2021 Annual Resilience Measurement Report

IV. Social Affairs committees

The social affairs committee is composed of representatives of other committees within the
village and is charged with the management of community social funds. The SAC kitty is aimed at
ensuring that there is an established mechanism for community contribution to the community
contingency funds. This includes funding through the existing structures and through private and
institutional donors. The structure and operations of the SAC is as shown here below.

Figure 55: SAC community structure

The assessment found out that there were Social Affairs Committee (SAC) in the community. The
proportion of the communities reported that there was SACs in their villages was 48.5% . The
proportion of pastoral respondents that reported the presence of SACs in their communities was
the highest at 52.1% followed by of agro-pastoral with 47.5% and peri-urban with 46.8%. While
72.)% of the respondents were aware that the SACs had opened bank accounts. Agro-pastoral
respondents had the highest response of those who knew that the SACs had opened bank
accounts at 78. % followed by Peri-urban with 64.4% and pastoral with 62.8%.

79 | P a g e

SACS in the community

90.0% 78.6%
80.0%
72.0%
70.0% 62.8% 65.4% 48.5%
60.0% 52.1% 46.8%
50.0% All
47.5%

40.0%

30.0%

20.0%

10.0%

0.0%

Agro-pastoral Pastoral Peri-urban

Presence of SACS SACS with Bank account

Figure 56 Presence of SACs in the community

V. The functionality of the committees in the management of DRR

The assessment sought to establish the respondent’s perception of the extent to which
committee leaders’ institutions in places were handling the issues related to disaster risk
reduction. The reactions of the respondents remained largely neutral, either because the
respondents did not want to respond or because they held back from giving their perceptions.
The overall perception was 80.7% while 12% of respondents reported that the committees
remained ineffective. The reasons why committee were felt ineffective was not established.
However, it would be important for Somrep and Partners to pursue the functionality of each
committee and establish the extent they function and determine needs that could be addressed
to make them more functional. Those who reported that the community leadership was effective
stood at 5.6%.

80 | P a g e

Beneficiaries'e perceptions on effectivess leaders/institutions on
handling of issues related risk reduction (DRR)

Very ineffective 0001...14.71%%%%

Very effective 111112..25.3%1%%5.5%

Somewhat ineffective 0001...3.771%%%%

Somewhat effective 4.516.%6.5%8%.8%

Neutral 74.2% 80.7%
8812.8.4%%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0%

All Peri-urban Pastoral Agro-pastoral

Figure 57: Community perception of leaders’ effectiveness

Across the various committees where involvement of the communities was necessary for
planning and making decisions, the SACs had the lowest response rate on the inclusion of the
community. 18.5% of the respondents said they were involved in the development of SAC plans.
The proportion of pastoral respondents reports the ted highest level of involvement at 27.6%
while the peri-urban reported the lowest at 14.0%.

Perceptions of beneficiries on whether local government
are accountable and responsive to community priorities
in providing equitable services and promoting resilience

interventions

60.0% 53.4%
50.0%
40.0% 39.0% 43.7% 27.4% 42.9%
30.0% 32.1% 30.8%
20.0% 30.6% 22.2%
10.0% 24.3% 23.3%
3.4% 0.7%
0.0% 14.6%

3.8% 0.9% 2.0% 0.4% 4.1% 0.6%

Agro-pastoral Pastoral Peri-urban All

Agree Disagree Neutral Strongly agree Strongly disagree

Figure 58 Government responsiveness and accountability in resilience

81 | P a g e

Perception of respondents on whether the local government are accountable and responsive to
community priorities in providing equitable services and promoting resilience interventions
varied widely. 42.9% of the respondents agreed, 22.2% strongly agreed while 30.8% remained
neutral. The percentage of those who disagreed was small meaning that most of the respondents
were aware of the local government involvement.

3.5.5 Accountability, feedback mechanisms

Beneficiary Feedback Mechanisms (BFMs) provide a method for strengthening aid agencies’
accountability to the communities where they work. BFMs provide a channel for community
members to easily raise questions, suggestions and concerns about aid activities and have agreed
on protocols for action to be taken in response. In this way community, members can ‘hold an
organization to account for their actions, and ensure their answerability for how resources are
used in their community

Data collected showed that the beneficiaries were aware of complaints and feedback
mechanisms in place. The proportion of respondents that reported to know mechanisms in place
dropped from 67.9% in 2020 to 61.1% in 2021. 68.7% of respondents were informed of the
selection criteria for their inclusion into the project. It was thought that part of the drop could be
associated to a number of programs that has previously closed, or the lack of use of the
mechanisms over time. The extent to which SomRep continue to popularize available
Accountability and feedback mechanism was not established. However, good programming
practice calls for continuous creation of awareness and constant feedback to ensure that
stakeholder engagement is active all along the project. KII showed that the feedback back
mechanism is multilayered within the partners and linked to Code of conduct and partner data
management policies. How the different levels of accountability mechanism is engaged.

Accountability mechanisms

70.0% 46.35%0.3% 54.45%9.2%
60.0%
50.0% 32.0%
40.0% 24.0% 18.3%
30.0% 10.31%0.2%
20.0% 7.6% 3.4%2.8%
10.0% 1.8%1.6% 1.3% 0

0.0%

Community E-mail Local SomReP SomReP Suggestion Telephone None

leader authorities field staff office box

Known Utilized

Figure 59: Accountability mechanisms in place

82 | P a g e

On existing structures for channeling accountability messages and information, Community
leader, SomReP staff and Telephone based mechanisms were the most popular. Similarly, the
most utilized mechanism was the Telephone, followed by the community leader and SomReP
staff in that order. On response and feedback, 90.4% of the respondents reported that they have
received responses to their complaints or comments. This was a significant increase from 2020
where 76.9% had reported receiving feedback. 96.6% of the respondents reported the response
was timely. In terms of the satisfaction with the response, 92.7% reported being satisfied (very
satisfied 55.7%, satisfied, 37.0%). This was an increase from 88.5% reported in 2020. 82.4% of
the respondents found SomReP staff as respectful. Compared to 2020, this figure was up by 2.4%,
which shows improvements in staff handling of the beneficiaries. The response generally showed
a well-functioning mechanism and a good response from SomRep partners. This could also imply
that the mechanism was easy to use and accessible and thus facilitating frequent engagement
and timely responses for both the program staff and the beneficiaries.

CRM voices accomodated by Somrep

1.0% 0.3%

19.2%

36.2%

43.2%

Figure 60: Beneficiaries CRM voices accommodated

On SomRep staff presence on the ground, 76.6% reported they were satisfied while a significant
22.1% remained neutral. 84.7% were satisfied with the SomRep CRM mechanism. In terms of
feeling their voices accommodated, 36.2% and 43.2% reported that they were satisfied that their
voices were accommodated.

3.6Food security status

Food security is the availability at all times of adequate food supplies of basic foodstuffs to sustain
a steady expansion of food consumption and to offset fluctuations in production and prices63.
Many studies and definitions have been put forward on the concept of food security. The World
Bank on its part has linked the definition to poverty and hunger by looking at the temporal

63 Https://www.fao.org/3/y4671e/y4671e06.htm

83 | P a g e

dynamics of food security. It introduced the widely accepted distinction between chronic food
insecurity, associated with problems of continuing or structural poverty and low incomes, and
transitory food insecurity, which involved periods of intensified pressure caused by natural
disasters, economic collapse, or conflict64. From these dynamics, there three measures of food
security were used in this survey. They include the Food Consumption Score (FCS), the Reduced
Coping Strategies Index (rCSI), and the Household Hunger Scale (HHS). The Reduced Coping
Strategy Index (rCSI)65.

3.6.1 Food Consumption Score

FCS is an aggregate seven-day consumption across standardized food groups, weighting food
group consumption by both days of intake and a predetermined set of weights designed to reflect
the dietary quality of each group. Weights associated to the food groups are then calculated and
ranked to given values that are categorized as acceptable, Borderline and poor66.

