About our data


IDMC monitors internal displacement across the world with the UN General Assembly resolution calling for “a more comprehensive and coherent system of collecting data on the situation of internally displaced persons”. Subsequently, the UN General Assembly has repeatedly reaffirmed IDMC’s role as the provider of that comprehensive and coherent system through its Global Internal Displacement Database.  Today, IDMC is the world’s leading source on data and analysis on internal displacement.

Our monitoring methodology is the result of a rigorous process of research, data management, analysis and validation to understand the causes and triggers of displacement, particularly for conflict and violence as well as disasters.

Monitoring internal displacement is not free from complications and requires sound and transparent methodologies to compile and report reliable estimates. This page presents the methodology that IDMC has developed to navigate these challenges. It takes stock of our existing practices, systems, and potential areas for future improvements. We highlight some of the main challenges we face, as well as the strategies, guidelines, quality-control principles and decision rules IDMC has in place to overcome them. More importantly, this reflects the commitment to continuously improve our methods, and to make our data and knowledge available and accessible to all audiences interested in learning more about internal displacement.

To ensure the highest level of reliability of IDMC’s estimates and analysis, we adhere to strict guidelines and processes. In pursuit of a clear and persistent methodology, these are the key principles that guide our process of monitoring internal displacement:

  • Monitoring is global in terms of geographical scope.
  • Monitoring is about research, data collection, analysis and triangulation of sources, partner engagement and quality-assurance.
  • Methods, definitions and standards need to be consistent across countries and over time.
  • Situations of displacement are reported in a timely manner.
  • All relevant metrics of the displacement data model (stocks and flows) should be monitored.
  • There is no threshold in terms of the number of people displaced, the distance they have travelled, or the length of the displacement. The events or different instances of internal displacement that IDMC reports on therefore largely depend on data availability, rather than a threshold. 
  • Reliable sources and triangulation are used for displacement estimates and figures.
  • Whenever possible, the duration of internal displacement should be estimated.
  • Whenever possible, geospatial data and disaggregated data on age and sex of IDPs should be collected.

What is internal displacement and what is an IDP?

Internal displacement refers to the forced movement of people within the country they live in. IDMC adopts the definition of an internally displaced person (IDP) categorised in the Guiding Principles on Internal Displacement:

Internally displaced persons are persons or groups of persons who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of or in order to avoid the effects of armed conflict, situations of generalized violence, violations of human rights or natural or human-made disasters, and who have not crossed an internationally recognized State border.

For accounting purposes, we focus on the three key elements of this definition when determining whom to include in our monitoring and data collection:

  • The forced nature of the displacement - The forced or coercive nature of people’s movement is fundamental in determining whether they are IDPs, as compared to migrants. As the Guiding Principles do not set other criteria by which to identify a person fleeing their “home or place of habitual residence”, we interpret IDPs to include not only citizens of a country in which displacement takes place, but also non-nationals whose habitual place of residence is in that country. We attempt to monitor all situations of internal displacement, regardless of the cause and trigger, however we focus our reporting and providing data on internal displacement caused by conflict and violence and disasters. We aim to continuously improve and expand the scope of our monitoring and reporting, based on the availability of data on movements.
  • Displacement from the habitual residence (or the displacement trigger preventing the people or group concerned from accessing or remaining in said place) - We also recognise that forced displacement is not solely associated with the notion of a fixed place of residence. For nomadic pastoralists, displacement may be the result of the loss of traditional grazing areas, the death of livestock, or a combination of both. Given that the concept of habitual residence is intimately linked to peoples’ livelihoods, some people who have lost their livelihoods can be considered IDPs. We have found this to be the case for pastoralists who have become displaced due to the impacts of drought and conflict.
  • People displaced remain within their country of origin or habitual residence – Based on the Guiding Principles, we only monitor forcibly displaced people who remain within national borders. Once an IDP crosses the border, it goes out of the scope of our monitoring. 


 IDMC's displacement data model

We developed this data model to illustrate, account for, and characterise how different types of population flows influence the total number of people displaced in any given situation at a specific point in time. This allows us to monitor in a consistent manner as possible and to make meaningful comparisons across all countries and from one year to the next. This data is essential to provide evidence for and inform targeted and effective policies to address complex crises. Additionally, it reflects reported cross-border movements and attempts to reach durable solutions, as these can also affect the total number of IDPs. Populating the model with data, however, can be a challenge. Data collected by IDMC’s partners almost never accounts for all relevant flows and it is often difficult to map all partners’ data onto the corresponding part of the data model.

