Protocol 2.6: Systematically document evidence and analysis and provide them upon request

All evidence and analysis needs to be clearly and systematically documented so that analysts have the body of evidence to support their classification. The documented evidence should be made available if requested for quality review purposes. 

The IPC Analysis Worksheet

The IPC Analysis Worksheet supports systematic, transparent and consistent evidence-based analysis by guiding the analysis through the IPC Food Security Analytical Framework and linking evidence to the IPC Reference Table. The use of the Analysis Worksheet, preferably in ISS or in MSWord™, is a major advantage to IPC analysis. The Analysis Worksheet is divided in seven steps (Box 57) that, if completed, will meet all analysis requirements, as detailed in protocol 2.5 (Box 56).  Procedures for completing the Analysis Worksheet are briefly described below. It is highly advisable that parts of the Worksheet, especially Steps 1, 2 and 3, are completed by analysts before the analysis workshop. The order of the steps is not pre-determined, and analysts may complete them in any order as well as edit previous steps during the analysis.

Step 1: Conduct a context analysis

Purpose: To support the contextualization of evidence and livelihood-based analyses of food security by providing information on livelihood strategies and assets, including a review of the seasonal calendar and key characteristics of population living in the area.

Approach overview:

In order to characterize each area to be analysed, analysts will utilize Step 1 of the Chronic Food Insecurity Analysis Worksheet. In addition, they should carry out the following:

  • Decide on the spatial extent of the area. A single-level classification will be determined for this area.  Generally, administrative areas are used for analysis, but other units such as livelihood zones can also be applied. Analysts must determine the spatial extent of the analysis area, depending on the needs of decision-makers as well as availability of evidence and feasibility of classifying the desired number of areas. In general, the analysis area should be as homogeneous as possible with regard to likely food security outcomes and causes.  
  • Provide a brief description of the area, including relevant information to be used in contextualizing evidence. Important aspects may include common livelihood strategies to acquire food and income, seasonal patterns, cultural habits and economic environment.  Optimally, a summary of the food security seasonal calendar should also be included in the description. 
  • Provide the number of population living in the area. Indicate population numbers and the source of evidence, and specify the reference year (usually the current year) if the population has been projected, e.g. based on an earlier census.
  • Identify and describe household groups living in the area, as relevant. HAGs may be identified and described to better support analysis, especially if evidence is available for them. HAGs should have a relatively homogeneous food security situation, including contributing factors and likely outcomes. These groups may be defined, for example, by variations in wealth, gender, ethnic affiliation, livelihood, religion, or any other factor or combination of factors that make the groups distinct. The number of groups identified can vary. For each group, preferably specify the estimated number of people and their percentage share of the total number of people in the area. 
  • Provide a brief narrative description of the recurrent shocks that affect the area and their usual frequency.
  • Identify if the analysis area experienced Acute Food Insecurity Phase 3 Crisis or more severe in at least three different years over the last ten years. If IPC Acute Food Insecurity Analyses have not been conducted in enough years to determine this, either use an equivalent classification system or highlight that recurrence of crisis cannot be identified.

Step 2: Document evidence in repository

Purpose: To help organize wide-ranging data from multiple sources for ease of access and reference.

Approach overview: 

  • Provide references for all evidence to be reviewed in analysis, including identification of sources and dates of evidence collection and season of data collection (e.g. lean or non-lean). If desired for easier reference during the analysis, include the actual evidence (e.g. graphs, text, figures) in the evidence repository and identify what food security elements it informs (i.e. it can inform more than one).
  • Provide a note on data collection methods to support assessment of Reliability Score whenever possible.  

Step 3: Identify periods with non-exceptional circumstances 

Purpose: To identify periods within the previous ten years during which the area did not suffer or benefit from the impacts of unusual shocks. Identification of periods of non-exceptional circumstances is key to correctly using quick-changing indicators against the Chronic Food Insecurity Reference Table cut-offs, which are set for the lean season of periods with non-exceptional circumstances. If evidence on quick-changing indicators was collected in a lean season with non-exceptional circumstances, the cut-offs in the Reference Table can be directly applied. However, if evidence was collected during exceptional circumstances, the evidence has to be inferred against the Reference Table and may not be granted even R1- but can still be used to support the analysis, especially if evidence collected over exceptional circumstances is scarce. Box 58 details concepts and an approach for the identification of non-exceptional circumstances.  

Approach overview: 

  • Assess if the area suffered or benefited from impacts of unusual shocks in the last ten years.
  • Identify occurrence of shocks that might have positively or negatively affected the area.
  • Assess if the shocks resulted in exceptional food insecurity conditions, and if so, for how long the effects were felt.
  • Identify if any structural changes affected the area.

Step 4: Analyse evidence

Purpose: To analyse evidence by following the IPC Analytical Framework and Reference Table considering the local context and evidence reliability score, including reference to historical trends and socio-economic differences.

