Skip to content
Likelier
Natural · reviewed 2026-05-16

What are the odds of the West Antarctic Ice Sheet's tipping point being crossed in your lifetime?

Evidence quality 4.25/5

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
4/5
D4 Uncertainty
4/5
D5 Scope
4/5
D6 Prose
4/5
D7 Perception honesty
4/5
D8 Caveat completeness
5/5
Average 4.25/5
Direct evidence

Lifetime probability · lifetime, global adult

1 in 1.1

90% lifetime chance

Most people underestimate this.

range 1 in 3.3 to 1 in 1.0

lifetime, global adult each band = 10× rarer → See full scale →
certain 1 in 1K 1 in 1M 1 in 1B

≈ As likely as

A flat stylized representation of Antarctica as an ice-covered landmass from above, flat vector in pale blue and white tones.

Perceived

West Antarctic Ice Sheet instability is discussed in scientific literature and climate policy circles but has not yet acquired a fixed cultural image in the way that flooding cities or forest fires have. Most people who have heard of it know roughly that it would mean substantial sea level rise if it collapsed, and that Antarctica is melting. What is not widely understood is that the science of tipping points distinguishes between the crossing of an irreversible threshold (the tipping point trigger) and the full expression of sea level rise — which could take centuries. Nor is it widely understood that under current emissions trajectories, multiple independent modelling studies assign trigger probabilities of over 90% before 2100. The risk is substantially underrated in public consciousness, which tends to frame Antarctic ice loss as a slow-moving and distant problem rather than a potentially committed one.

Rough estimate: ~47.7% of US adults report being 'afraid' or 'very afraid' of global warming and climate change broadly (Chapman University Survey, Wave 10, 2024) — no WAIS-specific survey exists

Source: Chapman University (2024) — Chapman University Survey of American Fears, Wave 10 — Complete List of Fears 2024

Actual

>90% probability of crossing the WAIS tipping threshold before 2100 (current emissions, SSP2-4.5)

Global — crossing the WAIS tipping point is a planetary-scale event, not population-specific

Show derivation

Wunderling et al. (2025, Earth System Dynamics) modelled the probability of triggering sixteen climate tipping points under various emissions scenarios, using a coupled tipping-element model with observationally constrained parameters. Under SSP2-4.5 (the scenario closest to current global policy commitments, projecting ~2.6-2.8°C warming by 2100), the WAIS triggering probability exceeded 90%. This is a trigger probability — the probability that global warming crosses the temperature threshold beyond which WAIS retreat becomes self-sustaining — not the probability of full collapse occurring within a human lifetime. Full collapse of the WAIS would release approximately 3.3-5.3 metres of sea level rise, but over timescales of decades to millennia depending on the forcing scenario and feedback dynamics. The crossing of the tipping threshold commits the world to that eventual outcome, but most of the sea level rise would occur well beyond the focal adult's lifetime. Armstrong McKay et al. (2022, Science) estimated the central threshold at ~1.5°C above pre-industrial, with a range of 1-3°C — a level that current trajectories suggest could be exceeded in the 2030s. IPCC AR6 WG1 (2021) uses a "low likelihood, high impact" storyline for processes contributing more than 1 metre of additional sea level rise before 2100 from ice sheet instability, while acknowledging "deep uncertainty" on timing. The uncertainty range (30-99%) captures the broad range from aggressive mitigation scenarios (SSP1-1.9, where trigger probability is lower but still substantial) to business-as-usual pathways.

Caveats: The >90% figure is a tipping-point trigger probability under current emissions (…

The >90% figure is a tipping-point trigger probability under current emissions (SSP2-4.5), not a probability of full WAIS collapse or of sea level rise reaching catastrophic levels within a human lifetime. Full collapse of the WAIS would take decades to millennia after the tipping threshold is crossed — the sea level consequences unfold far beyond the focal adult's lifetime in most scenarios. The central threshold of ~1.5°C (Armstrong McKay 2022) may already have been exceeded transiently: global mean temperature briefly exceeded 1.5°C above pre-industrial in 2023-2024, though the relevant metric for WAIS is the sustained multidecadal average rather than peak annual anomaly. IPCC AR6's more cautious framing ("medium confidence no abrupt collapse before 2100") differs from Wunderling 2025's >90% trigger probability because the two assessments measure different things: IPCC assesses "abrupt collapse" (rapid dramatic change) in CMIP models that do not simulate WAIS instability; Wunderling models crossing the threshold that commits eventual collapse in a tipping-element framework. These are compatible rather than contradictory assessments about different processes. Marine Ice Cliff Instability (MICI), a mechanism that could dramatically accelerate WAIS disintegration, remains contested and is excluded from IPCC's main projections.

Risks at similar odds

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

Natural

Water scarcity

What are the odds of experiencing severe water scarcity in your lifetime?

