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Likelier
Health · reviewed 2026-04-11

What are the odds of dying from COVID-19 over the course of the pandemic and endemic era?

Evidence quality 4.88/5

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

D1 Source grounding
5/5
D2 Source authority
5/5
D3 Arithmetic
4/5
D4 Uncertainty
5/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
5/5
D8 Caveat completeness
5/5
Average 4.88/5
Direct evidence

Lifetime probability · lifetime, global adult

1 in 400

0.3% lifetime chance

range 1 in 833 to 1 in 200

lifetime, global adult each band = 10× rarer → zoomed to your factors See full scale →
certain 1 in 1K 1 in 1M 1 in 1B
1 in 8.0 1 in 1,333

● your factors — click this risk ▾ to reveal

≈ As likely as

A single muted grey sphere with a faint corona of radiating lines against a pale grey-blue background, flat vector illustration.

Perceived

Public perception of COVID-19 mortality risk is one of the rare cases where intuition broadly tracked reality, at least in aggregate. Survey work through 2020-2022 found that adults in most high-income countries overestimated their personal age-specific infection fatality rate by roughly an order of magnitude, but correctly identified COVID-19 as one of the leading causes of death in the acute-phase years. By 2024-2026 most readers file COVID-19 somewhere between "serious respiratory illness" and "mostly an older-adult problem", which is approximately where the population-level numbers put it. The perception gap on this fear is smaller than on plane crashes, sharks, or terrorism — and runs in both directions across subgroups.

Rough estimate: Most adults put their cumulative COVID-19 death risk somewhere in the 1-in-100 to 1-in-1,000 range

Source: Preventive Medicine Reports / Ladapo, Rothwell, Ramirez (Franklin Templeton-Gallup) (2022) — Misperceptions of COVID-19 illness risk and preferences for business and school closures in the United States

Actual

~7.1 million confirmed deaths globally (2020-2026); ~18 million excess deaths 2020-2021 alone

global, all ages

Show derivation

This is the hardest entry on the site to normalize, because the “lifetime” frame has to absorb a sharp 2020-2022 acute-pandemic surge followed by a much lower endemic rate from 2023 onwards. The headline 1 in 400 figure uses the Wang et al. (Lancet, 2022) global excess-mortality estimate of 18.2 million deaths (95% UI 17.1-19.6) in 2020-2021, adds roughly 3-5 million further excess deaths in 2022-2026 from the WHO confirmed-death series and IHME-style updates, and divides by a global adult population of ~6.0 billion (age 18+). That yields a cumulative 2020-2026 per-adult probability in the range of 0.0030-0.0037 unadjusted. Rounding down to 0.0025 reflects: (a) a substantial but not full share of excess mortality falling on adults rather than children (the age gradient is enormous — see the regional breakdown), (b) uncertainty in the excess-mortality attribution (some of the 18.2M excess is indirect — delayed care, lockdown-era non-COVID deaths — rather than COVID itself), and (c) the WHO confirmed figure of ~7.1 million as a lower bound anchor. Readers trying to estimate their forward risk should use the endemic annual rate (row 3 of regional_breakdown), not the cumulative figure, because almost all the mortality is already in the past. Scope is deliberately global-adult-lifetime rather than US-adult-lifetime because per-capita pandemic mortality varied by roughly an order of magnitude between countries and the global figure is the honest baseline.

Caveats: The cumulative 2020-2026 figure collapses two very different epidemiological reg…

The cumulative 2020-2026 figure collapses two very different epidemiological regimes into one number. Roughly 80% of all COVID-19 mortality since 2020 occurred in the acute-pandemic 2020-2022 window; the 2023-2026 endemic rate is about 50-100 times lower in absolute terms and continues to decline slowly. A reader trying to estimate their own *forward* COVID-19 mortality risk from 2026 onwards should use the endemic annual row in the regional_breakdown (~1.5 per 100,000 adults per year, concentrated almost entirely in adults aged 70+), not the cumulative figure. The headline 1 in 400 number is retrospective, not predictive. The underlying excess-mortality estimates (WHO ~14.8M, Wang et al. 18.2M, Economist model up to ~22M for 2020-2021) differ because of different modelling choices for countries with incomplete vital-registration data; the uncertainty band on this entry is wide (0.0012-0.005) to honestly reflect that methodological spread. The personal_factor_multipliers are illustrative order-of- magnitude figures from cohort studies and surveillance reports, not a calibrated individual risk calculator. This entry makes no claims about the efficacy, safety, or policy merits of any specific public health intervention — it reports the mortality numbers as published in peer-reviewed and WHO sources and leaves policy debates to other venues.

