Presented by Joshua Aboah, ILRI, at the International System Dynamics Conference, 2022 Frankfurt, Germany and Online, 18-22 July 2022

1. Better lives through livestock
A System Thinking Approach to Understand the Drivers of Change in
Ghana’s Backyard Poultry Farming System
Joshua Aboah, ILRI
International System Dynamics Conference, 2022 Frankfurt,
Germany and Online,
18-22 July 2022

2. 2
Background
Increasing demand for poultry products (eggs & meat)
Decreasing local production
(Butler, 2016; Etuah et al., 2020; Yevu & Onumah, 2021 )
Backyard Poultry Farming System
- Most popular in rural areas
- Revenue is an additional source of household income
- Supplement household nutritional needs. (esp. festive
occasions)
BUT
Production practice is not the best
(Adusei-Bonsu et al., 2021; Kunadu, 2020)

3. 3
Farmers’ adaptability to socio-economic drivers and internal household
economic factors contribute to the observed changes in farming systems
(Garcıa-Martınez et al., 2009)
BUT
There is an underlying assumption of static drivers of change in backyard
poultry farming system (Anang et al., 2013)
(i) To understand how farm-level drivers of change in the backyard
poultry production system evolve.
(i) To examine how different production strategies contribute to farm
household income in Ghana
Objectives

4. 4
Methodology
Qualitative value chain mapping
Preliminary quantitative SD model
Model structure validation
Revised quantitative SD model
-60%
-40%
-20%
0%
20%
40%
60%
80%
100%
120%
0 2 4 6 8 10 12 14 16 18 20 22 24 26
Influence
level
(%)
Time (years)
R1 3 stocks 11 variables R2 2 stocks 10 variables
B1 2 stocks 8 variables B2 2 stocks 8 variables
Loops That Matter Analysis
What ifs
(Production Strategies)

5. 5
i) Production Module @ Individual Farm
household level
• 2 types of farm households - adopters
& non-adopters of GAP considered
• Captures – production of broilers, layers
& eggs
• Influenced by the Epidemiological
module via the mortality rate (which is
endogenised)
• Output becomes the inputs for the
Financial Module
ii) Financial Module @ Individual Farm Household
Level
This module uses output from the production sector
to estimate the profitability, which in turn, influences
the production decisions (i.e., feed and water
rationing, and vaccine uptake).
• Profitability estimation
iii) Epidemiological Module @ Aggregate level
• This module estimates the mortality rates, which
influences deaths of birds in the production module.
• Uses an extrapolation of the total number of birds
based on outputs from the production sector and the
farmer population in the consumption module
iv) Consumption Module @ Aggregate Level
• This module looks at how the demand and supply
patterns influence the price of egg and chicken
meat
• The price feeds into the financial module at the
individual farm household level
• Supply and demand are extrapolated from the
production module
Model Structure
Epidemiological
Module
Production
Module
Financial
Module
Consumption
Module

6. 6
Ls (x. z) = [∆x
z/∆Z]. sign [∆x
z/∆x] (1)
Where
∆x
z is the change in variable z concerning variable x.
∆x represents the change in the variable x for time(t), and
∆Z is a change in z from time (t) to time (t+1).
[∆x
z/∆Z] estimates the magnitude of the link score
sign [∆x
z/∆x] represent the polarity of the link score.
Gross income = ∑(P(ij) Q(ij)) – ∑Exp (ij) (2)
Where
P (ij) is the selling price of egg and poultry meat;
Q(ij) is the quantity sold
Exp (ij) is the total production cost
Methodology
E-Driver (change)
Loops That Matter Analysis
(Eberlein & Schoenberg, 2020)
Efficient production
strategies

7. 7
Results
12 loop sets from the epidemiological module
10 loop sets from the production module
2 loop sets from the consumption module
1 loop set (interaction of production, consumption , & financial module)
Loop
set
No reinforcing
feedback loops
No of balancing
feedback loop
No of feedback
loops describing
80% of model
behaviour
Main issues highlighted by the dominant feedback loops
1 4R 10B 2R 4B How changes in consumer price affects supply, and the
consequential feedback on on-farm profitability
2 - 16B 5B (i) The effect of changes of layers sold on layers stock at the farm
level, (ii) the delay in the maturing layers, (iii) proportion of
reserved breeders sold
3 - 16B 5B (i) Delay in the sales of layers, (ii) effect of day-old chicks’ death
on day-old chick stock, (iii) egg sales effect on stock of eggs
4 1R 2B 1B How vaccination affect the number of recovered birds (day-old
chicks GAP)
5 1R 2B 1B How vaccination affect the number of recovered birds (day-old
chicks No GAP)
 Production module
 Epidemiological module
 Consumption module
 Consumption, financial & production module
High Dominant feedback loops (≥
5%)
R is reinforcing feedback loop
B is balancing feedback loop

