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1EuFMD | Open Session special edition | #OS20se
Modelling and predicting national and
regional animal mobility affecting
livestock’s diseases circulation. A
comparison from studies in North/West
Africa and South-East Asia
Andrea Apolloni, Alexis Delabouglise
CIRAD Montpellier, Unit ASTRE, AQCR team
2
• Extensive system. Animals kept mobile because of
environmental conditions. Focus on small and large
ruminants
• NO animal identification system. Use aggregated
information collected by Vetrinary Services
• Network Analysis:
• A single large component in the mobility
network
• Heterogeneity in degree and volume
distribution
• Variation along the year due to religious
festivity
• Connectivity Analysis
Livestock’s in/out flows in administrative areas
change if we consider land use and probability of
passing
• Models capture existence/absence of links but fail
to estimate volumes
• Mobility complex phenomenon involving several
aspects form environmental to socio economical
factors
West/North Africa
(a) Connectivity (b) Network
Normalized Activity
[0,0.1]
]0.1,0.2]
]0.2,0.3]
]0.3,0.4]
]0.4,0.5]
]0.5,0.6]
]0.6,0.7]
]0.7,0.8]
]0.8,0.9]
]0.9,1]
3
• Small scale commercial production system. Focus
on poultry
• Longitudinal survey of 53 poultry farms in
Mekong river valley for 20 months
• Information collected:
• Introduction and harvest of birds
• Mortality + symptoms
• Preventive measure
• Mixed-effect generalized additive models:
• Non-linear relationship age – likelihood of
trade
• Random farm effect (farmers’ individual
characteristics)
• Fixed effect: poultry population, introduction
of new flocks, vaccination status, disease
outbreaks
• Small scale farms:
• Small flocks sold at slower rate
• Trade adjusted to evolving conditions
• Trade as risk-copying strategy : outbreaks
followed by increased sale rate
Viet Nam Small-scale flocks
Large-scale flocks
Outbreaks with
sudden deaths
Outbreaks no sudden
death
No outbreaks
4
Conclusions
• Network approach on aggregated data
• Mobility changes along the year
• Importance of festivities and social
events
• Landuse and environmental factors can
shape mobility pattern and change
locations activity
• What we miss:
• Harmonised data on production chain
could explain certain axes
• Individual choices toward certain
markets/locations
Vietnam
• Individual longitudinal surveys
• Explore individual motivations for
introducing and removing animals
• Sale rate and destination change in
response to events at individual level –
changes in stock size, disease outbreaks.
• In small-scale farms: slower sale rate and
adaptable to changing conditions
• What we miss:
• Response to changes in market prices
• Description of trade networks of infected
poultry
Need to combine large scale /national information with individual’s choices
West Africa

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OS20 - Modelling and predicting national and regional animal mobility affecting livestock’s diseases circulation. A comparison from studies in North/West Africa and South-East Asia - Dr. A. Apolloni, Dr. A. Delabouglise

  • 1. 1EuFMD | Open Session special edition | #OS20se Modelling and predicting national and regional animal mobility affecting livestock’s diseases circulation. A comparison from studies in North/West Africa and South-East Asia Andrea Apolloni, Alexis Delabouglise CIRAD Montpellier, Unit ASTRE, AQCR team
  • 2. 2 • Extensive system. Animals kept mobile because of environmental conditions. Focus on small and large ruminants • NO animal identification system. Use aggregated information collected by Vetrinary Services • Network Analysis: • A single large component in the mobility network • Heterogeneity in degree and volume distribution • Variation along the year due to religious festivity • Connectivity Analysis Livestock’s in/out flows in administrative areas change if we consider land use and probability of passing • Models capture existence/absence of links but fail to estimate volumes • Mobility complex phenomenon involving several aspects form environmental to socio economical factors West/North Africa (a) Connectivity (b) Network Normalized Activity [0,0.1] ]0.1,0.2] ]0.2,0.3] ]0.3,0.4] ]0.4,0.5] ]0.5,0.6] ]0.6,0.7] ]0.7,0.8] ]0.8,0.9] ]0.9,1]
  • 3. 3 • Small scale commercial production system. Focus on poultry • Longitudinal survey of 53 poultry farms in Mekong river valley for 20 months • Information collected: • Introduction and harvest of birds • Mortality + symptoms • Preventive measure • Mixed-effect generalized additive models: • Non-linear relationship age – likelihood of trade • Random farm effect (farmers’ individual characteristics) • Fixed effect: poultry population, introduction of new flocks, vaccination status, disease outbreaks • Small scale farms: • Small flocks sold at slower rate • Trade adjusted to evolving conditions • Trade as risk-copying strategy : outbreaks followed by increased sale rate Viet Nam Small-scale flocks Large-scale flocks Outbreaks with sudden deaths Outbreaks no sudden death No outbreaks
  • 4. 4 Conclusions • Network approach on aggregated data • Mobility changes along the year • Importance of festivities and social events • Landuse and environmental factors can shape mobility pattern and change locations activity • What we miss: • Harmonised data on production chain could explain certain axes • Individual choices toward certain markets/locations Vietnam • Individual longitudinal surveys • Explore individual motivations for introducing and removing animals • Sale rate and destination change in response to events at individual level – changes in stock size, disease outbreaks. • In small-scale farms: slower sale rate and adaptable to changing conditions • What we miss: • Response to changes in market prices • Description of trade networks of infected poultry Need to combine large scale /national information with individual’s choices West Africa