SOMREP ANNUAL RESILIENCE
MEASUREMENT
2021 ARM measurements
Acronyms
ADRA Adventist Development Relief Agency
ACF Action Contre Faim
AFM Accountability and Feedback Mechanism
ARM Annual Resilience measurement
ARM* Adaptive Response Messaging
BFMs Beneficiary Feedback Mechanisms
BRiCs Building Resilient Communities in Somalia
CAAPS Community Action Adaptation Plans
CAHWs Community Animal Health Workers
COOPI Cooperazione Internazionale
DRC Danish Refugee Council
DRR Disaster risk Reduction
EWEA Early Warning Early Action
FEWSNET Famine Early Warning Network
FAO SWALIM Food and Agriculture Organization-Somalia Water and Land Information
Management
FCS Food Consumptions Score
GAP Good Agricultural Practices
GFDRR Global Facility for Disaster Reduction and Recovery
IBLI Index-Based Livestock Index.
HHS Household Hunger Score
NRM Natural Resource Management
RCSI Reduced Coping Strategy Index
SDGs Social Development Goals
SomReP Somali Resilience Program
SomRIL Somali Response Innovation Lab
SNBS Somalia Bureau of Statistics
TANGO Technical Assistance to NGOs (Framework)
ToC Theory of Change
VDC Village Development Committee
VSLA Village Savings and Loans Associations
WVI World Vision International
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Acronyms
Executive Summary.......................................................................................................................viii
Summary of Results and Outcomes...................................................................................xii
Introduction to the Annual Resilience measurement (ARM) ............................................. 1
Background to the program ............................................................................................. 1
General program Context within the study period.......................................................... 1
1.2.1 Desert locusts............................................................................................................ 1
1.2.2 Drought conditions ................................................................................................... 2
1.2.3 COVID 19 ................................................................................................................... 2
Understanding of resilience ............................................................................................. 2
2.0 SCOPE OF THE ASSESSMENT............................................................................................... 3
About the Annual Resilience Measurement (ARM)......................................................... 3
Project objectives............................................................................................................. 4
Program Locations............................................................................................................ 5
Assessment scope ............................................................................................................ 6
2.3.1 Objectives of the study ............................................................................................. 6
Survey methodology ........................................................................................................ 6
2.4.1 Qualitative data collection........................................................................................ 7
2.4.2 Quantitative data ...................................................................................................... 7
2.4.3 Data analysis ............................................................................................................. 8
Study limitations............................................................................................................... 9
3.0 Assessment findings.......................................................................................................... 11
3.1 Demographics and Social Economic Characteristics .................................................. 11
3.1.1 Distribution by location.............................................................................................. 11
3.1.2 Gender, age and marital status of household head .................................................... 11
3.1.3 Education levels of household head ............................................................................ 12
3.1.4 Disability status ............................................................................................................ 13
3.2 Program Participation .................................................................................................... 14
3.2.1 Program participation by activity type ....................................................................... 14
3.2.2 Program intensity.................................................................................................... 15
3.2.3 Program participation across the location ............................................................. 18
3.2.4 Program participation across livelihood zones....................................................... 20
3.2.5 Participation by Gender .......................................................................................... 20
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3.3 Absorptive capacities ..................................................................................................... 21
3.3.1 Shocks and hazards over the last year ................................................................ 21
3.3.2 Shocks experienced in the previous year by type............................................... 23
3.3.3 Impacts of shocks on livelihood .......................................................................... 25
3.3.4 Shock Impact on Disability .................................................................................. 27
3.3.5 Impact of Shocks on Gender ............................................................................... 28
3.3.6 Early warning information................................................................................... 28
3.3.7 Sources of Early warning information................................................................. 29
3.3.8 Extent of recovery from shocks .......................................................................... 31
3.3.9 Community social capital and recovery from hazard ......................................... 32
3.3.10 Natural Resource management....................................................................... 35
3.3.11 Contingency reserves ...................................................................................... 37
3.3 Adaptive capacities ........................................................................................................ 40
3.4.1 Agricultural support ................................................................................................ 40
Access to Land................................................................................................................... 40
Type of farming practiced................................................................................................. 40
Source of water for farming.............................................................................................. 41
Crop varieties planted....................................................................................................... 43
3.4.2 Good Agricultural Practices capacity ...................................................................... 43
Training in GAP.................................................................................................................. 43
3.4.3 Yield production...................................................................................................... 45
Access to agricultural services .......................................................................................... 47
3.4.4 Livestock farming .................................................................................................... 47
I. Veterinary services ..................................................................................................... 48
II. Livestock insurance................................................................................................. 49
3.4.5 Water, Sanitation, and Hygiene.............................................................................. 50
3.4.6 Livelihood, income, and expenditure ..................................................................... 54
I. Income ........................................................................................................................ 54
II. Expenditure............................................................................................................. 57
III. Loans and debts ...................................................................................................... 59
IV. Markets access........................................................................................................ 64
3.4.7 Community and Household Asset Score................................................................. 65
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3.4.8 Financing input for the CAAPS and the role of Shaqodoon.................................... 65
3.5 Transformational capacities........................................................................................... 66
3.5.1 The role of SomRIL innovations in resilience building ............................................ 67
3.5.2 Transformational models adopted for VSLAs ......................................................... 69
I. Model one: Individual VSLA linked to Individual banks as clients.............................. 70
II. Model 2: several VSLAs come together to form a microfinance unit .................... 71
III. Impacts of VSLAs on Women .................................................................................. 72
3.5.3 Creating transformational linkages ........................................................................ 73
3.5.4 Community level governance structures................................................................ 75
I. Early Warning committees ......................................................................................... 75
II. Water management structures .............................................................................. 76
III. Village Development Committee............................................................................ 77
IV. Social Affairs committees ....................................................................................... 79
V. The functionality of the committees in the management of DRR.......................... 80
3.5.5 Accountability, feedback mechanisms ................................................................... 82
3.6 Food security status ....................................................................................................... 83
3.6.1 Food Consumption Score........................................................................................ 84
3.6.2 Household hunger score......................................................................................... 86
3.6.3 Reduced Coping Strategies Index ........................................................................... 89
3.6.4 Household Vulnerability Profile.............................................................................. 92
3.6.5 Correlation between food security indicators........................................................ 94
3.6.6 Concordance and discordance analysis between food security indicator ............. 95
I. Concordance between reduced coping strategy index (rCSI) vs food consumption
scores (FCS) ....................................................................................................................... 95
II. Concordance between reduced coping strategy index vs household hunger scale
97
III. Concordance between food consumption score vs household hunger scale........ 98
3.7 Resilience and Poverty indices ....................................................................................... 99
3.7.1 Resilience Indices ....................................................................................................... 99
3.7.2 Resilience index....................................................................................................... 99
3.7.3 Absorptive index ................................................................................................... 100
3.7.4 Adaptive capacity index ........................................................................................ 101
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3.7.5 Transformative index ............................................................................................ 102
3.7.6 Correlations between resilience index and program intensity ............................ 104
3.7.7 Correlation between resilience index and program activities.............................. 104
3.8 Poverty Indices ............................................................................................................. 105
4. Cross cutting issues............................................................................................................. 106
4.7 Project Sustainability.................................................................................................... 106
4.8 Gender.......................................................................................................................... 107
5. Conclusions and recommendations.................................................................................... 108
5.1 Conclusions ....................................................................................................................... 108
5.2 Recommendations ............................................................................................................ 109
6. Annexes............................................................................................................................... 113
List of figures
Figure 1: Gender distribution of respondents .............................................................................. 12
Figure 2: Education level of household head ............................................................................... 13
Figure 3 Respondent disability status:.......................................................................................... 14
Figure 4: Respondent distribution by interventions..................................................................... 15
Figure 5: Intensity of activities across beneficiaries ..................................................................... 17
Figure 6: Program participation across location........................................................................... 18
Figure 7: program participation by gender................................................................................... 21
Figure 8: Shocks across livelihood ................................................................................................ 21
Figure 9: Comparative Shock Exposure Index............................................................................... 22
Figure 10: Mean Shock Index........................................................................................................ 23
Figure 11: FEWSNET early warning in drought shock................................................................... 25
Figure 12Impact of Shock on Disability......................................................................................... 27
Figure 13: Impacts of Shocks on gender....................................................................................... 28
Figure 14: % that receive hazard alert .......................................................................................... 29
Figure 15: Early Warning information by type and source........................................................... 30
Figure 16: Usefulness of information received............................................................................. 31
Figure 17: Contingency measure in place..................................................................................... 31
Figure 18: Extend of recovery ....................................................................................................... 32
Figure 19: Beneficiaries reporting support to recover from shocks............................................. 33
Figure 20: Source of community support in responding to shocks .............................................. 33
Figure 21: respondents reported likelihood to support others faced by shocks ......................... 34
Figure 22: Proportion of beneficiaries that reported they are likely to receive support............. 35
Figure 23: Existence of NRM committee in the community......................................................... 36
Figure 24: Plans implementation.................................................................................................. 36
Figure 25: Contingency reserves................................................................................................... 37
Figure 26 :Type of contributions made by the households to contingency reserve .................... 38
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Figure 27: Experience of NRM related conflicts ........................................................................... 39
Figure 28 NRM conflicts solved amicably ..................................................................................... 39