Internal displacements

The total number of movements that has occurred over a period of time is considered a “flow” and the most common type of this metric is called “internal displacements”. We attempt to generate an estimate of internal displacements by event, be it for conflict or violence or disaster.

  • For example, “We recorded more than 32 million internal displacements globally due to disasters in 2022.” refers to the number of displacements recorded between two or more points in time (in this case, between 1 January and 31 December 2022).

It is important to note that this estimate is not necessarily the same as the peak number of IDPs, but instead aims to provide the most comprehensive cumulative figure of displacements during a given period of time. As internal displacements refer to movements, depending on certain situations the same people can be displaced several times over a given period.

Given the challenges in tracking population movements, it is difficult to determine what portion of internal displacements refer to people being displaced for the first time and what portion represents the same people being displaced a second, third, fourth or fifth time. As a result, internal displacements could include secondary or multiple displacement movements.


The total number of IDPs at a given time is referred to as a “stock” metric. It represents a static snapshot of the number of IDPs in a given location at a specific point in time. 

  • For example, “Ten thousand people were still displaced at the end of the month” indicates how many people were displaced at a specific point in time (“at the end of the month”). 

For example, IDMC’s main publication, the Global Report on Internal Displacement (GRID), reports on the total number of IDPs, or stock, at the end of a given year. Population movements such as internal displacements or births among IDP communities may increase it, while returns, cross-border flight and other outflows may decrease it. 

In cases where there is a lack of coverage of all the components of our data model, we take into account internal displacements and the previous year’s stock figure when estimating the total number of IDPs. However, there are cases where we are unable to apply this formula, because the data related to internal displacements and the number of people still displaced cannot be brought together in a meaningful manner. This can occur if there is a possibility that people included in the previous stock figure are the same as those newly displaced in a given year. In such cases, we refrain from adding possible internal displacements to the stock metric to avoid double counting people who were displaced more than once.

Return movements and other flows

Monitoring other flows such as returns, cross border displacement, births, deaths, settlement elsewhere, local integration are important to understand the scale of displacement. This allows us to assess displacement-related vulnerabilities and risks that often continue long after the end of the events that caused them. The challenge here is access and availability of this data.

We account for children born to IDPs and IDPs’ deaths only when our data providers collect and share this information. Given the fact that the fertility and mortality rates of IDPs may not correspond with national figures, we do not try to extrapolate births and deaths in displacement from national demographic data.

As much as possible, we also monitor for data on cross-border flows. We rely on data by partners to provide these displacement flows that can also include refugees, asylum seekers and migrants and whether people had been displaced internally before crossing the border. In some contexts, returning refugees, asylum seekers and migrants can become displaced when they return to their country of origin. This can occur when their return movement itself is a form of displacement, such as the deportation of some refugees or asylum seekers. It can also occur when people voluntarily return to their country of origin but find themselves in a condition of internal displacement – such as when they return to IDP camps or to destroyed homes. In these cases, we add these people to our year-end stock of the total number of people still displaced.

We also attempt to monitor, capture, and analyse data on IDP returns to their place of origin, local integration or resettlement to another location. It allows for a better understanding on the range of impacts of internal displacement on affected populations.

Data collectors, government agencies, media outlets, and humanitarian partners use different terms and expressions to describe when people are forced to flee their homes. As part of our monitoring process, we compile and interpret data to determine when internal displacement has occurred, even in cases where this information is not readily available or obvious. Additional analysis is required to make sense of the terms used by sources and to understand when and how they relate to displacement. For these purposes, a wide range of terms and situations are examined:

  • Displaced - Involuntary or forced movements, evacuation or relocation – when not specified - of individuals or groups of people from their habitual places of residence.
  • Evacuated - Voluntary and forced evacuations, both preventive and in response to the onset of a hazard.
  • Relocated - Voluntary and forced relocations, both preventive and in response to the onset of a hazard.
  • Sheltered / in relief camp - People accommodated in shelters provided by national authorities or organisations such as NGOs, the UN and IFRC.
  • Homeless - People rendered homeless and without adequate shelter.
  • Uninhabitable/ destroyed housing – Indicates destruction of a habitual place of residence, and includes houses, retirement homes, prisons, mental healthcare centres and dormitories. This term is used as a proxy for displacement
  • Partially destroyed housing - Data on partially destroyed houses should not necessarily be taken as a proxy for displacement. This information, however, helps us identify situations that we may need to examine further. 
  • Forced to flee - “Flee” implies the forced nature of people’s movement and we take it to indicate displacement. 
  • Affected – While data on affected populations should not necessarily be taken as a proxy for displacement it does refer to people whose life has been directly impacted by an event. Displaced people can be among those affected, but not all affected people are necessarily displaced.
  • Multiple/Other - Other indicators of displacement used by local authorities or organisations that can include context-specific terms such as rescued people, people in need, targeted people, resettled people and people living in temporary or transitional shelters. 


In our monitoring, we aim to be as comprehensive as possible when identifying and accounting for displacement events in any given country and to collect data that is spatially disaggregated. Some factors that limit the geographical coverage of our displacement data include access to areas affected, operational coverage of relief organizations, political sensitivities, and the availability of information on IDPs living inside and outside of camp-like accommodations. Other geographical considerations include:

  • Geopolitics - Amongst the primary and crucial criteria to determine whether a person or a group is internally displaced is the fact that the forced movement remains within the internationally recognised borders of the place of habitual residence. This is usually straightforward, and the data obtained from governments and other providers allows us to identify the location of departure and/or arrival of said movement(s). There are, however, cases in which the borders of a country or territory, as well as the sovereignty associated with them, are disputed or in question. This presents a challenge regarding what countries and territories to include in our reporting and how to account for certain groups of displaced people.
  • Foreign occupation - People displaced within areas of an internationally recognised state under foreign occupation are considered IDPs, irrespective of their location within the internationally recognised borders or the territorial claims of the occupying power.
  • Creation of new states - For countries that have been divided into two internationally recognised states, such as Sudan and South Sudan, we consider all people displaced within each of the new entities as IDPs and produce separate estimates for each one. People who fled within the previously undivided state and who crossed the border that delineates the new entities are no longer counted as IDPs.
  • Unilateral secession - For regional entities such as Abkhazia and South Ossetia, which have unilaterally seceded outside an internationally supported process, we do not count IDPs within them separately from those in the state they have seceded from, in this case Georgia. In cases such as Kosovo, however, where many UN member states have established diplomatic relations with a seceding entity, we do produce estimates for IDPs who have fled within it. We no longer count people as IDPs if they have crossed what has become a de facto international border and find themselves in different entity from the one in which they were originally displaced. As such, our estimate for Kosovo refers only to people who have fled within the territory itself.

The inclusion of countries and other contested territories does not imply any political endorsement or otherwise on IDMC’s part. IDMC collects and presents data on IDPs for UN members states and other self-governing territories, those with unsettled sovereignty such as the Abyei area and others with special status such as Palestine and Kosovo.

Table of data sources

IDMC’s workflow: Data aggregation, curation, standardization and quality control process, to publish our datasets

Event-based monitoring

We track displacements by events as much as possible to assist in analysing and producing estimates based on location, date of incident, triggers, causes and duration. Accounting for incidents of displacement as discrete events also allows us to measure the risk of future displacement.

Moreover, event-based monitoring results in a better estimation of internal displacements as it allows us to report on dynamic displacement situations or short-term displacements that would otherwise not be captured by large assessment exercises. Event-based monitoring can also be useful for monitoring and tracking historical changes or protracted displacement situations. It enables us to continue to monitor changes in figures and estimates beyond the year an event took place.

Data Storage

All relevant data and contextual information gathered by IDMC is stored in our Global Internal Displacement Database (GIDD). We use this database to store data and metadata, annotate and comment on the information we receive, analysis and validation associated with every figure we publish.

Since 2016, all information collected by IDMC has been recorded in this platform and allows IDMC analysts to organize the content in three interlinked objects:

  • Events group contextual information regarding the specific driver of displacement.
  • Entries are used to store metadata and a copy of the original data source. Information about the date of the data, the country and the publisher are also captured.
  • Figures contain an analysis of the data and its reliability, geospatial information, as well as sex and age disaggregation if available.


