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Likelier
Other · reviewed 2026-04-11

What are the odds of a soldier dying in combat?

Evidence quality 4.63/5

Eight-dimension review score against the quality rubric . Each dimension scored 1–5.

D1 Source grounding
4/5
D2 Source authority
5/5
D3 Arithmetic
5/5
D4 Uncertainty
4/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
4/5
D8 Caveat completeness
5/5
Average 4.63/5
Direct evidence

Lifetime probability · lifetime, subgroup

1 in 270

0.4% lifetime chance

Most people underestimate this.

range 1 in 426 to 1 in 100

lifetime, subgroup each band = 10× rarer → zoomed to your factors See full scale →
certain 1 in 1K 1 in 1M 1 in 1B
1 in 27 1 in 898

● your factors — click this risk ▾ to reveal

≈ As likely as

A single folded military-style cap resting on a pale neutral surface, flat vector illustration in muted olive and sand tones.

Perceived

"Soldier killed in combat" is one of the most vivid images civilians have of war, anchored by WWII film, cable-news casualty counters from Iraq and Afghanistan, and drone footage from Ukraine. We have not found a recent high-quality survey that isolates "fear of a soldier dying in combat" as a standalone question, so the perceived side is marked as editorial intuition rather than polled data. Civilians outside military communities tend to either overestimate the per-deployment death rate (influenced by WWII- and Vietnam-era priors) or underestimate it (influenced by the relatively low US casualty totals of the late Iraq and Afghanistan years). Families inside military communities typically calibrate better, because the base rate is something they hear discussed concretely.

Rough estimate: ranges wildly, from ~1 in 1,000 per deployment to ~1 in 10 per career depending on era and unit

Source: editorial intuition, not polled

Actual

~7,053 US military deaths / ~1.9M US service members deployed (post-9/11 wars, 2001-2021)

US service members who deployed to Iraq, Afghanistan, or related theaters under OEF/OIF/OND, 2001-2021

Show derivation

Reference subgroup: a US active-duty or reserve service member who deployed at least once to Iraq, Afghanistan, or a related theater during the post-9/11 wars (Operation Enduring Freedom, Operation Iraqi Freedom, Operation New Dawn, 2001-2021). Brown University’s Costs of War Project reports over 7,053 US service member deaths across the post-9/11 wars; between 1.9 and 3 million service members served in those theaters, with over half deploying more than once. Using the low end of the servicemember denominator (1.9M) as the per-person base gives 7,053 / 1,900,000 ≈ 0.00371, or roughly 1 in 270 over the entire post-9/11 war period per person who deployed at least once. This figure is for all in-theater deaths (hostile + non-hostile); hostile-only deaths are approximately 5,300-5,400, which gives a hostile-only rate of roughly 1 in 350. The scope is declared as subgroup_lifetime because it is the per-career risk for a specific deployed subgroup, not a general-population lifetime risk. It is not directly comparable to the population-lifetime figures on other Likelier pages — see regional_breakdown for how the number moves across era and unit type.

Caveats: "Soldier" is not a single population. A logistics specialist at a US airbase in …

"Soldier" is not a single population. A logistics specialist at a US airbase in Germany in 2018, an infantry rifleman in Fallujah in 2004, a tank crewman in Bakhmut in 2024, and a Marine on Iwo Jima in 1945 face risks that differ by more than two orders of magnitude. The headline figure is specific to US service members who deployed under OEF/OIF/OND during the post-9/11 wars and should not be generalized to "any soldier in any war". Within that subgroup, the risk was concentrated by year (2004-2007 in Iraq, 2009-2011 in Afghanistan), by branch (Army and Marine Corps higher than Navy and Air Force), and by MOS (combat arms higher than support roles). This figure also covers all in-theater deaths (hostile action, vehicle accidents, illness, suicide in theater). It excludes post-deployment suicide — the Costs of War project notes that post-9/11 veteran and active-duty suicide deaths have exceeded combat deaths by roughly a factor of four — and post-deployment deaths from chronic illness attributable to the wars, which are counted separately in veterans’ health statistics.

