1.
EuFMD
OS22 Mapping the Risk of Spread
of PPR in the Black Sea Basin
a Knowledge-driven Approach
Arede, Margarida1; Beltrán-Alcrudo, Daniel2; Benfield, Camilla3.;
Casal, Jordi1; Njeumi, Felix3.; Allepuz, Alberto1
UAB, Barcelona, Spain
FAO - Regional Office for Europe and Central Asia, Budapest, Hungary
FAO, Rome, Italy

2.
#OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
Margarida Arede
PPR Risk Mapping in the Black Sea
 PPR virus (Small Ruminant
Morbillivirus)
 Affects domestic and wild
small ruminants
Main transmission route
High morbidity and mortality
(acute phase of the disease)
Peste des petits Ruminants (PPR)
2
Threatens food security &
sustainable livelihood of
rural communities
Next livestock disease to be eradicated
Global Strategy for the control and eradication of PPR

3.
#OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
Margarida Arede
PPR Risk Mapping in the Black Sea
3
To identify the areas at higher risk of spread of PPR in domestic small ruminants of the Black Sea Basin

4.
#OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
C
4
Margarida Arede
PPR Risk Mapping in the Black Sea
Sheep and goat density
Proximity to PPR outbreaks
(2016-2019)
Smallholder farming
Proximity to market
Seasonal pastures
Most relevant RFs
for the region
Availability of spatial
data for all countries
Extensive literature review of risk factors associated with PPR spread
Consultation with 2 PPR experts
Integrates available knowledge about PPR use of free spatial data
Problem
definition
Data
collection
Weighting of risk factors
elicitation
Risk factor
mapping
Standardization of
risk factor maps
Suitability
map
Validation
Sensitivity
analysis
Generation of risk factor
weights
Identification of
risk factors
GIS Multi-criteria decision analysis *GIS-MCDA*

5.
#OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
Margarida Arede
PPR Risk Mapping in the Black Sea
2020-2021
5
9 consultants
from
Questionnaire
Ruminant specific information
Disease specific information
Data collation
Analysis & Visualization
Problem
definition
Data collection
Weighting of risk factors
elicitation
Risk factor
mapping
Standardization of
risk factor maps
Suitability
map
Validation
Sensitivity
analysis
Generation of risk factor
weights
Identification of
risk factors
GIS-MCDA
Study region Time frame Materials & Methods
9 countries of the study
region

6.
#OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
C
6
Margarida Arede
PPR Risk Mapping in the Black Sea
Pair-wise comparison matrix
Less important Equivalent More important
Extremely Very Strongly Strongly Moderately Moderately Strongly Very strongly Extremely Expert opinion to assess the relative importance of
each identified risk factor for the
spread of PPR in the Black Sea Basin
PARTICIPANTS
 FAO project consultants
 Country PPR focal points
 PPR Secretariat
 PPR-GREN (Global Research and Expertise Network)
 PPR international experts
Risk Factor
Risk Factor
Sheep and goat
density
Proximity to areas
affected by PPR
Smallholder
farming
Proximity
to market
Seasonal
pastures
Sheep and goat density
Proximity to areas
affected by PPR
Smallholder farming
Proximity to markets
Seasonal
pastures
Problem
definition
Data
collection
Weighting of risk
factors elicitation
Risk factor
mapping
Standardization of
risk factor maps
Suitability
map
Validation
Sensitivity
analysis
Generation of risk factor
weights
Identification of
risk factors
GIS-MCDA

7.
#OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
RF standardized
map
RF weight given by
expert [1:21]
(Example Expert 1)
0,47
0,20
0,15
0,11
0,06
7
Margarida Arede
PPR Risk Mapping in the Black Sea
SUM
21
Problem
definition
Data
collection
Weighting of risk factors
elicitation
Risk factor
mapping
Standardization of
RF maps
Suitability
map
Validation
Sensitivity
analysis
Generation of RF weights
Identification of
risk factors
GIS-MCDA

8.
#OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 8
Margarida Arede
PPR Risk Mapping in the Black Sea
Suitability map for PPR spread in the Black Sea basin

9.
#OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 9
Margarida Arede
PPR Risk Mapping in the Black Sea
Problem
definition
Data
collection
Weighting of risk factors
elicitation
Risk factor
mapping
Standardization of
risk factor maps
Suitability
map
Validation
Sensitivity
analysis
Generation of risk factor
weights
Identification of
risk factors
Cases Pseudo-absences
PPR cases for 2020 and 2021
(90 occurrences)
Randomly generated in Turkey
(90 points)
Suitability map for PPR spread in the Black Sea basin
GIS-MCDA

10.
#OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22
Discussion & conclusion
Limitations
 Quality of RF data
○ ≠ spatial resolutions for ≠ countries
 Use of proxies for animal movements (non-available data)
 Uncertainty of expert opinion
10
Margarida Arede
PPR Risk Mapping in the Black Sea
Our suitability map
 has a reasonable predictive accuracy
 may be used to inform authorities on further investigations for the implementation
of risk-based surveillance and control activities

11.
Thank you !..
Margarida Arede
margarida.decastro@uab.cat
Within the project:
Global Framework for the
Progressive Control of
Transboundary Animal Diseases
 Anna Bgzdravkan (Bulgaria)
 Andrii Pavlenko (Ukraine)
 Dmitry Morozov (Belarus)
 Ipek Keskin (Turkey)
 Jeyhun Aliyev (Azerbaijan)
 Mihai Ponea (Romania)
 Nicolae Starciuc (Moldova)
 Tengiz Chaligava (Georgia)
 Tigran Markosyan (Armenia)
 All experts who contributed to the
risk factor weighting exercise
Acknowledgements