103. Humanitarian Food Assistance (HFA) Needs

103. Humanitarian Food Assistance (HFA) Needs

VERSION

V1.0 - 2026.03 — NEW

INDICATOR CODE

103

TECHNICAL OWNER

PRG-R

INDICATOR TYPE

Country Level Outcome Indicator

INDICATOR CLASSIFICATION

Mandatory

INDICATOR SCOPE

Programme specific

APPLICABILITY

Note: This is the only indicator in the 2026–29 CRF whose selection is not based on sub‑activities.

Mandatory:

The selection of this indicator is mandatory for:

1. CSP activities under SO2 that support people who experienced recurring or protracted acute food insecurity.

   OR

2. CSP activities under SO2 that select the integrated resilience marker. These are activities that:

   • Aim to strengthen capacities of governments, communities, and people to deal with shocks, with the objective to mitigate and avert future humanitarian needs – and ultimately reduce reliance on assistance.

     AND

   • Focus on geographic areas and communities that experience protracted or recurrent acute food insecurity, prioritizing people whose food security and nutrition are most impacted by shocks.

This marker defines integrated resilience programmes as programmes that include a minimum of two complementary, multi-sectoral, and multi-year sub-activities that support the same beneficiaries. Programmes in this definition can be implemented directly by WFP or in collaboration with other agencies and partners.

Only CSP activities using the integrated resilience marker are required to report on follow-ups of this indicator. All other CSP activities using this indicator are required to report on baseline figures for each supported target group. The latter will be used to calculate the corporate outcome indicator “Percentage of people supported by WFP through resilience-building activities who experienced recurring or protracted acute food insecurity”.

UNIT OF MEASUREMENT & ANALYSIS

Percentage of households in need of humanitarian food assistance

DEFINITION

The HFA Needs indicator measures the proportion of households whose food security status necessitates humanitarian food assistance based on results of three food security indicators: Food Consumption Score (FCS), Reduced Coping Strategies Index (rCSI), and Livelihood Coping Strategies for Food Security (LCS-FS).

Below are some key definitions for this indicator:

Humanitarian Food Assistance Needs: This refers to the level of food insecurity that necessitates external humanitarian support. Households are classified as needing humanitarian food assistance if their food security status falls below acceptable thresholds, which indicates inadequate access to sufficient and nutritious food. Those falling into IPC-informed phases 3 (Crisis) and 4 (Emergency) are classified as in need of HFA.

Food Security Status: This describes the degree to which a household has access to sufficient, safe, and nutritious food that meets its dietary needs. It is assessed using food security indicators (FCS, rCSI, and LCS-FS) to understand whether a household can meet its food needs independently or requires external aid.

IPC-informed classification: The IPC-informed classification refers to an adaptation of the Integrated Food Security Phase Classification (IPC) system, used to categorize food insecurity into different phases. It helps to estimate food security status at a more localized level (e.g., households or communities) while maintaining consistency with IPC principles. This classification uses similar thresholds but is tailored for household-level assessments.

IPC Phase 3 crisis: In this phase, food insecurity is acute, with households unable to meet their minimum food requirements through normal coping mechanisms. Humanitarian assistance is needed to prevent further deterioration.

IPC Phase 4 emergency: This is a more severe phase, where food insecurity leads to emergency levels of malnutrition or mortality. Immediate humanitarian assistance is required.

Food Consumption Score (FCS): The FCS is a composite score based on dietary diversity, food consumption frequency, and the nutritional value of different food groups. It was developed by WFP to assess household food consumption, with flexibility to account for varying needs and contexts. It serves as a good proxy for the current food security status and is highly correlated with other food security proxy indicators.

Reduced Coping Strategies Index (rCSI): The rCSI measures the level of stress a household faces due to food shortages. It combines the frequency and severity of coping strategies that households adopt in response to a lack of food or money. The rCSI is impacted by short-term needs, combined with seasonality. In sudden periods of food shortfalls (and at the onset of emergencies) households tend to adjust their food consumption reflecting consumption-based coping.

Livelihood Coping Strategies for Food Security (LCS-FS): The LCS-FS indicator assesses long-term coping mechanisms that households employ in response to food insecurity. It helps to assess households’ coping capacity and productive capacities in the longer-term, as well as the future impact on access to food for households. It is also a powerful indicator to assess hardship and deprivations faced by households during new emergencies and protracted crises.