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
Global cumulative 2020-2026 1 in 400 Wang et al. excess mortality + WHO confirmed series, global adult denominator
US cumulative 2020-2026 1 in 250 ~1.2 million US COVID-19 deaths on ~260 million adults; US per-capita mortality above global average
Endemic annual rate 2024-2026 per-year 1 in 66,667 The ongoing endemic burden is much lower than 2020-2022 — readers estimating forward risk should use this row, not the cumulative one
Adults 80+ cumulative 1 in 25 Age is the single biggest risk factor for any Likelier fear — an order of magnitude above the global adult average

Risks at similar odds

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

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Unsafe imported products

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Childhood cancer diagnosis

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Choking

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Counterfeit medicine

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Compare to:

The cumulative global death toll from COVID-19 depends heavily on which number you trust. The WHO confirmed-deaths series, the conservative lower bound, sits at roughly 7.1 million as of April 2026. The Wang et al. systematic analysis in The Lancet (March 2022) estimated 18.2 million excess deaths worldwide in 2020-2021 alone (95% UI 17.1-19.6), and the WHO’s own excess-mortality model put the 2020-2021 figure at about 14.8 million with a 95% interval extending up to 36 million once 2022-2023 is included. Dividing the middle of that range across a global adult population of roughly six billion gives a cumulative 2020-2026 per-adult mortality of about 1 in 400 — roughly thirty times higher than the lifetime odds of dying in a car crash, but about thirty times lower than the lifetime odds of dying from heart disease.

The interesting thing about COVID-19 on a risk-calibration site is how cleanly its perceived-actual gap closed over time. In 2020 the fear ran well ahead of the numbers for most adults under 60; by 2023 it ran roughly level with the numbers for everyone except the very old and the immunocompromised. That is why this entry is tagged calibrated rather than debunked or underrated: population-level COVID-19 mortality is approximately what most readers now think it is. The harder question is temporal. Almost all of the deaths above happened in a ~30-month window in 2020-2022. By 2024-2026 the endemic annual rate had fallen to roughly 2,000-5,000 US deaths per year — closer to seasonal influenza than to the 2021 peak — which means the cumulative headline number is almost entirely retrospective. A reader using it to estimate their forward risk from 2026 onwards will overstate the danger by roughly two orders of magnitude.

Heterogeneity on this fear is larger than on any other health entry in the Likelier catalogue. The age gradient alone is extraordinary: COVID-19 mortality for a healthy 30-year-old runs somewhere around 100 times lower than for an 80-year-old, a spread bigger than the one on heart disease, cancer, or essentially any other cause of death tracked here. Cross-country variation is almost as large — per-capita excess mortality during 2020-2021 varied by roughly an order of magnitude between (for example) Japan, the United States, and Peru, driven by healthcare-system capacity, population age structure, initial-wave timing, and the reliability of vital-registration systems. A population-average number is, for this fear more than most, a starting point rather than a forecast for any individual reader.

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] World Health Organization — The top 10 causes of death
    The top 10 causes of death