Figure 29: Farming type ................................................................................................................ 41
Figure 30: Source of water for farming......................................................................................... 42
Figure 31: Weather seasons in Somalia........................................................................................ 42
Figure 32: Primary and secondary crops grown by beneficiaries................................................. 43
Figure 33: Respondents reporting training and adoption on GAP ............................................... 44
Figure 34: Comparative analysis of GAP adoption between 2019 and 2021 ............................... 45
Figure 35: Respondent reporting increased incomes as the subject of increased yields ............ 46
Figure 36: Access to extension services........................................................................................ 47
Figure 37: Type of extension services........................................................................................... 49
Figure 38: Access to insurance...................................................................................................... 50
Figure 39: Main sources of water across livelihood zones ........................................................... 51
Figure 40 Comparison of access to water across livelihood zones and seasons.......................... 53
Figure 41: Percentage increase in costs of water across livelihood and seasons ........................ 53
Figure 42: The loans repayment period........................................................................................ 59
Figure 43: Main mode of transport to markets ............................................................................ 64
Figure 44: SoMRIL Innovations incubation process...................................................................... 67
Figure 45: VSLA to bank model 1 .................................................................................................. 70
Figure 46: Amalgamation of VSLAs model.................................................................................... 71
Figure 47: Impacts of VSLAs on women........................................................................................ 72
Figure 48: transformational linkages created by the project ....................................................... 74
Figure 49: Awareness on the existence of EWA committees ....................................................... 75
Figure 50: Government involvement in Hazard analysis .............................................................. 76
Figure 51:% reporting functionality of water committees ........................................................... 76
Figure 52: Roles of water committee ........................................................................................... 77
Figure 53: Community involvement in formulation and implementation of CAPPs .................... 78
Figure 54: Government involvement in CAAPS ............................................................................ 78
Figure 55: SAC community structure ............................................................................................ 79
Figure 56 Presence of SACs in the community ............................................................................. 80
Figure 57: Community perception of leaders’ effectiveness........................................................ 81
Figure 58 Government responsiveness and accountability in resilience ..................................... 81
Figure 59: Accountability mechanisms in place............................................................................ 82
Figure 60: Beneficiaries CRM voices accommodated................................................................... 83
Figure 61: Comparison of FCS between 2020 and 2021 across livelihood................................... 84
Figure 62 Comparison of FCS across gender................................................................................. 86
Figure 63: Comparison of Hunger score between 2020 and 2021............................................... 87
Figure 64: RCSI across livelihoods................................................................................................. 90
Figure 65" Analysis of Disability versus rCSI ................................................................................. 91
Figure 66: Analysis of rCSI versus Gender .................................................................................... 91
Figure 67: Household vulnerability Analysis................................................................................. 92
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Figure 68: Livelihood Groups vulnerability profile ....................................................................... 93
Figure 69: District vulnerability profile ......................................................................................... 94
Figure 70: Resilience Index by gender ........................................................................................ 100
Figure 71: Absorptive Index by Livelihood.................................................................................. 101
Figure 72: Adaptive capacity Index............................................................................................. 102
Figure 73: Transformative Inx across livelihood ......................................................................... 103
List of tables
Table 1: Progressive measurements of the core indicators .........................................................xiii
Table 2: program objectives ........................................................................................................... 4
Table 3: Project target locations..................................................................................................... 5
Table 4: Distribution of respondents by district ........................................................................... 11
Table 5 Comparison of Program intensity performance by District............................................. 19
Table 6: Shocks experienced by respondents............................................................................... 24
Table 7: Impact of Shocks on Livelihood....................................................................................... 25
Table 8: Comparison of Shock exposure against program intensity ............................................ 26
Table 9: Sources of EWEA disaggregated by Source .................................................................... 29
Table 10 Percentage contribution to income by source and year ............................................... 55
Table 11: Income contribution by source and livelihood ............................................................. 56
Table 12 Average income by Source............................................................................................. 56
Table 13 Average income across gender ...................................................................................... 57
Table 14: Average expenditure across livelihood......................................................................... 58
Table 15: Expenditure analysis categorized by gender ................................................................ 58
Table 16: Form of loan taken by livelihood zone.......................................................................... 59
Table 17: reasons for taking loans ................................................................................................ 60
Table 18: Sources of Loans ........................................................................................................... 61
Table 19: Reasons for being denied loans .................................................................................... 62
Table 20: Deficit analysis............................................................................................................... 62
Table 21: HHS by Location ............................................................................................................ 88
Table 22 : HHS analyzed against gender and disability ................................................................ 89
Table 23: Correlation between Food Security Indicators ............................................................. 94
Table 24:Concordance between Rcs Ivs FCS................................................................................. 96
Table 25: Concordance between rCSIvx HHS................................................................................ 97
Table 26:Concordance between FCS vs HHS ................................................................................ 98
Table 27: Resilience capacities across districts........................................................................... 104
Table 28: Analysis of Stochastic poverty among the beneficiaries ............................................ 105
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Executive Summary
This report is part of a longitudinal survey conducted on annual basis to determine the extent to
which Somalia’s Resilience Program (SomRep) has impacted the chronically vulnerable
households within 16 districts. The project aims at enhancing the resilience of vulnerable
communities by increasing their adaptive and absorptive capacities, through community
participatory planning, the use of financial instruments such as savings groups, and the
management of rangelands and eco-system health.
The project has been made possible through the funding of DANIDA, SIDA, DFAT, SDC, BMZ and
European Union/European Aid and implemented by a team of International Non-Governmental
Organizations led by WVI with the Consortium members being World Vision COOPI, DRC ACF,
ADRA, CARE, and Oxfam and Shoqadoon
The purpose of the assessment was to assess the relevance, and effectiveness of the program
strategies and interventions, in achieving the project’s intended purpose. The project sought to
measure changes that occurred in various resilience capacities and wellbeing indicators. Finally,
the project sought to establish the effectiveness and efficiency of program interventions in
strengthening the response capacity of various shocks and stresses including COVID-19 effects,
Desert Locust, Conflict, drought, and floods.
The study was a cross-sectional study that drew a mix of quantitative and qualitative approaches.
Quantitative data used the same tool developed and used in previous studies with few
adjustments to improve on data captured. To capture additional complementary information,
Vision quest developed Key Informant and focus Group discussions and observation guides for
qualitative information gathering. The sampling formula used was Krejcie and Smith 1979,
producing an initial sample of 2781 households. The study adapted two stage cluster sampling
where the first stage the households were distributed across the 16 districts based on probability
proportionate to size of the program beneficiaries. At the second stage, the household
respondents were selected randomly using simple random sampling.
Data collected was disaggregated along with the study target districts for purpose of content
analysis about unique features of each of the 16 project districts and livelihood characteristics as
well as other variables such as gender and disability. Quantitative was analyzed using STATA
software for in-depth analysis. On qualitative data, individual KIIs and FGDs interviews were
transcribed and analyzed across key research themes and categories across the evaluation
objectives. Qualitative data accruing from this being processed in excel. Verbatim quotations
from qualitative data were extracted to justify and augment key findings as extrapolated from
the quantitative data set.
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The key findings from the research showed that there was a well-developed resilience strategy
for the project. The project partners were aware of the strategy and project theory. The period
of the assessment was characterized by multiple shocks that put the project theory and potential
outcomes to the test. The project battled triple shocks (Covid-19, Locusts and floods/droughts
during the 2020-2021 period and by the time of the reporting, the Dery rains had failed to lead
to an increase in the number of people expected to enter into food security crisis within 2022.
The shocks of 2020/2021 affected the various targeted districts differently. There was a
significant difference (P=0.00) between these the shocks’ severity across the district. The shock
severity was high in Baidoa (10.6) and Elbarde (10.0) and lowest in Salahley (0.04) and Lughaye
(0.03).
The study found out that the proportion of beneficiaries participating in one activity only
decreased by 3% point from 68.7% in 2021 to 65.1% the 2020 and the difference in proportions
was statistically significant at 5% level of significance (P=0.008). The number of respondents
reporting at least being involved in two activities increased by 0.4% point from 16.1% in 2021 to
15,8% in 2020 ( and the difference in proportions was not statistically significant at 5% level of
significance (P=0.3529)) while those involved in at least three interventions decreased by 3%
point from 18.8% in 2020 to 15.8%in 2021 ( and the decrease the difference in proportions was
statistically significant at 5% level of significance (P=0.0002).
Absorptive capacity index reduced significantly from 21.4 in 2020 to 10.6 in 2021. The difference
in mean absorptive capacities between the two periods was statistically significant at 5% level of
significance (P=0.0000). There was no statistically significant difference in absorptive capacity
index across the gender (P=0.35) even though male-headed households had a relatively higher
absorptive capacity index (11.1) than female-headed households (10.1). However, there was a
significant difference (P=0.00) in absorptive capacity scores between livelihoods. Agro-pastoral
and peri-urban had the highest score of 14.8 and 14.7 respectively while pastoral had the least
at 7.8. The absorptive capacity was significantly different (p=0.00) among respondent with
disability (12.1) and those without (23.9). T Across districts, Absorptive capacity was lowest in
Lughaye (1.81%), Salahley (2.55%), Hargeisa (3.5%), CeelBarde (4.64%), Burao (4.29%), and Hudur
(4.89%). Generally, absorptive capacity was weak across all districts, with the highest responses
being 24.2% and Laascanod (27.9%). The decrease in absorptive capacity could be attributed to
households’ exposure to multiple shocks. The mean shock exposure index among SomReP
beneficiaries increased from 2.79 in 2020 to 3.01 in 2021 and increased significantly amongst
households who reported to have experienced (i.e. from 6.24 in 2020 to 9.10 in 2021).
The average income reported in 2021 increased by 22% compared to the previous year. However,
there was a significant drop in livestock as the main sources of income reported in 2020 from
47.3% to 22%. Crop income increased significantly from 25% to 53% overtaking livestock-based
incomes. However, there was a wide gaps (standard deviation) in incomes reported with the
highest reported income being USD $ 4350 and minimum reported income being zero.
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Adaptive capacity index reduced marginally from 34 in 2020 to 32.2 in 2021 and the difference
in mean adaptive capacity indices between the two periods was statistically significant at 5% level
of significance (P=0.0000). . The results further show that men had higher adaptive capacity index
at 32.6% compared to women at 31.9% however the difference was not statistically different at
5% level of significance (P=0.1066). The decrease was pronounced among the agro-pastoral
households from 38.0 in 2020 to 33.3 in 2021 but marginally among pastoral households from 30
in 2020 to 28.1 in 2021. Interestingly and something important to note, the adaptive capacity
index increased significantly among the per-urban households from 27 in 2020 to 34 in 2021. The
increase in adaptive capacity index could be attributed to among other things opening up of
markets after a lift of COVID-19 restrictions which were intermittent in the previous year.
Adaptive capacities were stronger in Baidoa (46.9%), Afgooye (41.5%) Salahley (38.4%), and
Hargeisa (37.4%) but weaker in lughaye (18.5%), Ceelafweyne 22.7%) (Hudur (23.8%).
Transformative capacity index reduced from 29 in 2020 to 24.3 in 2021 and the difference was
statistically significant (P=0.0016). The results further show that men had higher adaptive
capacity index at 25.5 compared to women at 23.2 and the difference in means between men
and women were statistically significant at 5% level of significance (P=0.0012). The results also
show that transformative capacity index decreased across all livelihood groups. However, the
decrease was pronounced among the agro-pastoral and peri-urban households from 31.0 and
29.0 in 2020 to 25.5 and 22.4 in 2021 respectively. The decrease was rather marginal for peri-
urban households from 25.0 in 2020 to 23.1 in 2021. Weakening of transformative capacity
among households and communities in 2021 could be attributed to impact of covariate shocks
that undoubtedly weakened the capacity of informal and formal social networks to cushion each
other. In the face of adverse covariate shocks everyone becomes affected and the focus of
humanitarian actors shifts from building resilience to life serving responses which gradually leads
to weakening of the transformative capacity.