Integrated programmes: For this indicator, integrated programmes are defined as programmes including a minimum of two complementary, multi-sectoral, and multi-year activities that support the same beneficiaries. Programmes in this definition can be implemented directly by WFP or in collaboration with other agencies and partners. Programmes in this definition include but are not limited to climate and resilience programmes marked in the CRF as sub-activities/activity tags (FFA, FFT, CAP, SMS, SLA, MAI, MMI and CAR).

RATIONALE

The HFA Needs indicator measures household reliance on humanitarian food assistance by classifying food security status using an IPC-informed matrix of three core indicators: the Food Consumption Score (FCS), the Reduced Coping Strategies Index (rCSI), and the Livelihood Coping Strategies for Food Security (LCS-FS).

Households are classified into four IPC-informed categories (None, Stressed, Crisis, Emergency) based on a combination of these indicators. Those falling into IPC-informed phases 3 (Crisis) and 4 (Emergency) are classified as in need of HFA. This approach aims to maintain consistency with IPC guidelines while acknowledging that the IPC system and its scales were designed for estimating acute food insecurity on a larger scale. Thus, the interpretation of the HFA must be contextualized with information on the programme design, exposure to shocks, characteristics of target groups, etc.

This classification allows WFP to systematically track the proportion of households requiring emergency assistance and assess trends over time.

The indicator is grounded in WFP’s resilience-building approach, which operates on the principle that enhancing communities' and countries' ability to withstand recurrent shocks and stressors can significantly reduce the long-term costs associated with repeated crises. These costs extend beyond immediate humanitarian needs to include loss of lives and livelihoods, economic disruptions at national and regional levels, and the unsustainable financial burden of continually providing humanitarian food assistance to the same populations year after year. Assessing reductions in HFA needs over time provides critical evidence on the extent to which WFP resilience programming mitigates these impacts.

DATA COLLECTION TOOL

The main data sources for this indicator are representative face-to face baseline and outcome monitoring surveys (or Post Distribution Monitoring (PDM)) conducted at household level. For multi-year interventions panel data is needed to be able to track changes over time and assess long-term resilience impacts. When this is not possible, it is required to collect baseline data and at least one follow-up value. To assess the sustainability of these results in multiyear interventions the last follow-up should be collected when the target beneficiaries do not longer receive CBT of food transfers.

While the information is quantitative and obtained through a household survey, it may be complemented and contextualized by qualitative information obtained from the respondents themselves.

This XLSForm will help to design forms using Excel, which can be converted to a MoDa/ODK form, data collection software. The form was generated by selecting the sub-modules of:

• Food Consumption Score (FCS),

• Consumption-based Coping Strategy Index (rCSI), and

• Livelihood Coping Strategies for Food Security (LCS-FS)

in the modules Food Consumption and Coping Strategies in WFP Survey Designer.

To allow for a contextualized interpretation of these results, the form also includes basic questions on shocks, assistance received and household characteristics.

The indicator calculation follows the standard way of calculating and standard classifications of the Food Consumption Score (FCS), Consumption-based Coping Strategy Index (rCSI), and Livelihood Coping Strategies for Food Security (LCS-FS).

SAMPLING REQUIREMENTS

The sampling approach for the HFA Need indicator follows the general principles of PDMs or monitoring surveys, ensuring that data is representative of WFP resilience programming. Since this indicator is derived from FCS, rCSI, and LCS-FS, all three indicators must be collected from the same households within a single data collection round.

To ensure meaningful trend analysis and programmatic insights, the following guidelines should be applied:

• Sample representativeness:

  • The sample should be representative of CSP activities enhancing communities' ability to withstand recurrent weather related and other shocks and stressors.

  • While in multi-year interventions integrated programmes can be combined, sequenced or layered overtime, it is important that the sample is homogeneous in terms of the assistance provided. Likewise, if the last follow-up is done when transfers are no longer part of the programme design, the HFA results could be used to confirm that the target group is no longer in need of humanitarian food assistance. To the extent possible, sampling should include an equal number of men and women respondents to account for gender-specific differences in food security and coping strategies.