70.0% FCS across livelihood zones
60.0%
50.0% 63.46%1.0%
40.0%
30.0% 44.34%6.24%7.0% 37.4% 41.2% 38.5%
20.0% Acceptable 22.02%3.1% 22.22%3.4%
10.0% 31.92%9.8% 20.3%
18.0% 14.41%5.7% Poor
0.0%

Bordeline Poor Acceptable Bordeline

2020 2021

Agro-pastoral Pastoral Peri-urban/Urban

Figure 61: Comparison of FCS between 2020 and 2021 across livelihood.

Vision quest analyzed FCS as reported by the respondent across the project. Majority of the
respondents reported acceptable FCS improved in 2021 (50.4%) compared to 2020 (44.9%) and
the difference in proportions between the two periods was statistically significant at 5% level of
significance (P=0.002) This is important because it indicates despite a general drop in the
resilience measurement in 2021, the wellbeing of the households in as far as FCS is concerned
had improved.

64 World Bank. 1986. Poverty and Hunger: Issues and Options for Food Security in Developing Countries. Washington
DC
65 Somrep Midline report
66 Ibid

84 | P a g e

Acceptable FCS was highest amongst pastoral respondents with 63.4% while Peri-urban/Urban
respondents reported 61.0%. Agro pastoral respondents had fair acceptable levels at 41.2%.
Agro-pastoral respondents conversely reported the highest poor FCS with 38.5%. On borderline
FCS, the agro-pastoralist livelihood recorded the highest also with 20.3%. Findings from
qualitative data showed that there was increased embrace of irrigated crop farming especially
high value food crops. The available food especially among agro pastorals influenced the
outcome of the FCS. Further, income was highest among agro-pastoralists (USD $ 189) compared
to Pastoralist (USD$ 128.2) and peri-urban (USD$177). This means the agro-pastoralist had more
cash at their disposal which could meet their food needs. Data from the FGDS showed that people
were aware that nutrition was important in preventing diseases as part of Covid 19
prevention/response. As such, he communities may have prioritized improved food consumption
despite the biting shocks that they experienced. Further, it was observed that higher levels of
debt went to food at 56.2% of all debt incurred and explains the deviation of the FCS compared
to the rCSI and HHS which all declined in the same period. In other words, there was emphasis
on accessing food at the household level regardless the circumstances. Secondary data obtained
from Mudug showed that the FCS amongst Care Beneficiary was 67%67. There has not been data
from non project beneficiaries to compare and deduce the contribution of SoMrep. However,
compared to the baseline provided, there was an improvement from 53% as indicated in the
2019 report to 61%.

Compared to the previous year, there was an overall improvement across all categories except
Agro-pastoralist. While pastoral and Peri-urban respondents recorded an improvement from
46.2% and 47.0% in 2020 to 63.4% and 61.0% respectively in 2021, the Agro pastoral livelihoods
dropped from 44.3% to 41.2 in the acceptable category and increased from 18.0% and37.4% to
20.3% and 38.5% in the borderline and poor categories respectively. Despite the drop,
Agropastoralist demonstrated the highest levels of resilience and a better FCS score.

The drop in the agro-pastoral category could be associated to two things; first, there was the
failure of the Deyr rains translating to poor crop production and secondly, the seasons of the
evaluations were different with previous evaluation having been conducted in September while
this assessment was done in the month of November-December 2021. The RCSI as indicated is
highly sensitive to the season and hence the drop can be considered normal as the data was
collected at the height of drought.

67 http://careevaluations.org/wp-content/uploads/EFSP-II-Final-Report-102121.pdf

85 | P a g e

Comparison of FCS across gender

100% 51.6 16.93 31.47
50% 49.23 18.93 31.84
0% Acceptable Borderline Poor

Female Male

Figure 62 Comparison of FCS across gender.

Food Consumption score was weaker among women compared to men. Acceptable FCS was
higher among men with 51.6% compared to women who had 49.2 %. At the same time, the
borderline category was higher among women with 18.93% compared to men who had 16.93%.
The poor category was not very different. The difference between men and women was expected
as men had recorded higher income at USD188.2 compared to womenUSD$156.9. Men had
equally more opportunities for income with more men being involved in more than one
intervention (22.2%) compare to women (15.7%). As reported earlier, the cultural division of
roles and reponsibilites as well as the patrical approach to asset ownership favorably disposed
men to a better income and FCS as compared to women.

On disability, those that reported acceptable FCS were 49.71% while the borderline category was
17.35% and poor was 32.94%. The category reporting poor was a higher percentage and thus
implying that if the household had disability, it was highly predisposed to poor FCS.

3.6.2 Household hunger score

The HHS is a household food deprivation scale, derived from research that provides comparable
data across different settings. The approach used by the HHS is based on the idea that the
experience of household food deprivation causes predictable reactions that can be captured
through a survey and summarized in a scale68. Contrary to the food consumption score, there
was an overall increase in the number of respondents reporting increased hunger as recorded in
the hunger score. The category reporting little to no hunger dropped from 73.2% in 2020 to
69.6% in 2021 and the difference in proportions between the two periods was statistically
significant at 5% level of significance (P=0.0003). The category reporting severe hunger increased
by 7.0% from 2.4% to 9.4% and the difference in proportions was statistically significant at 5%
level of significance (P=0.0000). As seen in the FCS, the agro pastoralist recorded higher levels of
hunger compared to other livelihood categories. The FAO in the Somalia food Outlook report
predicts increased hunger as in the absence of humanitarian food assistance, a significant
proportion of households across the country are likely to deteriorate to Crisis (IPC Phase 3) by

68 https://www.fantaproject.org/sites/default/files/resources/HHS-Indicator-Guide-Aug2011.pdf

86 | P a g e

September 202169. This implies that if not for the SomRep intervention, the situation could have
been worse. Qualitative data from the project showed a deteriorating situation with the
respondents reporting that they have had to reduce certain foods or quantities in order to
manage the the situation. At the same time, the Care project evaluation indicated that ther wa a
consistent downward trajectory of the HHS in the severe Hunger category demonstrated in
the2021 project implementation70. Overall, there findings show that the community capacity to
deal with the shocks and stresses of 2021 may have been compromised. It is therefore critical to
examine ways to strengthen the community absorptive capacity in order to protect and
strengthen the adaptive capacity.

Comparison of Hunger score between 2020 and 2021

Severe hunger 9.4% 16.2%
3.3%

8.4%

2021 Moderate hunger 21.0%
26.3%

16.9%
21.1%

Little to no hunger 69.6%
70.4%
66.9%
70.5%

Severe hunger 2.4%
2.1%

3.2%
2.1%

2020 Moderate hunger 24.4%
29.8%

21.8%
24.6%

Little to no hunger 73.2%
68.0%

75.0%
73.3%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0%
All Peri-urban/Urban Pastoral Agro-pastoral

Figure 63: Comparison of Hunger score between 2020 and 2021

Across districts, Salahley (100%), Hargeisa (96.9%), and Badhan (96.4%) reported the least
hunger. Afgooye and Salahley reported no severe hunger while Badhan (0.5%), and Dholow

69

https://reliefweb.int/sites/reliefweb.int/files/resources/Somalia%20Food%20Security%20Outlook_022021_Final_
0.pdf
70 http://careevaluations.org/wp-content/uploads/EFSP-II-Final-Report-102121.pdf

87 | P a g e

(1.6%) reported minimal severe hunger situations. CeelAfweyne (74.0%), CeelBarde (30.2%), and
Hudur (29.1%) posted the highest respondents reporting hunger.The increased hunger is a direct
result of the wider impacts of triple shocks (covid-19, Locusts, and Drought). The study was also
conducted at a time that the rains had acutely delayed and therefore this definitely impact the
outcomes. This explains wwhydistricts like Afgooye experienced acute hunger despite being an
agropastoral zone with a high program intensity. At the same, the findings could imply heaving
dependence one source of income even for locations and households that have higher program
intensity. It would be recommended for Somrep to assess the contribution of each intervention
into the household income with an aim of boosting alternative household income sources.

