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Likelier

Perceived fear vs. actual probability

What are the odds of getting a serious infection during a hospital stay?

Lifetime probability · activity

~1 in 31

per US hospital admission (any HAI)

3.2% lifetime chance

Most people underestimate this.

Scopes vary — shown as typical adult lifetime odds. See methodology.

Health · reviewed 2026-04-11
Evidence quality 4.5/5

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
4/5
D5 Scope
5/5
D6 Prose
4/5
D7 Perception honesty
4/5
D8 Caveat completeness
5/5
Average 4.5/5
Direct evidence
Source Government statistic · Centers for Disease Control and Prevention (CDC)
lifetime, activity-specific each band = 10× rarer → zoomed to your factors See full scale →
certain 1 in 1K 1 in 1M 1 in 1B
1 in 3.9 1 in 31

● your factors — click this risk ▾ to reveal

  1. Your factors
A single empty hospital bed rendered as a minimal flat vector on a muted background.

Perceived

There is no standing survey that isolates fear of a healthcare-associated infection, but the category sits in a near-universal blind spot. Patients being wheeled into an acute-care bed tend to model the hospital as a place that neutralises infection risk, not a place that generates it. The iatrogenic framing — that roughly one admission in thirty picks up a bloodstream, surgical-site, urinary, pneumonia, or C. difficile infection that was not present on arrival — is absent from almost every informed- consent conversation and from almost every lay intuition about hospital safety.

Rough estimate: most patients assume the per-admission rate is well under 1 in 1,000

Source: editorial intuition, not polled

Actual

~1 in 31 US hospital patients has at least one HAI on any given day

US acute care hospital patients

Show derivation

The headline figure is per hospital admission, not per adult lifetime. CDC's 2015 point-prevalence survey (the follow-up to Magill et al. 2014) found that about 3% of hospitalised patients had one or more HAIs on any given day, which the agency rounds to "1 in 31 hospital patients." Magill et al. 2014 reported a slightly higher 4.0% prevalence (1 in 25) from 2011 data; the 16% relative decline between the two surveys is real and documented. Likelier reports the more recent 2015 figure as the headline (0.032) with Magill's 0.040 as the upper end of the uncertainty band. Note that point prevalence slightly understates per-admission cumulative incidence — patients admitted briefly and discharged without an HAI are fully represented in the denominator, but a patient who develops an HAI on day 10 is only counted on days when the infection is present — so the "per admission" framing here is a lower bound. The fatal-HAI per-admission figure (~0.005) comes from 72,000 HAI-associated deaths against roughly 14.4 million annual US acute-care admissions with HAI exposure windows, which is the second regional_breakdown row below.

Caveats: The headline point-prevalence figure ("1 in 31") is a snapshot, not a cumulative…

The headline point-prevalence figure ("1 in 31") is a snapshot, not a cumulative per-admission risk, and slightly understates the probability that a given admission includes an HAI somewhere along its timeline. The WHO per-admission figures (7/100 high-income, 15/100 LMIC) are the cleaner per-admission numbers and are closer to what a patient being admitted should mentally budget. The distribution is also radically non-uniform: a 48-hour observation admission on a general ward is a very different risk than a three-week ICU stay with a ventilator and two central lines, which is what the personal_factor_multipliers above are trying to capture. Finally, the US figure has improved meaningfully since 2011 (a 16% relative decline between Magill 2014 and CDC 2015, with further gains through 2024 in CAUTI and C. difficile), so the headline is a trailing indicator — the 2026 figure is probably somewhat lower than 1 in 31, though no current survey cleanly replaces the 2015 baseline.