• Tracking changes over time:

  • Panel sampling (following the same households over multiple rounds) is needed to measure changes in HFA Needs over time.

Whenever feasible, the use of comparison groups (e.g., groups receiving different types of assistance or the same assistance at different time) is encouraged to strengthen causal analysis.

Detailed guidance on sampling options is available here.

INDICATOR CALCULATION FOR REPORTING

This indicator is calculated by using the following steps:

I. Compute FCS, rCSI, and LCS-FS scores for surveyed households.

To calculate the indicator, the standard food security monitoring module must include FCS, rCSI, and LCS-FS submodules.

FCS

The FCS aggregates household-level data on the diversity and frequency of food groups consumed over the previous seven days. These food groups are then weighted based on their relative nutritional value. The FCS provides insights into the adequacy of food consumption and helps assess food security. It considers both the variety and quantity of food consumed by households. The FCS is further grouped into the following food consumption categories¹:

• Poor: <= 28 FCS

• Borderline: 28.5 to 42 FCS

• Acceptable: > 42 FCS

Detailed information on the calculation of the Food Consumption Score indicator can be found here.

rCSI

The rCSI measures the hardship faced by households due to food shortages. Specifically, it assesses the frequency and severity of coping behaviors related to food consumption in the seven days preceding a household survey. Households engage in coping strategies when they lack sufficient food or money to purchase food. A higher rCSI score indicates more frequent and extreme negative coping strategies. The minimum possible rCSI value is 0, while the maximum is 56 and it is grouped into the following food coping strategy categories:

• Food secure (corresponding to IPC Phase 1): 0-3 rCSI

• Stressed (corresponding to IPC Phase 2): 4-18 rCSI

• Crisis and Emergency (corresponding to IPC Phase 3 and above): >=19 rCSI

Detailed information on the calculation of the rCSI indicator can be found here.

LCS-FS

The LCS-FS is designed to understand households’ medium and longer-term coping capacity in response to food scarcity or lack of funds to purchase food. It assesses their ability to overcome challenges in the future. The indicator is derived from a series of questions related to livelihood stress and asset depletion strategies employed by households to cope with food shortages.

The LCS-FS indicator is calculated as categorical variable with four groups in which households are allocated:

• Households not applying coping strategies due to lack of food

• Households applying stress coping strategies due to lack of food

• Households applying crisis coping strategies due to lack of food

• Households applying emergency strategies due to lack of food

Detailed information on the calculation of the LCS-FS indicator can be found here.

NOTE: The classification in the following steps is an IPC‑informed proxy and does not replace the IPC analytical framework.

II. Classify households into IPC-informed phases using a matrix-based approach (Table 1).

Since we have:

• 3 categories of FCS (Acceptable, Borderline, Poor)

• 3 categories of rCSI (Food Secure, Stressed, Crisis and Emergency)

• 4 categories of LCS-FS (No strategies, Stress, Crisis, Emergency),

we can calculate the total number of possible unique combinations: 3 × 3 × 4 = 36

Each combination corresponds to a unique “food consumption cell” with values from 1 to 36.

Thus, we first create a “FC cell” variable representing a unique classification of each combination of the three indicators. Each household is assigned to one of 36 unique food security cells determined by its specific combination of FCS, rCSI, and LCS-FS categories.

Table 1: Combined matrix FCS, rCSI, LCS-FS, adapted from FEWS Net methodology

Note: the numbers in the table correspond to a “cell” or one each of the 36 possible combinations of the three indicators, based on their respective groupings.

Once the FC_cell values are created, they are further classified into IPC-informed phases, which group different food security conditions:

• IPC Phase 1 (Food Secure) → Minimal food insecurity:

• FC_cell = 1, 5

• IPC Phase 2 (Stressed) → Households experiencing some food insecurity but not yet in crisis:

• FC_cell = 2, 6, 9, 10, 13, 14, 17, 18, 21, 25, 29

• IPC Phase 3 (Crisis) → Households facing significant food shortages:

• FC_cell = 3, 4, 7, 15, 16, 19, 22, 26, 27, 30, 33, 34

• IPC Phase 4 (Emergency) → Households experiencing extreme food insecurity:

• FC_cell = 8, 11, 12, 20, 23, 24, 28, 31, 32, 35, 36

This classification helps in identifying households needing immediate assistance.

