Understanding cattle movement patterns allow us to predict hotspots and
control strategies to save scarce resources. This study therefore compares
the utility of molecular and census data in predicting cattle
movement networks in Cameroon.
Cattle movement network predictions were made using two approaches: a
molecular-based Network (MN) by transforming phylogenetic distances of
Mycobacterium bovis (Spoligotype &MIRU-VNTR)
genotypes recovered from an abattoir-based study across four regions of
Cameroon conducted in 2013; and a gravity model network (GN) based on the
³Cattle/Human² ratio retrieved from 2005-2007 census data and the Euclidean
distances computed from GIS data from Cameroon was generated. The models
were validated by comparing the
predictions to an empirical network (EN) generated using data on cattle
at livestock markets located in the four regions collected in 2014.
Statistical, spatial and network measures of centrality comparisons were
using the ggmap and igraph packages in R version 3.0.
The three networks showed similar
spatial patterns of cattle movements. We however observe more consistency
animal flow across MN and EN from the North Region towards the Adamawa and
North-West Regions. The measures of centrality in the EN indicate that
Nyambaka, Nankoue and Ngaoundal are prominent actors in the cattle movement
network, three and two of which were also predicted by the MN and the GN
There is better statistical and spatial agreement between EM & MN
than GN, which suggests that molecular genotypes are better predictors of
cattle movement networks in Cameroon.
|Conference||The Colorado Mycobacteria Conference 2016|
|Period||7/06/16 → …|