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Compare to:

The numbers land in a place most patients do not expect. CDC’s 2015 point-prevalence survey of US acute-care hospitals found that about 1 in 31 hospitalised patients has at least one healthcare-associated infection on any given day, translating to roughly 687,000 HAIs and 72,000 HAI-associated in-hospital deaths per year. The Magill et al. 2014 NEJM survey, using 2011 data, put the equivalent prevalence at 4.0% (about 1 in 25) before the post-2011 decline. Divide the 72,000 deaths across the at-risk admissions window and the per-admission fatal-HAI probability lands somewhere around 1 in 200. Stacked against this entry’s own comparison anchors — a roughly 1-in-58,800 lifetime risk of dying in a plane crash, or a roughly 1-in-93 lifetime risk of dying in a car crash — a single hospital admission’s roughly 1-in-200 fatal-infection risk is one of the highest per-exposure iatrogenic hazards a typical adult will encounter.

What’s in the category is worth seeing up close. Magill reported pneumonia and surgical-site infections tied as the two largest buckets (21.8% each), followed by gastrointestinal infections (17.1%), with C. difficile as the single most common pathogen at 12.1% of all HAIs. Catheter-associated urinary tract infections and central line-associated bloodstream infections round out the top five. These categories are not evenly distributed across hospital geography: the ICU baseline is several multiples above the ward, ventilator-days drive the pneumonia curve almost linearly, and central lines and urinary catheters create the device-associated infections whose rates have fallen the most since the mid-2000s checklist era. The two biggest levers, in every serious review of the literature, are antibiotic stewardship (to contain C. difficile and multidrug-resistant organisms) and barrier precautions plus hand hygiene (to contain everything else).

The global picture is the part that is genuinely underrated. WHO’s 2022 Global Report on Infection Prevention and Control found that 7 per 100 admissions in high-income countries and 15 per 100 admissions in low- and middle-income countries acquire at least one HAI during their stay, with roughly 1 in 10 affected patients dying of the infection. ICU rates in low- and middle-income countries run 2 to 20 times higher than in wealthy-country ICUs. Put plainly: a patient admitted to an ICU in a resource-limited setting faces an HAI probability that approaches a coin flip. For a US reader the headline 1-in-31 figure is the right baseline, with ICU admission, ventilation, central lines, and stays past a week each adding multiplicative risk on top of it. For a global reader the LMIC figures are the ones that dominate the aggregate burden, and they are the least-discussed large public-health statistic on this site.

About 1 in 31 US hospital patients carries a healthcare-associated infection on any given day. Most people picture the hospital as a place that removes infection risk rather than one that can generate it.

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.

