Protocol 2.6: Methodically document evidence and analysis, and provide them upon request

The IPC Acute Malnutrition Analysis Worksheet supports methodical, transparent and consistent evidence-based analysis by taking the analysis through the IPC Acute Malnutrition Analytical Framework and linking evidence to the IPC Acute Malnutrition Reference Table. The Worksheet is a major advantage to analysis and, although not mandatory, is highly recommended.

The IPC Acute Malnutrition Analysis Worksheet consists in 11 steps (Box 87). While Steps 1 and 2 are applied to both current as well as Projection classifications, Steps 3 to 8 are only applicable for Current classifications, and Steps 9 to 11 are applicable only for Projections. If multiple projection classifications are carried out, Steps 9 to 11 should be repeated.

Procedures for completing the Worksheet are briefly described below. It is highly advisable that parts of the Worksheet, especially Steps 1 and 2 and optimally also Steps 3 and 5, are prepared before the analysis workshops.

Step 1: Context and analysis parameters

Purpose: To introduce the characteristics of the area and population to allow for contextualization of evidence.

Approach overview:

  • Decide on the spatial extent of the analysis area. A single phase classification will be determined for this area. The determination of the analysis area can be informed by, but not limited to, units such as administrative boundaries, livelihood zones, hazard zones, market catchment zones, and others. The IPC is adaptable and applicable to any spatial size, and the spatial area of the classification can vary widely. The IPC analysts must determine the spatial extent of the analysis area, depending on the situation and the needs of decision-makers, as well as the availability of evidence and feasibility of the number of areas being classified. In general, the analysis area should be as homogeneous as possible with regard to likely Acute Malnutrition outcomes and causes.
  • Decide on time periods of analysis. The analysis is a snapshot of the current or projected Acute Malnutrition situation and each analysis has a validity period determined by the analysts. The validity period can be as short as a few weeks or as long as a few months or even up to a year. However, the existing (current) or expected (projection) Acute Malnutrition situation should not significantly change during the validity period of the analysis. If the Acute Malnutrition situation does change during the validity period of the analysis, analysts can either conduct a new analysis or update the projection analysis, depending on how significant the change has been and what new evidence is available. Decision-makers often require information on expected conditions many months in advance for planning purposes. Multiple projections can be prepared, each with its own validity period. In the case of multiple projections, Steps 9, 10 and 11 of the IPC Acute Malnutrition Analysis Worksheets would need to be repeated for each new projection.
  • Provide a brief description and population characteristics of the area, including relevant information to be used in contextualizing evidence. Important aspects may include population subgroups such as crop and livestock farmers, common livelihood strategies employed by households in the area, seasonality patterns, cultural habits and economic environment. Add population figures (both total and under five population in the area), specifying sources and reference years. If applicable, use projected populations if significant population movement is expected.
  • Identify if the analysis area experienced IPC Acute Malnutrition Phase 3 “Serious” or more severe in three years over the previous ten years. If the IPC Acute Malnutrition analysis has not been conducted in enough years to determine this, either use an equivalent classification system, or highlight that a recurrence of crisis cannot be identified.

Step 2: References for evidence

Purpose: To help organize wide-ranging data from multiple sources for ease of access and reference, and provide a tool for supporting documentation of the evaluation of reliability of evidence.

Approach overview:

  • Provide references for all evidence to be reviewed in analysis, including identification of sources and dates of evidence collection. If desired for easier reference during the analysis, include the actual evidence (e.g. graph, text, figures).
  • Optimally, provide a note on methods of data collection to support the assessment of the reliability score.

Step 3: Analysis of outcomes (current classifications)

Purpose: To analyse evidence following the IPC Acute Malnutrition Analytical Framework and Reference Table, considering the local context and reliability score, including reference to historical trends.

Approach overview:

  • Include information on all outcome indicators (i.e. GAM based on WHZ and GAM based on MUAC) that meet IPC Acute Malnutrition reliability criteria, identifying current levels and linking current conditions to IPC phases, context and historical trends.
  • Include source of information, linking all evidence to the reference specified in Step 2.
  • Assign reliability scores for all evidence.

Step 4: Analysis of contributing factors and other issues (current classifications)

Purpose: To analyse evidence on contributing factors to Acute Malnutrition as well as other issues of concern so as to identify major contributing factors to Acute Malnutrition in the analysis area.