III. Calculate the proportion of households in each IPC phase.

To calculate the proportion of households in IPC-informed Phases, follow these steps:

Step 1: Count the number of households assigned to the FC_cells that correspond to each of the IPC-informed phases

Step 2: Calculate the total number of households in your sample

Step 3: Compute the percentage (step 1 / step 2 ) for each IPC-informed phase

This calculation provides one percentage for each IPC-informed phase that if collected in multiple data collection rounds can be summarized as follows:

Table 2: Example of percentage of households in IPC-informed phases 1 to 4

Note: the percentages in Table 2 have been calculated using the R script provided below and sample data available here.

Since IPC Phase 3 & 4 households are considered in food crisis or emergency, their sum also represents the percentage of households in need of Humanitarian Food Assistance (HFA). Households in IPC Phase 3 (Crisis) and Phase 4 (Emergency) face acute food deficits or livelihood gaps that they cannot address without external support. For this reason, the combined proportion of households in IPC 3 and 4 is used as a proxy for those requiring Humanitarian Food Assistance (HFA).

Thus, the percentage of households in IPC Phase 3 & 4 = Percentage of households in need of HFA.

Guidance on how to calculate the indicator in R is available here.

DATA ENTRY AND DISAGGREGATION IN CORPORATE SYSTEMS

Data is recorded in the logframe module in COMET. One number is entered for every category.

Mandatory

Cohort/target group desegregation is mandatory.

Panel sampling and the use of control groups are strongly recommended. Therefore, it is particularly important when entering information into COMET, that the sampling size and sampling frame of each data collection exercise are entered into the corresponding COMET field of the outcome data entry module.

For each follow-up it is also required to specify the type of applicable weather-related shocks (multiple choice between Floods, Drought, Storm/Cyclone, Heat Wave, Wildfire, other) or other shocks to which the target groups were exposed in the previous year to the data collection round. In multi-year integrated resilience programmes, it is also required to keep track of the applicable and changing sub-activities (activity tags) supporting the same group of beneficiaries and/or changes in the transfer modalities between follow-ups.

For this indicator's purpose, a cohort is defined as a group of beneficiaries that minimally share characteristics such as receiving the same type of WFP assistance/support and during the same period. They can also share other characteristics such as geographic area, vulnerability level, transfer modality, residence status, donor, or cooperating partner.

The table below shows the main information to be entered into COMET for the same cohort/target group with multiple data collection rounds.

When reporting on baselines and follow-ups of this indicator, values for all IPC phases will be required in COMET. Zero is considered a valid entry but this information to be consistent COMET should check that the sum of all IPC phases should always be 100%.

Recommended disaggregation (when sample size allows) for reporting outside of COMET:

• Beneficiaries/non-beneficiaries (when relevant)

• Sex of household head

• Admin and livelihood zone

Important data entry options: Since SO2 CSP activities commonly combine, sequence and/or layer multiple sub-activities to support the same cohort/target group, this indicator can be reported with all applicable sub-activities. COs are requested to use multiple sub-activities to report on this indicator when its results should be presented as the outcome of multiple sub-activities supporting the same target group.

BASELINE

Baseline values should be established within three months before and after the start date of the activity implementation. However, it is highly preferable to collect baseline values before the start of the activity implementation.

TARGET SETTING

Annual targets:

The annual target for HFA Needs should aim for a reduction in the percentage of households classified as needing humanitarian food assistance (IPC-informed phases 3 and 4). At a minimum, the annual target should be equal to or lower than the most recent follow-up value, or the baseline figure if no previous follow-up data exists.

The aim of the target can vary depending on the specific context and situation:

• Improvement: The goal could be to significantly reduce the percentage of households in need of humanitarian food assistance, leading to a measurable improvement over time.

• Maintenance: In some cases, the objective may be to maintain the current level of humanitarian food assistance needs, particularly in situations where households are relatively stable or where external factors prevent significant improvement. The same occurs in highly volatile or shock-prone areas where the primary aim might be to avoid any increase in the need for humanitarian food assistance. This could be a key focus where external shocks or limited programme capacity make further reductions challenging.