Transformational capacity was strongest in Beletawo (40.1) and Xudur (39.9), and Eyl (35.3%) but
weakest in Lughaye (10.1%) followed by CeelBarde with 16.3%.
The overall resilience index reduced from 30 in 2020 to 22.4% in 2021 and the reduction was
statistically significant at 5% level of significance (P=0.0000). The resilience index was higher for
men (23.0) compared to women (21.7) and the resilience index was highest among the agro-
pastoral households at 23.3 followed by Peri-urban households at 22.7 and lastly pastoral
households at 20.0. The decrease in resilience index was most among the agro-pastoral and
pastoral household (i.e. from 32.0 to 23.3 among the agro-pastoral households and from 30 to
22.7 among the pastoral households) which could be attributed to their high exposure to shocks
with a mean shock exposure index of 9.13 among those who experienced shocks. Overall,
resilience was stronger in Badhan (31.2%) followed by Afgooye (29.8%) and Beletawo (29.2%)
but weaker in Lughaye (10.1%) and Burao (14.2).
There was a positive correlation between number of interventions and the overall resilience
index (r=0.302, P=0.00). The food consumption score was negatively correlated with reduced
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coping capacity (r= -0.2194, p=0.00) meaning that household prioritized food consumption thus
adapting higher coping mechanism. The correlation hunger scale and coping mechanism was a
positive one (r= 0.2215, p=0.00) meaning household with high hunger score tends to use one or
more of the mechanism to cope up with the hunger.
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Summary of Results and Outcomes
Core indicators Indicator ARM 2017 ARM
Results
% households who are Results Not compu
structurally non-poor [1] as
measured by stochastic and Not computed Not compu
structural poverty.
Resilience index 1 ( as measured Not computed
by Tango framework)
Absorptive Capacity Index 32% 52%
Adaptive capacity Index
Transformative capacity Index
% of targeted households with
little to no hunger as measured
by Household Hunger Scale
SoI1: % of households having 54% (livelihood 63%
acceptable food consumption disaggregation (Peri-Urban
scores (disaggregated by was not Urban
household head gender, and computed) Pastoral,
vulnerability type) IDP 68%,
Not computed Pastoral 60
SoI2: % of communities who 12.5%
(livelihood
report to utilize EWEA disaggrega
was
information to make risk computed)
informed decisions
2019 ARM 2020 Results ARM 2021 results
uted 37.5% 35.3%
uted 30 22.4 (female 21.7; Male 23.0,
Agro-pastoral 23.3; Pastoral
23.7 20.0, Peri-urban 22.7)
34 10.6 (Female10.1, Male11.1)
32.2 (Female31.9,Male32.6)
29 24.3 (female(23.2, Male-24.3)
69.6% (Agro-pastoral 70.5%,
73.20% Pastoral 66.9%, Peri-urban
70.4%; Female 69.2%, Male
70.1%
n/ 44.9% 50.4% (Agro-pastoral 41.7%,
80%, (Peri-Urban/ Urban Pastoral 63.4%, Peri-urban
49%, 47 %, Pastoral 46.2%, 61.0%; Female 49.2%,
Agro- IDP 29.5%, Agro- Male51.6%
Pastoral 44.3%)
0%) 53.1% (Agro-pastoral 53.7%,
22.1% Pastoral 57.5%, Peri-Urban
ation 45.7%)
not (Peri-Urban/ Urban
) 12.3%, Pastoral
18.5%, IDP 7.4%,
(disaggregated by livelihood Not computed HH 41
zone) (Pastoral
SoI3: % increase in community community
asset score (disaggregated by Agro-pasto
livelihood zone) in program community
areas 10.5%
(Male
So14: % of people in targeted Not computed Female
(Peri-Urban
districts (gender-disaggregated) Pastoral
Agro-pasto
who view local governments as 18%, IDP=5
accountable and responsive to Not compu
community priorities in
providing equitable services and
promoting resilience
interventions
So15: % of innovations piloted Not computed
through SomRIL and adopted for
scale-up
Table 1: Progressive measurements of the core indicators
Outcome indicators Not computed 60
(P
Io111: % of target households who have positive (7
coping strategies as measured by the reduced (8
coping strategy index (rCSI) (disaggregated by A
household head gender, vulnerability type, and (6
livelihood zone).
Io211: % reduction in households who need Not computed N
humanitarian assistance during shocks and stress
1 This is a process-oriented indicator and hence difficult to capture in absolute fi
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Agro-Pastoral 30.3%,
Fisher-folk 33.3%)
HH 24.3 HH 35.3 (Peri-urban/urban 54,
Pastoral 31.3, Agro-pastoral
(Peri-urban/urban 30.6)
y 32, 37, Pastoral 23.7, IDP 65.1% (Agro-pastoral 63.27%,
oral Pastoral 67%, Peri-urban/Urban
y 42 9.1, Agro-pastoral 67.9%; Female 63.9%, Male
66.3%)
7.9%, 19.5, Fisher fork 8.2)
1.3%)/ 33.3%1
n 10%, 66.8%
9%, (Male 64.6%, Female
oral
5% 66.9)/ (Peri-Urban/
uted Urban 67.4%,
Pastoral 63.3%, IDP
61.1%, Agro-Pastoral
64.6%, Fisher-folk
66.7%)
TBD
0% 30.3% 22.6% (Peri-
Peri-Urban/ Urban
75%) Pastoral (Peri-Urban/ Urban urban/urban 28.7%,
85%) IDP (68%)
Agro-Pastoral (28.0%) Pastoral Pastora10.7%, Agro-
69%)
(27.3%) IDP (30.5%) pastoral 25.5%; Male
Not computed
Agro-Pastoral (33.5%) 19.4%, Female 25.5%)
Fisher-folk (0.0%)),
(Male (31.9%), Female
(28.5%))
26.80% 30.4%
igures.
Io212: % increase in household incomes (data Not computed N
disaggregated by household head gender,
vulnerability type, and livelihood zone).
Io213: % of the targeted populations with all-year 15% 60
access to multi-use water (for irrigation
agricultural production & domestic use) as a result Not computed 5
of investment in large scale water infrastructure Not computed
and small scale water infrastructure disaggregated 40
by men and women household head gender, Not computed d
vulnerability type, and livelihood zones 20% (Gender n
Io214: #of hectares under soil and water and livelihood N
conservation measures disaggregation 35
Io215: % of households experiencing yield was not liv
improvements (by gender and livelihood zone) computed) d
n
Io216; % Increase in yield per unit hectares
Io3I1: % of HHs engaging in multiple income-
generating activities as measured by participation
index [1]. (disaggregated by household head
gender, vulnerability type, and livelihood zone)
Io3I2: % increase in household asset diversification Not computed H
score (disaggregated by household head gender, co
vulnerability type, and livelihood zone) A
co
Io313: % increase in households who realize Not computed N
improved profit gains from their sales
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Not computed Mean 140.4522 N 2,871, Minimum 0.00,
0% N: 2700 Minimum 0.0, Maximum 4350; Mean
Maximum 5,245, , Std. 171.9 USD std deviation
Deviation 263.09463 1035. Agro-pastoral
189.0 USD, Pastoral
77.50% 1128.2 USD, Peri-urban
177.0 USD
78.65%
Hectare 28.9 Hectare Not comuputed*
0% (Gender 28.3% 48% (Male 56.2%, Male
disaggregation was (Male 31.3%, Female 41.7%)
not computed) 23.7%)
Not computed Not computed Not computed*
40.1%
5.3% (Gender and (Male 41.8% Female 66.8% (Male69.3%,
velihood 38.1%), (Agro-Pastoral
disaggregation was 44.7%, Pastoral 31.6%, Female=64.4%; Agro
not computed) Fisher-folk (0.0%), IDP
35.8%, Peri-Urban/ pastoral 72.7%, Pastoral
HH 41 (Pastoral Urban 42.6%)
ommunity 32, 24.3% 63.0%, Peri-
Agro-pastoral (Peri-urban/urban 37,
ommunity 42 Pastoral 23.7, IDP 9.1, urban/Urban 53.8%)
Agro-pastoral 19.5,
Not computed Fisher fork 8.2) HH 35.3 (Peri-
63.9% urban/urban 54,
Pastoral 31.3,
pastoral 30.6) Agro-
72.3% (Agro-pastoral
74.3%, Pastoral 69.2%,
Io314: % increase in households who reports easy Not computed N
access to markets
Io315: % increase in households who report Not computed N
improved $ sales volume per season Not computed N
Io316: % increase in households who have access
to formal financial services (e.g. those able to open
accounts /access loans from formal banks, mobile
money providers)
Io317: % point increase in the proportion of Not computed N
women that engage in jobs in sectors of Not computed N
sustainable livelihoods (diversified production-
related incomes) and economic growth (business
development services like transport, milling,
bulking, and input supply)
Io411: Extent to which targeted communities are
satisfied with delivery of basic services by local
government (measured on a scale of 1 to 5)
Io412: % increase of participation of women and
other disadvantaged groups in decision making at
the district level in the determination of
development priorities and CAAP financing
xv | P a g e
Not computed (Agro-Pastoral 76.3%, Peri-urban/Urban
Fisher-folk 66.7%, IDP, 71.4%, Female 68.6%,
Not computed 35.8%, Pastoral 68%, Male 76.1%)
Not computed Peri-Urban/ Urban
36.6%), (female 68.6%, 65.0% (Agro-pastoral
Not computed 58.6%) 58.3%, Pastoral 73.5%,
66.5% Peri-urban/Urban
73.9%; Male 64%,
63.90% Female 65.9%)
62.40%
36.40% 17.0% (Male 16.7%,
56.50%
Female 17.1%; Agro-
pastoral 15.3%, Pastoral
17.1% Peri-
urban/Urban 21.6%)
55.30%
3 (64.8%) 3 (54.86%)
Not computed 46.2% Women, 37.4 of 43.75 (Agro-pastoral
47.8%, Pastoral 40.6%,
disabled household Peri-urban 37.5%)
heads (peri-
urban/Urban 45.4%,
Pastoral 54.9%, IDP
23.2%, Agro pastoral
Io511: Extent to which local development Not N
annual plans have incorporated priorities from computed
communities identified through CAAPs
(measured on a scale of 1 to 5)
Io512: % of targeted government staff who are Not N
able to lead CAAPs monitoring and evaluation computed
processes at the community level
*The “#of hectares under soil and water conservation meas
population and not a sample survey. Refer to recommendat
xvi | P a g e
Not computed 45.7%, Fisher folk
66.7%)
2.8
Not computed
Not computed 42.90% 78.1%
sures” indicator was not calculated as would best come from total
tions for more details.