Our displacement estimates are based on the most reliable data available. A main method to determine the reliability of our figures is to triangulate data using several sources whenever possible, prioritising those we have historically deemed to have been most objective and accurate. This means that some numbers or data we obtain, or that have been published by some sources, might not be included in our reporting and our database. Compared to other published figures, our estimates tend to be conservative. When we have insufficient data or cannot verify the data we have received, we do not publish any figure at all.

Additionally, triangulation is also used to assess the quality of the data and contextual information we receive. Consequently, we aim to verify and validate estimates by researching and comparing data and information from various sources and publishers. In cases where several sources report on the same event, we compare these reports and the methodology employed by each. This is essential when data from two or more partners appear to conflict.

An example of why triangulation is useful can be found in our spotlight on data triangulation published in GRID2019.

Quality Assurance

Data that has been collected in our database, over the course of the year, is examined and controlled before being released to the public. The quality assurance stage is as important as the data collection itself, as it allows for possible errors, data gaps, and caveats to be identified, and for the data to be refined before it is published. This process is led in-house, via a rigorous internal peer review process that is supplemented by an external peer review involving feedback and discussions with our partners to understand the different methodologies behind the data collection and possible limitations and caveats.

Publishing Data

After the quality assurance process, we release and update our global dataset typically along with the publication of the annual Global Report on Internal Displacement (GRID). This dataset is publicly available and is part of our global repository of all our validated data on internal displacement since 2008. Note that we update our data regularly to ensure we have the most reliable estimates, and as a result, previous published data in reports, such as the GRID, may differ from what is found in the GIDD - our most updated repository of data.

IDMC has identified the most recurring and critical challenges for our monitoring and analysing of internal displacement. These issues are summarised in the sections below.

Data availability

Data availability varies considerably. While one challenge of monitoring internal displacement is the lack of data availability, there is also the challenge of verifying and analyzing the amount of data we obtain.

Sources and information tend to be more numerous during major disasters, humanitarian crises and visible emergencies, especially when targeting assistance efforts. Furthermore, population movement tracking can often be limited only to the most affected areas, limiting the geographical coverage, and potentially leading to some movements not being captured.

Data availability is also linked to access challenges, such as insecurity in some areas, political sensitivities or because IDPs are displaced in non-government-controlled areas. In such situations, it is rare that one partner can cover an affected region. In other cases, access restrictions are so severe that IDMC lacks any reliable data on a given crisis. While this is rarely the case for entire countries, it can be relatively common that certain regions of a country go uncovered. As a result, data collection and publication may be delayed, unavailable, or out-of-date.

While we rely on multiple sources to crosscheck figures, this exercise may not always be straightforward, especially when there is incomplete information on the methodology by data sources, or on the extent to which two or more different data sets overlap. Hence, we may decide to base our estimate on only one source. That decision may vary from year to year depending on the geographical and temporal coverage of the data, or its reliability. Changes in the scope of a data providers’ geographical coverage also pose challenges. To fill data gaps, we may be working with different datasets from one year – or even one month – to the next.

The frequency of data publication can vary from daily bulletins, weekly or monthly reports, to quarterly and annual publications. This cycle can impact our analysis as different data sources and publishers might follow different schedules of data collection, verification, reporting and publication. This also can pose a challenge when IDMC compares trends across different countries within the same region, or at the global level.

Displaced households or housing destruction

Housing information is important in estimating displacement because sources may only report on housing damage rather than the number of people displaced. As a result, IDMC considers displaced households or destroyed housing as a key proxy for displacement. When there are data on homes destroyed, homes uninhabitable, or the number of households and families displaced, we multiply them by a country’s average household size (AHHS). However, there is no universal dataset with updated and standardised AHHS data. Building on our AHHS methodology detailed in GRID2016 (page 81), in 2021, we developed AHHS multipliers for each country and territory we monitor. This is based on the cataloguing of AHHS reported by official UN statistics, national statistical offices, census and other reliable sources. Yet there is still a potential that the use of AHHS can influence the overestimation or underestimation of figures.

Data disaggregation

We seek to obtain not only quantitative data on possible increases and decreases in the number of IDPs and displacement movements, but also more specific disaggregated information which can inform targeted and effective responses to the needs of IDPs. This includes information such as sex and age disaggregated data (SADD), data on disability status and on the location of IDPs, such as whether they are in urban or rural areas and whether they are displaced within shelter or non-shelter settings.