Household hunger scale per district

District Little to no hunger Moderate hunger Severe hunger
Afgooye 0.0%
Badhan 87.2% 12.8% 0.5%
Baidoa 3.1% 4.1%
Balet-Xaawo 96.4% 25.3% 10.2%
Bossaso 12.5% 11.9%
Burao 70.6% 26.6% 5.8%
Cee-Afweyne 8.8% 74.0%
Ceel_Barde 77.3% 29.6% 30.2%
Doolow 39.2% 1.6%
Eyl 61.5% 22.4% 15.2%
Hargeisa 21.1% 0.0%
Laas Caanood 85.4% 3.1% 5.2%
Lughaye 10.9% 22.8%
Odweyne 69.6% 42.7% 9.9%
Salahley 25.2% 0.0%
Xudur 30.6% 0.0% 29.1%
All 38.2% 9.4%
76.0% 21.0%
Table 21: HHS by Location
63.7%

96.9%

83.9%

34.5%

64.9%

100.0%

32.7%

69.6%

Further analysis on the household hunger score showed that minor deviation between hunger
score between men and women. Despite the minor differences, households led by men had had
a better HHS score with men reporting 70.06% compared to Women headed household that
scored 69.16%. Inversely, the category reporting esvere analyzed as higher among women
headed households (9.83%) against men (8.87%). On Disability, the overall percentage of those
reporting little to no hunger was 70.57%, moderate hunger was 21.35% and severe hunger was
8.08%. As indicated earlier, access to assets and roles assigned to would could negatively
predispose women to lower opportunities of imcome generation and therefore exposing the
households to more hunger as compared to men. Other other hand, Disability is instself a limiting
factor and persons with disabilities are not able to effectively participate in economic activities
unless enabling factors are addressed. This would inclide provision of wheel chairs, medical care

88 | P a g e

and even friendly infrastructure. SomRep therefore need to focus on women and persons with
special needs in order to address the disparities observed.

80.00% 70.06% HHS vs Gender and disability 70.57%
70.00%
60.00% 69.16%
50.00%
40.00% 21.08% 21.00% 21.35%
30.00% 8.87% 9.83% 8.08%
20.00%
10.00%

0.00%

Male Female Disability
Little to no hunger Moderate hunger
Severe hunger

Table 22 : HHS analyzed against gender and disability

3.6.3 Reduced Coping Strategies Index

The Reduced Coping Strategy Index (RCSI) indicates the kinds of coping behaviors (e.g., limiting
portion sizes, relying on less preferred foods) households have had to engage in to cope with
food scarcity and/or access issues71. Thus, higher RCSI scores indicate lower food security.
However, it is noted that RCSI is highly sensitive to seasonality and therefore variability could be
because of season in which data is collected.

71 SomRep midline report

89 | P a g e

rCSI across livelihood zones

High coping 53.6% 61.8% 71.0%
Medium coping 60.6%
Low or no coping
2021 131.95%.11678%..71%%
High coping
Medium coping 11.0% 22.6% 28.7%
Low or no coping 25.5%

9.2%121.32.%6% 30.3%

2020 54.3%585.90.%1%62.8%

11.7% 2278.3.0%% 33.5%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0%

All Peri-urban/Urban Pastoral Agro-pastoral

Figure 64: RCSI across livelihoods

Analysis of rCSI computed against 2020 showed a significant increase in respondents reporting
high coping mechanisms. The overall percentage of those that reported high coping mechanism
in 2021 was 61.8% compared to 30.3% in 2020 and the difference in proportions between the
two periods was statistically significant at 5% level of significance (P=0.0000). The increase in
high coping could be partly attributed to the households increased exposure to shocks and their
concomitant effects which could have weakened their absorptive capacity hence adopting high
coping strategies. Further pastoral livelihood category reported a far higher coping mechanism
with 71.0% compared to 13.6% the previous year. Overall, all categories reporting high coping
mechanism increased significantly as shown in the figure above. There was also an overall shift
in those reporting low and medium coping mechanism with 11.7% and 58.0% to 22.6% and 15.6%
in 2021. According to FAO, significant reductions in household income from agricultural labor and
household food stocks for consumption from Gu crops, followed by a third consecutive season
of below-average crop production in late 2021, will be the main driver of sustained Crisis (IPC
Phase 3) outcomes. The report went further to state that the July harvest will offer most poor
households less than two months of food stocks for food and income, a portion of which will go
toward repayment of debt that households accumulated to purchase inputs for cultivation or
purchase food and non-food needs72. This essentially means by the time the 2021 ARM data was
being collected the food security had deteriorated explaining the use if the high coping
mechanism.

72 file:///C:/Users/HP/Downloads/SOMALIA-Food-Security-Outlook-June-2021-January-2022.pdf

90 | P a g e

As indicated earlier, rCSI is affected by seasonality, shocks and the overall vulnerability context
and data on rCSI is likely not to reflect the current conditions if there have been changes in these
conditions after the last data collection. Vision quest established that the 2020 data exercise was
collected in September while 2021 data exercise was conducted in November. Further, the
season was categorized by failed Deyr rains. The rCSI score is recommended therefore to be used
to inform the program, especially where quick interventions are needed but not for comparisons
purposes.

Disability versus rCSI

61.11% 23.22%
15.67%

Low or no coping Medium coping High coping

Figure 65" Analysis of Disability versus rCSI

When analyzed against Disability, it was found that majority (61.11%) of the households with
disability engaged in high coping mechanisms. Those engaging medium coping mechanisms were
a minority (15.67%) while another 23.22% engaged in low or no coping mechanism. Thus,
disability predisposed households negatively on rCSI. SomRep will need to look at ways of
supporting HH with a disability to eliminate disadvantages experienced because of this criteria.

rCSI vs Gender

High coping 64.10%
59.67%

Medium coping 16.50%
14.85%

Low or no coping 9.40% 24.48%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00%

Male Female

Figure 66: Analysis of rCSI versus Gender

91 | P a g e

More households headed by male engaged in higher coping mechanism (64.10%) compared to
female headed households (59.67%). There were more women (24.48%) engaging in low coping
mechanism compared to male headed households (9.40%). What this essentially means is that
more male headed households engaged in negative coping mechanism compared to women.

Compared to the FCS score, then this means that the male headed household prioritized finding
food even when the risk was higher in the long terms as compared to women who took lower
risks.

3.6.4 Household Vulnerability Profile

Using the vulnerability index, the Household Vulnerability Profile classified households into three
categories: less vulnerable, moderately vulnerable, and highly vulnerable. Less vulnerable
households are those that are in a vulnerable situation but can still cope; moderately vulnerable
households are those that require immediate but temporary assistance in the event of shock and
stress; and highly vulnerable households are those that are almost at a point of no return. The
results show that the majority of households are less vulnerable, with 60% of households having
an index ranging from 0.5 to 1.00. The moderately vulnerable households had an index of -0.5 to
0.4 and made up 17% of the total households sampled, while the highly vulnerable households
had an index of -0.6 to -2.0 and made up 23% of the total households sampled (Figure 67).
According to the findings, 40% of the households were experiencing moderate to highly (severe)
humanitarian conditions at the time of the study. These findings are consistent with the findings
of the coping strategy index, which show that the conditions in these households are alarming
and are exhausting their coping mechanisms. According to the FewsNet seasonal monitoring
report for Somalia, humanitarian conditions are expected to worsen, implying a further decrease
in the number of households falling into the less vulnerable category. Households in the less
vulnerable category may be considered vulnerable, and SomReP should take special precautions
to keep them from falling into the moderate and high vulnerable categories.

Less Highly Vulnerable
Vulnerable 23%

60% Moderately
Vulnerable

17%

Figure 67: Household vulnerability Analysis

92 | P a g e

The severity of the conditions is clearly linked to the households' livelihood zones. Households in
the Peri-Urban livelihood zone were more likely to fall into the less vulnerable or highly
vulnerable categories, with only two out of every ten falling into the moderate vulnerable
category. These findings matched those of Agro-Patoralist livelihood zones. The Pastoral
livelihood zone produced interesting results, with nearly two-thirds of the households in this zone
falling into the less vulnerable category. Interestingly, the findings on reduced coping
mechanisms indicate that Pastoral households adopted high coping strategies, implying that
these households are being subjected to worsening conditions and hence may soon fall into the
highly vulnerable category.