Regional breakdown

The headline figure averages across very different populations. Here’s how the probability varies by geography or context:

Region / context Lifetime probability Notes
US service member deployed to OEF/OIF/OND (2001-2021, any role) 1 in 270 Headline figure. 7,053 deaths / 1.9M unique deployers. All in-theater causes.
US service member deployed to OEF/OIF/OND — hostile deaths only 1 in 352 Approximately 5,400 hostile deaths / 1.9M deployers. Excludes accidents, illness, suicide in theater.
US infantry / combat arms in active Iraq or Afghanistan combat zone, peak years 1 in 100 Order-of-magnitude estimate. Combat arms soldiers in forward operating roles during 2004-2007 Iraq and 2009-2011 Afghanistan saw per-deployment fatality rates several times higher than the all-forces average. Exact subgroup rates are not publicly broken out by MOS.
US service member per deployment (not per career) 1 in 426 7,053 deaths / ~3.0M deployment-tours ≈ 1 in 425 per tour. Low end of uncertainty band.
US military, WWII-era (per career) 1 in 40 Approximately 407,000 US military deaths across ~16.1 million service members who served in WWII, or about 1 in 40 per career.
US military, Vietnam War (per in-country deployment) 1 in 149 Approximately 58,200 US military deaths across ~8.7 million Vietnam-era service members (~2.7 million in-country). Order-of-magnitude figure; exact per-deployment rate depended heavily on MOS and unit.
Russian military personnel in Ukraine (Feb 2022 - end 2024) 1 in 10 Estimated. Mediazona/Meduza statistical analyses using probate-registry data put cumulative Russian military deaths at ~165,000+ by end of 2024 against a rotating force on the order of 1-1.5 million. Numbers are contested and evolving; included only as an order-of-magnitude anchor for a high-intensity conflict.

Risks at similar odds

Other risks with roughly the same likelihood — useful for calibration.

Other

Civilian war casualty

What is the probability of a civilian being killed or seriously injured during a Ukraine-scale conventional conflict over five years?

Other

EMS duty death

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Other

Gambling financial ruin

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Other

Mining career death

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Other

Sports betting financial ruin

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Transport

Car crash

What are the odds of dying in a car crash?

Other

Frontline soldier casualty

What is the probability of a front-line infantry soldier being killed or seriously and permanently wounded over five years in a Ukraine-scale conventional conflict?

Other

Fighter pilot death

What are the odds of a US military fighter pilot dying in an aviation mishap or combat over a career?

Compare to:

The useful question is not “what are the odds a soldier dies in combat” but “which soldier, in which war, in which job, in which year.” A US service member in 2020 sitting at a Pentagon desk and a Red Army rifleman in Stalingrad in 1942 are both technically soldiers, and their per-year death probabilities differ by something like four orders of magnitude. The headline figure on this page fixes one specific reference subgroup — US service members who deployed to Iraq, Afghanistan, or related post-9/11 theaters between 2001 and 2021 — because that population has the best-documented casualty data of any modern war and is the one most readers actually have in mind when they think “the war”.

The numbers for that reference group come out to roughly 1 in 270 across an entire post-9/11 war career: about 7,053 US military deaths divided by approximately 1.9 million unique service members who deployed at least once. Hostile-only deaths (killed in action plus died of wounds) are closer to 1 in 350. Averaged across the ~3 million deployment tours those same service members logged, the per-tour death rate is closer to 1 in 425. That is meaningfully higher than most civilian categories on this site — about 75 times the lifetime risk of dying in a plane crash for a regular flyer — but also far below the priors set by older wars: the US WWII cohort lost roughly 1 in 40 of the 16 million people who served, a rate almost seven times higher than the post-9/11 figure.

The within-subgroup heterogeneity is the real story. Combat arms soldiers in forward roles during 2004-2007 Iraq or 2009-2011 Afghanistan faced per-deployment rates several times higher than the all-forces average; support roles at secure bases faced rates much lower. Era matters more than anything else: Russian forces in Ukraine have sustained an estimated ~165,000 deaths from a force on the order of 1-1.5 million across 2022-2024, an order of magnitude above the US post-9/11 figure, and WWII and WWI Eastern Front rates were higher still. The “1 in 270” headline is a scale marker for one specific well-measured modern conflict. It is not a forecast for any future one.

Claim ledger

Every number below is what each source reported, with the verbatim quote we relied on and how we arrived at our figure. Click any link to verify directly.