While a downward trend in HFA Needs is expected over time as resilience-building efforts take effect, targets should be interpreted in the context of external shocks and stressors that may impact food security and programme implementation. Unexpected events, such as climatic shocks, economic downturns, or interruptions in assistance, may temporarily slow or reverse improvements, and this should be accounted for when setting and reviewing targets.

End of CSP target:

The end-of-CSP target should be determined at the country level, considering baseline figures, programme context, CSP duration, and the design of interventions (e.g., transfer modality, transfer value, duration of assistance, and complementary activities).

For multi-year interventions targeting the same population, a progressive decline in the proportion of households in need of HFA is expected. In particular, the percentage of households classified as IPC-informed phase 3 (Crisis) and phase 4 (Emergency) should decrease over the CSP cycle, reflecting strengthened resilience and reduced dependency on humanitarian food assistance.

However, context-specific factors must be considered when setting final targets, particularly in highly shock-prone environments where fluctuations in food security are more pronounced.

FREQUENCY OF DATA COLLECTION

At least one comprehensive household survey per year, repeated at the same time of the year or season to ensure comparability across surveys. The Country Office can adapt the data collection frequency to align with planned PDM or other outcome surveys considering that:

For multi-year interventions, panel data is required with at least one data collection round per year.

INTERPRETATION

A high proportion of households in need of humanitarian food assistance indicates significant food insecurity. Ideally, the indicator should decline over time as resilience programming takes effect. However, fluctuations may occur over time due to seasonal variations or external shocks.

When interpreting results, it is important to consider:

• The scale, duration and programme design (transfer modality, integrated sub-activities (activity tags), etc...) of WFP interventions.

• The sampling size and sampling frame of each round of data collection.

• The initial food security conditions in target areas.

• Results of food security indicators.

• Type and magnitude of shocks such as conflict, climate events, or economic disruptions.

Since the HFA Need indicator is derived from three standard food security indicators – FCS, rCSI, and LCS-FS – it is crucial to compare trends in these individual indicators with the overall HFA Need results. In some cases, one or more of the individual indicators may show improvements over time, but this may not immediately translate into a reduction in HFA needs. The HFA Need indicator reflects a matrix of these three indicators, and for this reason it provides a composite picture of household vulnerability. However, its trends may not always move in the same direction as the individual components. A discrepancy between the HFA Need indicator and its underlying measures can indicate complex resilience dynamics, where households experience improvements in one aspect of food security while remaining vulnerable in others.

Tracking the HFA Needs indicator over time enables a nuanced understanding of resilience dynamics and programme effectiveness in different contexts. When interpreting the results, the relationship between programme participation and the observed HFA Needs should be examined while controlling for shocks and other influential factors that influence how a household copes with shocks and stressors.

In multi-year interventions, if the last follow-up is collected when transfers are no longer part of the programme design, the HFA results could be used to confirm that the target group is no longer in need of humanitarian food assistance, which significantly reduces the long-term costs associated with repeated crises. The reduction of cost can be associated to the annual cost of providing food assistance to this target group when it is no longer required.

The interpretation of HFA results of multi-year integrated resilience programmes should always refer when applicable to expected/unexpected changing conditions over time such as the occurrence of shocks or changes in support provided to the same target group (e.g. sub-activities or transfer modalities). The table below shows an example of how this information can be summarized.

REPORTING EXAMPLE(S)

The following examples illustrate how the HFA Needs indicator results can be presented:

• X% of households in targeted communities were classified as in need of humanitarian food assistance.

• Z% of surveyed households reported improvements in their need for humanitarian food assistance, moving from IPC-informed Phase 3 or 4 to IPC-informed Phase 2 or below from year X to year Y. While this suggests progress, the impact of external shocks or seasonal effects should be considered. For example, improvements during a post-harvest period may reflect seasonal changes rather than programme effects, so longer-term trends should also be monitored.

• Between [year X] and [year Y] post-harvest season, the percentage of households in IPC-informed Phase 3 or 4 decreased from A% to B%. This reduction should be contextualized by comparing it with previous years' trends, especially during similar seasonal periods. If the decrease is more substantial than usual, it may indicate positive programme impact, though further analysis of external shocks is needed to rule out other factors.

• HFA Needs remained consistently high (X%) between [year X] and [year Y] despite programme interventions. This could indicate that structural issues persist, and additional interventions may be needed. It is essential to assess whether resilience programming needs to be expanded or adjusted to address persistent vulnerabilities that external shocks and stressors may have exacerbated.