Approach overview:

Provide evidence and critical reasoning for all contributing factors for which evidence is available and relevant to Acute Malnutrition, considering the following guidance:

  • Preferably use current estimates for indicators affected by seasonality, such as diseases. If unavailable, analysts may rely on a critical analysis of conditions during the same season in the previous years and inferred estimates based on estimates seen recently, but not necessarily from the same season.
  • For slow-changing indicators such as exclusive breastfeeding, information from the past three to five years can be used with contextualization and justification of evidence. The maximum age of the evidence will depend on how stable the condition is.
  • Information on contributing factors from higher administrative levels can be extrapolated to lower administrative levels with documented justification. Historical trends of contributing factors should be considered, and any increasing trends should be carefully reviewed and their impact on Acute Malnutrition analysed.
  • Add additional indicators as relevant. The IPC Acute Malnutrition analysis worksheets provide a list of standard indicators to look at under the contributing factors, but analysts may need to consider other indicators depending on their context; for example, dengue may need to be considered under diseases in some contexts.

Other issues: Other important issues (e.g. mortality, anaemia, vitamin A deficiency) that are not necessarily directly/strongly related to Acute Malnutrition but are important considerations should be taken into account and highlighted in the IPC Acute Malnutrition products as necessary.

Step 5: Phase classification (current)

Purpose: To conclude on phase classification and provide the critical reasoning based on supporting and contradictory evidence used to arrive at phase conclusion (Box 88).

Approach overview:

  • Conclude on phase classification for the current period based on all supporting and contradictory evidence as relevant.
  • If a piece of R1- level evidence on GAM based on MUAC is used to arrive at a final classification, convergence of evidence should be used (see Box 74).
  • If GAM based on MUAC is used to determine the IPC Acute Malnutrition phase of an area, the historical relationship between WHZ and MUAC as well as the contributing factors should be taken into account when the phase is determined.
  • Provide justification for phase classification, particularly when convergence of evidence is used to arrive at the phase.
  • Identify evidence levels of analysis, by identifying the type of indicator (GAM based on WHZ or GAM based on MUAC), source of information (e.g. surveys, sentinel sites, historical data) and number of pieces of evidence (for contributing factors) used in the classification. (See Table 39 for criteria for evidence level.)
  • Calculate the total number of children acutely malnourished and in need of treatment. The calculation of the total number of children acutely malnourished and in need of treatment (B) should include the internationally agreed formula (B=NPK, where N = total number of children under 5 in the unit of analysis, P = estimated prevalence of GAM for the unit of analysis, and K = correction factor of 2.6). Where possible and where data are available, Technical Working Groups should work with Country Nutrition Clusters/Sectors to assess the added value of using the combined estimates of GAM for P (i.e. taking into account all forms of Acute Malnutrition).

Step 6: Key drivers

Purpose: To highlight the key drivers so that decision-makers are aware of the key factors triggering the crisis and action can be more strategically planned.

Approach overview:

List the key drivers of Acute Malnutrition, not only the immediate and underlying causes, but also include acute shocks, such as drought and conflict.

Box 88: Considerations for convergence of evidence in Acute Malnutrition classification

Convergence of evidence, taking into account contributing factors and historical data on Acute Malnutrition, is required when estimates of historical Acute MalnutritionGAM based on WHZ, or GAM based on WHZ from similar areas, or evidence collected within the six months preceding the time of analysis (but not from the same season) are used to classify areas. Additionally, historical data on the relationship between GAM based on WHZ, and GAM based on MUAC in the area of analysis are required when classification is performed on GAM based on MUAC.

During the convergence of evidence, analysts first need to gather information on the following indicators:

  • historical GAM prevalence (based on MUAC and WHZ) and their relationship;
  • the relationship between MUAC and WHZ in the area of analysis (or at the regional level, livelihood zone level, etc. if data at the unit of analysis are unavailable);
  • food intake indicators, e.g. minimum dietary diversity, minimum meal frequency and minimum acceptable diet;
  • diseases (i.e. diarrhoea, malaria/fever and acute respiratory infection) and disease outbreaks;
  • health system functioning (i.e. routine immunization coverage);
  • health-seeking behaviour;
  • coverage of the community management of Acute Malnutrition programme;
  • outcome of the IPC Acute Food Insecurityanalysis.

Both current and historical/trend data should be gathered; the historical data should come from the same season of analysis. At least two of the above indicators must be available to carry out the convergence of evidence, although more would strengthen the analysis. Ideally, information on these indicators should come from representative surveys. However, other source such as the Health Management Information System (for diseases) can also be used. In terms of the community management of Acute Malnutrition coverage data, coverage surveys using acceptable methods should ideally be used. However, other methods of estimating coverage can also be used as proxy. Analysts would then look at the current as well as the historical/trend data on the contributing factors and determine if these factors have been stable, deteriorating or improving.