  1. [1] Costs of War Project, Watson Institute for International and Public Affairs, Brown University — U.S. Military, Veterans, Contractors & Allies
    U.S. Military, Veterans, Contractors & Allies
    Statistic
    Over 7,053 US service members died in the post-9/11 wars; between 1.9 and 3 million US service members served in military operations in Afghanistan, Iraq, and related theaters, with over half deploying more than once.
    Excerpt
    “"Over 7,053 U.S. service members died in the post-9/11 wars. Between 1.9 and 3 million U.S. service members served in military operations in Afghanistan, Iraq, and related theaters, and over half of them deployed more than once." ”
    Source data from
    2023-09-01
    Accessed
    2026-04-11 · archived copy
    Calculation
    The Costs of War Project aggregates DoD DCAS casualty totals with VA and Census deployment counts. Dividing 7,053 total US service member deaths by 1.9 million unique deployed service members ≈ 3.71e-3, or roughly 1 in 270 per person who deployed during the post-9/11 wars. Using the upper Costs of War servicemember figure of 3 million (which counts more peripheral deployments) pushes the denominator up and the rate down to roughly 1 in 425. The 1.9M-denominator figure is used as the headline because it matches the Institute of Medicine (NCBI source below) count of unique OEF/OIF deployers and because it is the population most readers would think of when they picture "a soldier who went to the war". Per-tour (not per-person) rates are lower still, because service members averaged ~1.6 deployments each: roughly 7,053 / 3,000,000 tours ≈ 1 in 425 per deployment.
    Independence
    Costs of War draws its US military death count from the DoD Defense Casualty Analysis System (DCAS), which is the same upstream source the IOM/NCBI volume below used. Treat the two sources as consistent rather than fully independent on the death-count side; they are independent on the servicemember-count side, which Costs of War derives from Census/VA data while the IOM derived it from DoD personnel tempo reports.
  2. [2] Institute of Medicine (National Academies Press), National Center for Biotechnology Information bookshelf — Operation Enduring Freedom and Operation Iraqi Freedom: Demographics and Impact (in Returning Home from Iraq and Afghanistan)
    Operation Enduring Freedom and Operation Iraqi Freedom: Demographics and Impact (in Returning Home from Iraq and Afghanistan)
    Statistic
    Over 1.9 million US military personnel deployed in 3 million tours of duty of more than 30 days under OEF/OIF; as of November 24, 2009, 5,286 US troops had died and 36,021 had been wounded.
    Excerpt
    “"Since the beginning of the wars in Afghanistan and Iraq in 2001, over 1.9 million US military personnel have been deployed in 3 million tours of duty lasting more than 30 days as part of Operation Enduring Freedom (OEF) or Operation Iraqi Freedom (OIF)." ”
    Source data from
    2013-03-12
    Accessed
    2026-04-11 · archived copy
    Calculation
    The IOM volume is the peer-reviewed benchmark for OEF/OIF deployment totals and gives the 1.9 million unique-deployer figure used in the normalized calculation. Its November 2009 snapshot of 5,286 deaths across roughly the first eight years of the wars implies an average of ~660 US military deaths per year during the peak of OEF/OIF, or roughly 1 hostile+non-hostile death per ~360 deployed service members at that point in the conflict — consistent with the 1-in-270 figure after the wars continued through 2021 and the cumulative death count reached ~7,053.
    Independence
    The IOM’s casualty total is drawn directly from DoD reporting, so it is not independent of DCAS on the death-count pipeline. Cited here primarily for the peer-reviewed deployment-count denominator.
  3. [3] Mediazona, in collaboration with BBC Russian Service — Russian losses in the war with Ukraine — Mediazona verified count
    Russian losses in the war with Ukraine — Mediazona verified count
    Statistic
    200,186 Russian military deaths confirmed by name as of February 2026; methodology captures estimated 45-65% of actual deaths
    Excerpt
    “"On 24 February 2026, the fourth anniversary, the total exceeded 200,000 entries: 200,186 names were published." ”
    Source data from
    2026-02-24
    Accessed
    2026-04-12 · archived copy
    Calculation
    Provides the formal citation for the Russian casualty estimate referenced in the regional_breakdown. Each entry requires verification from official Russian sources, obituaries, social media posts with photograph matching, or cemetery photographs. Automated de-duplication. The 45-65% capture rate estimate comes from cross-referencing with Probate Registry excess male mortality analysis.
    Independence
    Independent of US DoD DCAS and Brown University Costs of War — different conflict, different methodology (open-source intelligence vs official military records).