Introduction to the Annual Resilience
measurement (ARM)
Background to the program
SomReP program is a multiyear effort by eight NGOs to tackle the challenge of recurrent
droughts- and the chronic vulnerability that results- among pastoralists, agro-pastoralists, and
peri-urban households across Somalia. International Non-governmental Organizations (INGOs)
and one local NGOs which include: ACF, ADRA, CARE, COOPI, DRC, Oxfam, and World Vision, and
a local NGO Shaqadoon with deep experience in Somalia, have joined as a long-term consortium
to build and field test a resilience model based on the latest global resilience thinking innovative
livelihood approaches for the Somalia context and bridging the relief to development continuum.
The consortium was formed following the famine of 2011. With support from several donors,
SomReP has implemented several projects, which aim at enhancing the resilience of vulnerable
communities by increasing their absorptive, adaptive and transformative capacities, through
community participatory planning, promotion of agriculture interventions (crop/livestock) the
use of financial instruments such as savings groups, and the management of rangelands and eco-
system health.
General program Context within the study period
COVID-19, Desert livestock infestation, and extensive flooding followed by drought and uncertain
election process have been the hallmark of 2020-21. These shocks have compounded an already
bad situation because of decades of war and chronic poverty. According to the UNOCHA, Climate
change continues to be a major contributing factor to displacement and food insecurity in
Somalia. Erratic weather patterns and climatic shocks have led to prolonged and severe drought
conditions and floods, with devastating humanitarian consequences. Flooding displaced 919,000
people in 2020 and destroyed essential infrastructure, property, and 144,000 hectares of
agricultural land2. After the floods, then came failed rainfalls that continued to bite until the time
of this research.
1.2.1 Desert locusts
At the same time Somalia was experiencing flooding, desert locusts invasion, thousands of
hectares of cropland and pasture were damaged, with potentially severe consequences for
agriculture and pastoral-based livelihoods. FAO estimated that locusts in Ethiopia and Somalia
invaded 173,000 areas of land. Pockets of land in Somalia that were affected by desert locusts
included SOMREP project areas. By January 2021, a few small immature swarms remained on the
plateau in northwest Somalia and the northeast.
2 2021 Somalia Humanitarian needs overview; https://reliefweb.int/report/somalia/2021-somalia-humanitarian-
needs-overview
1.2.2 Drought conditions
FewsNet seasonal monitoring report indicated that ground information and remote-sensing data
both confirmed rainfall failure across most of Somalia during November 2021. Most central and
northern regions were completely dry, while rainfall totals in the southern regions were
indicative of a 25-100 mm deficit from the long-term mean, River. According to SWALIM’s river
station gauge data on November 23, all river level monitoring stations on both the Shabelle and
Juba Rivers, except Beledweyne and Buloburte, indicated the rivers are below the long-term
mean and significantly below the flood risk thresholds.
Low river water levels have negatively affected irrigation activities in riverine areas. With a
forecast of low to moderate precipitation over the Ethiopian highlands over the coming week,
the risk of drought remains high.
By the time of this study, the country is experiencing a total failure of 2021 Gu rains, and drought
conditions are at the peak with populations across the agriculturalist zone of central moving to
IDP camps in Baidoa.
1.2.3 COVID 19
Somalia’s total confirmed cases of Coronavirus cases stand at 23,025. Like all other countries, the
first reaction to the disease outbreak was the closure of movements, borders, and airports.
UNOCHA in Somalia estimated that the cumulative positivity rate since the start of the COVID-19
outbreak in Somalia has declined gradually to 7 percent while the cumulative case fatality rate
stands at 2.6 percent. With the reduction in the level of infection and greater global
understanding of the virus, Somalia started opening up movements, airports, and border-
crossing areas though with restrictions. The latest World Bank Somalia Economic Update3 reports
that the economy contracted by 0.4 percent in 2020. This was partly a result of disruptions
stemming from COVID-19 containment measures. However, there was a significant effort to
trigger social protection measures to cushion vulnerable households, and higher-than-expected
remittance inflows mitigated the adverse effects of the triple shock4.
Understanding of resilience
Resilience is recognized as central to achieving the Sustainable Development Goals (SDGs), the
Sendai Framework for Disaster Risk Reduction (DRR) 2015–2030, and the Paris Climate
Agreement. The term ‘resilience’ is widely used in policy, practice, and academic discourse.
Resilience is the ability of countries, communities, and households to manage change, by
maintaining or transforming living standards in the face of shocks or stresses, without
compromising their long-term prospects5. Resilience has been conceptualized in various ways,
3 WorldBank 2021, Somalia’s Economy Rebounding from ‘Triple Shock’. https://www.worldbank.org/en/news/press-
release/2021/09/14/somalia-s-economy-rebounding-from-triple-shock
4 Floods, Desert locusts and Covid 19
5 DFID definition
2|Page
ranging from traditional ideas around resistance to shocks and the ability to maintain or bounce
back to the status quo to more progressive ideas linked to adaptive management and the
creation of new capacities to deal with unforeseen changes.6 In Somalia, the term is used by a
number of agencies who have come together as consortia or working individually to respond to
chronic emergencies that have continued to threaten the future of the Somali people.
Resilience is more of a process than an outcome. It can potentially act as a bridge between
emergency response and long-term development aid, tackling the vulnerabilities that make
people susceptible to shocks7. As such, the way to building resilience ought to be multifaceted.
This has been witnessed in Somalia as actors have come up with models anchored in multi-prong
approaches with graduation models.
2.0 SCOPE OF THE ASSESSMENT
About the Annual Resilience Measurement (ARM)
The Somalia Resilience Program (SomReP) goal is to increase the resilience of chronically
vulnerable people, Households (HHS), communities, and systems in targeted pastoral, agro-
pastoral, and peri-urban livelihood zones by improving adaptive capacity, absorptive capacity,
and transformative capacities. Increase the resilience of chronically vulnerable Somali people,
households, communities, and systems to climatic shocks and other related risks in targeted
pastoral, agro-pastoral, and peri-urban livelihood zones by 2023. The program Theory of Change
(ToC) assumes that creating layered and sequenced pathways of activities around the absorptive,
adaptive and transformative capacities of the targeted community will create resilience. SomReP
has included a learning and research component whose purpose is to document the program’s
impact, assess the progress so far made on key outcomes and output indicators to understand
the impact of the project, test the theory of change underpinning the strategies and interventions
delivered, but will also inform future strategic programming and project development.
Accordingly, SomReP has conducted annual resilience measurements since 2016/17/19/20 to
document the impact of the SomReP programs and assess the progress made annually on key
outcomes and output indicators. This resilience measurement study will build on these studies
to document the program’s impact and assess the progress so far made on key outcomes and
output indicators. SomReP want to take advantage of this assessment to establish whether the
hypotheses and assumptions set to underpin SomReP Theory of Change and causal linkages
between inputs and activities and outcomes and impacts were plausible and valid.
6 https://cdn.odi.org/media/documents/12585.pdf
7 https://www.thenewhumanitarian.org/analysis/2013/03/04/understanding-resilience
3|Page
Project objectives
The program objectives and specific outcomes are outlined in the table below
Project Goal Increase the resilience of chronically vulnerable Somali people, households,
communities, and systems to climatic shocks and other related risks in
targeted pastoral, agro-pastoral, and peri-urban livelihood zones by 2023
Specific Sustainably improve food security and livelihoods of Somali people,
Objective households, communities through effective risk management, protection of
productive assets, improved governance of resilience structures, and
promotion of innovations and evidence-based programming
Intermediary Improved capacity of households to implement disaster risk reduction and
Outcome 1 positive coping strategies to mitigate the immediate effect of exposure to
shock;
Intermediary
Outcome 2 Improved capacity of individuals, households, and communities to adhere to
positive development trajectories; despite exposures to shocks and utilize
strategies designed to allow adaptation to rapid and slow on-set hazards;
Intermediary
Outcome 3 Improved capacity of households to engage in strategies for sustainable
livelihoods and economic growth to enhance food security and resilience
Intermediary
Outcome 4 Governance structures at community, district, and national levels are
strengthened to enhance participation, transparency, and accountability.
Intermediary
Outcome 5 Programming, policy actions, and decisions on resilience in Somalia informed
on evidence-based resilience research, learning, and innovation
Table 2: program objectives
According to the terms of reference and documents obtained, SomReP programming supports
resilience through four different pathways:
Livelihoods & food security: HHs in targeted communities have improved access to
productive livelihoods for enhanced food access and diversity;
Social Safety Nets: HHs in target communities have their livelihoods and assets
protected during shocks and stressors through the establishment and strengthening of
social safety nets, including the use of crisis modifier mechanisms such as Savings Group
Schemes;
Natural resource management: Ecosystem health improved through the promotion of
equitable and sustainable natural resource management;
Local governance capacity building: Communities, civil society, and local institutions are
better equipped with resilience strategies and response capacities to cope with
recurrent shocks and stressors.
4|Page
Program Locations
Program locations cover a wide geographic scope, including areas of South Central Somalia,
Somaliland, and Puntland.
Region Districts
Lower Shabelle Afgooye and Bosaso
Sanaag Badhan and Ceel Afweyne
Bay Baidoa
Gedo Belet Xaawo and Dollow
Togdheer Burao and Odweyne
Bakool El barde, Wajid and Xudur
Maroodi-Jeex Hargeisa and Salahley
Sool Las Canood
Awdal Lughaya
Nugaal Eyl
Table 3: Project target locations
The criteria used to select program districts is as follows:
Fragility: Districts that have historically experienced recurrent swings between IPC
classification Phase 2 (Stressed) and Phase 3 (Stressed)/Phase 4 (Emergency) and
supported by member’s assessment, validated by 2013 program baseline
Need: Long-isolated, marginalized locations in Phase 3 and above to support drought
recovery and stability;
Members’ current and historic operational presence: Understanding local community
dynamics and having existing and/or historic ties is important for establishing long-term
programming. SomReP will consider expansion when members have operational bases,
access (air/transport), capacity to implement and monitor projects, an intent to build
long-term programs;
Security: Current and anticipated accessibility by senior agency staff, e.g. managers and
coordinators (whether or not a remote programming model is used), and political
stability and security (related to access), based on security assessments by key technical
staff.