    See all 3 Likelier entries citing this source →

    Statistic
    COVID-19 was directly responsible for 8.8 million deaths in 2021, emerging as the second leading cause of death globally
    Excerpt
    “"COVID-19 was directly responsible for 8.8 million deaths in 2021, and consequently, largely pushed down other leading causes of death by one place. [...] COVID-19 emerging as the second leading causes of death globally." ”
    Source data from
    2024-08-07
    Accessed
    2026-04-11 · archived copy
    Calculation
    WHO's fact sheet establishes 2021 as the peak COVID-19 mortality year with 8.8 million directly attributed deaths globally, making COVID-19 the second leading cause of death that year behind ischaemic heart disease. Combined with the Wang et al. excess-mortality work, which puts 2020-2021 excess deaths at ~18.2 million, this anchors the acute-phase scale used in the normalized calculation. The WHO top-10 fact sheet and the Wang et al. analysis share upstream vital-registration data so are not fully independent — treat as a combined authoritative baseline.
    Independence
    WHO fact sheet and Wang et al. Lancet analysis both draw on the same national vital-registration pipeline through the WHO Global Health Estimates framework. Treat as partially dependent.
  2. [2] The Lancet / COVID-19 Excess Mortality Collaborators (Wang H, et al.) — Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020-21
    Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020-21
    Statistic
    18.2 million (95% UI 17.1-19.6) excess deaths globally attributable to the COVID-19 pandemic, 2020-2021
    Excerpt
    “"18.2 million (95% uncertainty interval 17.1-19.6) people died worldwide because of the COVID-19 pandemic [...] Global rate: 120.3 deaths (113.1-129.3) per 100,000 of the population [...] the full impact of the pandemic has been much greater than what is indicated by reported deaths due to COVID-19 alone." ”
    Source data from
    2022-03-10
    Accessed
    2026-04-11 · archived copy
    Calculation
    Wang et al.'s 18.2M excess deaths over 2 years ≈ 9.1M/year during the acute phase — approximately the same order of magnitude as annual heart disease mortality, which is the comparison most readers find useful. Dividing 18.2M across a global adult population of ~6.0 billion (age 18+) gives ~0.003 direct acute-phase probability, before adding the 2022-2026 endemic-phase excess. The 120.3 per 100,000 per-year crude rate is the cleanest cross-country anchor. Country-level highs — India 4.07M, USA 1.13M, Russia 1.07M — show the order-of-magnitude cross-national spread the regional_breakdown rows are drawn from. The paper explicitly notes its estimates "far exceed" the 5.94M officially reported deaths through end-2021, justifying the gap between the WHO confirmed-death anchor and the excess-mortality headline.
    Independence
    Shares vital-registration upstream with WHO Global Health Estimates; the Wang et al. model adds independent statistical reconstruction for countries with weak registration systems but is not fully independent of WHO official counts.
  3. [3] World Health Organization — WHO COVID-19 Dashboard — Deaths
    WHO COVID-19 Dashboard — Deaths
    Statistic
    ~7.1 million confirmed COVID-19 deaths reported to WHO worldwide (cumulative through 2026); WHO excess mortality estimates 14.8 million (95% UI 13.3-16.6 million) for 2020-2021
    Excerpt
    “"Globally, from 3 January 2020 to 3 April 2026, there have been over 7 million confirmed deaths reported to WHO. The WHO excess mortality estimates suggest the full death toll was approximately 14.8 million for 2020 and 2021 alone." ”
    Source data from
    2026-04-03
    Accessed
    2026-04-12 · archived copy
    Calculation
    The WHO COVID-19 Dashboard provides the authoritative running total of confirmed deaths reported by member states. The 7.1M confirmed figure is the lower bound used in the uncertainty band. The WHO's own excess-mortality model (14.8M for 2020-2021, 95% UI extending up to ~36M when 2022-2023 is included) anchors the upper end. Used as the official real-time data source that the Wang et al. Lancet excess-mortality analysis was designed to complement.
    Independence
    WHO Dashboard is the primary data pipeline — the Wang et al. Lancet paper and the WHO top-10 causes fact sheet both draw on this same upstream. Treat as the canonical running total, not an independent third estimate. running total and for cross-linking the primary authoritative sources.
  4. [4] Our World in Data — Coronavirus (COVID-19) Deaths
    Coronavirus (COVID-19) Deaths
    Statistic
    Confirmed COVID-19 deaths substantially understate the true pandemic death toll; excess mortality is the more accurate measure
    Excerpt
    “"Research has shown that these figures are an underestimate of the total pandemic death toll. [...] This is because of limited testing, poorly functioning death registries, challenges in determining the cause of death, and disruptions during the pandemic. [...] The actual death toll from COVID-19 is likely to be higher than the number of confirmed deaths." ”
    Source data from
    2025-12-01
    Accessed
    2026-04-11 · archived copy
    Calculation
    OWID's COVID deaths page is the methodological anchor for why this entry headlines the Wang et al. excess-mortality number rather than the WHO confirmed-death figure. OWID explicitly documents that confirmed counts in many countries — particularly India, Russia, and much of sub-Saharan Africa — are large multiples below actual excess mortality, and directs readers to excess-mortality series for cross-country comparisons. Used as the authoritative reference for the methodological choice, not as an independent headline number.
    Independence
    OWID compiles the WHO, JHU CSSE, and country-level vital-registration series directly; treat as a processing layer over the same upstream, not an independent estimate.

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