Natural

AMOC collapse

What are the odds of the AMOC experiencing an abrupt collapse before the end of your lifetime?

Natural

Carrington-class solar storm

What are the odds of a catastrophic solar storm hitting Earth?

Natural

Climate change death

What are the odds of dying from the effects of climate change?

Natural

Extreme heat

What are the odds of dying from extreme heat?

Natural

Hurricane

What are the odds of being killed by a hurricane (tropical cyclone)?

Natural

Asteroid impact

What are the odds of dying from an asteroid or comet impact?

Natural

Avalanche

What are the odds of dying in an avalanche?

Compare to:

The West Antarctic Ice Sheet contains enough ice to raise global sea levels by 3.3 to 5.3 metres if fully disgorged into the ocean — an amount sufficient to permanently inundate coastal cities from Miami to Shanghai to Amsterdam. The debate is not whether this would be consequential but whether the process is already irreversibly committed. Wunderling et al. (2025, Earth System Dynamics), using a coupled tipping-element model parameterised from Armstrong McKay et al.’s (2022, Science) threshold synthesis, found that under SSP2-4.5 — the scenario closest to current global policy commitments — the probability of the WAIS crossing its tipping threshold before 2100 exceeded 90%. Armstrong McKay estimated the central threshold at roughly 1.5°C of global warming above pre-industrial levels, within the Paris Agreement’s target range.

The critical distinction is between triggering and completing. When the WAIS tipping point is crossed, global warming has reached a level at which ice retreat becomes self-sustaining: ocean warming beneath the ice shelves melts the underside, the grounding line retreats into deeper water, and the geometry of the ice sheet means retreat accelerates rather than stabilising. But this process unfolds over decades to millennia, not years. Naughten et al. (2023, Nature Climate Change) found that ice-shelf warming in the Amundsen Sea sector is already committed to accelerate at roughly triple the historical rate until at least 2045 regardless of near-term emissions choices — the ocean warming that drives basal melt is locked in by historical emissions. For most people alive today, the sea level consequences lie far beyond their lifetimes even if the threshold is crossed tomorrow. IPCC AR6 frames this as a “low likelihood, high impact” storyline while acknowledging “deep uncertainty.”

The Thwaites Glacier, sometimes called the “Doomsday Glacier,” holds about 65 centimetres of global sea level equivalent and is considered the most vulnerable sector of the WAIS. Satellite altimetry and ocean observations show active basal melting, and the glacier’s “ice shelf” — the floating apron that pins the inland ice — is cracking in ways that some glaciologists believe could accelerate collapse within this century. None of this translates straightforwardly into a personal risk number: the framing here is the probability of a planetary commitment being made in a person’s lifetime, not the probability of dying from it. That probability — on current trajectories — is what makes this entry unusual on this site: the risk is not rare but the consequences are diffuse, slow, and fall predominantly on future generations.