Peri -urban 32.6% 19.0% 48.4%

Pastoral 9.9% 18.8% 71.3%

Agro pastoral 26.7% 14.9% 58.4%

Highly vulnerable Moderately vulnerable Less Vulnerable

Figure 68: Livelihood Groups vulnerability profile

Most of the districts with a high proportion of households adopting high coping strategies and
experiencing high shock exposure have a high proportion of households falling into the moderate
to high vulnerable category, for example, Lughaye, Badhan, Las Canood, Ceel Barde, Bosasso,
Afgoye, Baidoa, and Doolow, among others. Districts such as Eyl, Burao, Xudur, Belet Xaawo, and
Ceel Afweyne, on the other hand, have a high proportion of their households classified as less
vulnerable. This might be attributed to the fact that these are the same districts that reported
experiencing relatively low shock exposure as well as moderate to little or no hunger during the
study. Hargeisa and Salahley are major outliers, with the largest proportion of households falling
into the high-vulnerable category. These districts have a high concentration of households
belonging to the peri-urban livelihood zone, which also happens to be the livelihood zone with a
disproportionately large percentage of households falling into the high vulnerable category.
Overall, these geographical differences are highly evident, and they serve to highlight the need

93 | P a g e

for SomReP to specifically target those districts whose humanitarian situation is likely to worsen
as a result of the predicted drought.

01% 0%

38% 47% 41% 39%

61% 58% 78% 69% 70%
71% 72%

93% 90% 28% 99% 10% 100% 96%
36%
0% 7% 29%

39% 35% 15% 18% 24% 31% 12% 15% 51%
26% 30%

70%% 14% 8% 11% 10% 16% 04%%
2% 1%

Highly vulnerable Moderately vulnerable Less Vulnerable

Figure 69: District vulnerability profile

3.6.5 Correlation between food security indicators

A Spearman correlation test is conducted to establish the correction between food security
indicators. The results of the tests show that the correlations were significant at 5 % level of
significance and the food security indicators are associated in the expected direction. The
Spearman correlation coefficients varied from 0.1 552 to 0.2215 demonstrating that relatively
weak to medium correction between food security indicators.

Correlation between food security indicators

FCS HHS rCSI
1
FCS 1 1
0.1555***
0.2215***
HHS (0.000) (0.0000)

-0.2194 ***
rCSI (0.0000)
*** All correlations significant at p < 0.05 level

Table 23: Correlation between Food Security Indicators

94 | P a g e

The results in the table above show FCS is positively but weakly correlated to HHS (r=0.1555,
P=0.0000) and the correlation is significant at 5% level of significance. While the two food security
measures different dimensions73 of food security, both indicators are less sensitive to mild
changes in food security hence the positive but weak correction. With HHS, households are only
identified as food insecure if their situation is quite severe, as the measure only counts the most
extreme behaviors. FCS comes second after the HHS as is as well least likely to identify a
household as food insecure in mild food secure conditions. By contrast, the rCSI picks up some of
the less-severe coping behaviors as such there is relatively mild strong correlation between HHS
and rCSI than between the other measures.—which may be explained in part by the fact the food
insecurity situation was moderate to severe in the year 2021. The correlation between FCS and
rCSI was as expected negative but moderately strong (r=10.2194; P=0.0000). This results imply
that as households FCS increases, the rCSI decreases.

3.6.6 Concordance and discordance analysis between food security

indicator

The concordance analysis between food security indicators measures the degree to which two
different food security indicators agree (i.e. they place the households in the same food security
category –food secure, medium food secure, or severe food insecure). When one food indicator
places the household in one food category different from the other, the indicators are said to be
discordant. The extreme case is when one indicator places the household as food secure while
the other classifies the household as food insecure. This sort of analysis is particularly important
to understand which measure of food security is more sensitive to changes that occur in the
environment and gives an informative insights on what could be useful measure in short, medium
and long term. In the paragraph that follow we describe how the results of the analysis are
presented.

The green cells summarize cases in which both indicators place the household in the same food
security category. The yellow cells summarize where the indicators are discordant by one
category (one indicator classifies a household as food secure while the other shows moderate
food insecurity, or one shows moderate food insecurity while the other shows severe food
insecurity). The red cells summarize where the indicators are discordant by two categories (one
indicator indicates food security while the other indicates severe food insecurity).

I. Concordance between reduced coping strategy index (rCSI) vs food

consumption scores (FCS)

Food consumption scores (%)

Acceptable Borderline Poor Total
11.4% 22.6%
No or low coping 8.3% 2.9%

73 HHS is skewed to measure changes in household consumption regarding quantity while FCS is skewed to
measuring household food consumption regarding quality.

95 | P a g e

Reduced Medium coping 7.2% 1.8% 6.6% 15.6%
Coping High coping 34.8% 13.3% 13.7% 61.8%
Strategy
index (%) Total 50.3% 18.0% 31.7% 100%

Table 24:Concordance between Rcs Ivs FCS

The results show that the concordance between rCSI and FCS was at 23.8% while discordant was
at 76.2%. Thus in general the level of concordance was rather low and this can be partly because
the two indicators measure two different dimensions of food security. rCSI is skewed to
measuring household changes consumption of diet quantity while FCS is skewed to measuring
household changes in consumption of diet quality. This is particularly important to understand
because it partly explain the variance that is observed in the two indicators. Since the FCS is
skewed to measuring dietary quality –i.e. whether the household ate grains, piluses, vegetables,
daily products, sugar and fats and oils, among others, it is less likely that in dietary quality in
where food insecurity in just moderate as the tradition is that households may reduce quantity
of food or number of meals but will continue to diversify even though they are likely to move
from consuming high class food items to secondary or lower class food items as their ability to
provide to sustain the first choice items becomes weaker in the face of food insecurity74. This
situation will lead to a situation where the FCS would place the household as food secure yet the
rCSI would categorize the household as moderately food secure or severe food secure dependent
on the coping strategies adopted. However as the situation worsens households are more likely
to reduce the quantity as well as well as narrow their dietary food basket.

Both rCSi and FCS categorized 8.3% of households as food secure, 1.8% as moderately food
secure and 13.7% as severely food insecure. The results further show that 7.2% of the households
who were categorized as food secure by the FCS were categorized as moderately food secure by
the rCSI and only 2.9% that were categorized as food secure by the rCSI were categorized as
moderate food secure by the FCS. It is further observed that 13.3% of the households who were
categorized as moderately food secure by the FCS were categorized as severely food insecure by
the rCSI and only 6.6% of the households that were categorized as moderately food secure by
the rCSI were categorized as severely food insecure by the FCS. Finally, 34.8% of the households
who were classified as food secure by the FCS were classified as severely food insecure by the
rCSI and yet only 11.4 that were classified as food secure by the rCSI were categorized as severely
food insecure by the FCS. These results imply that FCS did not align well with rCSI when food
insecurity was severe which could partially explained by the fact that the former is less sensitive
at the more severe end of the acute food insecurity spectrum. The results on the overall show
that the proportion of households that were categorized as worse off than better off were higher
under rCSI than under FCS which indicates that the rCSI was less sensitive in discriminating

74 The behavior of diversifying food diet is very influence with culture.

96 | P a g e

among relatively food secure households compared to FCS in Somali context. As the FCS
increased (implying a more food secure situation), rCSI scores did not change greatly.