5|Page
Assessment scope
2.3.1 Objectives of the study
The specific objectives of the assessment will include the following:
i. Assess the relevance, and effectiveness of the program strategies and interventions
about the context and the programme strategic framework, documenting the lessons
learned and best practices to inform future adaptations of interventions typologies.
ii. Establish the extent to which the consortium has achieved its purpose and delivered on
intended outputs, and whether the intended outcomes were met about resilience
programming
iii. Assess the impact of the program with particular focus on establishing changes that
have occurred as measured by resilience capacity indices (absorptive capacity index,
adaptive capacity index, and transformative capacity index ) and wellbeing indicators
(provided for in SomRep master logical framework). For example food security and
coping strategies indicators (i.e. HHS, FCS, rCSI), ownership of household and
community productive assets, (climate-sensitive and non-climate sensitive assets),
income and expenditures among others; and disaggregated to livelihood zones and
other vulnerabilities.
iv. Assess the effectiveness and efficiency of program interventions in strengthening the
response capacity of various shocks and stresses including COVID-19 effects, Desert
Locust, Conflict, drought, and floods.
Survey methodology
This section sets out the data collection tools utilized during this research. Vision quest utilized
a mixed-method design, using qualitative data to augment and triangulate the quantitative
research findings. Data collection tools were developed and implemented based on research
principles. This included the adoption of the HH survey tool used previously with minor changes
to ensure the data generated is comparable. At the end of the research, VQ collated the findings
from 168 districts across the program. The study methodology was designed to respond to
questions posed on the Terms of Reference (TOR) and the project purpose.
Inception phase: During the inception phase of the project, vision quest held a meeting to
conceptualize the project, agree on assessment methodology and sample frame. Following this
discussion, an inception report was developed that guided the whole process of data review and
collection.
Desk review: Vision quest undertook a broad review of literature on the resilience landscape in
Somalia and across other areas for drawing useful lessons and best practices. Further, the
Consultants reviewed data from the project to provide a comparative analysis of the findings.
Some of the data reviewed include reports and studies mentioned by KII during the interviews
8 The 17th district, Luuq, dropped out of the study due to insecurity.
6|Page
and hence broadening the scope of the study to capture as much information relevant to the
study as possible. Secondary data review broadly looked at;
i. The resilience landscape in Somalia and across other areas in the world
ii. Data generated by the SoMReP over the period –, to what extend the theory of change
is plausible, document progress, inquiries on the extent the project has achieved its
goals as well as how lessons learned integrated to improve the program design and
outcomes.
iii. Develop an evidence base for the current assessment.
2.4.1 Qualitative data collection
The assessment integrated a descriptive explanatory qualitative study using semi-structured
interviews. In each of the locations, enumerators conducted a focus group discussion with men
and women separately. A total of 28 FGD were conducted half of these interviews targeted
women while the other half-targeted men. Discussion groups were limited to 8-10 persons and
targeted already structured committees and community representation. Alongside the FGD,
Vision quest conducted 32 key interviews were conducted (23 Humanitarian actors and 9
governments officials) an observation checklist was also developed to guide field observations.
Where possible, enumerators took photos of the project interventions as observed.
2.4.2 Quantitative data
Vision Quest used a representative sample drawn from the beneficiary population using multi-
cluster sampling as represented in the figure below. A sampling frame was drawn across the
program implementation locations based on population and the number of target beneficiaries
in line with the project documents. The sample size was calculated using Krejcie and Smith1979
given below which was also used in the previous ARMs assessments for results comparability.
Vision quest has adopted the same sample frame used in the 2020 ARM, as the sample
population provided by SoMReP remains the same.
( − )
= ( − ) + ( − )
Where:
S= Sample size
X2 = the table value of chi-square for 1 degree of freedom at the desired confidence level of 95%
(3.841)
N= total number of target household beneficiaries for the program area
P= the population proportion (assumed to be .50 since this would provide the maximum sample
size).
d= the degree of accuracy expressed as a proportion (.08)
7|Page
The total number of pastoralists, urban/peri-urban, and agro-pastoralists was 9406, 6866, and
43213 respectively. Using the above, the sample size for the households was calculated to be 734
(pastoralists), 801 (peri-urban), and 1629 (agro-pastoralists) in that order.
Total sampled households. =3164 drawn from an estimated target of 59, 485 HH.
However, changes were made during implementation. Due to inaccessibility in Luuq, the entire
district was omitted. The study also excluded; Hadaftimo village in Odweyne District whichhad
been dissolved and the population dispersed to other locations. Eventually total interviewed
were 2781.
2.4.3 Data analysis
Collected data was stored in a secure local server, thus enabling real-time access to information
for immediate analysis and timely daily feedback with the data collection teams. Data were
disaggregated along the study target districts for purpose of content analysis about unique
features of each of the 16 project districts and livelihood characteristics. Quantitative data was
downloaded from the server, exported to Excel for collation and cleaning, and later exported to
STATA software for in-depth analysis. Data entry took place concurrently with data collection
through the uploading of filled questionnaires in smartphones directly to Server. Concurrent data
entry through direct uploading to the server allowed for early detection of mistakes/errors in
data collection and ensured timely intervention while the data collection teams were still in the
field. Data cleaning involved validation and checking for outliers during exploratory analysis. The
data was then weighted before analysis. At the first stage of analysis, descriptive statistics were
used to present the sample data characteristic and also to explore the distributional properties
of the data.
The individual KIIs and FGDs interviews were transcribed and analyzed across key research
themes and categories across the evaluation objectives. Qualitative data accruing from this were
was transcribed and analyzed in excel. Verbatim quotations from qualitative data were was
extracted to justify and augment key findings as extrapolated from the quantitative data set. The
data were also triangulated with summarized data from a review of secondary data and project
documents and reports. The content analysis involved the detailed exploration of common
themes and assigning labels to variable categories. The categories or themes were identified in
advance, in line with the objectives and scope of the assessment. Inferences were made from
particular data under each theme and conclusions were drawn from the findings, which informed
the content of the draft report.
8|Page
Study limitations
The assessment is premised on an assumption that continuous investment in the people, within
a predetermined approach results in a certain direction of outcomes. However, it has been
indicated before that over the last year, there were several interruptions into the “normal9”
environment in which the program was designed. As such, any review of the assessments and
finding thereof should have limitations herein in mind.
The 2021 ARM was conducted at a time movement in pastoral and pastoral areas had
increased due to acute drought. As a result, several areas such as Baidoa, Dolow, and
Elbarde had observed movements of population in and out of location. In Baidoa, the
research teams observed increased movements into the camps. Women and children
moved into the camps while men and boys remained in the pastoral and pastoral areas
taking care of their livestock. In the camps, there was anticipation that they would receive
humanitarian aid to cope with the drought.
In some of the regions in Dollow and Laascanod, the data collection happened at the time
that there was the distribution of SIM cards for unconditional cash transfer and food aid
respectively. Some of the target beneficiaries in these regions could not be reached for
data collection as they were following up on the distribution.
The election system in Somalia is a tier system that started in SeSeptember021. And were
supposed to culminate with the indirect election of the president through the elected
federal representatives. The election however was protracted and has experienced delays
leading to the postponement of the presidential election. The uncertain election process
which in some location resulted in fights and limited SomRep staff support to interventions
areas and instead local and beneficiary were charged with task to follow up and support
interventions after being trained in nearby towns that were deemed safe in some of the
locations in South West and Jubaland.
Enumerator capacity in some of the data collection areas was limited. This was addressed
through intensive training which included one on one sessions and daily feedback. In
certain areas particularly the north, getting enumerators especially within the targeted
locations was almost impossible. The balance between satisfying the local need for
employment and getting quality enumerators was on some occasions delicate and hence
led to delays in the data collection process.
The scale of the study and sample calculations expectation needed to have been clarified
within the TOR. This would enable the consultant to prepare for the massive data
collection within the geographical coverage. The tool for data collection has been
lengthened overtime requiring far more time to collect data, hence risks creating and
avoidance of future surveys as respondents consider the survey too long. The number of
9 Normal here refers to the contextual environment including cyclic emergencies in the form of floods, drought and
insecurity. Deviation experienced during the assessment period include COVID-19, Desert locust and the combined
effect of the same.
9|Page
respondents required to keep the sample representative is also high and spread wide. That
needs proper logistics planning for a successful data collection exercise. This kind of
information should be included in the Terms of reference to ensure that bidders know
what to expect in the data collection exercise.
The harmonization of units of measuring in terms of land under cultivation- it was assumed
that acre and hectare would easily be adopted and used. However, the study revealed that
the local respondents were not conversant with the units of measurement as they are and
hence were not able to accurately estimate their land size in acreage. More limiting was
the fact that there was no standard measure for the traditional land currently underuse,
which also differed between North and South. As result we were not able to accurately
calculate the land under use and yield.
10 | P a g e
3.0 Assessment findings
This section summarizes the aggregate findings across study locations, representing 3 livelihood
zones. They capture both primary findings and secondary evidence in line with research
methodology.
3.1 Demographics and Social Economic Characteristics
3.1.1 Distribution by location
2871 respondents were interviewed across 16 districts. Initially, the study targeted 17 districts
but Luuq was dropped off the list at the point of data collection due to inaccessibility challenges.