Approach overview:

  • Write evidence statements identifying the current levels of key indicators and linking current outcomes and conditions to IPC levels, context, historical trends and other relevant analysis such as specific socio-economic groups and gender inequalities. Consider the other four protocols for Function 2 (i.e. use of the Analytical Framework, Reference Table, reliability scores and key parameters) as well as the local context when writing statements. 
  • Include source of information, linking all evidence statements to the references specified in Step 2. 
  • Assess reliability scores of all evidence (see Table 28) and assess if evidence that does not reach R1 should be included in the analysis for contextualization and explanation.
  • Provide conclusions for each food security element , including reference to evidence and critical reasoning as relevant, for example:
    • Food security contributing factors:
  • Hazards and vulnerability: Assess the key usual hazards and unusual hazards and vulnerabilities that likely limit consistent food security. Include available evidence on vulnerability, such as livelihood strategies, livelihood assets (financial, physical, human, social and natural) and policies, institutions and processes. Also include evidence and analysis on usual and unusual shocks that impact the analysis area. Identify key drivers of chronic food insecurity.
  • Food availability, access, household utilization and stability: Include evidence and analysis statements on typical food availability (e.g. levels of food production, functioning of markets and transportation networks, imports and food movements); food access (e.g. ability of households to obtain food, as a function of physical, financial and social access); household food utilization (e.g. access to safe water, food preparation, cooking, storage, and care practices); and stability (e.g. considering typical and seasonal stability and how stability affects each food security dimension). Conclude to what extent each of the dimensions limits food security in the area.
    • Food security outcomes: 
  • Food consumption quality: Include relevant evidence on indicators included in the Reference Table (i.e. Starchy Staple Satio (SSR), Starchy Staples Expenditure Ratio (SSEXR, and share of children who meet the requirements for minimum dietary diversity). Also include indirect evidence (e.g. on the typical food groups consumed by households, seasonality aspects, and any inference of food consumption quality through evidence on contributing factors based on data available). Conclude on the indicative level based on the evidence and analysis conducted, and distribute the total population across the four severity levels based onthe analysis conducted on food consumption quality.
  • Food consumption quantity: Present relevant evidence on indicators included in the Reference Table (e.g. FCS, HHS, HDDS and FIES) as well as other evidence relevant to the area being analysed and seasonality aspects together with inference of contributing factors (including, for example, number of meals or expected number of households with food gaps). Provide summary conclusions for quantity of food consumption and distribute the total population across the four severity levels based on the analysis conducted on food consumption quantity.
  • Nutrition: Include relevant evidence on stunting of children and on any indirect indicators (e.g. recurrent low weight for height/wasting of children, BMI of women, or evidence on micronutrient deficiencies). Also include any inference based on contributing factors. Prepare an indicative level classification for nutrition outcome, as well as population distribution across the different levels.

Step 5: Perform area classification and population estimations

Purpose: To provide a critical review of supporting and contradictory evidence used to arrive at level classification and estimation of populations.

Approach overview:

  • Use convergence of evidence to conclude on level classification based on all relevant supporting and contradictory evidence. Area classification should be carried out based on the chronic food insecurity conditions of the worst-off (at least) 20 percent of the population. The classification is performed through convergence of evidence, where analysts consider the whole body of evidence, including evidence on outcomes, contributing factors and context.  Only evidence that is relevant to chronic food insecurity should be used for classification. Evidence on chronic malnutrition is considered to support distribution of households among the four severity levels due to likely common key underlying drivers. For a discussion on convergence of evidence and population estimations, see associated guidance in Box 59 and in Resources of the IPC Technical Manual Version 3.0.
  • Conclude on the final classification by adding a critical rationale for area classification, summarizing key supporting and contradictory evidence in support of area classification into a short text (Box 60). The final conclusion has to provide an overall view of the evidence used to support the classification and explore the situation through the IPC Food Security Analytical Framework, encompassing the food security elements and how they contribute to the final decision taken on the classification. As much as possible, the conclusion should also mention which household groups are the most affected. In simple terms, the summary conclusion has to describe the storyline behind the classification and reflect the group discussion and rationale for the conclusion. If carrying out a supplementary HAG-based analysis, provide also indicative classification of each HAG.
  • Distribute the population of households in each level by converging the body of evidence as described in Step 3. Population should be estimated for IPC levels by taking into account both contributing factors and outcomes, and considering direct and indirect evidence, including inferences from contributing factors for outcomes and locally specific indicators (Box 61). Analysis of direct evidence, considering the context, is usually the most useful type of evidence for population estimates, as the prevalence of households in each category as per the Reference Table allows the distribution of households across the four severity levels. For example, when estimating the population in Level 4, it is more helpful to analysts to know that 40 percent of women have a MDD-W that is less than five food groups, and 5 percent have HDDS of four, and 10 percent have HDDS of five to six rather than to know that the poorest households depend on rainfed agriculture, that crisis recurs on average every four years, and that access to markets is restricted. Nevertheless, evidence on indirect and contributing factors is helpful when used for inference to contextualize the estimates and to ascertain or contradict the results from direct evidence. It is also recommended that a rationale be provided for the population estimates when feasible.
  • Assign evidence levels of analysis (*, **, ***) by counting the number of pieces of evidence used for food consumption quality and quantity, and nutrition outcomes and other supporting evidence on contributing factors or outcomes.

Step 6:  Identify key drivers

Purpose: To enable decision-makers to identify key factors driving existing levels of chronic food insecurity so that action can be more strategically planned. 

Approach overview:

  • Identify key drivers of chronic food insecurity, including reference to a possible recurrence of acute shocks, such as drought or conflict, as well as ongoing conditions and high vulnerability to shocks, such as poverty levels, lack of diversified income, heavy reliance on rainfed agriculture and harmful policies.
  • Identify individual drivers by looking at the entity of evidence on livelihood assets (human, social, natural, financial and physical capital) and policies, institutions and processes, and assessing which factors belonging to different capitals and policies, institutions and processes are likely to be the key drivers of chronic food insecurity in the area. 

Step 7:  Identify limiting factors

Purpose: To enable decision-makers to identify limiting dimensions of food security so that the response can target areas of interventions (availability, access, utilization and stability).

Approach overview: 

  • Identify for each dimension to what extent the dimension limits food security, including reference to evidence on food availability, access, utilization and stability (Box 62). Refer to key evidence used in Step 4.