II. Concordance between reduced coping strategy index vs household
hunger scale

While both the rCSI and HHS are skewed to measure household changes in food consumption as
regard to quantity, the rCSI mainly focuses on measuring the behavior of household over the past
seven days when they did not have enough food or money to purchase food. Household hunger
scale on the other hand is collected by asking three questions on a potentially experienced food
deprivation at household level over the past 4 weeks/30 days. Household hunger scale is
generally appropriate for assessing severe food insecurity situation where households
experience food deprivation and is less relevant for areas and situations where food deprivation
is not widespread. On the other hand, RCSI is not suited to measuring food security in severe and
long term emergencies where households have already run out of many food coping options as
it is likely to artificially inflate the share of households perceived as food secure.

Concordance between reduced coping strategy index vs household hunger scale

Households hunger scale (%)

Reduced No or low coping Little or no Moderate Severe Total
Coping Medium coping hunger hunger hunger 22.6%
Strategy High coping 19.5% 2.4% 15.6%
index Total 0.6% 61.8%
(%) 100%
11.7% 3.0% 0.9%

38.4% 15.6% 7.8%

69.6% 21.0% 9.4%

Table 25: Concordance between rCSIvx HHS

The results show that the concordance between rCSI and HHS was at 30.3% while discordant was
at 69.7%. Thus the concordance level between rCSI and HHS is relatively higher than between
rCSI and FCS which could possibly be attributed to the fact that they are both skewed to
measuring changes in consumption of quantity diet. Both rCSi and HHS categorized 19.5% of
households as food secure, 3.0% as moderately food secure and 7.8% as severely food insecure.
The results further show that 11.7% of the households who were categorized as food secure by
the HHS were categorized as moderately food secure by the rCSI and only 2.4% that were
categorized as food secure by the rCSI were categorized as moderate food secure by the HHS. It
is further observed that 15.6% of the households who were categorized as moderately food
secure by the HHS were categorized as severely food insecure by the rCSI and only 0.9% of the
households that were categorized as moderately food secure by the rCSI were categorized as
severely food insecure by the HHS.

97 | P a g e

Finally, 38.4% of the households who were classified as food secure by the HHS were classified
as severely food insecure by the rCSI and yet only 0.6% that were classified as food secure by the
rCSI were categorized as severely food insecure by the HHS. The results overall show that the
proportion of households that were categorized as worse off than better off were higher under
rCSI than under HHS which again it indicates that the rCSI was less sensitive in discriminating
among relatively food secure households compared to HHS in Somali context. As the HHS
decreased (implying a more food secure situation), rCSI scores did not change greatly.

III. Concordance between food consumption score vs household hunger

scale

Household hunger scale (%)

Little or no Moderate Severe Total
hunger 50.3%
hunger hunger 18.0%
3.8% 31.7%
Acceptable 38.7% 7.8%
Borderline 1.8%
Food Poor 11.7% 4.5%
consumption 3.8%
scores (%) 19.3% 15.6%

Total 69.6% 21.0% 9.4% 100%

Table 26:Concordance between FCS vs HHS

The results show that the concordance between FCS and HHS was at 47% while discordant was
at 53%. The convergence between FCS and HHS was high and particularly on proportion of
households that were categorized as food secure (38.7%). The results further show that both
FCS and HHS categorized 4.5% as moderately food secure and 3.8% as severely food insecure.
The results further show that 11.7% of the households who were categorized as food secure by
the HHS were categorized as moderately food secure by the FCS and only 7.8% that were
categorized as food secure by the FCS were categorized as moderate food secure by the HHS. It
is further observed that 15.6% of the households who were categorized as moderately food
secure by the HHS were categorized as severely food insecure by the FCS and only 1.8% of the
households that were categorized as moderately food secure by the FCS were categorized as
severely food insecure by the HHS. Finally, 19.3% of the households who were classified as food
secure by the HHS were classified as severely food insecure by the FCS and yet only 3.8% that
were classified as food secure by the FCS were categorized as severely food insecure by the HHS.
The results overall show that the proportion of households that were categorized as worse off

98 | P a g e

than better off were higher under FCS than under HHS which implies that the FCS was less
sensitive in discriminating among relatively food secure households compared to HHS in Somali
context. As the HHS decreased (implying a more food secure situation), FCS scores did not change
proportionately. As observed that while there is significant convergence in times of food security,
the results show that divergence increases when food insecurity becomes more severe which
could partially be explained by the fact that the FCS less sensitive at the more severe end of the
acute food insecurity spectrum.

On the overall is it evident that to obtain a better picture of food security situation it is important
that a combination of food security indicators that measure household food consumption
regarding quality (FCS or HDDS) and quantity (rCSI or HHS) are utilized. It is further important to
note that in the short term or in case when food insecurity id not severely, rCSI and FCS are ideal
measures for food security.

However in the long term and in cases where food security is really severe, a combination of the
FCS and HHS would be ideal as the rCSI is bound to inflate the people who are considered as food
secure in extreme cases of food insecurity.

3.7Resilience and Poverty indices

3.7.1 Resilience Indices

The SomReP consortium defines resilience as the ability of people, households, communities, and
systems to mitigate, adapt, and recover from shocks and stresses in a manner that reduces
chronic vulnerability and facilitates inclusive growth. Vision quest used three capacities to
compute the resilience index across various levels. These capacities include an absorptive
capacity index, Adaptive capacity index, and Transformative capacity index. The contributory
outputs and findings have been analyses in section 3.0. As the resilience, indexes were computed
key determinants for each capacity were identified

3.7.2 Resilience index

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). While resilience index remained high
for some selected districts, It is envident that resilience of the households weakened further in
2021 than in 2020 and there is a need for more pragmatic interventions and concerted efforts

99 | P a g e

to improve household and community resilience. The program should strive to improve for
example layering and sequencing of interventions across the impact areas which currently appear
not to happen at the same scale across the project areas.

Resilience indices by gender

Resilience index 22.4%
Transformative capacity index 23.0%

Adaptive capacity index 21.7%
Absorptive capacity index
24.3%
0.0% 25.5%
Figure 70: Resilience Index by gender
23.2%

32.2%
32.6%
31.9%

10.6%
11.1%
10.1%

5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0%

All Male Female

3.7.3 Absorptive index

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 is 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).

100 | P a g e

FGDs revealed that while the community faced the triple shocks of Covid-19, Locusts and
flooding, the impacts of such shocks continued to hurt some beneficiaries even in 2021.

25.0 Absorptive capacity index 21.4
21.6
23.7
20.0
18.0

15.0
11.0 9.4 10.9 10.6

10.0

5.0

0.0 Pastoral Peri-urban/Urban All
Agro-pastoral

Absorptive capacity index 2020 Absorptive capacity index 2021

Figure 71: Absorptive Index by Livelihood

Factor analysis revealed that the key interventions that have significant influence on absorptive
capacity index are informal safety nets, contingency reserves (cash, grain and fodder), finally
household’s access to early warning information, and access to insurance.

3.7.4 Adaptive capacity index

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. Market
functionality are key to the peri-urban households as it offers a range of economic opportunities
through trade and employment. Besides, the program intensity was significantly higher among
the peri-urban households than other livelihood groups which could have somehow given them
a leverage to build their adaptive capacity more than other livelihood groups. 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%).

101 | P a g e

Adaptive capacity index

40 38 30 28.1 34.1 34 32.2
35 33.3 27
30
25 Pastoral Peri-urban/Urban All
20
15
10

5
0

Agro-pastoral

Adaptive capacity index 2020 Adaptive capacity index 2021

Figure 72: Adaptive capacity Index

Factor analysis revealed that the key interventions that have significant influence on adaptive
capacity index are social networks, education and trainings, adoption of practices, bridging of
social capital, and finally household’s access to credit.

3.7.5 Transformative index

Transformative capacity index reduced from 29 in 2020 to 24.3 in 2021 and the difference was
statistically significant at 5% level of significance (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%.

102 | P a g e

Transfromative capacity index

35.0 31.0 29.0 25.0 29.0
30.0 22.4 23.1 24.3

25.5 Pastoral Peri-urban/Urban All
25.0

20.0

15.0

10.0

5.0

0.0
Agro-pastoral

2020 2021

Figure 73: Transformative Inx across livelihood

Factor analysis revealed that the key interventions that have significant influence on
transformative capacity index are social cohesion (sense of belongingness to a group inside or
outside the community), access to veterinary services, access to agricultural services, access to
basic services (i.e. formal financial services, insurance services, radio and TV stations), and finally
living or belonging to a community which has functional community governance structures (i.e.
ADC, EWEA committees, Water committees, and NRM committees, among others.