412 risks with measured probability
1 in 10 1 in 100 1 in 1K 1 in 10K 1 in 100K 1 in 1M 1 in 10M 1 in 100M 1 in 1B certain rarer → Cosmetic surgery abroad risk — 1 in 10 Infant sugar/salt and adult disease — 1 in 10 Endometriosis — 1 in 10 Hair transplant Turkey risk — 1 in 10 Knee replacement — 1 in 10 Chronic painkillers — 1 in 10 Elderly abandonment — 1 in 9.1 Complete tooth loss — 1 in 9.1 Alzheimer's — 1 in 8.3 Sleep deprivation — 1 in 8.3 Smokeless tobacco — 1 in 8.3 Cycling w/o helmet — 1 in 8.0 Bruxism tooth damage — 1 in 7.7 Vision loss — 1 in 6.7 Hernia from lifting — 1 in 6.7 Hip fracture risk — 1 in 6.7 Regular drinking — 1 in 6.7 First heart attack — 1 in 5.9 Infertility — 1 in 5.7 5+ years paid LTC — 1 in 5.6 CTE (football) — 1 in 5.0 Major depression — 1 in 4.9 Hiking injury — 1 in 4.8 Infection from sharing food with child — 1 in 4.2 Lyme disease — 1 in 4.0 Loneliness & health — 1 in 3.8 Job loss & depression — 1 in 3.7 Inheriting AUD risk — 1 in 3.5 Alcohol use disorder — 1 in 3.4 Menopause CV risk acceleration — 1 in 3.0 Silent diabetes — 1 in 3.0 Flying with cold — 1 in 2.9 Tick illness (forest) — 1 in 2.9 Silent high cholesterol — 1 in 2.9 Grandparent loss in childhood — 1 in 2.8 Pacifier floor drop — 1 in 2.8 Drug-resistant infection — 1 in 2.6 No marrow match — 1 in 2.4 Nursing home admission — 1 in 2.2 Skipping dental checkups — 1 in 2.1 False-positive mammogram — 1 in 2.0 Regular smoking — 1 in 2.0 Travelers' diarrhea — 1 in 2.0 Adventure sports — 1 in 1.8 Family caregiver probability — 1 in 1.8 LTC need after 65 — 1 in 1.8 Widowhood probability — 1 in 1.7 Unprotected sex — 1 in 1.5 Silent hypertension — 1 in 1.3 Chronic back pain — 1 in 1.3 Hand hygiene — 1 in 1.0 Cancer (any) — 1 in 7.1 E-scooter no helmet — 1 in 4.5 E-bike no helmet — 1 in 4.0 Mishandled luggage — 1 in 3.7 Deer collision — 1 in 2.7 At-fault injury crash — 1 in 2.5 Flight cancellation — 1 in 1.8 Trip disruption: war or disaster — 1 in 1.7 Home burglary (global) — 1 in 9.1 Hitchhiking assault — 1 in 8.8 Mail check fraud — 1 in 7.7 Child sexual abuse — 1 in 6.8 Stalking — 1 in 6.2 Student sexual assault — 1 in 5.7 Domestic violence — 1 in 3.7 Night walk assault — 1 in 3.6 Bicycle theft — 1 in 2.9 Sexual assault — 1 in 2.9 Home burglary — 1 in 2.6 Sexual harassment (lifetime) — 1 in 1.6 Water scarcity — 1 in 2.5 Carrington-class solar storm — 1 in 1.9 WAIS tipping point — 1 in 1.1 Indoor cat escape harm — 1 in 10 Off-leash dog bite — 1 in 8.9 Rabbit dies in 4 years — 1 in 3.3 Dog bite (non-fatal) — 1 in 1.8 Hamster dies before teenager — 1 in 1.0 Vitamin D gap — 1 in 2.9 Undercooked food — 1 in 1.6 Raw meat cross-contamination — 1 in 1.4 Food left out — 1 in 1.2 AI voice scam — 1 in 2.9 Online scam loss — 1 in 2.5 Teen cyberbullying — 1 in 2.0 Kids & explicit content — 1 in 1.9 Data breach — 1 in 1.1 Miscarriage — 1 in 6.7 Teen suicide attempt — 1 in 5.6 Postpartum depression — 1 in 4.8 Painkiller before infant vaccination — 1 in 3.8 Excessive pregnancy weight — 1 in 2.6 Unvaxxed child & measles — 1 in 2.0 Elder fraud loss — 1 in 10 Pension fund collapse — 1 in 10 Personal bankruptcy — 1 in 10 Housing crash — 1 in 8.3 Crypto total loss — 1 in 6.7 IRS audit — 1 in 6.7 Visa overstay deportation — 1 in 5.6 Long term