SADD is only available in certain countries and some displacement contexts. This is mainly because information on sex, age and disabilities of IDPs tend mainly to be captured in official sites, such as relief camps, whereas a significant majority of IDPs in many cases live in dispersed settings among host families and communities. Even when disaggregated data is available, however, it tends to not represent a statistically significant portion of the overall data collected.

Decaying data

When situations remain unchanged from one year to the next, or when data is not available, we base our stock estimates on the most reliable source available. In many countries, however, they may not have been updated for several years. In countries with complex or multiple displacement crises, data for one crisis may be regularly reported, while for others it may be missing. If there is no credible evidence that IDPs in such situations have returned, integrated locally or settled elsewhere and thus achieved durable solutions, we continue to include them in our stock estimates.

Data on returns and other forms of durable solutions

IDMC collects data on returns, resettlements and local integration when the data is available. Data related to durable solutions is difficult to come by, as data sources often report only on displacement movements, but rarely report on more contextual information related to the progress towards durable solutions. And even when they do, information on solutions is often incomplete and does not paint a comprehensive picture of the living conditions of IDPs. For instance, a report may indicate that an internally displaced population has returned to their homes, but it may not be clear to which conditions they have returned or to what extent their basic needs are being met or their fundamental rights protected. The fact that information on solutions, when available, is often incomplete, creates complications for the categorization and analysis of the relevant data. In addition, it is further challenging to gather this information because achieving durable solutions is a long-term and multi-step process for which publicly available information is scarce. 

Reporting bias

We attempt to reduce reporting bias through triangulation and assessment of data sources. We are aware, however, that our methodology and data may be subject to different types of reporting bias:

  • Unequal availability of data: Displacement data availability tend to be found in large events in a small number of countries where international agencies, funding partners and media have a substantial presence, or where there is a strong national commitment and capacity to collect and report on displacement information. 
  • Under-reporting: Small-scale events are far more common, but less reported on. In addition, events that occur in isolated, insecure or marginalised areas tend to be under-reported because of limited access or media coverage.
  • “Invisible” IDPs: There tends to be significantly more information available on IDPs who take refuge at official or collective sites than on those living with host communities and in other dispersed settings. As the vast majority fall into the second category, figures based on data from collective sites are likely to be substantial underestimates. 
  • Terminology: The term “displaced” is rarely, if ever, adopted consistently and unequivocally by different countries or sources. This means that some indicators might refer to a specific thing in one place, and to something different in another. Additional analysis is required to make sense of the terms that sources use, and to understand when and how they signal displacement.  
  • Language: We can only obtain and analyse information in the languages we speak, read, or can interpret through translation services. Our staff and partners speak most of the required languages, but we inevitably fail to capture some information, particularly for small scale incidents in parts of Asia and Europe.

Monitoring challenges specific to conflict and violence 

  • Access constraints: Humanitarian partners and data collectors can face access constraints due to conflict and insecurity which prevent them from accessing and assessing displacement sites in certain areas. As a result, these access constraints may not fully capture the extent of the displacement caused by armed conflict and violence in some contexts. 
  • Data gaps: Short-term evacuations or spontaneous movements driven by conflict and violence may not be available by data providers. For example, in the context of criminal violence many displacements are smaller in scale (ex. only one family member is displaced following threats by criminal groups), making these small-scale displacements very difficult to track. Data on small-scale displacements linked to inter-communal violence is further difficult to obtain and verify. 
  • Continuity of engagement: Oftentimes, due to the volatile and challenging nature of field work for humanitarian or development agencies workers, continuous engagement can prove difficult over the long term. Therefore, our engagement efforts can, at times, be affected by high turnover and changes in personnel in the field, and cause reporting to be unequal or interrupted. This can result in data over time seeing some fluctuations more related to the availability of data rather than due to the dynamics of the conflict or violence.