The table below provides a summary of resilience indices per district.

District Absorptive Adaptive Transformative Resilience capacity
capacity (%) Capacity (%) capacity (%) (%)
Afgooye 18.1 41.5 29.9 29.8
Badhan 24.2 31.9 35.7 31.2
Baidoa 8.14 46.9 22.7 25.9
Balet- 11.5 36 40.1 29.2
Xaawo
Bossaso 13.6 36 28.2 25.9
Burao 4.29 23.1 15.2 14.2
Cee- 9.22 22.7 16.2 16
Afweyne
Ceel_Barde 4.64 30.6 16 17.1
Doolow 20.3 34.1 24.4 26.3
Eyl 9.61 35.3 35.3 26.7
Hargeisa 3.5 37.4 25.4 22.1
Laas 7.17 27.9 16.3 17.2
Caanood
Lughaye 1.81 18.5 10.1 10.1

103 | P a g e

Odweyne 17.4 29.8 27.8 25
17.3 19.4
Salahley 2.55 38.4 39.9 22.9
24.3 22.4
Xudur 4.89 23.8

All 10.6 32.2

Table 27: Resilience capacities across districts

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%).

Adaptive capacities were stronger in Baidoa (46.9%), Afgooye (41.5%) Salahley (38.4%), and
Hargeisa (37.4%). The lowest responses on the adaptive capacity in lughaye (18.5%), Ceelafweyne
22.7%) (Hudur (23.8%). Transformational capacity was strongest in Beletawo (40.1) and Xudur
(39.9), and Eyl (35.3%) while weakest in Lughaye (10.1%) followed by CeelBarde with 16.3%.

Overall, resilience was stronger in Badhan (31.2%) followed by Afgooye (29.8%) and Beletawo
(29.2%). Lughaye (10.1%) and Burao (14.2) are considered the least resilient based on the
findings.

3.7.6 Correlations between resilience index and program intensity

Correlation is a linear association between two variables. Thus correlation analysis helps to
determine both the nature and strength of relationship between two variables. Correlation value
therefore range from +1 to -1. A zero correlation value indicates that there is no relationship
between the two variables while -1 indicates a perfect negative correlation and +1 indicates a
perfect positive correlation. The result from pearson’s correlation tests between resilience index
and program activities indicates that there is a weak positive correlation (r=0.3202; P=0.000)
between program intensity (number of project interventions the households participates in) and
the household resilience index and the correction is statistically significant at 5% level of
significance. Thus the results imply as he household participates in more interventions their
resilience index is more likely to increase and so the vice-versa. These results underscore the
importance of project layering and sequencing in improving household and community resilience
and thus far confirms the project validity of program’s ToC on program activity layering and
sequencing.

3.7.7 Correlation between resilience index and program activities

The results from the correlation tests between resilience index and program activities show that
there is weak positive correlation between the following activities and resilience index: livestock
production (r=0.1371; P=0.0000), crop production (r=0.1436; P=0.0000), EWEA (r=0.2705;
P=0.0000), NRM (r=0.3355; P=0.0000), TVET (r=0.3666; P=0.0000), VSLA (r=3260; P=0.0000). The
correlation between resilience index and these variables is significant at 5 %. The results suggest
that despite the weak relationship, household’s participation in these activities increases its
likelihood to increase the resilience capacity. The results, however, showed that there is weak
correlation between resilience index and cash transfers and the correlation was not significant.

104 | P a g e

3.8 Poverty Indices

One of the core indicators of the SomRep Annual Resilience Measurement is Stochastic and
Structural poverty Index measurement. The whole aim of building community resilience is
providing pathways that build economic groups while at the same time protecting them from the
shocks and stresses that are likely to negate that development. In this program SomReP
embraces the definition of poverty based on the structural and stochastic elements. Stochastic
and structural poverty is observed based on households' assets and other characteristics to
create four categories of households: income and asset poor (structurally poor), income rich and
asset poor (stochastically non-poor), income poor and asset rich (stochastically poor), and
income and asset-rich (structurally non-poor)75.

Overall, there was no significant change in poverty levels. The proportion of households that
were found to be structurally poor and stochastic poor decreased from 62.5% and 0.90% in 2020
to 61.9% and 0.73% in 2021 respectively The proportion of households who were stochastically
non-poor increased marginally from 35.1% in 2020 to 35.5% in 2021. There was also a marginal
increase in proportion of households who were structurally non poor from 1.60% in 2020 to
1.88% in 2021.

Structurally poor Stochastically Stochastically Structurally non-
poor non-poor poor

2020 2021 2020 2021 2020 2021 2020 2021

Agro-pastoral 62.10% 56.00% 1.20% 1.10% 35.50% 40.40% 1.30% 2.45%
39.70% 23.80% 0.90% 0.47%
Pastoral 58.40% 75.40% 1.00% 0.31% 27.00% 38.50% 3.50% 2.35%
35.10% 35.50% 1.60% 1.88%
Peri-urban 69.00% 58.90% 0.00% 0.23%

All 62.50% 61.90% 0.90% 0.73%

Table 28: Analysis of Stochastic poverty among the beneficiaries

Across the livelihood groups, unlike in 2020 when peri-urban households were the most
structurally poor, in 2021 pastoraL households were the most structurally poor at 75.4%,
followed by the agro-pastoral households at 56.0%. The proportion of households who were
structurally poor decreased significantly from 69% in 2020 to 58.9% in 2021. These results imply
that poverty levels worsened among pastoral households but improved significantly among peri-
urban households with 38.5% classified as stochastically non poor in 2021 compared to only 27%
in 2020. While there was also an increase in proportion of households classified as stochastically
non poor among agro-pastoral households from 35.5% in 2020 to 40.4% in 2021, the proportion
of households classified as stochastically non poor decreased significantly among pastoral
households from 37.7% in 2020 to only 35.3% in 2021. This basically means that there were
negative livelihood strategies employed that affected accumulation of assets for program
beneficiaries as well as series of shocks and stresses affecting the household. For the poor,
Household assets are a social safety net in the event of shocks and stresses. However, in the case

75 Worldbank group

105 | P a g e

of this study, shocks and stresses experienced and as demonstrated in the drop in absorptive
capacity had an impact of productive assets (land and live livestock) decimating the overall value
of these assets.

Analyzing across section study of structural and stochastic poverty, the World Bank observed
that the income and asset poor generate 29 percent of their income from environmental
resources, more than the other three categories. The income poor are more exposed to extreme
and variable climate conditions. They tend to live in dryer (and hotter) villages in the dry forest
zones, in wetter villages in the wet zones, and experience larger rainfall fluctuations. Among the
self-reported income-generating responses to income shocks, extracting more environmental
resources ranks second to seeking wage labor. Given high reliance on forest and other
environmental resources, a concerning finding is that, in the Africa subsample (dominated by dry
forests), the rate of forest loss is more than four times higher for the income asset poor compared
with the income asset rich. Special attention should be given to the poorest households in dry
areas, predominantly in Africa. They are (already) exposed to more extreme climate conditions,
they suffer the highest forest loss, and the forest benefits are at risk in global warming
scenarios76.

4. Cross cutting issues

4.7 Project Sustainability

Sustainability means meeting a generation’s current needs without compromising the ability of
doing so in the future77. In addition to natural resources, we need social and economic resources.
Analysis of the project established that the design was deliberate to promote sustainability by
addressing natural environment rehabilitation and management, Building social capital and
economic resources. The assessment established that the objectives of the project were
anchored upon the need to protection and foster a better future. SomRep conducted a Climate
and Gender analysis across the target districts to inform designing of programs across the
partners and create the beneficiaries’ awareness on the impact the twin issues may impact their
livelihoods.