The total number of surveys conducted in each location is shown here below:
District Female # (%) Male # (%) Total
Afgooye 61 (56.0%) 48 (44.0%) 109
130 (67.4%) 193
Badhan 63 (32.6%) 110 (34.4%) 320
76 (43.2%) 176
Baidoa 210 (65.6%) 67 (61.5%) 109
128 (43.4%) 295
Belet_Xaawo 100 (56.8%) 70 (51.8%) 135
90 (36.7%) 245
Bossaso 42 (38.5%) 120 (38.5%) 312
128 (62.7%) 204
Burao 167 (56.6%) 61 (62.9%) 97
98 (51.0%) 192
Ceel Afweyne 65 (48.2%) 99 (57.9%) 171
70 (46.4%) 151
Ceel Barde 155 (63.3%) 33 (63.5%) 52
48 (43.6%) 110
Doolow 192 (61.5%) 1,376 (47.93%) 2,871
Eyl 76 (37.3%)
Hargeisa 36 (37.1%)
Laas Canood 94 (49.0%)
Lughaye 72 (42.1%)
Odweyne 81 (53.6%)
Salahley 19 (36.5%)
Xudur 62 (56.4%)
All 1,495 (52.1%)
Table 4: Distribution of respondents by district
3.1.2 Gender, age and marital status of household head
Categorized by gender 55.5% of the respondents were female while 44.5 % were male. The
average ages of household heads were as follows; female 38.7 while males were 41.4. These
results imply that majority of the household heads are in productive age group. The minimum
age was 18 for both males and females while the maximum ages were 77 for female heads and
85 for male heads. On Marital status, 86.3% of the respondents were married while 5.4% were
divorced. The proportion of respondents that indicated they were widowed was 2.4% while those
separated accounted for 2.2%. The results further show that the numbers of beneficiaries
reporting divorced and widowed were higher among females than males at 107 against 35 and
77 females against 17males respectively. Analysis of the Somalia Population Estimation Survey
11 | P a g e
shows the gender distribution of the population is 49.3 female against 50.7 male while the
productive age group (15-64) are the majority with 53.1% of the total population10. To the extent
that the study population was selected based on vulnerability criteria, the gender distribution
findings affirm that there was deliberate selection of women and confirm that the program target
aiswithin the productive category.
Gender of the respondents
1,277, 44%
1,594, 56%
Female Male
Figure 1: Gender distribution of respondents
3.1.3 Education levels of household head
The majority of the respondents(62.4%) had qur’anic education Formal education was very low
across the respondents with primary education accounting for only 14.3% while secondary
accounted for 2.21%. Post-secondary education accounted for 0.5%. 20.6% did not have any
form of education. According to the Somalia Bureau of Statistics (SNBS), adult literacy Somalia has
the third-lowest literacy rate among ten sub Saharan neighboring countries. Somalia’s rate of 40 percent is
only lower than Ethiopia (39 percent) and South Sudan (27 percent). The report further says that gross
enrolment for primary education is very low at 30 percent; for secondary education the gross enrolment
rate is 26 percent11. The fact that majority of the people had no formal education implies that
majority of the SomReP beneficiaries are constrained to participating in skilled labour market.
Besides, due to the limited knowledge and the lack of extension services would mean, majority
of them are dependent on indigenous knowledge to produce crops and rear animals. Thus
informal trainings such as good agricultural practices and other trainings that SomRep provides
aiming at improving their productivity, skills development to engage is other economic activities,
or acquisition of the essential skills to bargain for better prices on the market are very relevant
and paramount to address this gap.
10 https://www.nbs.gov.so/docs/PESS_Somal_population.pdf
11 https://www.nbs.gov.so/docs/Analytical_Report_Volume_3.pdf
12 | P a g e
Education level of the household head
70.0% 62.4% 59.4%
60.0% 55.8%
50.0%
40.0% 20.6% 18.2% 14.3% 17.9% 16.0%
30.0% 15.6%
20.0%
10.0% 0.29% 1.72% 0.95% 0.07% 0.08% 0.08% 8.03% 4.92% 0.50%
2.21% 0.14% 0.90%
0.0%
Qoranic school First degree None Post graduate Primary Secondary Vocational
school training
Female Male All
Figure 2: Education level of household head
3.1.4 Disability status
Persons with disabilities include ‘those who have long-term physical, mental, intellectual or
sensory impairments which in interaction with various barriers may hinder their full and effective
participation in society on an equal basis with others’12. On Disability, studies have shown that
there is a correlation between disability and poverty. The relationship between poverty (and
therefore exposure to shocks) has been referred to as vicious. While not all persons with disability
are poor or significantly disadvantaged, research has shown that persons with disability are more
likely to be poor than persons without a disability.13 Considering that most of the SomReP
interventions require human power, it can be argued that most of people with physical
disabilities are likely to be excluded by the program unless deliberate efforts or arrangement are
put in place to ensure their inclusion. This is echoed in SomReP strategy which argues that People
with disabilities are rarely considered or included in mainstream economic empowerment
programs (SomReP strategy 2017-2022) due to largely based on false assumptions relating to
their productive capacities, barriers to accessing skills training, and discrimination by a range of
market actors
12 UNCRPD, 2006
13 https://www.unescap.org/sites/default/files/SDD_PUB_Disability-Livelihood.pdf
13 | P a g e
Household disability status
100.00% 95.0% 93.9% 94.5%
90.00%
80.00% 5.00% 6.10% 5.50%
70.00% Female Male All
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%
Yes No
Figure 3 Respondent disability status:
In this study, we analyzed the proportion of persons reporting disability. An average of 5.5% of
the respondents reported being disabled. There were higher cases of males reporting disability
(6.1%) compared to women (5.0%). Various studies have estimated the population of people with
disabilities at above 15% mainly because of their exposure to internal conflict and war or over
the past two decades coupled with a weak and inadequate healthcare services14. (AI, 2015, p. 3;
Civil Rights Defenders, 2017, p. 10; Nyanduga, 2015, p. 12).
3.2 Program Participation
3.2.1 Program participation by activity type
The assessment evaluated the reach of the SomRep program across the interventions. The
majority (47.8%) of the respondents received cash transfers. Crop production was the second
most popular intervention targeting 30.1% of the beneficiaries while water interventions reached
27.1% of the total beneficiaries. Animal health, a significant contributor of Somalia’s economy
was at 20.2%. Other activities reported were Community health 20.2%. Village Savings and Loans
(VSLA) (19.1%), Early Action and Early warning (EWEA) (9.7%), Natural resource management
(NRM) (7.6%) Technical and Vocation Education and Training (TVET) 7.2% and others 3.2%. Those
that reported others indicated that they received donkey carts, Cash for work activities, or
training on IGAs.
14 AI, 2015, p. 3; Civil Rights Defenders, 2017, p. 10; Nyanduga, 2015, p. 12.
14 | P a g e
% of beneficiaries per intervention
Other 3.2% 27.1%
Water interventions 19.1%
7.2%
VSLA 7.6% 30.1%
TVET
Natrual resource management 9.7%
Early warning Early action
Crop production 7.0%
Community health
Cash transfers 20.2% 47.8%
Animal health 50.0% 60.0%
0.0% 10.0% 20.0% 30.0% 40.0%
Figure 4: Respondent distribution by interventions
3.2.2 Program intensity
Program intensity seeks to check the extent to which layering and sequencing are happening in
SomReP impact regions. The more the people participate in more than one intervention, the
greater the indication that sequencing and layering of activities are happening. When assessed
against the level of participation, the study found out that 68.7% of the beneficiaries participated
only in one activity while 15.8% and 15.5% of beneficiaries participated in two and three
interventions respectively.
Compared to 2020, the study found that the proportion of beneficiaries participating in one
activity only decreased by 3% point from 68.7% in 2021 to 65.1% the 2020 and the difference in
proportions was statistically significant at 5% level of significance (P=0.008). The number of
respondents reporting at least being involved in two activities increased by 0.4% point from
16.1% in 2021 to 15.8% in 2020 ( and the difference in proportions was not statistically significant
at 5% level of significance (P=0.3529)) while those involved in at least three interventions
decreased by 3% point from 18.8% in 2020 to 15.8%in 2021 (and the decrease the difference in
proportions was statistically significant at 5% level of significance (P=0.0002).
15 | P a g e
80.0% Intensity of activities among SomReP beneficiaries
70.0%
60.0% 65.1% 68.7%
50.0%
40.0% 16.1% 15.8% 18.8% 15.5%
30.0%
20.0%
10.0%
0.0%
One Two Three or more
2020 2021
The results imply that there have been stagnation in increasing sequencing and layering of
activities in the program which can be attributed to a number of factors: one factor could be
response bias, as beneficiaries can only indicate what they remember as such activities that have
implemented recently are more likely to be mentioned than those that were implemented earlier
and possibly were once off such as a training. Second, the COVID-19 pandemic could have
affected the effective implementation and monitoring of SomReP interventions, hence affecting
the intensity of interventions15. Thirdly, the drought in 2021, that led to decimation of crop and
livestock production as well some displacements as a coping mechanism in some of the study
areas such as Baidoa. Nonetheless, SomReP needs to carefully review its approach and ensure
that layering and sequencing is taking place as this is one of fundamental cornerstones of its
theory of change and most likely to contribute towards the success of the program. .
15 The drop in the number of activities was associated with interventions that ended prior to the evaluation. At the
same time, the study was conducted in November December period during failed Deyr season. This too could have
affected the participation in activities.
16 | P a g e
80.0% Intensity of activities among SomReP
70.0% beneficiaries
60.0%
50.0% 65.1% 68.7%
40.0%
30.0% 16.1% 15.8% 18.8% 15.5%
20.0%
10.0%
0.0%
One Two Three or more
2020 2021
Figure 5: Intensity of activities across beneficiaries
Across the livelihood zones, the results show that program intensity was highest among peri-
urban households with 20.3% participating in three or more interventions and another 20.3%
participating in two interventions. Second from the peri-urban households were, agro-pastoral
households with 19.0% of the households participating in three or more interventions and 14.5%
participating in two interventions. The pastoral households were ranked the lowest in terms of
program intensity with only 17.2% participating in three or more interventions and 16.8%
participating in two interventions. This was, however an improvement from 2020 where the least
layering was reported among periurban. However, the Somrep ToC foresees layering and
sequencing across all livelihood zones and in all program locations. In order to build resilience
effectively, SomRep should follow strictly the Toc and avoid reacting by ensuring the spread of
activities across all livelihood zones and locations are layered and sequenced. The Consultants
observed a number of projects had ended and there was a gap in funding meaning that it is
possible that the intensity had changed in the months preceding the study. However, for a
program as big as SomRep, negotiating multiyear funding the spirit is a critical step that need to
be enhanced using the collective capacity of the membership. This is not without the appreciation
of the dwindling donor funding reality.