3/3 sources independently verified verbatim against the cited source

  1. [1] New England Journal of Medicine / Magill SS, Edwards JR, Bamberg W, et al. — Multistate Point-Prevalence Survey of Health Care-Associated Infections Verified
    Multistate Point-Prevalence Survey of Health Care-Associated Infections
    Statistic
    4.0% point prevalence of HAI among hospitalised patients (95% CI 3.7-4.4); estimated 648,000 patients with 721,800 HAIs in US acute care hospitals in 2011
    Excerpt
    “"Of 11,282 patients, 452 had 1 or more health care-associated infections (4.0%; 95% confidence interval, 3.7 to 4.4)." "We estimated that there were 648,000 patients with 721,800 health care-associated infections in U.S. acute care hospitals in 2011." ”
    Source data from
    2014-03-27
    Accessed
    2026-04-11 · archived copy
    Verification
    Excerpt independently re-fetched and confirmed word-for-word against the cited source during our grounding audit.
    Calculation
    Magill et al. is the canonical US HAI point-prevalence study and the origin of the widely-cited "1 in 25 hospitalised patients has an HAI" figure. Pneumonia (21.8%) and surgical-site infections (21.8%) were the two most common categories, followed by gastrointestinal infections (17.1%, dominated by C. difficile, which was the single most common pathogen at 12.1% of all HAIs). The 4.0% point- prevalence figure anchors the upper end of Likelier's uncertainty band; the 2015 CDC follow-up survey (3%, "1 in 31") is used as the headline because it is more recent and reflects a genuine decline in HAI rates post-2011.
    Independence
    Methodologically upstream of CDC's 2015 survey: both are point-prevalence surveys run through the Emerging Infections Program using the same case definitions, so the two should be read as one dataset compared against itself across years rather than as two fully independent estimates. WHO's global report is independent of both and is the cleaner cross-check.
  2. [2] Centers for Disease Control and Prevention (CDC) — Healthcare-Associated Infections (HAIs) Data Verified
    Healthcare-Associated Infections (HAIs) Data
    Statistic
    ~1 in 31 US hospital patients has at least one HAI on any given day; ~687,000 HAIs and ~72,000 HAI-associated in-hospital deaths in 2015
    Excerpt
    “"On any given day, about one in 31 hospital patients has at least one healthcare- associated infection." "There were an estimated 687,000 HAIs in U.S. acute care hospitals in 2015." "About 72,000 hospital patients with HAIs died during their hospitalizations." ”
    Source data from
    2015-01-01
    Accessed
    2026-04-11 · archived copy
    Verification
    Excerpt independently re-fetched and confirmed word-for-word against the cited source during our grounding audit.
    Calculation
    CDC's 2015 HAI Hospital Prevalence Survey is the direct successor to Magill et al. 2014 and is the source of the headline "1 in 31" figure used throughout this entry. The 72,000 annual HAI-associated in-hospital deaths, divided across roughly ~14.4 million at-risk US acute-care admissions, gives a per-admission fatal-HAI rate of roughly 0.5% — the second regional_breakdown row. The CDC also notes a 16% relative decline in HAI prevalence between 2011 (Magill) and 2015 and further decreases between 2023 and 2024 across CAUTI and C. difficile infections, which is why the 2011 4.0% figure is the ceiling of the uncertainty band rather than the headline.
    Independence
    CDC's 2015 survey shares methodology with Magill et al. 2014 (same point- prevalence design, same Emerging Infections Program network). Treat as a time- series update of the same dataset, not a fully independent estimate.
  3. [3] World Health Organization — WHO launches first ever global report on infection prevention and control Verified
    WHO launches first ever global report on infection prevention and control
    Statistic
    7 per 100 patients in high-income countries and 15 per 100 patients in low- and middle-income countries acquire at least one HAI during hospital stay; ~1 in 10 affected patients dies
    Excerpt
    “"out of every 100 patients in acute-care hospitals, seven patients in high-income countries and 15 patients in low- and middle-income countries will acquire at least one health care-associated infection." "On average, 1 in every 10 affected patients will die from their HAI." ”
    Source data from
    2022-05-06
    Accessed
    2026-04-11 · archived copy
    Verification
    Excerpt independently re-fetched and confirmed word-for-word against the cited source during our grounding audit.
    Calculation
    WHO's 2022 Global Report on Infection Prevention and Control gives the cleanest cross-country comparison. The 7%/15% figures are per admission (cumulative incidence over the stay, not point prevalence), which is why they are higher than the US point-prevalence number used as the headline: a 7% per-admission cumulative incidence in a high-income system is consistent with a ~3% point prevalence on any given day once you account for admission length and infection-onset timing. The 10% HAI case-fatality rate, applied to the WHO high-income figure, gives ~0.7% per-admission fatal-HAI probability, bracketing the CDC-derived 0.5% figure. The 15% LMIC figure is the source of the regional_breakdown row for LMIC admissions below.
    Independence
    Fully independent of Magill and CDC: WHO synthesises hundreds of national surveys across dozens of countries, most of which are not part of the US Emerging Infections Program network. This is the strongest cross-check in the entry.

