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The impact of selected risk factors on the occurrence of highly pathogenic avian influenza in commercial poultry flocks in Poland

Anna Gierak

Anna Gierak

Department of Epidemiology and Risk AssessmentPuławy, Poland
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Gierak, Anna
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Krzysztof Śmietanka

Krzysztof Śmietanka

Department of Poultry Diseases, National Veterinary Research InstitutePuławy, Poland
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Śmietanka, Krzysztof
  
Jan 29, 2021
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Published Online: Jan 29, 2021
Page range: 45 - 52
Received: Aug 05, 2020
Accepted: Feb 03, 2021
DOI: https://doi.org/10.2478/jvetres-2021-0013
Keywords
© 2021 A. Gierak, K. Śmietanka, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Fig. 1

Locations of affected and unaffected commercial farms. The map was produced using the maps package (maps: Draw Geographical Maps, R package version 3.3.0 (21))
Locations of affected and unaffected commercial farms. The map was produced using the maps package (maps: Draw Geographical Maps, R package version 3.3.0 (21))

Fig. 2

Results of decision tree model
Results of decision tree model

Fig. 3

The importance of considered risk factors designated by the decision tree (red dots) and random forest (blue dots) models. WB – wild birds. The importance values were scaled to 0 and 100 (values of 100 and 0 indicated the most important and the least important risk factor in the model, respectively)
The importance of considered risk factors designated by the decision tree (red dots) and random forest (blue dots) models. WB – wild birds. The importance values were scaled to 0 and 100 (values of 100 and 0 indicated the most important and the least important risk factor in the model, respectively)

Fig. 4

Impact of changes in the selected variables on the predicted value of probability of HPAI occurrence using different models: logistic regression (black line), decision tree (green line), and random forest (red line). WB – wild birds
Impact of changes in the selected variables on the predicted value of probability of HPAI occurrence using different models: logistic regression (black line), decision tree (green line), and random forest (red line). WB – wild birds

Fig. 5

Spatial distribution of the predicted values of the probabilities using different models: a) logistic regression, b) decision tree, and c) random forest
Spatial distribution of the predicted values of the probabilities using different models: a) logistic regression, b) decision tree, and c) random forest

Results of logistic regression model

Notation Description of the variable Estimation 95% Confidence interval P value
log(x1+50) log-transformed density of turkeys 0.973 [0.634, 1.355] 9.94e−08
log(x2+5) log-transformed density of geese 0.409 [0.113, 0.709] 6.92e−03
log(x3+10) log-transformed density of ducks 0.447 [0.108, 0.791] 9.8e−03
log(x4+10) log-transformed density of chickens −0.193 [−0.375,−0.018] 3.31e−02

The list of preliminary selected risk factors with their spatial distribution in Poland and the distribution of values in experimental (from affected farms) and control (from unaffected farms) groups_ The maps and graphs were produced using raster and ggplot2 packages (ggplot2: Elegant Graphics for Data Analysis, R package (21)), respectively
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Life Sciences, Molecular Biology, Microbiology and Virology, Life Sciences, other, Medicine, Veterinary Medicine
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