17 | P a g e
Level of participation in project activities
70.0% 66.5% 66.0% 65.1%
60.0%
50.0% 59.5%
40.0%
30.0% 19.0% 16.8% 17.2% 20.3% 20.3% 16.1% 18.8%
20.0% 14.5% All
10.0% Agro-pastoral
0.0%
Pastoral Peri-urban/Urban
One Two Three
3.2.3 Program participation across the location
SomReP program strategy for building resilience is based on the theory of layering and
sequencing of interventions. Thus, it is anticipated that households will be targeted with more
than one intervention. To determine the extent to which the project has adopted this pathway,
Vision quest computed program participation across locations.
Proportion of beneficiaries participarting in the interventions
120.0%
100.0% 0.0% 0.0% 0.7%
80.0% 3.3%
60.0% 4.7% 6.8% 12.8% 11.5% 2.2% 5.3% 10.3% 5.8% 2.7%
40.0% 7.3% 24.7% 7.7%
20.0% 24.5%
26.5% 37.3% 19.6% 26.4%
44.0% 25.0% 15.6%
22.9%
60.3%
17.6% 20.8%
13.2% 100.0% 96.0%
86.5%
14.7% 88.1% 97.8%
22.2% 68.2% 64.3% 72.9% 68.2% 70.1% 70.9%
57.7% 49.5% 54.7%
41.3%
17.5%
0.0%
One Two Three
Figure 6: Program participation across location
The results of the study show that layering and sequencing is significantly higher in Afgooye,
Baidoa, Eyl Doolow, districts and significantly lower in Lughaye, Odweyne, and Ceel Afweyne
18 | P a g e
districts. Area with least layering were found to be Lughaye, CeelAfweyne and Odweyne. It was
also established that SomRep had its programs in the south for a longer period compared to the
North. Further, the area had multiple programs implemented over the course of time from
various donors. Some of the areas reporting multiple funding included Baidoa and Afgooye.
However, even in areas where the project is designed to deliver layered interventions, it was
observed that the layering was area based as opposed to individuals targeted. At the individual
level, there is need to ensure that program participants are deliberately targeted with several
interventions that directly affect their wellbeing across board.
Comparative analysis of program intensity by location over time show a major increase in areas
that had low intensity coverage. This means that there were more areas where participants were
involved in only one program compared to 2020. As show in the table below. Further there was
a general drop in the program participation Agooye and Dholow within the high program
intensity category while there was an improvement in Baidoa. There was marked improvement
in Eyl, Laascanod and Salahley as shown in colour orange below. The Colors green and red denote
areas with high intensity and low intensity programming respectively. The drop reported in
Afgooye and Dholow could be associated with the drought which affected mostly sections of
South Central Somalia including these two locations. This therefore could mean weather
dependent interventions were acted lead to the reduction in the percentage of respondents with
three or more interventions.
Program Intensity comparison between 2020 and 2021
2021 2020
Low Medium High Low Medium High
Afgooye 41.3% 14.7% 44.0% 3.39 22.88 73.73
Badhan 88.1% 7.3% 4.7% 32.83
32.54
Baidoa 17.5% 22.2% 60.3% 33.84 33.33
12.5
Balet-Xaawo 68.2% 25.0% 6.8% 42.58 24.88 5.32
Bossaso 64.3% 22.9% 12.8% 47.12 40.38 0
2.82
Burao 72.9% 15.6% 11.5% 80.4 14.29 41.19
Cee-Afweyne 97.8% 2.2% 0.0% 98.48 1.52 1.1
0
Ceel_Barde 68.2% 26.5% 5.3% 85.89 11.29
12.41
Doolow 57.7% 17.6% 24.7% 38.21 20.6 0
Eyl 49.5% 13.2% 37.3% 86.26 12.64 7.74
0
Hargeisa 70.1% 19.6% 10.3% 88.3 11.7
2.7
Laas Caanood 54.7% 20.8% 24.5% 76.55 11.03
Lughaye 100.0% 0.0% 0.0% 98.8 1.2
Odweyne 96.0% 3.3% 0.7% 76.13 16.13
Salahley 86.5% 7.7% 5.8% 100 0
Xudur 70.9% 26.4% 2.7% 86.49 10.81
Table 5 Comparison of Program intensity performance by District
19 | P a g e
3.2.4 Program participation across livelihood zones
Across the livelihood zones, the results show that program intensity was highest among peri-
urban households with 20.3% participating in three or more interventions and another 20.3%
participating in two interventions. Second from the peri-urban households were, agro-pastoral
households with 19.0% of the households participating in three or more interventions and 14.5%
participating in two interventions. The pastoral households were ranked the lowest in terms of
program intensity with only 17.2% participating in three or more interventions and 16.8%
participating in two interventions.
Level of participation in project activities
70.0% 66.5% 66.0% 65.1%
60.0%
50.0% 59.5%
40.0%
30.0% 19.0% 16.8% 17.2% 20.3% 20.3% 16.1% 18.8%
20.0% 14.5% All
10.0% Agro-pastoral
0.0%
Pastoral Peri-urban/Urban
One Two Three
3.2.5 Participation by Gender
There was no huge variation in program participation between males and females. Overall, 66.6%
of the respondents that participated in one activity were women, 17.7% of women participated
in two activities while only 15.7% of women participated in three project interventions. For men,
63.4%, 14.4%, and 22.2% participated in one, two, and three interventions respectively. In other
words, there was slightly more diversification among men (36.6%) compared to women (33.4%).
One plausible reason why men participated in slightly more interventions can be linked to the
cultural ownership of resources (assets) and division of roles that for instance puts land and
livestock in the hands of men. More men are likely to have access to land for farming, livestock
and therefore capital for livelihood diversification as compared to women.
20 | P a g e
70.0% Program Particpation by Gender 15.7% 22.2% 18.8%
60.0% Three
50.0% 66.6% 63.4% 65.1%
40.0%
30.0% 17.7% 14.4% 16.1%
20.0%
10.0% One Two
Female Male All
0.0%
Figure 7: program participation by gender
3.3Absorptive capacities
Absorptive capacity is the capacity to take intentional protective action and to cope with known
shocks and stress. It is needed as shocks and stress will continue to happen, for example, due to
extreme weather events caused by climate change, protracted conflict, and disasters.16
3.3.1 Shocks and hazards over the last year
Building resilience involves making investments that strengthen the capacities of vulnerable
populations to cope with and recover from specific shocks and stressors. Understanding how
different types of shocks affect household and community wellbeing is therefore fundamental to
designing resilience-building programs.
Responses on whether the beneficiary experienced a shock or
not
80.0% 68.1% 72.0% 56.7% 66.9%
60.0% 31.9% 28.0% 43.3% 33.1%
40.0%
20.0%
0.0%
Agro-pastoral Pastoral Peri-urban All
No Yes
Figure 8: Shocks across livelihood
16 Oxfam International.
21 | P a g e
Precisely 33.1% of respondents reported experiencing shocks during the reporting period. Most
affected were the peri-urban/urban livelihood respondent where 43.3% of respondents reported
experiencing shocks. The proportion of agro-pastoral and pastoral respondents that reported
experiencing shocks were 31.9% and 28.0% respectively.
To understand the Shock Exposure levels, the shock exposure index was computed and
compared that of 2020. The shock exposure index measures the overall degree of shock exposure
for each household and the perceived severity of the shock on household income and food
consumption17. The shock exposure index, therefore, a weighted average of the incidence of
experience of each shock (a variable equal to one if the shock was experienced and zero
otherwise), weighted by the perceived severity of the shock measured based on a Likert scale of
1 to 4 where 1=no impact, 2 =moderate impact, 3=strong impact and 4=worse-ever impact.
Comparative shock exposure index 2020 vs 2021
16 14.8
11.89
14 11.02
7.85
12 9.62 9.1
10 Strong 6.24
impact
8 6.11
6 3.733.27 2.793.01
4
2 00
0
No exposure No impact Moderate Severe All (without All
impact hhds not (including
to shock impact exposed) hhds not
exposed)
2020 2020 Mean index 2021 2021 Mean index
Figure 9: Comparative Shock Exposure Index
The Shock Exposure index increased across all the categories except the no impact category. This
means more people experienced shocks in 2021 compared to 2020.The deteriorating situation
was captured by FAO in the IPC classification as the worst in 40 years18. According to data from
IPC December 2021, the delayed start, early end, and erratic rainfall distribution characterized
the April to June 2021 Gu rainfall season. As a result, cumulative rainfall was below the 40-year
average across much of the country, especially in central and southern Somalia. The poor rains
led to below-average Gu crop production in southern Somalia and poor crop harvest prospects
in agro pastoral livelihood zones in the Northwest19. Similarly all the FGD conducted reported
that the drought decimated their crop and fodder production, and only farmers with sustainable
water source for irrigation had been able to produce signficant crops in 2021. The mean shock
across all categories was 3.01 up from 2.79 in 2020. The differences in mean shock exposure
index between the two periods was not statistically significant at 5% level of significance
17 Methodology_Guide_Nov2018508.pdf (fsnnetwork.org)
18 https://www.ipcinfo.org/ipc-country-analysis/details-map/en/c/1155100/
19 Ibid
22 | P a g e
(P=0.0510). Analyzed across those who experienced shock only, the mean increased from 6.24 in
2020 to 9.10 in 2021 and the difference in means in the two periods was statistically significant
at 5% level of significance (P=0.000). These results imply that households were expected to have
more shocks 2021 than last and effects of those shocks were more biting 2021 than last year.
Mean shock exposure index
12 8.27 9.79 9.1
10 9.13 5.09 6.98 6.24
1.812.31 4.21 2.793.02
8 6.56 2.59
6 Pastoral All
4 3.622.91 Peri-urban
2
0
Agro-pastoral
All sample 2020 All sample 2021
Households who experienced shock 2020 Households who experienced shock 2021
Figure 10: Mean Shock Index
3.3.2 Shocks experienced in the previous year by type
From the survey, the most common shock reported was drought followed by Covid-19. Drought
was felt as the strongest shock across all livelihood zones. Covid-19 was most populous among
urban and periurban respondents followed by High food prices at31.1% and 20.1%respectively.
The table below shocks as reported in the survey. From the qualitative data, FGD respondents
reported that they knew someone who had or was suspected to have Coronavirus and in some
cases, they identified persons that had lost their lives to the virus. The desert locust was also
identified especially among pastoral and agro pastoral livelihoods. Among locations where the
desert locusts were reported were Badhan and Ceelafweyne.
