C1
Conflict and political violence
The first of four kinds of harm. Every organised violent event recorded since 1989 by the Uppsala Conflict Data Program (UCDP), loaded one event at a time with its own death count, its own low and high estimates, and how precisely its location is known.
War deaths are counted as they were recorded, event by event — not estimated from a cause — because a death in battle is seen and recorded. Nobody records the WOUNDED event by event, so the number of injured is estimated from the number of deaths, using a ratio of wounded to dead from published research, with a range of five times between its low and high ends. It is always graded LOW.
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The products this kind of harm reaches
Each product whose figure includes Conflict and political violence, with its deaths per item and the part of that figure this kind of harm accounts for.
Scenario Economic-embedded, using FIGARO 2023.
| Product | Deaths per item |
|---|---|
| Bag of charcoal Part from here: 100% | 1.5 × 10⁻⁷ per item(0.61–3.5 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Cocoa butter Part from here: 99% | 4.1 × 10⁻⁸ per item(0.16–1.1 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Cocoa mass Part from here: 99% | 4.1 × 10⁻⁸ per item(0.16–1.0 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Printed circuit board assembly Part from here: 98% | 1.6 × 10⁻⁶ per item(0.60–3.4 × 10⁻⁶)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Smartphone Part from here: 98% | 3.0 × 10⁻⁸ per item(1.2–6.3 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Laptop Part from here: 98% | 5.4 × 10⁻⁷ per item(0.21–1.2 × 10⁻⁶)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Copper Part from here: 98% | 2.0 × 10⁻⁷ per item(0.81–4.2 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Diamond ring Part from here: 98% | 9.2 × 10⁻⁶ per item(0.44–2.0 × 10⁻⁵)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Chocolate bar Part from here: 98% | 2.5 × 10⁻⁹ per item(1.2–5.8 × 10⁻⁹)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Petrol car Part from here: 97% | 9.5 × 10⁻⁶ per item(0.55–1.7 × 10⁻⁵)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Coffee, one cup Part from here: 96% | 4.7 × 10⁻¹⁰ per item(0.19–1.2 × 10⁻⁹)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Roasted coffee Part from here: 96% | 6.7 × 10⁻⁸ per item(0.27–1.7 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Passenger car tyre Part from here: 95% | 5.2 × 10⁻¹⁰ per item(0.27–1.1 × 10⁻⁹)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Steel Part from here: 95% | 3.1 × 10⁻⁹ per item(1.7–6.7 × 10⁻⁹)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Electric car Part from here: 94% | 3.0 × 10⁻⁵ per item(1.8–5.5 × 10⁻⁵)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Lithium-ion cell Part from here: 93% | 8.4 × 10⁻⁸ per item(0.50–1.7 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Lithium-ion battery pack Part from here: 93% | 6.9 × 10⁻⁸ per item(0.36–1.4 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| NMC cathode powder Part from here: 93% | 1.4 × 10⁻⁷ per item(0.71–3.2 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Cotton fabric Part from here: 91% | 3.9 × 10⁻⁸ per item(1.5–9.5 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Cotton T-shirt Part from here: 91% | 6.4 × 10⁻⁹ per item(0.25–1.6 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Cotton yarn Part from here: 91% | 3.8 × 10⁻⁸ per item(1.5–9.3 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Jeans Part from here: 91% | 3.2 × 10⁻⁸ per item(1.2–8.0 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Denim fabric Part from here: 91% | 3.8 × 10⁻⁸ per item(1.5–9.8 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Refined sugar Part from here: 90% | 6.1 × 10⁻⁹ per item(0.24–1.5 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Wheat flour Part from here: 89% | 1.1 × 10⁻⁸ per item(0.44–2.6 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Croissant Part from here: 89% | 0.42–2.4 × 10⁻⁸ per itemINDICATIVES-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Butter Part from here: 89% | 3.2 × 10⁻⁷ per item(1.3–7.2 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Pack of cigarettes Part from here: 80% | 3.6 × 10⁻¹⁰ per item(1.4–8.8 × 10⁻¹⁰)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Aluminium Part from here: 54% | 4.8 × 10⁻¹⁰ per item(0.19–1.2 × 10⁻⁹)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Glass Part from here: 9.5% | 2.2 × 10⁻¹⁰ per item(0.93–4.5 × 10⁻¹⁰)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
The figure is the product’s own, with its range. The share beside it is a middle estimate only: the calculation stores a range for each figure, not for each part of one.
What this kind of harm counts
This covers organised violence: fighting between governments and armed groups, fighting between armed groups, and the deliberate killing of civilians by an organised group. It is the one kind of harm that is directly seen, so nothing has to be estimated from a cause — there is only something to count.
What still has to be argued is which economic activity a death is linked to, and that happens later, in a separate step. Nothing on this page has been linked to anything.
Counted directly from war records: each death was seen and recorded, so nothing is estimated from a cause. Deaths outside organised violence are not counted here.