Example 1: Consider an area with 11 percent GAM based on WHZ from re-analysed survey data (from a high administrative unit). According to the IPC Acute Malnutrition Reference Table, this level of prevalence indicates IPC Acute Malnutrition Phase 3. As per a health assessment, about 35 percent of children in the area are affected by diarrhoea during the current season of analysis. The historical data on diarrhoea for the same area show that diarrhoea prevalence has always been around 30 percent for the area in the past three years. The IPC Acute Food Insecurity analysis has always placed the area into Phase 3 in the past two years, and the current IPC Acute Food Insecurity analysis indicates the same situation. There has been no major change in the health or the community management of Acute Malnutritioncoverage for the area. In this case, it is reasonable to assume that all main contributing factors remained stable during the current season of analysis.

Analysts would then look at the available historical data on Acute Malnutrition (i.e. GAM based on WHZ) for the area. Assume that according to the historical data, other than being in Phase 2 once two years ago, the area has always remained in Phase 3 in the same season in the past five years. Considering both current as well as historical data on both contributing factors and outcome indicators, in this case it is reasonable to classify the area as Phase 3.

Example 2: Consider that the same area has only GAM based on MUAC data from an exhaustive screening (8.3 percent) and assume that the contributing factors are described as above. In this case, analysts would look at the historical data on the relationship between GAM based on WHZ and GAM based on MUAC. Assume that the relationship shows the following:













It is evident from the above that the WHZ-based prevalence is always higher than MUAC prevalence in this area; additionally, the upper bound of the phase (according to the GAM based on MUAC) has always corresponded with the GAM based on the WHZ phase - i.e. when the area was in Phase 4 based on WHZ, it corresponded with the upper Phase of MUAC; the same applied when the area was in Phase 3 based on WHZ). Therefore, given that there are no changes in the contributing factors, it is reasonable to assume that with the GAM prevalence of 8.3 percent, the area is likely to be in Phase 3.

Step 7: Limitations of the analysis

Purpose: To help provide information on the limitations faced by analysts during the analysis.

Approach overview:

Document all limitations (not only data, but also analytical limitations) faced during the analysis.

Step 8: Priory response objectives

Purpose: To highlight to decision-makers and partners the key response objectives needed to address the situation at hand.

Approach overview:

  • Identify and document the key priority response objectives based on the analysis. For example, if the dietary intake is extremely poor (e.g. 5 percent) among children, this calls for an urgent response and should be highlighted.
  • Highlight the magnitude of the Acute Malnutrition problem (as identified in Step 5 above) in order to help trigger appropriate response.

Step 9: Analysis of evidence on contributing factors and other issues (projection classification)

Purpose: To determine the potential (most likely) changes in the contributing factors in order to identify their possible impact on outcome indicators so that potential changes in the classification can be determined. In the projection analysis, the IPC Acute Malnutrition tries to determine the most likely evolution ofGAMAcute Malnutrition. Since Acute Malnutrition is an outcome of various contributing factors, the potential changes in contributing factors are first looked at in this Step 9; that is, based on the historical trends and seasonality, etc., the most likely changes in each of the contributing factors to Acute Malnutrition are first determined. Based on the changes in the contributing factors, the changes in outcome (i.e. the GAMAcute Malnutrition) are then determined (in Step  10).

Approach overview:

  • Consider the most likely change. Indicate how the indicator is likely to change in the projection period – i.e. if is it likely to improve, deteriorate, or to stay the same.
  • Provide explanation for the most likely change, taking into account historical trend data, key assumptions for the projection period, seasonality changes (where applicable), etc. Explain how the likely change was determined.

Step 10: Analysis of outcomes (Projection classification)

Purpose: To provide early warning information for decision-makers by highlighting the potential changes in the Acute Malnutrition situation.

Approach overview:

  • Conclude on phase classification for the projected period based on the review of all contributing factors and their potential changes in the projection period. (Note: Acute Malnutrition is an outcome of a range of contributing factors; the outcome indicators are determined by predicting the changes in the contributing factors.)
  • Provide the rationale for the phase classification.

Step 11: Risk factors to monitor

Purpose: To identify triggers for analysis updates and validity of projections.

Approach overview:

Identify risk factors to monitor: Consider risk factors that could raise Acute Malnutrition during the projection period and thus need to be monitored against assumed evolution included in Step 8