Country-specific examples:

The sum of IPC phases 3 and 4 in table 8 suggests that few households (7.3% percent) in the 2020 July/August lean season were in need of HFA. However, starting in the November/December 2020 post-harvest period through the July/August period, HFA Needs became more elevated, peaking at 80.4% percent of households in the 2021 July/August lean season. This dramatic shift reflects the impact of widespread shocks during that period – especially drought, crop failure, and price spikes – as also reflected in qualitative and quantitative shock monitoring data. The scale and speed of this shift highlight the critical importance of investing in early warning systems and anticipatory action, particularly when predictable seasonal stressors may be amplified by compounding shocks as in this specific case.

Following this peak, the proportion of households in need of HFA declined but remained worryingly high, standing at 37.3% in July/August 2022 and 41.0% in July/August 2023. While this suggests some degree of recovery, the persistence of high needs indicates that many households remain vulnerable and unable to fully recover between shocks. The data point to the necessity of resilience-building efforts that go beyond immediate food assistance. In particular, interventions during the lean season should be paired with support in the post-harvest period to help households build buffers — for instance, through income diversification, improved water access, or savings mechanisms — thereby reducing their exposure in future stress periods.

The data also reveal a strong seasonal pattern in food security outcomes. For example, while 64.2% of households were classified in IPC Phase 1 in November/December 2022, this share fell sharply to just 10.2% by July/August 2023. Such seasonal volatility underscores the importance of integrated, year-round programming. Food security gains achieved after harvest tend to erode during the lean season, suggesting that a more deliberate effort is needed to sustain progress across seasonal cycles.

Table 8: IPC-informed phase, Niger M&E survey data by round

Example from RBD study Estimating Averted Assistance through WFP’s Integrated Resilience Programme in the Sahel:

Figure 4 illustrates the evolution of food security among IRP beneficiaries in the Sahel from 2018/19 to 2022/23, highlighting both seasonal fluctuations and longer-term trends. Across all years, the proportion of food secure households consistently decreases during the lean season (LS) compared to the post-harvest (PH) period — a pattern that reflects the cyclical nature of food access in the region. Encouragingly, the data show an overall upward trend in food security during the post-harvest periods, rising from 69% in 2018/19 to 75% in 2022/23. This suggests that resilience-building interventions may be contributing to improved conditions following the harvest. However, the persistence of significant drops in food security during the lean seasons — with one-third of households still food insecure in 2022/23 — indicates that these gains remain precarious.

The data underscore the need for resilience programming to more systematically address seasonal vulnerabilities. While the post-harvest improvements are promising, the lean season continues to pose a major challenge. Programmes should therefore aim to strengthen year-round resilience by enhancing food storage, diversifying income sources, and supporting adaptive safety nets that can absorb shocks before they escalate. Additionally, timing and sequencing of interventions become critical: ensuring that support reaches households ahead of the lean season could prevent the erosion of post-harvest gains and reduce recurring cycles of need.

INDICATORS COLLECTED & ANALYSED AT THE SAME TIME

This indicator should be collected as part of periodic face-to-face household surveys that cover programme participation data and other outcome indicators including:

• 1. Food Consumption Score - FCS

• 3. Reduced Coping Strategies Index - rCSI

• 4. Livelihood Coping Strategies for Food Security - LCS-FS

COs must equally report on any other applicable indicator under strategic outcome 2 “Reduced needs and enhanced resilience to withstand shocks”. Any other applicable outcome indicator requiring a cross-sectional household survey could be collected at the same time.

COMPLEMENTARY QUALITATIVE RESEARCH

Complementing this indicator with qualitative data collection is highly recommended. Following analysis of the indicator data, Focus Group Discussions (FGD) or qualitative interviews can be organized to better understand communities’ perceptions of the shock experienced as well as of their resilience capacities, including how they have changed over time because of WFP’s activities.

Please refer to the latest version of the qualitative guide available here.

DECISIONS DATA CAN INFORM

The data derived from the HFA Needs indicator can inform a wide range of strategic and operational decisions, with distinct applications depending on whether the intervention is multi-year (trend analysis) or non-multi-year (situation analysis).

