Improving the accuracy of livestock distribution estimates through spatial interpolation

Bryssinckx, Ward and Ducheyne, Els and Muhwezi, Bernard and Godfrey, Sunday and Mintiens, Koen and Leirs, Herwig and Hendrickx, Guy (2012) Improving the accuracy of livestock distribution estimates through spatial interpolation. Geospatial Health, 7 (1). pp. 101-109. ISSN 1970-7096

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Abstract

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P <0.009 based on a sample of 2,077 parishes using one-stage stratified samples). During aggregation, area-weighted mean values were assigned to higher administrative unit levels. However, when this step is preceded by a spatial interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level). Whether the same observations apply on a lower spatial scale should be further investigated.

Item Type:	Article
Uncontrolled Keywords:	Livestock survey, sample size reduction, accuracy, cost efficiency, population estimates
Subjects:	600 Tecnologia - Scienze applicate > 610 Medicina e salute (Classificare qui la tecnologia dei servizi medici) > 614 Medicina legale; incidenza delle malattie; Medicina preventiva pubblica > 614.5 Incidenza di specifiche malattie e tipi di malattia e misure pubbliche per prevenirle
Depositing User:	Chiara D'Arpa
Date Deposited:	31 Jul 2014 10:50
Last Modified:	31 Jul 2014 10:50
URI:	http://eprints.bice.rm.cnr.it/id/eprint/9159

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