Exposure levels can be calculated by incident, location, time, armed group, and group type, or can be aggregated to observe national and global trends. These data are available over time, and trends in exposure can be tracked.
Globally, conflict exposure is rising as more locations experience conflict (see the ACLED Conflict Index). Significant shares of the population in highly conflict-affected countries live near frequent and deadly conflict. Populations exposed to pronounced and repeated conflict risks are distributed widely at a global level. Because of the severe increase in conflict over the past five years, exposure rates to all forms of disorder and demonstrations have increased. In 2023, the average rate of conflict exposure across countries was 16%2 but varied across countries (see Figure 1).
Figure 1: National Conflict Exposure Variations in 2023
Conflict Exposure Measures
People living in conflict areas are not equally affected by conflict. Locations are differently exposed to violence, and armed groups use alternative strategies to advance conflicts that have an adverse effect on communities. Using the conflict exposure measure, it is possible to know the civilian impact by proximity to an incident by type of incident, by armed group and type of armed group, by time, by location, administration, or country, and globally.
What can this measure be used for?
People are exposed to conflict when it occurs in their geographic proximity. Population exposure statistics complement more typical conflict indicators, including incident or ‘event’ counts (measuring form and frequency), fatality summaries (a measure of intensity), or number of locations affected. ‘Exposure’ describes the outcome and extent of harm of these conflict events where the unit is an ‘estimated number of exposed people’ to those events in that location during a specific time period. Consider the example in Figure 2 in the Sahel from 2020-23, where conflict exposure is juxtaposed with conflict event frequency. Using both parameters, we see how intensely high rates of conflict due to competition between armed groups in the border regions of these three countries have exposed the same communities many times over to relentless violence.
Figure 2: Conflict Exposure and Conflict Frequency Rates Across the Sahel 2020-23.
Conflict exposure measures tell us the demographic and geographic characteristics of populations affected by conflict. Almost all countries experience some form of political violence. However, we know little about the size and characteristics of populations exposed to violent incidents within those countries, despite significant advances in conflict research using event-level data,3 practitioner assessments of ‘population in need’ within violent environments,4 and attempts to ascertain the economic ‘cost’ of conflict.5 Conflict exposure measures can address several important questions, including:
- How many people are exposed to conflict?
- How many people are exposed to different forms of conflict? Who is exposed to conflict?
- Where and how many people are repeatedly exposed to conflict?
| Geographic Exposure | Demographic Exposure | Exposure Trends | |
|---|---|---|---|
| Addresses which question? | Where is exposed to conflict? | Who is exposed to conflict? | What are the exposure trends? |
| Assessment, Significance and Example | This dimension suggests patterns, strategies and variations of civilian exposure using maps, graphs, proportional location sizes and statistics | This assessment of risk reveals unequal and unseen exposure of civilians and its legacy through conflict exposure pyramids | This evaluation of trends and differences shows where and how risks to civilians are pooling and growing in global or national statistics, graphs and maps |
How accurate is conflict exposure data?
These measures of the civilian population living in areas affected by conflict or demonstrations are estimates. These estimates are based on a set of assumptions about the likely impact of those living proximate to conflict and demonstrations, and they are subject to other estimations, including the location of an event, and the best globally referenced method for estimating population. At present, these are annual, extrapolated estimates, subject to a calculation procedure that is designed to minimize population aggregation and possible exaggeration. Updates to locations used for ‘events’ in the ACLED dataset occur continuously; significant changes to WorldPop estimates are projected to be available in mid-2024. However, continuous efforts to estimate and integrate important population flows, including refugee and IDP movements, are ongoing.
What are the most important caveats and considerations when using these data?
Conflict exposure data measure the dispersed and concentrated outcome of events as ‘people exposed’ and is designed to limit over-aggregating exposed populations. The exposure measure will increase by year (or another observed time period), if people in new locations are exposed to violence or a demonstration. For example, if 100,000 people are living in the city of Nyala in Darfur and that city is attacked 15 times in one month, the conflict exposed number will remain 100,000 per month (rather than 1.5 million people). If Nyala is attacked 10 times in June and 10 times in July, and an analyst wishes to know the exposed population during each month, the conflict exposure measure will tell them that 100,000 people were exposed to conflict each month. It should only change if a new location and population are exposed, or if a new time period begins.
The conflict exposure measures need to be carefully calibrated by location and specific time period to avoid resulting in implausible aggregations. When using these raw data, calculate the exposure rate by location (e.g. global, country, town, etc.) and time period (year, month, day), and divide by the number of events that occurred in that location during that time period. This will provide the base assessment.