Conflict Agro-pastoral Pastoral Peri-urban All
COVID-19 5.0% 1.6% 9.2% 5.0%
High crime rates 11.9% 16.4% 31.1% 16.6%
Crop diseases 0.6% 0.0% 0.0% 0.3%
Death of household 6.5% 0.4% 1.8% 4.1%
member 0.9% 0.6% 1.3% 0.9%
Drought
Flash floods 23.4% 22.6% 35.2% 25.5%
High food prices 1.5% 2.1% 3.3% 2.0%
10.5% 9.2% 20.1% 12.0%
23 | P a g e
Livestock diseases 3.0% 1.8% 0.2% 2.1%
outbreak 8.1%
Desert locusts 1.0% 4.1% 5.6%
1.3% 1.7% 1.7%
Loss of employment 1.8% 0.3% 0.7% 0.4%
Sickness of a household 0.4% 0.1% 0.0% 0.0%
member 2.7% 0.2% 1.1%
Tropical cyclone 0.0%
Other 0.8%
Table 6: Shocks experienced by respondents
Farmers along the Shabelle (Afgoye) and Baidoa identified flooding as a major shock experienced
in late 2020 but whose effect spread across Jan- Feb 2021. Secondary data shows that an average
of 43% of populations living in flood zones were affected by the flooding. Overall, almost half
(47%) of respondents reported that some households left the sites due to the last floods20. Most
of these households were reported to have moved within the Districts, in other close-by camps
or settlements including Baidoa. The affected populations reported having their agriculture and
livelihoods disrupted and therefore reducing production for 2021 as a result of flooding in the
Deyr of 2020 drought of 2021. Despite what seemed to be above normal rainfall in 2020 resulting
in to flooding, key informant data showed that the rainfall period was far shorter and ended
before crops could reach maturity stage in most of the locations. Further, Some of the flooding
experienced in the area are as a result of rains in the Ethiopian highlands, that affect the lower
shabelle basin. The impacts of the flooding can often be massive, submerging crop fields and
destroying irrigation canals on the river banks.
Most of the respondents from FGDs reported drought impacts that affected them from mid-
2021. As at the time of assessment, FGD respondents reported that they had experienced
delayed rainfall and expected the drought to have a significant effect on agricultural production
(crop and livestock). At the same period, FEWSNET reported failed Deyr rains.
BOX 1: CONSEQUENCES OF FAILED DEYR 2021
The deyr rains have largely failed since October, causing alarm for the deterioration of food
security conditions in Somalia. Intensifying drought has led to water shortages, a high likelihood of
crop failure, and atypically high levels of livestock migration and deaths. Households face both a
significant decline in income derived from crop and livestock production and a sharp increase in
water and staple food prices, resulting in steep declines in household purchasing power. There is
very high concern for a rapid rise in the size of the population in Crisis (IPC Phase 3) and Emergency
(IPC Phase 4) between November (2021) and March (2022), especially in southern and central rural
livelihood zones and IDP settlements. A scale-up in humanitarian food assistance beyond currently
planned levels is urgently needed to save lives and livelihoods.
FEWSNET December 2021.
20
https://reliefweb.int/sites/reliefweb.int/files/resources/COMPILED_%20Triple%20Threat_factsheet_to%20submit.
pdf
24 | P a g e
Figure 11: FEWSNET early warning in drought shock
3.3.3 Impacts of shocks on livelihood
In terms of impact, there was a higher percentage of agro-pastoral respondents reporting strong
impact with 44.7% compared to pastoral respondents with 38.1%.Posibly for agro-pastoral, the
failed rains Gu and Deyr rains affected both livestock and crop production and therefore being
reported more than amongst other livelihood groups. The figure below outlines the impacts of
shocks across the different live. A sizeable proportion of Pastoral and agro-pastoral reported
experiencing severe impacts of shock with 2.7% and 2.5% respectively.
No impact Moderare impact Strong impact Severe impact
Agro-pastoral 16.6% 36.0% 44.7% 2.7%
Pastoral 38.1% 21.3% 38.1% 2.5%
44.7% 44.7% 0.4%
Peri-urban 10.2% 35.12% 43.3% 2.1%
All 19.5%
Table 7: Impact of Shocks on Livelihood
Secondary data21 showed that (57%) of households have incomes deteriorated since the recent
floods and COVID-19. The most cited reasons for income deterioration were the unreliable
availability of casual labor, high unemployment due to Covid-19 social distancing measures, as
well as indebtedness due to shelter and livelihood damages. The floods were also reported to
have destroyed crops and agriculture-related incomes, leading to lower production for affected
households.
Further data from FEWSNET indicate that rainfall has performed worse than previously
assumed. According to CHIRPS remote-sensing data, rainfall during the October 1-November 25
period ranged from 55 to 70 percent below the 40-year average. The amounts of rainfall received
were inadequate to support recovery in cropping and rangeland conditions.
Floods and droughts are particularly the two natural cyclic events that frequently affect the
country and lead to repeated loss of lives, crops and livestock. Both floods and droughts return
with different degrees of intensity and impact, and losses vary depending on the early warnings,
preparedness, and response being done by the Somali government and its partners22.
Following the drought, the price of a kilo of sorghum and maize were 70 percent and 60 percent
above the five-year average, respectively in Baidoa.
21 Ibid
22 https://reliefweb.int/report/somalia/role-climate-information-and-early-warning-systems-supporting-disaster-
risk-reduction
25 | P a g e
Imported food prices such as rice and wheat flour are also high due to increased demand amid
the low maize and sorghum supply, high shipping and fuel costs, global supply factors, and the
localized inflation of the Somali Shilling in the northeast23.
Comparison between program intensity and Shock Exposure index
2021 Shock Exposure Index
Low Medium High 4.25
44.0% 0.10
Afgooye 41.3% 14.7% 4.7% 10.61
60.3% 0.13
Badhan 88.1% 7.3% 6.8% 0.91
12.8% 1.23
Baidoa 17.5% 22.2% 11.5% 0.76
0.0% 10.00
Balet-Xaawo 68.2% 25.0% 5.3% 3.56
24.7% 1.20
Bossaso 64.3% 22.9% 37.3% 0.06
10.3% 0.72
Burao 72.9% 15.6% 24.5% 0.03
0.0% 0.69
Cee-Afweyne 97.8% 2.2% 0.7% 0.04
5.8% 1.16
Ceel_Barde 68.2% 26.5% 2.7%
Doolow 57.7% 17.6%
Eyl 49.5% 13.2%
Hargeisa 70.1% 19.6%
Laas Caanood 54.7% 20.8%
Lughaye 100.0% 0.0%
Odweyne 96.0% 3.3%
Salahley 86.5% 7.7%
Xudur 70.9% 26.4%
Table 8: Comparison of Shock exposure against program intensity
Shock exposure index did not necessarily correspond to program intensity. Districts such as
Baidoa experienced high shock exposure regardless of having high program intensity. However,
it is worth noting that higher shock exposure across the districts affects particularly the
absorptive capacity in the immediate and this could lead to depletion of overall resilience
capacity if the shock continues for a long term. The variance analysis between groups and within
districts was significant (p=0.00). The shock severity was high in Baidoa (10.6) and Elbarde (10.0)
and lowest in Salahley (0.04) and Lughaye (0.03.
The standard deviation in shock exposure between districts was 5.86 while Baidoa and CeelBarde
that recorded the highest shock exposure index was 9.2 and 7.67 respective. What this means is
that the level of shock impact was different across the districts and also within the districts,
different respondents and perhaps villages were impacted differently.
23 https://fews.net/east-africa/somalia
26 | P a g e
As a result, it is important for SomRep to address level of shocks and put mitigating measures
based on the context and vulnerability, without which the risk is to erode the gains made over
the project time. There was significant difference (P=0.00) between the shocks severity across
the district)
3.3.4 Shock Impact on Disability
Shocks exposure had severe impacts on Households with disability. Out of 905 respondents
surveyed 80.23% reported being impacted moderately, strongly or severely by shocks. Those
reporting strong impact were 43.54% followed by those affected moderately as shown in the
figure below. As such Households with disability as a vulnerability criteria were found to be
impacted more by shocks compared to other categories.The Global Facility for Disaster Reduction
and Recovery (GFDRR) reports that persons with Disability are disproportionally affected by
disasters, shock s and stresses. Reasons for this disparate impact include not only aspects of
disability but also the interplay between disability and other risk factors for enhanced
vulnerability during emergencies, such as poverty24. For a country like Somalia where protection
policy and capacities for the disabled persons are limited, chances are higher that they are likely
to face discrimination, lack of necessary assets to support them such as wheel chairs and
therefore expose them to more poverty and other limitations. Disasters exacerbate such
conditions, enhancing the disparities between persons with disabilities and other members of
society and increasing the likelihood that those with disabilities will be disproportionately
negatively affected both during and after an emergency.25
Shock Impact on HH disability
2.1
19.78
43.54
34.59
No impact, # (%) Moderate impact, # (%)
Strong impact, # (%) Severely impact, # (%)
Figure 12Impact of Shock on Disability
24
https://www.gfdrr.org/sites/default/files/publication/GFDRR%20Disability%20inclusion%20in%20DRM%20Report
_F.pdf
25 Ibid
27 | P a g e
3.3.5 Impact of Shocks on Gender
Concerning gender, the proportion of women that reported experiencing severe shock was 2.11%
against that of men with 2.09%. those reporting strong impact averaged 43% for both men and
women. The difference on impacts of the shocks across all categories were rather minimal as
shown in the table below. There was no statistical significance between men and women on
shock exposure.
Percentage shock impact on gender
Severely impact, 2.09
2.11
Strong impact, 43.46
43.23
Moderate impact, 34.82
35.33
No impact, 19.63
19.33
0 10 20 30 40 50
Male Female
Figure 13: Impacts of Shocks on gender
3.3.6 Early warning information
An Early Warning System (EWS) represents the set of capacities needed to generate and
disseminate timely and meaningful warning information that enables at-risk individuals,
communities and organizations to prepare and act appropriately and sufficient time to reduce
harm or loss26.
The results show that 61.3% of respondents received early warning information. The majority of
those who received the information were urban/peri-urban households (70.6%), followed by
pastoral households (59.9%) and lastly, agro-pastoral households (57.7% ). The results further
show that majority of the respondent indicated to have received early warning information on
the occurrence of the following shocks/hazards: drought (77.4%), high market prices (38.9%),
locusts invasion (38.5%), conflicts (23 %), and diseases (11.7. Those that received information on
flash and riverine floods were 7.5% and 6.0% respectively.
26 Javier M et al (2017) early warning system, Science direct journal
28 | P a g e
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