Monitoring challenges specific to disaster

  • Overlapping hazards: This is particularly the case in regions where there is a rainy, hurricane or monsoon season where continuous storms makes it a challenge to define when storm systems begin and end, as well as secondary effects such as triggering flooding and landslides. In addition, sometimes sources do not provide reference to when, how, or what hazard(s) triggered people to be displaced. 
  • Evacuations: We often use data on mandatory evacuations and people staying in official evacuation centres to estimate disaster displacement. Accounting only for people staying in shelters may underestimate the total number of evacuees as others may take refuge elsewhere. On the other hand, basing estimates on people ordered to evacuate may overestimate the actual number, given that some people do not comply. The potential for such discrepancies is much greater when authorities advise rather than order people to evacuate, and as a result we do not incorporate such figures into our estimates. Depending on the context, evacuation terminology and reporting may vary from country to country. 
  • Length and severity of displacement: Since 2019, we have been developing a methodology to estimate the number of people still displaced at the end of year by disasters. It aims to challenge the notion that people who flee are not likely to remain displaced for long. Our methodology indicates that there are likely to be many more people living in protracted disaster displacement than previously thought. This has significant implications for people who remain displaced, but are not counted, and those responsible for protecting and assisting them.
  • Slow-onset hazards: Displacement associated with slow-onset hazards such as drought, sea-level rise, coastal erosion and environmental degradation is challenging to monitor. The slow-onset nature of certain hazards and processes means that it is difficult to identify incidents of displacement or to relate population movements to specific hazard events. It is therefore often difficult to distinguish displacement from internal migration. Furthermore, displacement associated with slow-onset hazards is usually the result of a combination of factors such as planning and foresight, incremental actions, decision-making processes.


All too often, data collection stops a few days or weeks after a disaster event. This limits our understanding of the needs and living conditions of those displaced as well as our ability to estimate how many people remained displaced due to disasters. Displacement isn’t associated exclusively with conflict, when in fact it is a much broader and more complex phenomenon. As a result, any aggregate global estimates at the end of the year of the number of people still living in displacement are incomplete without including disaster displacement.

Since 2019, we’ve been developing a methodology to estimate disaster stock at the end of the year. It is based on time-series and housing destruction data collected for specific disaster events, as well as aggregated figures on the number of people displaced by disasters recorded by governments and other stakeholders. Despite the use of various sources and data compiled by our monitoring team, our disaster stock estimates are considered a conservative estimate due to data availability and quality.

In 2020, we produced an algorithm that reduced tens of thousands of data points in IDMC’s database into a final IDP stock estimate per country. The script filtered the data into a variety of pre-defined scenarios (see figure below), as well as ensuring that no overestimation can occur (see figure below). The code was developed in collaboration with the Department of Statistics, University of Oxford, and funded by the Engineering and Physical Sciences Research Council (EPSRC) Impact Acceleration Account grant.

Building on and guided by the 2020 methodology, in 2021 and 2022, our monitoring experts reviewed thousands of entries in IDMC’s database to provide a year-end IDP estimate per disaster event based on reported IDPs by data providers and destroyed housing information. Our methodology remains a work in progress.

Simplified decision tree highlighting the methodology used to estimate the number of people displaced by disasters


Sex and Age Disaggregated Data (SADD) for displacement associated with conflict or disasters is often scarce. One way to estimate it is to use SADD available at the national level. IDMC employs United Nations Population Estimates and Projections to break down the number of internally displaced people by sex and age.

Datasets used

Population data was obtained from the United Nations Population Estimates and Projections. The following population datasets were downloaded from the World Population Prospects’ Download Center:

Population by Single Age – Both sexes
Population by Single Age – Male
Population by Single Age – Female

Displacement data, namely the number of internally displaced people (IDPs), was extracted from IDMC’s Global Database on Internal Displacement.


First, the mid-year 2022 and 2023 values of WPP’s medium variant projected estimates were averaged to approximate the end-of-2022 figures for each single age category of male/female/both sexes data. Custom age groups were created. The percentage of each age group by sex of the total population was computed. These percentages were multiplied by the respective disaster and conflict IDP values for each country to obtain the number of IDPs disaggregated by sex and broad age groups.


Using absolute values to estimate SADD for IDPs could lead to issues of accuracy and representativeness. In addition, this method does not capture the dynamic nature of displacement, as it assumes a static population structure over time. Finally, using national-level statistics derived from census data may not fully reflect the experiences and needs of different groups, such as men and women, or different age groups, who may be disproportionately affected by conflict or disaster displacement situations.

Therefore, it is important to interpret the results of this analysis with caution and consider other sources of information, such as qualitative data and local knowledge, to gain a more comprehensive understanding of the situation.