This presentation shows the discrepancy of different sources of livestock data. This was presented in the LD4L meeting in Naivaisha for ILRI.

1. Getting locally relevant livestock numbers
What we learn from livestock data comparison from Ethiopia and Burkina Faso?
Catherine Pfeifer , Stephen Oloo & Salifou Ouedraogo
LD4D
Naivasha, 19.2.2018

2. Data sources with livestock information
and their resolution
DHS (DHS
unit)
% LKH
avg herd size
avg HH size
Expert
(landscape)
%LKH
mode herd size
FAO stat
(country) /
Livestock
distribution maps
Census data
(admin)
#livestock
# HH
population
Livestock
population
in an area?
LKH= livestock keeping
household
HH=household

3. Data sources with livestock information
and their resolution
Conversion
DHS (DHS
unit)
% LKH
avg herd size
avg HH size
Expert
(landscape)
%LKH
mode herd size
FAO stat
(country) /
Livestock
distribution maps
Census data
(admin)
#livestock
# HH
population
Livestock
population
?
LKH= livestock keeping
household
HH=household
Population :
1. FAO population (country)
2. Worldpop : map
#𝑙𝑖𝑣𝑒𝑠𝑡𝑜𝑐𝑘
= 𝑎𝑣𝑔 𝐻𝑒𝑟𝑑𝑆𝑖𝑧𝑒
× 𝑝𝑜𝑝 𝑎𝑣𝑔 𝐻𝐻𝑠𝑖𝑧𝑒
# HH

4. Insights from the national level data

5. Insights from the national level data
2004 : livestock census

6. Insights from the national level data
2004 : livestock census
Comparison FAO data with
DHS for cattle
𝑎𝑣𝑔 𝐻𝑒𝑟𝑑𝑆𝑖𝑧𝑒 ×
𝐹𝐴𝑂𝑝𝑜𝑝
𝑎𝑣𝑔(𝐻𝐻𝑠𝑖𝑧𝑒)

7. Insights from the national level data
2004 : livestock census
Comparison FAO data with
DHS
𝑎𝑣𝑔 𝑙𝑖𝑣 ×
𝐹𝐴𝑂𝑝𝑜𝑝
𝑎𝑣𝑔(𝐻𝐻𝑠𝑖𝑧𝑒)

8. Insights from the temporal data
Average herd size for 2 DHS rounds

9. So what is happening in Burkina Faso?
Animals ownership at household level
Men
owned
Women
owned
Children
owned
Splitting of animals in the dry season
Dairyherd
Animal at homestead
Animal in transhumance
Route1Route2Route3

10. Expert based livestock population numbers
Approach for the study area
1. Define livestock categories as perceived by
stakeholders, adjust to local language (Were)
2. Mapping the categories
3. define %LKH and mode number of animal per
category per household (HHhs) or Were
4. Digitalize the map (Dmap)
5. Apply the conversion
livTot = 𝑐 HHhs 𝑐 × %𝐿𝐾𝐻𝑐 × 𝑝𝑜𝑝×𝐷𝑚𝑎𝑝 𝑐
𝐻𝐻𝑠c
For Ethiopia SA : 10 % difference with local census
For Burkina Faso SA : +10% difference with DHS data and -25% from
FAO maps

11. Conclusions
Data in non-pastoral area is OK
Data in pastoral area is very inaccurate
We need to get smarter :
• Talking the language of the livestock
keeper in surveys (for example work
with Were)
• Need for novel approaches for
pastoral area
• Using drones / high resolution
satellite

12. This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
better lives through livestock
ilri.org
ILRI thanks all donors and organizations who globally supported its work through their contributions
to the CGIAR system