434 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 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 Skipping care over ICE fear — 1 in 7.1 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 Inheriting AUD risk — 1 in 3.5 Alcohol use disorder — 1 in 3.4 Anxiety disorder — 1 in 3.2 Menopause CV risk acceleration — 1 in 3.0 Silent diabetes — 1 in 3.0 Flying with cold — 1 in 2.9 Job loss & depression — 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 Silent hypertension — 1 in 2.7 Drug-resistant infection — 1 in 2.6 No marrow match — 1 in 2.4 Nursing home admission — 1 in 2.2 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 LTC need after 65 — 1 in 1.8 Widowhood probability — 1 in 1.7 Unprotected sex — 1 in 1.5 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 At-fault injury crash — 1 in 2.9 Deer collision — 1 in 2.7 Car-crash injury — 1 in 2.6 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 2.3 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 9.8 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 Iron gap (women) — 1 in 3.9 Vitamin D gap — 1 in 2.9 Magnesium gap — 1 in 1.9 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 Child head lice — 1 in 2.0 Elder fraud loss — 1 in 10 Pension fund collapse — 1 in 10 Housing crash — 1 in 8.3 IRS audit — 1 in 6.7 Currency collapse — 1 in 5.6 Visa overstay deportation — 1 in 5.6 Subprime auto-loan repossession — 1 in 5.0 Long term disability working age — 1 in 4.0 Student loan default — 1 in 3.8 Whistleblower retaliation — 1 in 3.2 Forced job exit before retirement — 1 in 2.9 Retirement shortfall — 1 in 2.6 BNPL missed payment — 1 in 2.4 Divorce — 1 in 2.4 Burst pipe damage — 1 in 2.2 Workplace bullying — 1 in 2.1 Prolonged grid blackout — 1 in 2.0 Deportation (undocumented) — 1 in 1.8 Funeral cost shock — 1 in 1.7 Identity theft — 1 in 1.7 Credit card fraud — 1 in 1.5 School bullying — 1 in 1.5 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 Problem-tenant loss — 1 in 1.8 LASIK complications — 1 in 100 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 Drug overdose — 1 in 56 Gas-stove asthma in a child — 1 in 50 Cat litter toxoplasmosis — 1 in 48 Mental health LTD claim — 1 in 45 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 Wisdom-tooth surgery — 1 in 22 Dental tourism complication — 1 in 20 Elderly abandonment — 1 in 20 Parkinson's — 1 in 20 Pet parasites — 1 in 20 Undiagnosed ADHD — 1 in 20 Adult-onset food allergy — 1 in 19 Non-Alzheimer's dementia — 1 in 17 Cannabis use disorder — 1 in 16 Stroke — 1 in 15 PTSD — 1 in 15 Severe hearing loss — 1 in 14 Type 2 diabetes — 1 in 13 Appendicitis — 1 in 13 Indoor cooking smoke — 1 in 13 Untreated depression — 1 in 13 Soda and diabetes — 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 Parent death/disability — 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 26 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 Unbelted crash death — 1 in 53 Speeding 20% over limit — 1 in 50 Motorcycle no helmet — 1 in 45 Spaceflight (astronaut) — 1 in 42 Video watching + driving — 1 in 32 Child crash injury — 1 in 27 Drowsy driving — 1 in 26 Cruise ship norovirus — 1 in 24 E-scooter injury — 1 in 10 Pickpocketed while traveling — 1 in 38 Catalytic converter theft — 1 in 37 Knife-involved 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 Keyless relay car theft — 1 in 13 Protest under autocracy — 1 in 12 AMOC collapse — 1 in 20 Sting anaphylaxis — 1 in 50 Cat collar injury — 1 in 25 Restaurant food poisoning — 1 in 58 B12 deficiency — 1 in 28 Vegetarian deficiency — 1 in 14 Intimate deepfake — 1 in 25 Social media problematic use — 1 in 13 Child swallows object (ER) — 1 in 91 Life-threatening birth (US) — 1 in 61 Childbirth death (SSA) — 1 in 55 Toddler stair fall — 1 in 37 Co-sleeping death — 1 in 36 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 Dying without heir — 1 in 100 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 Medical bankruptcy — 1 in 25 