36
Applying EMMA in slow onset disasters
‘By definition, there is more time to plan and implement an appropriate response in a slow-onset disaster such as
drought. Yet evaluations still criticise the apparent lack of learning and the repetition of mistakes, including the
fact that the humanitarian system often does not intervene until the crisis stage. One reason for this is while it is
known in advance there will be an impact – on water availability, crop and livestock production and prices – it is
not always clear how well people will manage.
…It is difficult during a humanitarian crisis to distinguish between people suffering from chronic and acute food
insecurity. In the absence of other assistance, people experiencing chronic food insecurity will need humanitarian
assistance…’
Slow-onset disasters: Drought and food and livelihoods insecurity; Learning from previous relief and recovery responses.
ALNAP and ProVention publication
http://www.alnap.org/pool/files/ALNAP-ProVention_lessons_on_slow-onset_disasters.pdf
Overall:
When applying EMMA to slow onset disasters, where the impact of the disaster and its implications on the lives
and livelihoods of the population are not yet known, the analysis team should consider:
1.
Slow onset disasters are commonly cyclical and complex. Evaluations and data from past emergencies
can be applied to better understand: (a) the impact and consequences of the disaster (on the
population, the market system, government and key actor responses etc…), (b) additional influencing
factors that in turn render the emergency more complex, (c) projected population needs (items
needed and timing), (d) NGO and government response and, (e) lessons learned. Where possible,
reliable representative and retrospective baseline and emergency data should be applied.
2.
Due to the gradual deterioration of the context over months/ seasons, it can be difficult to determine
when the population will require support (response time frame). Identifying indicators that would allow
close monitoring of population needs and context deterioration is ideal but should be linked to a response.
Additional guidance on applying EMMA in slow onset disasters is given below, in 12 Steps.
Crucial EMMA preparation: Consider:-
(a)
The speed of context change, and whether or not the disaster has reached its peak. In instances where the
disaster is still unfolding, then EMMA teams will have to work with a scenario of predicted disaster impact
and population need. For example identifying the current and projected needs of the potential population;
i.e. as the situation worsens, what are the needs going to be and how many people will require assistance?
(b)
Asking affected households (a) what actions would help mitigate the current and potential impact of the
unfolding disaster and, (b) how their coping strategies are going to evolve as the disaster unfolds
(c)
Referring to past emergencies for examples of needs, responses, lessons learned and coping strategies used
(d)
Spending longer discussing with key informants/ stakeholders to better ascertain population need, assistance
preferences, as well as gender, vulnerability and marginalisation aspects to tailor responses and reduce exclusion
(e)
Identifying ‘emergency indicators’ and respective values that would ‘trigger’ an emergency response with
affected households to share with the NGO sector / Cluster. The IPC is a useful tool in such circumstances
(
www.ipcinfo.org
), as it aids decision making and encourages dialogue amongst agencies, respective
government bodies and the UN. Make linkages to, and share information with Early Warning Systems such as
the Famine Early Warning Network (
http://www.fews.net/Pages/default.aspx
).
(f)
Consulting existing development programmes in the affected area as a lot of the data you require relating to
the pre-disaster/ baseline situation may be available
Step 1: Essential Preparation
(a)
Have more time to focus on information quality through the identification of key informants, market
specialists (where and when relevant) the inclusion of relevant governmental bodies and institutions.
(b)
Have time to involve other sectors (gender, development team, finance and logistics) as well as access EMMA
trained and experienced staff or train staff in EMMA.
(c)
Relate the overall objective to the planned outputs from the EMMA, for example: “to mitigate the impact of
the shock on affected households and assist rapid recovery of livelihoods and food security”.
37
Step 2: Critical Market Selection
(a)
Identifying markets that are essential at different stages of the emergency evolution i.e. a market that reflects
current needs and potential mitigation of the disaster impact (for example livestock in a pastoralist setting
suffering from drought), and one that relates to future/ forecasted needs (based on past experience such as
staple foods or potable water or livestock).
(b)
Using past experiences of needs and their related markets as slow onset disasters tend to be recurrent.
(c)
Including at least one Key Analytical Questions that relates to the overall objectives (see Step 1).
(d)
Consider markets that could lead to advocacy for improved NGO/ Government practice (see S Sudan case
study example above). To do so, review repeated NGO responses that are potentially/ reputedly
inappropriate and consider an analysis of the markets utilised/ affected/ side-lined.
Step 3: Preliminary Analysis
(a)
The seasonality of the emergency and baseline maps should be the same to allow for comparative analysis.
This can be tricky especially when the disaster has unfolded over seasons.
(b)
EMMA practitioners need to ascertain the speed of context change to decide on the number of maps
required. The EMMA team may be forced to elaborate a number of maps depending on when the EMMA
process takes place within the evolution of the disaster (as discussed in Step 2). For example:
-
In Chad 2012, 3 maps were elaborated, for a ‘good’ year, ‘bad’ year and ‘normal’ year. For Chad,
factors that determined good or bad year included harvest and pastoral conditions. In Liberia; refugee
influx, Ethiopia; rain and pastoralist movements. Additional contributing factors were taken into
consideration: for examples in Chad, on top of bad rain and harvest, other factors worsening the
situation included the Libya crisis, Nigeria border closing, fuel prices soaring etc... It is very difficult to
elaborate complex scenarios, compare years of reference and avoid confusion among team and
stakeholders. Therefore 1 or 2 main contributing factors were identified and used.
Another example:
-
A baseline map. This is pertinent where market activity has changed significantly since the onset of
the disaster. Where there has been little change, then the EMMA team may prefer to focus on the
‘current’ map. The EMMA team should consider carefully the added value of developing a
retrospective baseline map.
-
An current / interim map that will document and illustrate changes taking place in the market system
before the emergency reaches its peak. Such a map is helpful in identifying mitigation activities and in
understanding the on-going impact of the shock on the markets and those that use/ exist within them.
-
A predicted/ forecasted emergency map: based on past experiences of that type of shock, what is
expected? Again, this type of map is helpful in identifying mitigation activities, to lessen the impact of
the shock.
-
Eventually, an emergency map once the disaster is considered to have reached its full impact (difficult
to ascertain in slow onset disasters).
(c)
Taking time to investigate gender, protection and marginalisation issues in more detail.
(d)
Keep the Key Analytical Questions in mind when interviewing key informants.
Step 4, 5 and 6: Data collection and Final Mapping
(a)
If past emergencies (of similar type and magnitude) resulted in market actors exhibiting negative behaviours
(significant price increases, stock hoarding, credit freezing, reduced or terminated services etc…) or business
closure (temporary or permanent), investigate the cause of this change and whether or not it is likely to occur
again. If so, what could be done to mitigate/ prevent its occurrence, especially if this plays a crucial role in
assisting potential/ actual beneficiaries.
(b)
Speak to key informants about behavioural change ‘triggers’ (for example, does the price of a good have to
reach ‘X’ price before consumer/ trader/ service provider behaviour changes significantly (such as purchase of
cheaper goods, not stocking items, closing transport routes etc…)? Such information can help in
implementation timing decision making and identifying responses for key market actors/ beneficiaries. These
triggers can be incorporated into monitoring systems to enable faster and more suitable responses.
(c)
Investigate potential disaster mitigation ideas at the same time as collecting the data.