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] Earth System Dynamics — Wunderling, Sakschewski, Rockström, Flores, Hirota, Staal, 2025 — High probability of triggering climate tipping points under current policies modestly amplified by Amazon dieback and permafrost thaw
    High probability of triggering climate tipping points under current policies modestly amplified by Amazon dieback and permafrost thaw
    Statistic
    WAIS triggering probability >90% under SSP2-4.5 (current policy scenario); all sixteen tipping elements analyzed show elevated triggering probabilities under policies as of 2025
    Excerpt
    “"Under SSP2-4.5, which best represents current global climate policies, the probability of triggering West Antarctic Ice Sheet collapse exceeds 90%... The high probability of triggering multiple climate tipping points underscores the urgency of emissions reductions to remain within safer temperature bounds." ”
    Source data from
    2025-05-01
    Accessed
    2026-05-09 · archived copy
    Calculation
    Wunderling et al. 2025 is the primary quantitative source for the >90% headline. SSP2-4.5 is described as the scenario "best representing current global climate policies" at time of publication (2025). The triggering probability means the probability that global temperature crosses the threshold at which WAIS retreat becomes self-sustaining and irreversible on multi-century timescales. The paper uses a coupled tipping-element model incorporating interactions between tipping elements (e.g., Amazon dieback slightly amplifying WAIS triggering probability through global mean temperature). The core result for WAIS is robust to whether or not Amazon and permafrost interactions are included.
    Independence
    Wunderling et al. use a tipping-element network model parameterised from the Armstrong McKay 2022 threshold estimates, which are themselves derived from paleoclimate evidence and process understanding. This is a different approach from IPCC AR6's process-based climate model ensemble, though both draw on overlapping paleoclimate evidence for threshold estimates.
  2. [2] Science — Armstrong McKay, Staal, Abrams, Winkelmann, Sakschewski, Loriani, Fetzer, Cornell, Rockström, Lenton, 2022 — Exceeding 1.5°C global warming could trigger multiple climate tipping points
    Exceeding 1.5°C global warming could trigger multiple climate tipping points
    Statistic
    WAIS central temperature threshold ~1.5°C (range 1-3°C); 'likely' to be triggered above 1.5°C of global warming; full WAIS collapse would raise sea level by more than 3.3 metres over centuries
    Excerpt
    “"The West Antarctic Ice Sheet has a central threshold of approximately 1.5°C of global warming above pre-industrial levels, with a range of 1 to 3°C... Above 1.5°C, the WAIS becomes 'likely' to cross its tipping threshold, committing to eventual collapse over decades to millennia and a sea level contribution of 3.3-5.3 metres." ”
    Source data from
    2022-09-09
    Accessed
    2026-05-09 · archived copy
    Calculation
    Armstrong McKay et al. 2022 is the most comprehensive recent revision of climate tipping point thresholds, synthesising paleoclimate evidence and process understanding for sixteen tipping elements. The WAIS threshold lowering from the previous Lenton 2008 estimate of ~3-5°C to ~1.5°C was significant: it places the threshold within the Paris Agreement target range, meaning that even the most ambitious emissions reduction targets do not guarantee avoiding WAIS commitment to collapse. The 1-3°C range captures deep uncertainty in the threshold itself.
    Independence
    Armstrong McKay et al. synthesise paleoclimate and process evidence using a different methodology than Wunderling et al.'s probabilistic network model. Both reach compatible conclusions about WAIS proximity to its threshold under current conditions.
  3. [3] Nature Climate Change — Naughten et al., 2023 — Unavoidable future increase in West Antarctic ice-shelf melting over the twenty-first century
    Unavoidable future increase in West Antarctic ice-shelf melting over the twenty-first century
    Statistic
    All four tested emissions scenarios produce similar accelerated Amundsen Sea warming until at least 2045; ice-shelf warming projected at ~triple the historical rate regardless of near-term mitigation
    Excerpt
    “"These results suggest that mitigation of greenhouse gases now has limited power to prevent ocean warming that could lead to the collapse of the West Antarctic Ice Sheet... Under all scenarios, the Amundsen Sea is committed to accelerated warming at approximately triple the historical rate until at least 2045." ”
    Source data from
    2023-10-23
    Accessed
    2026-05-09 · archived copy
    Calculation
    Naughten et al. 2023 focuses on ocean warming beneath WAIS ice shelves in the Amundsen Sea sector — the primary driver of ice shelf basal melt and the mechanism by which warming triggers WAIS instability. The finding that all emissions scenarios produce similar warming until 2045 is significant: near-term mitigation cannot prevent the accelerated melting already committed by historical emissions. This does not mean full collapse is committed, only that the process driving it is locked in for at least two decades. The paper's single-model design limits certainty, but it uses a high-resolution ocean model specifically designed for Amundsen Sea dynamics.
    Independence
    Naughten et al. use an ocean model focused on the Amundsen Sea specifically, rather than the global climate models used by Wunderling 2025 and Armstrong McKay 2022. The result addresses ice-shelf basal melt rates rather than full tipping point probability, providing a physically independent mechanism-level corroboration.
  4. [4] Intergovernmental Panel on Climate Change (IPCC), Working Group I, Sixth Assessment Report — Climate Change 2021: The Physical Science Basis — Chapter 9: Ocean, Cryosphere and Sea Level Change
    Climate Change 2021: The Physical Science Basis — Chapter 9: Ocean, Cryosphere and Sea Level Change

    See all 2 Likelier entries citing this source →

    Statistic
    Antarctic ice mass loss 'likely' to continue all century; MISI physically plausible and observed; 'low likelihood, high impact' storyline for >1m additional SLR from ice sheet instability; deep uncertainty acknowledged
    Excerpt
    “"There is medium confidence that significant Antarctic ice mass loss will not involve an abrupt collapse before 2100... Marine Ice Sheet Instability (MISI) is physically plausible, has been observed in Thwaites Glacier, and would result in substantial irreversible sea level rise if triggered... Low-likelihood, high-impact storylines include scenarios leading to more than one metre of additional sea level rise from ice sheet instability before 2100." ”
    Source data from
    2021-08-09
    Accessed
    2026-05-09 · archived copy
    Calculation
    IPCC AR6 does not assign a numerical probability to WAIS collapse before 2100, instead using "medium confidence that [abrupt collapse] will NOT happen" — implying some non-trivial probability that it will. The Bamber et al. 2019 structured expert judgment cited by AR6 gave WAIS sea level contribution by 2100 as median 8-18 cm with 95th percentile up to 44-93 cm depending on warming scenario — reflecting deep uncertainty but not ruling out large contributions. IPCC AR6's position is more cautious than Wunderling 2025 because it relies on CMIP model ensembles that do not simulate WAIS collapse, rather than the tipping-point network models used by Wunderling.

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