Analysis of patterns of livestock movements in the Cattle Corridor of Uganda for risk-based surveillance of infectious diseases

Abstract

IntroductionThe knowledge of animal movements is key to formulating strategic animal disease control policies and carrying out targeted surveillance. This study describes the characteristics of district-level cattle, small ruminant, and pig trade networks in the Cattle Corridor of Uganda between 2019 and 2021.MethodologyThe data for the study was extracted from 7,043 animal movement permits (AMPs) obtained from the Ministry of Agriculture, Animal Industry and Fisheries (MAAIF) of Uganda. Most of the data was on cattle (87.2%), followed by small ruminants (11.2%) and pigs (1.6%). Two types of networks representing animal shipments between districts were created for each species based on monthly (n = 30) and seasonal (n = 10) temporal windows. Measures of centrality and cohesiveness were computed for all the temporal windows and our analysis identified the most central districts in the networks.ResultsThe median in-degree for monthly networks ranged from 0–3 for cattle, 0–1 for small ruminants and 0–1 for pigs. The highest median out-degrees for cattle, small ruminant and pig monthly networks were observed in Lira, Oyam and Butambala districts, respectively. Unlike the pig networks, the cattle and small ruminant networks were found to be of small-world and free-scale topologies.DiscussionThe cattle and small ruminant trade movement networks were also found to be highly connected, which could facilitate quick spread of infectious animal diseases across these networks. The findings from this study highlighted the significance of characterizing animal movement networks to inform surveillance, early detection, and subsequent control of infectious animal disease outbreaks.

Exploring community-based reporting of livestock abortions for Rift Valley Fever surveillance in Uganda: A pilot study

“…For example only 3/184 farms reported history of animal movements. The tracking of animal movements in Uganda is not well established and synchronized (González-Gordon et al, 2023; Hasahya et al, 2023; Payne et al, 2021). For example, the available animal movement tracking efforts are for those to be transported on major/highway roads and the motivation is trade and revenue generation.…”

“…Our study was motivated by Budasha et al and de Glanville, W. A. et al’s observation that RVF antibodies could be detected in abortions and their recommendation that these could be used as an early warning signal for RVF in endemic areas (de Glanville et al, 2022; Glanville et al, 2022). In Uganda and many African countries where animal health surveillance is not systematic (Hasahya et al, 2023; Qiu et al, 2023) livestock abortions are neither routinely documented nor reported for action, yet could be leveraged as cost-effective proxies for arboviruses surveillance in ruminants (Walt et al, 2023).…”

Identifying target areas for risk-based surveillance and control of transboundary animal diseases: a seasonal analysis of slaughter and live-trade cattle movements in Uganda

“…The network analysis presented here offers insight into the structure of cattle mobility in Uganda. By analysing the temporal patterns of country-wide cattle shipments for the purpose of trade and slaughter, we have extended the scope of the analyses by Mugezi et al and Hasahya et al 34 , 77 . These analyses focused on qualitatively assessing the risk of FMD during the dry season through pastoral and trade-related cattle mobility along the Ugandan-Tanzanian border and on studying the patterns of live trade livestock movements (cattle, small ruminants, and pigs) in the cattle corridor of Uganda.…”

“…The aim of this study was to comprehensively characterise the network structure of cattle movements in Uganda based on official data collected in 2019. We considered this data to be an unaltered, representative overview of cattle movements before COVID-19 disrupted routine trading operations, distorting the collection of mobility data to date 33 , 34 . First, the annual static network is analysed as a snapshot of the cattle movements.…”