It was also established that the project had initiated initiatives that supported interventions
beyond its (project) own life time. This was evident through the intense linkages established and
those that continue to be established as analysed in section 3.5.3 this include the linkages
between the community structures and local authorities where the local authorities support the
development of CAAPs and use information from the community to inform and contribute to the
District level planning. Further, SomRep worked very closely with the local authorities to build
their capacity, provide technical support and lead the process especially the planning and
monitoring of interventions. At the community level, SomReP continued to Support community

76 https://elibrary.worldbank.org/doi/abs/10.1596/1813-9450-7474
77 https://www.mcgill.ca/sustainability/files/sustainability/what-is-sustainability.pdf

106 | P a g e

structure development for self-governance across the social, environmental and economic
spheres. The impact of such linkages were evident through the high numbers of respondents that
reported having participated or known the existence of the structures and their functionality in
the community.

FGD discussions acknowledged that communities will need the support of the the humanitarian
agencies much longer to create sustainable interventions. Community appreciated capacity
building that gave them the ability to plan and develop and manage their own priorities. In
addition, there was strong appreciation of the government involvement as a back stop measure.
There was appreciation also that villages where SomRep was intervening such as Beer-ittir were
had more sustainable interventions compared to neighboring villages. However, the social affairs
committee expressed fear that if SomRep does not go back to support Beer-Ittir, in the long term,
the village may regress in terms of achievements.

At the policy level, it was established that SOMREP did contribute to the resilience working group
and was influencing discussions in favor of resilience building. Participation at the higher levels
of decision making such as within the resilience working group was strong.

The drop of resilience indices though remain a matter of concern in as far as the consortium
program is concerned. While the drop in resilience index is not a direct implication of lack of
sustainability, it posits at the ability of the community not able to use the resources available to
them to reduce the impacts of the shocks. However, it was also observed that in terms of program
intensity, there were more people falling under the low intensity category meaning the gains
made through to 2020 in terms of intensity may have been eroded.

4.8 Gender

The project sought to promote equity in the community. Women were prioritized across all
interventions due to their vulnerability and contribution to the household economy. VSLA were
established to strengthen women’s capacity to save and invest, providing opportunities for
financial inclusion and livelihood diversification.

On the community governance, Vision quest established that the criteria for selection of
leadership included deliberation selection and involvement. Across all committees that
participated in FGDS, women were represented women reported that they were actively involved
and that their voices were heard. Women FGD confirmed participation in the planning and
prioritization of community-level projects. For committees that had bank accounts, at least one
of the signatories was a woman.

Review of the 2020 ARM confirms that SomRep project is committed to mainstreaming gender.
For example, women, girls, boys and men were reached in different dialogues and trainings to
meet their differential needs. Further, the report indicated that the needs of women were
addressed through development of water resources that reduced distance and time to water
points, hence increasing water access.

107 | P a g e

5. Conclusions and recommendations

5.1 Conclusions

The study has revealed the implementation of well-structured and harmonized approaches
across the partners and locations. The selection criteria were based on vulnerability, both in
terms of households units selected and district fragility. The communities’ continued to
experience shocks during the reporting period with droughts reported towards the end of 2021.
The project has well-developed mechanisms to cushion the extremely vulnerable from extreme
shocks and stresses. Further, SOMREP has gone to a great deal to establish community
governance structures and link those structures to relevant government arms to create a
seamless flow of information and technical support. There was a substantial flow of early warning
early action information flow to all districts and across various channels including by the staff and
community members. Due to the timely flow of information, there were improvements in
preparedness and investment in contingency reserves.

There was a slow recovery from the triple shocks of 2020/2021 namely Covid-19, locusts, and
floods. The process has been slowed even further by drought reported in 2021 that has led to
the failure of Deyr rains 2021. As a result of the shocks, there was a general drop in the well-
being of the project beneficiaries in the year 2021 compared to measurements reported in 2020.
Beneficiaries were found to be structurally and stochastically poorer by 2.2% while in terms of
resilience as measured by TANGO, the indices dropped by 7.6%. The drop was a result of the
cumulative effect of Covid-19, poor harvests as a result of locusts, flood ( Dery 2020, and drought
Deyr 2021). Atleast a quarter of programme respondents have reported exposure to the drought
across programme areas with extensive use of negative coping strategies rising by at least 30%
points in 2021 compared to 2020 indicative that previous gains are at risk of being eroded. Again,
there is significant increases in the prices of water and food commodities limiting households
that are income and asset poor as well as those with large household sizes. The study also noted
extensive loss of livestock due to lack of water, present estimated livestock death in affected
villages is presently 77,810 livestock units. This has resulted in increasing the population in most
need which presently stands at 20,250 Households while those at risk of falling into extreme food
insecurity presently stands at 49,410 Households. Household hunger has remained relatively
stable compared to 2020, at least a third of project areas continue to experience moderate to
severe hunger.

At the time of the study, at least 40% of the households were classified as moderate to highly
(severely) vulnerable. These findings are consistent with the reduced coping strategy index and
shock exposure index findings, which show that the conditions in these households are alarming
and are exhausting their coping mechanisms. With humanitarian conditions expected to worsen,
a further reduction in the number of households classified as less vulnerable is unavoidable. As a

108 | P a g e

result, households in the less vulnerable category are more likely to progress to the moderate
and high vulnerable categories.

The assessment revealed a positive investment in high-value crops among irrigated crops
especially in Hargeisa where the demand exceeds supply. Investments in irrigation allowed some
of the beneficiaries to produce food all-round the year including in Hagaa and Jilaal seasons.

The project invested in the capacity of the beneficiaries through good agricultural practices. As a
result, there was an improvement in yield across those that undertook the training. On the
livestock sector, animal health and access to clinical services remained the highest priority for
those seeking extension services. Access to livestock insurance remains largely difficult due to
the lack of service providers and risk aversion attitude amongst beneficiaries. There was no much
evidence pointing to significant investments in livestock value chains despite livestock
contributions in the Somali food chain and income being critical.

SomRep investment in ensuring linkages between VSLAs and banks, Village Development
committees with local authorities and the innovations of new approaches is a sustainable way of
ensuring that the project gains are sustained and outlive the intuitions itself. The government
involvement in all categories of community structures and in the actual planning, review, and
monitoring of the implementation of resilience-related plans was very strong. The respondents
reported high levels of satisfaction on their perception of government role.

The project approach is relevant and suitable to the context. Further, the project is highly
sustainable, has contributed to alleviating poverty and development of knowledge on the sector.

Overall, the was a decrease in the resilience index and proportion of people that reported being
structurally non-poor by 7.5% and 2.45 respectively. This means that the communities were less
resilience in 2021 compared to 2020.

5.2 Recommendations

Based on the findings of the assessment the following are recommended actions;

The program approach is well though and harmonized between partners. There is evidence of
common approach and incorporation of new knowledge to improve the program and build the
capacity of the staff. Within the project strategic approach, program layering and sequencing still
remain weak. SomRep should increase program sequencing and layering with a specific focus on
Lughaye, Odweyne Laascanod Ceelafweyne, Badhan, and Sahlaley.

Due to the intensifying water and food crisis and humanitarian needs across affected districts,
the following areas of intervention are recommended to be prioritized based on community
action plans and EWEAC/HADMA to ensure project achievements are not eroded and to avert a
scenario which will see households in less vulnerable category falling into the moderate and high
vulnerable category.

WASH:

109 | P a g e

 To deliver immediate water trucking and install temporary water distribution systems while
promoting household water treatment and safe storage to reduce the burden of diarrhea and
water contaminations across the drought affected locations.

 To establish emergency and long-term water storage facilities, design the WASH infrastructure in
disaster prone locations to resist potential risks including flash floods, cyclones and other
catastrophes by improving of water facilities in areas prone to flooding.

 Conduct emergency distribution of Hygiene kits and NFI kits to improve HH water collection and
storage –distribution of water treatment chemicals and other supplements for household

 Engage community hygiene promoters from the crisis affected locations and displacement areas
to ensure regular supervision and monitoring of the community conducting hygiene promotion
activities. –the action will promote pastoral community awareness.