What the records hold today
417,968
Events in the records
4,257,891
Deaths recorded by the source
126
Countries
1,581
Wars
1989–2025
Years covered
These figures are the publisher’s own, shown with the credit its licence asks for. Nothing on this page has been linked to a product, a company or a material.
| Confidence of the death records | Records |
|---|---|
| HIGH | 324,334 |
| MEDIUM | 60,856 |
| INDICATIVE | 32,778 |
The causes it includes
| Cause | Estimated from its cause | Records |
|---|---|---|
| State-based armed conflict C1-STATE |
no | 292,121 |
| One-sided violence against civilians C1-ONESIDED |
no | 64,396 |
| Non-state conflict C1-NONSTATE |
no | 61,451 |
| Indirect conflict deaths C1-INDIRECT |
yes | not counted here |
Where the injury figure comes from
UCDP publishes no count of the injured. It records deaths for each event and stops there, and no other source fills the gap event by event. Since injuries are one of the two headline measures of this project, there were two honest options: estimate them from a published ratio with a wide range, or publish nothing.
This is the first option, done in the open. Deaths are multiplied by a ratio of wounded to killed. The low estimate of deaths is multiplied by the low end of the ratio (and the high by the high), so the two uncertainties add up rather than cancel out. Every estimated record is graded LOW.
| Type of violence | Injured per death | Grade |
|---|---|---|
| state-based | 2–10 (3) | LOW |
| non-state | 2–10 (3) | LOW |
| one-sided | 2–10 (3) | LOW |
The same ratio is used for all three types of violence. No separate figure for each type was found in published research, and there is good reason to think attacks on civilians leave fewer wounded per death than battles do — they are meant to kill. Inventing three numbers from one source would be false precision, so the gap is recorded instead.
Which sectors carry this harm
Which industries this kind of harm is linked to, weighted by how much harm lies behind each share rather than averaged over countries.
56.9% of the deaths recorded for this kind of harm belong to a subject that has been attributed at all — that is, to a war or a report that has been linked to industries — 22 of 1,581.
| sector | share | Grade |
|---|---|---|
| Other and unattributed economic activity OTHER |
18.7% | MEDIUM |
| Crop and animal production, hunting and related service activities 01 |
12.5% | MEDIUM |
| Extraction of crude petroleum and natural gas 06 |
5.6% | MEDIUM |
| Mining of metal ores 07 |
5.3% | HIGH |
| Transportation and storage H |
5.3% | MEDIUM |
| Defence activities 8422 |
2.1% | MEDIUM |
| Wholesale and retail trade; repair of motor vehicles and motorcycles G |
1.7% | HIGH |
| Other mining and quarrying 08 |
1.5% | MEDIUM |
| Mining of coal and lignite 05 |
1.3% | MEDIUM |
| Manufacture of weapons and ammunition 252 |
1.2% | MEDIUM |
| Manufacture of basic metals 24 |
0.9% | MEDIUM |
| Manufacture of coke and refined petroleum products 19 |
0.5% | MEDIUM |
These are shares, not counts of people. The number of deaths each industry stands for is calculated but not published: it has no range yet and has not passed the test on past years.
Conflict attribution is SCORED: each war’s link to each industry is scored against nine criteria, using a published guide and a source for every score, for twelve wars chosen to cover the range of the argument. The remaining shares belong to wars nobody has scored yet, and they are missing, not zero.
What it does not capture
- Deaths a war causes indirectly — through the hunger, disease and displacement it brings rather than its weapons — are not in these records at all. Published estimates run from three to fifteen times the deaths in fighting, and no source records them event by event, so they come in later as a scenario setting with a wide range, not as a number hidden inside this one.
- An event whose location is known only to the level of a country cannot be linked to a particular mine or plantation. How precisely each event is located travels with it, and imprecise events are never quietly placed somewhere.
- An event that killed both civilians and fighters is recorded as neither. The source gives one low-to-high range for the whole event, so splitting it would mean inventing two ranges from one; the separate counts are kept so a later step can split them properly.
- Some events arrive with a low or high estimate that leaves out the source’s own best estimate. The range is then widened to include it, never narrowed — a wider range claims less — and every record changed this way says so.
- A death recorded here may also be counted under another kind of harm: a miner killed in an armed attack is both a war death and a death at work. No total for one kind of harm is added to another until the overlap is measured.
Sources and credit
| Version of the data | Downloaded | File fingerprint (SHA-256) |
|---|---|---|
| ucdp · ged-v26.1 | 2026-09-10 | 8c941d84954e555e… |
Uppsala Conflict Data Program (UCDP), Uppsala University — Davies, Pettersson and Oberg, "Organized violence 1989-2025, and violent political protests", Journal of Peace Research (2026), doi:10.1093/jopres/xjag046 — ged-v26.1, retrieved 2026-09-10 from https://ucdp.uu.se/downloads/ged/ged261-csv.zip. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
Questions
Are these HumanToll’s numbers?
No. The death counts on this page are UCDP’s, shown with the credit its licence asks for and with the exact version of the data file they came from. HumanToll’s own figures — harm linked to products and materials — are not published yet.
Why is there no total for the injured on this page?
Because it would be an estimate made by the model, and no such estimate is published until the model has passed its test on past years. The method, the ratio, its range and its source are all here; the number is not.
What happens when UCDP corrects a year?
The correction arrives as a new version of the data file. The old records are kept and marked as replaced, not deleted, so anything published from the old version can still be traced to the events it came from.
Does a war death mean some business is to blame for it?
Not by itself, and this page makes no such claim. It records that the death happened, where, and how certain the record is. Whether any economic activity is linked to it is a separate step that needs evidence, and the assumptions behind it can be switched on the scenarios page.