disability working age — 1 in 4.0 Student loan default — 1 in 3.8 Whistleblower retaliation — 1 in 3.2 Career obsolescence — 1 in 2.9 Forced job exit before retirement — 1 in 2.9 Retirement shortfall — 1 in 2.6 Divorce — 1 in 2.4 Burst pipe damage — 1 in 2.2 Workplace bullying — 1 in 2.1 Deportation (undocumented) — 1 in 1.8 Funeral cost shock — 1 in 1.8 Identity theft — 1 in 1.7 Credit card fraud — 1 in 1.5 School bullying — 1 in 1.5 Insurance claim denial — 1 in 1.4 Frontline soldier casualty — 1 in 1.3 Economic recession — 1 in 1.0 Stock market crash — 1 in 1.0 Hail roof damage — 1 in 3.0 Dry toilet paper harm — 1 in 100 Secondhand smoke — 1 in 91 Gaming disorder (adults) — 1 in 83 High-heel ER visit — 1 in 79 Child throwing object — 1 in 67 Medication reaction — 1 in 58 Cat litter toxoplasmosis — 1 in 48 Mental health LTD claim — 1 in 45 Drug overdose — 1 in 42 Benzo dependence — 1 in 40 Tap water lead — 1 in 40 Medication misuse — 1 in 35 Traumatic brain injury — 1 in 33 Hospital infection — 1 in 31 Air pollution — 1 in 29 End-stage kidney disease — 1 in 29 Traveler's diarrhea (water) — 1 in 26 Skiing injury — 1 in 26 Bipolar disorder — 1 in 23 Dental tourism complication — 1 in 20 Pet parasites — 1 in 20 Undiagnosed ADHD — 1 in 20 Adult-onset food allergy — 1 in 19 Indoor cooking smoke — 1 in 18 Non-Alzheimer's dementia — 1 in 17 Working-age disabling stroke — 1 in 17 Cannabis use disorder — 1 in 16 Stroke — 1 in 15 Parent death/disability — 1 in 14 Severe hearing loss — 1 in 14 Type 2 diabetes — 1 in 13 Appendicitis — 1 in 13 Untreated depression — 1 in 13 Untreated back pain disability — 1 in 13 Heart disease — 1 in 12 Medical error death — 1 in 12 Compulsive sexual behavior — 1 in 12 Eating disorder — 1 in 11 Hip replacement — 1 in 11 Kidney stones — 1 in 11 Sedentary lifestyle — 1 in 11 Salon infection — 1 in 11 Ovarian cancer — 1 in 91 Colorectal cancer — 1 in 77 Breast cancer — 1 in 59 Liver cancer — 1 in 59 Lung cancer — 1 in 56 Prostate cancer — 1 in 50 Melanoma (UV) — 1 in 29 Low-fiber CRC risk — 1 in 23 Red meat & CRC — 1 in 21 Charred meat & cancer — 1 in 20 Maintenance crash — 1 in 83 Driving on sedating meds — 1 in 77 Texting + driving — 1 in 56 Driving after cannabis — 1 in 53 Eating while driving — 1 in 53 Unbelted crash death — 1 in 53 Speeding 20% over limit — 1 in 48 Motorcycle no helmet — 1 in 45 Spaceflight (astronaut) — 1 in 42 Video watching + driving — 1 in 32 Drowsy driving — 1 in 26 E-scooter injury — 1 in 26 Cruise ship norovirus — 1 in 24 Driving at 0.10% BAC — 1 in 16 Catalytic converter theft — 1 in 83 Pickpocketed while traveling — 1 in 38 Stabbed in an assault — 1 in 37 Vehicle theft — 1 in 34 Street robbery / mugging — 1 in 26 Wrongful conviction — 1 in 24 Drink spiking — 1 in 17 Protest under autocracy — 1 in 12 AMOC collapse — 1 in 20 Sting anaphylaxis — 1 in 50 Cat collar injury — 1 in 25 Fish bone injury — 1 in 68 Restaurant food poisoning — 1 in 58 Vegetarian deficiency — 1 in 25 Intimate deepfake — 1 in 25 Social media problematic use — 1 in 13 Infant fall — 1 in 100 Childbirth death (SSA) — 1 in 55 Co-sleeping death — 1 in 43 Toddler stair fall — 1 in 37 Play swing & slide injury — 1 in 33 Autism diagnosis — 1 in 31 C-section complications — 1 in 29 Toy injury