Compulsive buying disorder — 1 in 20 Rental listing scam loss — 1 in 20 Losing SNAP under 2025 work rules — 1 in 18 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 NAION (Ozempic) — 1 in 909 Infant pool submersion — 1 in 800 MS — 1 in 769 Workplace fatality — 1 in 690 Typhoid fever — 1 in 654 GLP-1 anesthesia aspiration — 1 in 613 Unsafe imported products — 1 in 565 Brain aneurysm — 1 in 400 COVID-19 — 1 in 400 Fireworks injury — 1 in 385 Too much caffeine — 1 in 366 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 Heat-triggered preterm birth — 1 in 200 Skipping daily showers — 1 in 200 Not scrubbing feet — 1 in 200 Marrow donation risk — 1 in 167 Tick-borne encephalitis — 1 in 167 Schizophrenia — 1 in 143 Accidental fall — 1 in 135 Sudden death during exercise — 1 in 123 Suicide (US) — 1 in 121 Opioid addiction — 1 in 114 Tuberculosis (global) — 1 in 109 HIV diagnosis — 1 in 105 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 709 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 159 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 357 Homicide — 1 in 339 Pig-butchering scam — 1 in 106 Extreme heat — 1 in 333 Climate change death — 1 in 204 Bat bite & rabies — 1 in 278 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 Infant fall — 1 in 500 Baby walker injury — 1 in 455 Maternal mortality — 1 in 272 Maternal age & birth defects — 1 in 200 Child death (<18) — 1 in 103 Caving career death — 1 in 167 EMS duty death — 1 in 909 Civilian war casualty — 1 in 499 Soldier in combat — 1 in 270 Student visa revocation — 1 in 263 Mining career death — 1 in 214 Gambling financial ruin — 1 in 159 Lightning home fire — 1 in 461 Wildfire home destruction — 1 in 120 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 Child nicotine-pouch ingestion — 1 in 7,937 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 Listeria from deli meat — 1 in 6,061 Serious E. coli from fresh produce — 1 in 4,831 Food poisoning (US) — 1 in 1,862 Fish mercury — 1 in 1,695 Fish bone injury — 1 in 1,429 Phone/laptop battery fire — 1 in 4,545 Laundry pod ingestion — 1 in 6,494 Pool drowning — 1 in 5,882 Untreated infant hip dysplasia — 1 in 5,000 SIDS — 1 in 2,398 War (civilian) — 1 in 2,000 Flu brain swelling in a child (IAE/ANE) — 1 in 100,000 Fatal bee/wasp sting — 1 in 76,923 Locally-acquired dengue (continental US) — 1 in 66,667 Anesthesia death — 1 in 45,662 Dog hot car death — 1 in 41,667 Vibrio vulnificus wound infection — 1 in 32,051 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 Post-crash car fire — 1 in 25,000 Railroad crossing death — 1 in 20,576 Car submersion — 1 in 16,667 Child bike trailer — 1 in 14,286 Runway near-miss — 1 in 13,699 Acid attack — 1 in 94,340 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 Post-hurricane heat death — 1 in 20,000 Landslide death — 1 in 18,416 Supervolcano eruption — 1 in 12,376 Bee sting — 1 in 78,927 Swallowed bee/wasp — 1 in 29,155 Fatal scorpion sting — 1 in 26,110 Dog chocolate death — 1 in 13,889 Lead-tainted cinnamon pouch — 1 in 40,000 Plastic container leaching — 1 in 16,949 Infant car-seat asphyxia — 1 in 64,935 Bouncer chair fall — 1 in 60,606 Toddler choking — 1 in 50,000 Unsupervised infant choking — 1 in 50,000 Forward-facing toddler death — 1 in 26,738 Magnet ingestion — 1 in 12,048 Snorkeling death — 1 in 21,739 Pet in transport — 1 in 20,000 Death in ICE custody — 1 in 17,065 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 Ferry sinking — 1 in 133,333 Turbulence injury — 1 in 114,943 School shooting — 1 in 192,308 Mass shooting — 1 in 113,636 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 Crocodile attack — 1 in 337,838 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 Infant swing death — 1 in 714,286 Whole-grape choking — 1 in 625,000 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 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
Lottery jackpot 1 in 95,238

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