 Conduct rehabilitation and construction of communal water assets (productive multi-use water
infrastructures) including shallow-wells, berkeds, water catchments (ponds, pans) and other
water storage facilities to ensure water availability during this period and beyond.

 Provision of plastic water mobile tanks (bags) 5 CubicM to affected and displaced communities
across project locations for emergency water storage and management –sustain water tracking
in the short run.

Food security and livelihoods

 To ensure availability and utilization of sufficient nutritious foods to vulnerable and drought
affected communities, conduct provision of diversified supplementary foods and non-food items
for household consumption. –including ready meal to displaced communities.

 Conduct multi-purpose cash assistance (unconditional and conditional cash transfers) targeting
the most crisis and drought affected communities and households from pastoralist and agro-
pastoralist populations based on (IPC 3) including the newly displaced households and provide
basic household needs support (including Food and non-food items).

 Provision of livestock supplementary feeds (fodder) to emaciated and weak body condition of the
displaced livestock to improve lifespan, health and quality of livestock and produce better quality
of meat and milk with positive impacts on food security, nutrition and income.

 Provision of veterinary drug supplies to the CAHWs and other government mobile health teams
to carryout disease prevention and treatment campaigns at the target displacement locations –
facilitation of logistics and other services to mobile teams and CAHWS.

 Immediate supplies of human drugs and water treatment chemicals to the affected communities
in response to the possible outbreak of AWD and provision of emergency treatment kits –
provision of first aid kits.

 Provision of diversified agricultural inputs –high productive, early maturing and drought resistant
crops to ensure access to immediate food recovery and crop production for the affected agro-
pastoral communities.

110 | P a g e

In addition, SomReP should focus on high capacity investments in such areas such as cash crops
(fruits and vegetables) market linkages and cash-based interventions. Focus on scaling up
strengthening existing livelihoods and diversification of livelihoods for stronger results. The
variance analysis between groups and within districts was significant at 5% level of significance
(p=0.00). 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. Shocks exposure had severe impacts on Households with disability.
As such Households with disability as a vulnerability criteria were found to be impacted more by
shocks compared to other categories.

On program intensity, 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

Focus on increasing the community absorptive capacity across the board as it proved to be
positively linked to livelihood improvements. The more communities are able to prepare in
advance the more they are able to mitigate the adverse effects on shocks. Despite the great effort
to invest in shock mitigation and preparedness initiatives, the percentages of those who had
contingency reserves were relatively low. Hence, there is need to strengthen community
preparedness and mitigation efforts.

Overall expenditure was extremely high compared to income. This could have been triggered by
the shocks experienced during the assessment period. Nevertheless, it shows the emergency
caseload is high within the project target groups. The higher the emergency caseload, the lesser
the chances of realizing resilience. SomRep will need to re-strategize on how to effectively
support communities to reduce on the emergency caseload. This may include renegotiating with
donors to ensure multiyear funding is sustained with no gaps in between funding.

Through field-based farmer support, focus on high-value crop farming and market development
coupled with postharvest loss management to increase agro-pastoralist access to disposable
cash. Also, include nutrition security in capacity building to support diet diversification at the
household level.

As indicated, factor analysis revealed that the key interventions that have significant influence
on adaptive capacity index are social networks, education and trainings, adoption of practices,
bridging of social capital, and finally household’s access to credit. SomRep can focus on building
this set of activities that support the improvement of the adaptive capacities for effective
resilience building. Similalry, Factor analysis revealed that the key interventions that have
significant influence on absorptive capacity index are informal safety nets, contingency reserves
(cash, grain and fodder), finally household’s access to early warning information, and access to
insurance. This activities should be given greater focus as part of learnings from this study.

111 | P a g e

Strengthen the linkages between CAAPs (VDC) with district and state authorities for sustainable
results. Though there are already existing links and the community highly regarded the
contribution of the local within the framework with Shoqadoon, scale-up programs that enhance
the capacity of the VDCs and support mechanism of accountability so that VDCs can increase
chances of securing funding for the plans. At the humanitarian level, encourage the use of CAAPS
in determining community level priorities and therefore providing linkages between
humanitarian actors and CAAPs (VDCs). On the http://bulshokaab.com site that provides data of
CAAPS, Shoqadoon and SomRep should disaggregate projects to provide a quick view of the
projects completely implemented and closed from those funded as the goal of fundraising is to
see an increase in proportion of implemented priorities increase. The availability of a site with
data on funding is a commendable and should be popularized so that contributors can be able to
visit the page and see progress of the CAAPS.

Strengthen the role of the government and especially in EWEA dissemination, CAAPs planning
and review as well as coordinating the community structures and government ministries. This
can be useful in promoting sustainability as well as preparing the exit of the SOmrep partners.

Vision quest recommends that SomRep develop and exit strategy that includes capacity support
for villages where programs has ended in order to continue to ensure the momentum is
maintained. Beneficiaries in some of the areas where they programme had ended such as Beer-
Ittir had expressed fear that the long term absence of SomRep may lead to lose of some of the
gains achieved during the program period. Communication on the kind of supported and
interaction expected when the program ends will be important. Further, the monitoring of the
community projects can be done in a public handover with the local authorities as this is the very
essence of their engagement.

With the beneficiaries embracing off season farming to increase food security, SomRep partners
will need to think how to expand water access to ensure availability through all seasons. The
program should consider the development and inclusion of a household graduation model. In
such a case, it is possible to start graduating Households that report remarkably improved
incomes to pave way for the inclusion of other vulnerable households.

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. Further, due to the intensity of information required and the length of
tools as revised over time, it will be advisable to make the study concise in the future. Overall the
ARM is taking shape, it is highly technical. There will be need to do put more resource for future
studies.

VSLAs have increasingly provided financial services in the forms of loans and savings to their
members. However savings are not easily available to members when in needs as they are used
as collateral against loans taken by members. SomRep should support the groups to explore how

112 | P a g e

to ensure that members of the VSLAs can access portions of their savings from VSLAs when in
need.

On community structures, a number of respondents reported committees being ineffective. The
reasons why committee were felt ineffective was not established. However, it would be
important for SomRep and Partners to pursue the functionality of each committee and establish
the extent they function and determine needs that could be addressed to make them more
functional.

The findings revealed that shocks exposure had severe impacts on Households with disability.
SomRep should increase its support on households with disability knowing that they are already
disadvantaged. Consider also supporting women whose impact of shocks was also poorer
compact to men.

On the indicator on land under cultivation “#of hectares under soil and water conservation
measures”, SomRep should consider the Farm managed & Natural Resource Managements and
farmer field schools as possible source of data during routine monitoring. The indicator as it is
needs to be captured from a total population and not a sampled survey. If this has to be captured
under survey, the indicator may need to be change to an average household land allocated to
soil and water conservation.

On strengthening resilience indices overall, there was evidence that household who participates
in more interventions their resilience index are more likely to increase and so the vice-versa.
These results underscore the importance of project layering and sequencing in improving
household and community resilience and thus far confirms the project validity of program’s ToC
on program activity layering and sequencing. The program should focus on finding funding that
support intensity across all locations and strengthening the areas that face frequent shocks.
Couple with this, SomRep should increase market based interventions and development of value
chains for increased market competition.

6. Annexes

Provided separately is the tools used in this study. The tools are:

Annex 1: SomRep Annual Resilience Measurement Survey Kobo tool

Annex 2a: SomRep and Partner KII Guide

Annex 2b: FGD SAC Guide

Annex 2c: FGD TVET guide

Annex 2d: FGD guide Savings and Loans

Annex 2e: FGD guide EWEA committees

Annex 2f: Producer and Market groups

113 | P a g e

Annex 2g: FGD NRM and FMNR Committees
Annex 2h: FGD CAHWs and Vet guide
Annex 3: Observation checklist
Annex 4: Most Significant Change Story collection template.

114 | P a g e