8. 8
Results
s
s
s
o
Epidemiological
Module.Recovered
birds[Dayold, GAP]
Epidemiological
Module.Susceptible
Birds[Dayold, GAP]
Epidemiological
Module.Total
Bird
population[GAP, Dayold]
Epidemiological
Module.Vaccination
rate[Dayold, GAP]
Epidemiological
Module.Vaccination[Dayold, GAP]
Epidemiological factors (vaccination of day-old chicks) are critical
drivers of change in the backyard poultry system when
dominance threshold is set at 50%

9. 9
Results
Dominant Feedback Loops in Loop set 1 Highest cumulative influence for loop set 1 is the reinforcing
feedback loop revolving around the effect of price changes
on the desired egg price desired (R1)
From the onset of simulation run, the balancing feedback
loop revolving around changes in the unit price of poultry
(B3) initiates the dominance but loses dominance to R1.
The dominance of the feedback loop (R1) commences after 6.5 weeks
continues to the 9th week and losses dominance to the balancing
feedback loop revolving around the supply of egg (B2) on the market
till the 22nd week when the feedback loop revolving around the
changes in the unit price of egg and desired price (R1) regains
dominance
In Sum:
unit price of egg dictates the supply of eggs on the market, and drives
more changes in behaviour (production decisions) of the backyard
production system than the changes in the unit price of poultry.

10. 10
Cumulatively, the balancing feedback loop revolving around the laying
stock and adult layers has the highest dominance level (B1) (i.e., total
score of 32.62%).
From the onset of the simulation, changes of the model behaviour are
dominated by the balancing feedback loops revolving around the
death of layers (B5) between the 1st and 2nd weeks
The balancing feedback loop revolving around the delay in the sales of
layers (B3) dominates between the 6th and 7th week
In Sum:
There is a potential risk that a farm household might encounter when it
begins the poultry production with only growers. However, the early
sales of broilers and the adoption of homegrown hatcheries can help
curtail the risk by ensuring production continuity
Results
Dominant Feedback Loops in Loop set 2

11. 11
Profitability (GHS) GAP
Strategy 1# Strategy 2+ Strategy 3*
Mean (GHS) -2,776.34 11.33 2,260.00
Max (GHS) 0 6,026.36 11,1572.59
Min (GHS) -4,331.27 -2,182.69 -1,577.00
Periods in weeks (<0) 51.00 33.25 22.50
Periods in weeks (>0) 0.00 17.75 28.50
Periods in weeks (=0) 0.25 0.25 0.25
Profitability (GHS) Non-GAP
Strategy 1# Strategy 2+ Strategy 3*
Mean -1,482.50 669.25 2,216.17
Max 2,099.53 6,799.16 10,433.69
Min -2,912.96 -1,575.54 -1224.98
Periods in weeks (<0) 44.25 28.75 20.50
Periods in weeks (>0) 6.75 22.25 30.50
Periods in weeks (=0) 0.25 0.25 0.25
Results
Layer prod (#) 1:0 ratio of layer to broiler day-old chicks purchased
Layer & broiler(+) 0.5:0.5 ratio of layer to broiler day-old chicks purchased
Broiler prod(*) 0:1 ratio of layer to broiler day-old chicks purchased

12. 12
Results
No statistically significant difference
in the profitability for both GAP and
Non-GAP adoption households
under strategy 3 (i.e., Broiler
production)
Statistically significant difference in
profitability under Strategies 1 & 2.
For these strategies (layer production
& mixed production) Non-GAP
adopting households earn more than
GAP-adopting households
T stat= -9.81 p-value = 2.2e-
16**
T stat= -2.89 p-value =
0.0039**
T stat= 0.123 p-value = 0.902

13. 13
Results
Statistically significant difference in the
profitability under strategies 2 & 3
when compared with the profitability
under strategy 1 for both GAP and
Non-GAP adopting households.
1st Broiler production (Strategy 3)
2nd Mixed layer & broiler production (Strategy 2)
3rd Layer production (Strategy 1)
Ranking of profitable production
strategy

14. 14
Conclusions
 From the onset of the poultry production, disease prevention at different
growth stages of the chicken (especially for day-old chicks) is a critical
driver of change that has a high but short-lived dominance. Thus, there is
a potential for total loss and discontinuation of production activities.
 Beyond the grower stage, the changes in the unit price of eggs have a
relatively higher and longer influence on production dynamics than
changes in the unit price of poultry.
 Post-grower stage, the dominance level of the delay in the maturation
and sales of layers highlights the need for determining the optimal
production strategy that provide a financial cushion for farmer
households
PROFIT (Non-GAP-Adopters) > PROFIT (GAP-Adopters)
Because the unit cost of production is higher than the
unit price for poultry meat.
Layers Production (only) is NOT a financially viable
strategy for GAP-Adopters
Broiler Production (only) is a financially viable
strategy with mid-year break even for all farmer
households
E-Driver (change) Profitable Production
strategies

15. 15
Thanks
Photo: Ghana Poultry Project

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