Further, because conflict exposure measures are specifically designed to limit over-aggregation, the extent of the buffers are for 1 km, 2 km, or 5 km, but the adjusted size is likely much smaller for areas with many conflict events and locations. For example, if in the city of Aden in Yemen, there are 50 locations that had at least one event in a year, and even 1 km buffers will overlap with neighboring buffers (as will 2 km and 5 km buffers). To prevent this, all buffers are designed to not overlap with any neighboring buffer. This results in a smaller unit than 1 km, 2 km, or 5 km as the area in which to assess the exposed population.
How does the ‘best’ estimate vary?
For each event in the ACLED dataset from 2020 onwards, the 1, 2, and 5 km estimates for each location and year are adjusted to create a unique ‘best’ conflict exposure estimate.
ACLED includes a ‘best’ estimate of conflict-exposed populations based on our knowledge of the impact and intensity of different ACLED ‘event types’. We base the ‘best’ estimate solely on a general rule for ‘event types’ and whether at least one fatality occurred. The default measures that comprise the best estimate are:
| Event types | Default measures |
|---|---|
| Battles | 5 km |
| Explosions/Remote violence | 5 km |
| Violence against civilians with no reported fatality | 2 km |
| Violence against civilians with at least one reported fatality | 5 km |
| Riots | 2 km |
| Strategic developments | N/A |
When summarizing the conflict-exposed population, the ‘best’ estimate will vary based on if that location has number of different ‘event types’. For more information on ACLED ‘event types’ and how events are recorded in the dataset see the ACLED Codebook.
How can you access conflict exposure measures?
Conflict exposure measures can be accessed in three ways.
The first is through the data portal. Once all data filters are complete, please note at the final step that conflict-exposed population measures need to be selected. There are two options for adding population data to the exported file: the default is to include only the ‘population_best’ column, providing the best estimate of exposed population, but users can also choose to download all four population columns with data on the different buffer sizes. That resulting file will include four columns called:
- Population_1km
- Population_2km
- Population_5km
- Population_best
The second way to access conflict exposure information is by downloading it via the ACLED API. The ‘population’ parameter allows for downloading either just the population_best column or all four population columns. See the ACLED API Guide for more details.
All registered ACLED users will have the same level of access to the conflict exposure data as they would to ACLED’s broader dataset. Please reach out to ACLED’s Access Team ([email protected]) if they require extended access.
The third way to access conflict exposure information is by using the Conflict Exposure Calculator. Using the calculator does not require downloading the data or registration.
What is the conflict exposure calculator?
The calculator is a tool that provides the most direct estimate of the exposed population for a given spatial unit (e.g. country/administrative region/town) during a specific time period (year, month, date) and can also vary by ‘event type’ and conflict actor.
How does the calculator aggregate population estimates?
The calculator summarizes population conflict exposure estimates based on applied filters, including spatial, temporal, interactions, armed groups or targeted groups, and/or ‘event types’. When there are multiple ‘event types’ for a location, the calculator applies the ‘best’ population estimate from the modal event type. This ensures that the ‘best’ estimate is the one associated with the most frequently occurring event type for each location. For example, if there was 1 ‘Battle’ event at a location (which defaults to the 5 km population estimate) and 10 ‘Violence against civilians’ events with no reported fatality (defaults to the 2 km population estimate) at that same location, the calculator applies the 2 km population option as the ‘best’ estimate, since this is the modal event type for the location.
If dates are selected in the calculator that span multiple years, the tool uses a weighted mean to account for different baseline population estimates for each ‘location-year.’ The calculator weights by the number of events that occurred within each selected year. For example, if 2022 and 2023 are selected, and there were 5 events in 2022 and 1 event in 2023 for a location, the estimate will weigh the 2022 population estimate five times more than the 2023 estimate. If the population estimate in 2022 and 2023 were 50,000 and 60,000, respectively, the weighted mean would be approximately 51,667.
Conflict exposure estimates may be viewed at varying levels of spatial granularity (location, first administrative level, country, or global). When aggregating above locations, the calculator sums the location-level estimates after accounting for modal event types and multiple-year rules above. When viewing the country-level results, the calculator shows the percentage of each selected country’s total population exposed to conflict, given the selected parameters and time periods. For the global results, the percentage of global population exposed estimate is calculated as the global exposed population given the menu selections relative to the summed population for countries that experienced at least 1 event, also given the selected parameters and time periods.
How often will conflict exposure estimates be updated?
ACLED data are updated weekly. For new locations added during the update, a revised population estimate at 1, 2, and 5 km is generated. If the 1, 2, or 5 km buffer of a new location overlaps with an existing location, the population estimate for the existing location will also be updated to prevent over-aggregation. For WorldPop updates, please refer to updates in the methodology section.
How do you cite conflict exposure measures?
Please refer to: ACLED data-conflict exposure. Date. Specific filters used.
Referring to the methodology or the concept, please cite:
Raleigh, C; C Dowd; A Tatem; A Linke; N Tejedor-Garavito; M Bondarenko and K Kishi. 2023. Assessing and Mapping Global and Local Conflict Exposure. Working Paper.
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