1. For multi-year interventions (trend analysis):

The HFA Need indicator allows to track trend in humanitarian food assistance needs over time, helping to assess the effectiveness of resilience-building efforts. By identifying which activities are most successful in reducing these needs, it can guide the refinement of long-term intervention strategies. The indicator also provides insights into changes in resilience, highlighting areas where progress is being made and where further action may be needed.

At policy level, the results can serve as evidence to advocate for continued or expanded resilience programming, demonstrating the impact of sustained interventions on reducing reliance on humanitarian assistance. The results can also help shape COs strategies and interventions to better respond to emerging vulnerabilities and trends over time, improving both the planning and monitoring of long-term programme impact.

2. For non-multi-year interventions (situation analysis)

In the context of non-multi-year interventions, the HFA Need indicator is not mandatory but can provide a snapshot of the current situation, offering insights into the immediate needs of the population. It is particularly useful for informing short-term decision-making, such as targeting beneficiaries, planning resource allocation, and identifying areas of vulnerability. Furthermore, results can be used to advocate for multi-year resilience programming by highlighting the limitations of short-term interventions in addressing the root causes of food assistance needs.

In both scenarios, this indicator supports external coordination with donors, governments, and partners by providing a clear understanding of the current state of food assistance needs and how interventions are addressing those needs. This can help strengthen stakeholder confidence and enhance collaboration for long-term resilience-building efforts.

VISUALIZATION

Example 1: 2D-line chart for multiple years

Example 2: bar chart for multiple years

Example 3: 2D-line chart for multiple years, targeted households versus general population

Example 4: pie chart for a single point in time, IPC-informed Phase 1-4

Example 5: bar chart for a single point in time, disaggregation by climate shock type

LIMITATIONS

• While the methodology aligns with IPC guidelines to ensure consistency, it is important to recognize that the IPC system was originally designed for large-scale, area-based assessments of acute food insecurity rather than for household-level analysis. This poses some limitations when applying IPC-informed classifications to measure HFA needs at the household level, as the IPC system is designed to classify food insecurity at a regional or national level using a convergence of evidence approach. For this reason, IPC‑informed household classifications should be interpreted with caution. They provide a useful proxy for identifying households likely to face acute food insecurity, but they should not be considered equivalent to an IPC analysis. Where possible, they should be complemented with additional household‑level indicators, contextual information, or qualitative insights to ensure a more accurate understanding of households’ food assistance needs.

• Accuracy of the indicator depends on rigorous collection and classification of underlying indicators (FCS, rCSI, LCS-FS).

• Detailed information on programme design is critical to derive robust inferences about the programme’s effect on reducing the need for humanitarian food assistance.

• Inconsistent collection of households’ socioeconomic information, including livelihoods and households’ composition, may obscure key insights. Additionally, data on households’ exposure to shocks and stressors is essential to assess how these factors influence households’ resilience and how their severity may diminish or amplify the expected programme impact on humanitarian food assistance needs.

• While a reduced percentage of households in need of humanitarian food assistance is a good proxy for programme effectiveness, low values do not necessarily indicate programme success alone. Other external factors, such as individual circumstances or broader contextual elements, including shocks and stressors, can influence food security outcomes beyond programme interventions. These should be taken into consideration when interpreting the indicator. In addition to this, it is important to recognize that the data reflect the situation at a specific point in time, offering a snapshot rather than a sustained trend. As such, these results do not allow for firm conclusions about the long-term sustainability of food security gains. Moreover, like other food security indicators, HFA-related outcomes are highly sensitive to the timing of data collection and, more specifically, the timing of transfer deliveries. This reinforces the need for cautious and contextual interpretation of the HFA need indicator when assessing programme performance.

FURTHER INFORMATION

• TANGO International, 2024. Measuring the Contribution of WFP Resilience Programming to Averting the Need for Humanitarian Food Assistance (HFA).

• WFP, 2024. Estimating Averted Humanitarian Assistance Needs through WFP’s Integrated Resilience Programme (IRP) in the Sahel.

• R Syntaxes for Humanitarian Food Assistance (HFA) Needs. XLS module for Humanitarian Food Assistance (HFA) Need. This can be converted to ODK form for consistent data collection across mobile and web platforms.