Modelling the distribution of domestic ducks in Monsoon Asia

Domestic ducks are considered to be an important reservoir of highly pathogenic avian influenza (HPAI), as shown by a number of geospatial studies in which they have been identified as a significant risk factor associated with disease presence. Despite their importance in HPAI epidemiology, their large-scale distribution in Monsoon Asia is poorly understood. In this study, we created a spatial database of domestic duck census data in Asia and used it to train statistical distribution models for domestic duck distributions at a spatial resolution of 1 km. The method was based on a modelling framework used by the Food and Agriculture Organisation to produce the Gridded Livestock of the World (GLW) database, and relies on stratified regression models between domestic duck densities and a set of agro-ecological explanatory variables. We evaluated different ways of stratifying the analysis and of combining the prediction to optimize the goodness of fit of the predictions. We found that domestic duck density could be predicted with reasonable accuracy (mean RMSE and correlation coefficient between log-transformed observed and predicted densities being 0.58 and 0.80, respectively), using a stratification based on livestock production systems. We tested the use of artificially degraded data on duck distributions in Thailand and Vietnam as training data, and compared the modelled outputs with the original high-resolution data. This showed, for these two countries at least, that these approaches could be used to accurately disaggregate provincial level (administrative level 1) statistical data to provide high resolution model distributions.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► High resolution data on duck distribution is key to understanding the ecology of avian influenza in Monsoon Asia. ► Data on domestic duck are available at coarse and heterogeneous levels. ► We use agro-ecological and anthropogenic covariates to disaggregate domestic duck census data in at a resolution of 1 km. ► We compare modelling methods, and validate the model using high resolution data from Thailand and Vietnam. ► Statistical regressions stratified by livestock production systems allow predicting domestic duck density with a good accuracy.