requiring ER (child) — 1 in 21 Preeclampsia — 1 in 20 Severe birth tearing — 1 in 17 Gestational diabetes — 1 in 13 Child fall head injury — 1 in 12 Sports betting financial ruin — 1 in 100 Fighter pilot death — 1 in 48 Commercial fishing career death — 1 in 45 Logging career death — 1 in 34 Dying without heir — 1 in 33 Medical bankruptcy — 1 in 25 Compulsive buying disorder — 1 in 20 Rental listing scam loss — 1 in 20 Mortgage foreclosure — 1 in 14 Musculoskeletal LTD claim — 1 in 14 Day-trading losses — 1 in 13 Extremist govt catastrophe — 1 in 13 Hurricane home destruction — 1 in 17 LASIK complications — 1 in 1,000 Infant pool submersion — 1 in 800 MS — 1 in 769 Workplace fatality — 1 in 690 Typhoid fever — 1 in 654 Unsafe imported products — 1 in 565 Brain aneurysm — 1 in 400 COVID-19 — 1 in 400 Fireworks injury — 1 in 385 Sickle cell disease — 1 in 365 Counterfeit medicine — 1 in 361 Spinal cord injury — 1 in 313 Childhood cancer diagnosis — 1 in 285 Next pandemic death — 1 in 208 Dengue (travel) — 1 in 200 Skipping daily showers — 1 in 200 Not scrubbing feet — 1 in 200 Marrow donation risk — 1 in 167 Schizophrenia — 1 in 143 Accidental fall — 1 in 135 Parkinson's — 1 in 125 Sudden death during exercise — 1 in 123 Suicide (US) — 1 in 121 Opioid addiction — 1 in 114 Tuberculosis (global) — 1 in 108 Radon cancer — 1 in 435 Testicular cancer — 1 in 250 Cervical cancer — 1 in 167 Pancreatic cancer — 1 in 125 Pedestrian death — 1 in 806 Motorcycle crash — 1 in 694 Boating drowning — 1 in 685 Driver kills pedestrian — 1 in 552 Phone-distracted walking injury — 1 in 400 EV battery fire — 1 in 333 Cyclist killed by car — 1 in 196 Hand-held phone call + driving — 1 in 143 Petrol car fire — 1 in 125 Self-driving car fatality — 1 in 115 Car crash — 1 in 105 Firefighter duty death — 1 in 455 Police duty death — 1 in 313 Homicide — 1 in 287 Pig-butchering scam — 1 in 106 Extreme heat — 1 in 333 Climate change death — 1 in 204 Swallowed bee/wasp — 1 in 500 Bat bite & rabies — 1 in 238 Mosquito-borne disease — 1 in 190 Food poisoning (global) — 1 in 317 Solar panel fire — 1 in 667 Untreated childhood scoliosis — 1 in 1,000 Child window fall — 1 in 855 Walker stair fall — 1 in 625 Baby walker injury — 1 in 455 Maternal mortality — 1 in 272 Untreated childhood flat feet — 1 in 250 Maternal age & birth defects — 1 in 200 Child death (<18) — 1 in 143 Caving career death — 1 in 167 EMS duty death — 1 in 794 Civilian war casualty — 1 in 499 Soldier in combat — 1 in 270 Mining career death — 1 in 214 Gambling financial ruin — 1 in 159 Wildfire home destruction — 1 in 120 Lightning home fire — 1 in 105 Malaria (travel) — 1 in 10,000 Infection from shared drink — 1 in 10,000 Chagas disease — 1 in 8,475 Wild berry fox tapeworm — 1 in 8,475 Schistosomiasis death — 1 in 6,667 Sudden death (young adult) — 1 in 3,922 Unsafe wiring — 1 in 3,390 Sepsis from wound — 1 in 2,857 Anesthesia awareness — 1 in 2,500 Heat stroke (outdoor) — 1 in 1,905 House fire — 1 in 1,818 Rabies from dogs — 1 in 1,449 Drowning — 1 in 1,379 Shallow-water diving SCI — 1 in 1,111 Choking — 1 in 1,099 EVALI vaping hospitalization — 1 in 1,064 Betel nut cancer — 1 in 1,290 Blood clot (flight) — 1 in 4,651 Killing a cyclist — 1 in 3,937 Teen road-crash death — 1 in 3,030 Child rear bike seat — 1 in 2,500 Child without restraint — 1 in 2,000 Fatal police encounter — 1 in 4,739 Honor killing — 1 in 2,381 Intimate-partner homicide — 1 in 1,767 Hurricane — 1 in 8,929 Drought famine death — 1 in 6,536 Blizzard death — 1 in 4,367 Earthquake — 1 in 3,802 Dog chocolate death — 1 in 2,000 Food poisoning (US) — 1 in 1,862 Fish mercury — 1 in 1,695 Phone/laptop battery fire — 1 in 1,136 SIDS — 1 in 7,143 Laundry pod ingestion — 1 in 6,494 Untreated infant hip dysplasia — 1 in 5,000 Pool drowning — 1 in 2,299 War (civilian) — 1 in 2,000 Fatal bee/wasp sting — 1 in 76,923 Anesthesia death — 1 in 50,000 Dog hot car death — 1 in 41,667 Anaphylaxis — 1 in 27,548 Chiropractic neck manipulation — 1 in 16,667 CO poisoning — 1 in 14,006 Hepatitis A (travel) — 1 in 12,500 Skipping allergy immunotherapy — 1 in 11,111 Acrylamide & cancer — 1 in 16,667 Bus crash — 1 in 100,000 Plane crash — 1 in 58,824 Child pedestrian (residential) — 1 in 45,455 Railroad crossing death — 1 in 20,704 Child bike trailer — 1 in 14,286 Acid attack — 1 in 89,286 Terrorism — 1 in 77,519 Child stranger abduction — 1 in 38,760 Stranger kidnapping — 1 in 35,211 Dowry death — 1 in 13,158 Accidental gun death — 1 in 11,299 Wildfire — 1 in 100,000 Tornado — 1 in 80,645 Tsunami — 1 in 52,632 Ocean drowning — 1 in 29,155 Flood — 1 in 20,202 Landslide death — 1 in 18,416 Supervolcano eruption — 1 in 12,376 Crocodile attack — 1 in 84,746 Bee sting — 1 in 78,927 Fatal scorpion sting — 1 in 26,110 Plastic container leaching — 1 in 16,949 Infant in car seat — 1 in 64,935 Bouncer chair fall — 1 in 60,606 Toddler choking — 1 in 50,000 Unsupervised infant choking — 1 in 50,000 Magnet ingestion — 1 in 12,048 Snorkeling death — 1 in 21,739 Pet in transport — 1 in 20,000 Landmine or UXO injury — 1 in 14,728 Vaccine reaction — 1 in 763,359 Aluminum & Alzheimer's — 1 in 169,492 Residential gas leak — 1 in 140,845 Child hot car death — 1 in 102,041 Glyphosate & cancer — 1 in 1,000,000 Teflon cookware cancer — 1 in 169,492 Roller coaster injury — 1 in 312,500 Cruise ship accident — 1 in 188,679 Ferry sinking — 1 in 133,333 Turbulence injury — 1 in 114,943 School shooting — 1 in 192,308 Mass shooting — 1 in 113,636 Nuclear accident — 1 in 833,333 Avalanche — 1 in 210,526 Lightning — 1 in 209,205 Snake bite — 1 in 884,956 Spider bite — 1 in 833,333 Hippo attack — 1 in 564,972 Dog bite — 1 in 142,045 Pesticide residue — 1 in 1,000,000 Dirty can illness — 1 in 200,000 PLA bioplastic harm — 1 in 169,492 Charger left plugged in — 1 in 200,000 Infant swing death — 1 in 714,286 Child blind cord strangulation — 1 in 416,667 Child plastic bag suffocation — 1 in 263,158 Button battery — 1 in 250,000 Inclined sleeper death — 1 in 238,095 Elevator/escalator death — 1 in 188,324 Japanese encephalitis (travel) — 1 in 2,000,000 Kid + front airbag — 1 in 10,000,000 Asteroid impact — 1 in 1,351,351 Banana spider eggs — 1 in 10,000,000 Shark attack — 1 in 5,681,818 Bear attack — 1 in 3,787,879 Wild berry poisoning — 1 in 2,222,222 Space debris hits property — 1 in 10,000,000 Piranha attack — 1 in 135,135,135 Phone at gas pump — 1 in 1,000,000,000 Phone on plane — 1 in 1,000,000,000 Alien contact — 1 in 169,491,525
Lottery jackpot 1 in 95,238