000 |
| GLMM4 | Distance to urban site | 3 | 410.465 | 21.647 | 0.000 |
*AICc, Akaike information criterion corrected for small samples; ∆AICc, difference between AICc and the AICc from all other models; k, number of estimated parameters; SLEV, St. Louis encephalitis virus; wi, relative likelihood that the specific model is the best of the suite of all models; WNV, West Nile virus.
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