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Likelier
Food · reviewed 2026-05-31

What are the odds of getting sick from rarely cleaning the inside of the fridge?

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

No reliable estimate

Not quantified

A single closed glass jar rendered as a flat vector shape in muted dusty sage and off-white, with plenty of empty space around it.

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
Healthy non-pregnant adult, conservative practice (clean spills promptly, fridge at or below 40°F, wipe-out every month or two) 1 in 10,000 Baseline. Whatever incremental GI-illness risk is attributable specifically to fridge-cleaning cadence in a healthy adult sits below detection against the ambient ~14% annual foodborne illness rate from all sources.
Healthy non-pregnant adult who essentially never cleans the inside of the fridge (years between wipe-outs, sticky shelves, expired condiments) 1 in 1,000 Structural upper bound for a clinical infection per year attributable to cleaning cadence specifically, in a healthy host. Not a measured rate — the cohort comparison does not exist. The plausible increments are occasional cross-contamination episodes from a leaking package onto ready-to-eat food, not chronic illness from the fridge's general state.
Immunocompromised adult (transplant, chemotherapy, advanced HIV, long-term immunosuppression) 1 in 100 Order-of-magnitude placeholder. The immunocompromised population is the one for whom Listeria in the meat drawer is a real clinical threat rather than an academic one. Specific guidance for this group lives outside the scope of this entry; CDC, transplant centres, and oncology teams issue tailored food-safety instructions that go well beyond "clean the fridge".
Pregnant adult (listeriosis-specific risk) 1 in 500 Pregnancy is the defining carve-out. US invasive listeriosis incidence in pregnancy is roughly 3 per 100,000 pregnancies (CDC FoodNet pregnancy surveillance); the figure shown is a rough annualised probability of any listeriosis-attributable illness over a pregnancy duration, not per-meal risk. The mechanism that makes fridge cleaning matter at all sits here, in the deli-meat-and-soft-cheese cross-contamination pathway, not in the general "stomach bug" framing.
Household with a known raw-juice spill (poultry, ground beef, raw fish drip onto a ready-to-eat shelf, not cleaned) 1 in 20 Different regime entirely. The published USDA and CDC guidance for "raw juice onto a shelf that then touched salad greens" describes a real, near-term Salmonella or Campylobacter exposure event with a measurable per-incident attack rate. This is what fridge-cleaning advice is genuinely written for — discrete spill events, not "I should wipe the shelves monthly".
Compare to:

What the published literature actually measures and what the fear actually asks are not the same question. Beczkiewicz and Kowalcyk found Listeria species in 15% of US home refrigerators, concentrated in the meat drawer, with the contamination strongly tied to higher fridge temperatures rather than cleaning cadence directly. Yamaguchi et al. swabbed 100 Japanese homes and recovered Staphylococcus aureus as the most frequent isolate plus coliforms in multiple households, while Salmonella, Listeria, and Yersinia were absent; cleaning frequency was the dominant correlate of bioburden. A 1,020-household Irish survey found S. aureus in 41% of fridges, Salmonella in 7%, Listeria in 6%, and E. coli in 6%. None of these papers does the thing the fear needs them to do, which is compare the per-year clinical illness rate of households that clean their fridge weekly to those that essentially never do. The bioburden half of the question has been answered four times over; the outcome half has not.

The interesting part is the gap between visible filth and measurable disease. The CDC headline figure is that 48 million Americans, 128,000 hospitalisations, and 3,000 deaths are attributable to foodborne illness each year — roughly one in seven of the population has a foodborne illness episode annually from all sources combined. The attribution work behind that number splits illness across food categories and pathogens, but does not slice it by household cleaning practice, because the surveillance system would need a counterfactual it has never had: matched cohorts of identical eaters in identical households with different cleaning cadences. The “your fridge is dirtier than a toilet seat” headlines are not wrong about the colony-forming unit count. They are wrong about the inference that follows from it, in the same way that recovering staph from a kitchen sponge does not predict a staph infection.

Where this entry does not apply is concentrated in four places, and the first two are the entire reason for any concern at all. Pregnant adults sit in a population for whom invasive listeriosis — rare in absolute terms — is genuinely catastrophic when it occurs, and the meat-drawer cross-contamination pathway is the mechanism the pregnancy-food-safety literature is written for. Immunocompromised adults, in transplant or oncology care, get tailored food-safety instructions that override anything in the general population guidance and treat Listeria, Salmonella, and Yersinia in the fridge as the clinical threats they actually are for that group. Infants are outside the healthy-adult frame. And a known spill event — raw poultry drippings onto a ready-to-eat shelf, ignored — is genuinely a different scenario from a slow background of crumbs and expired jars, with specific USDA and CDC cleanup guidance to match. The sticky shelves are not the thing that gets healthy adults sick. The unattended chicken puddle might.

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] Journal of Food Protection (Yamaguchi N, et al.) — Microbial contamination and cleaning practices in domestic refrigerators in Japan
    Microbial contamination and cleaning practices in domestic refrigerators in Japan
    Statistic
    100 Japanese domestic refrigerators; cleaning frequency correlated with microbial contamination; S. aureus was the most frequent isolate; Salmonella, L. monocytogenes, and Y. enterocolitica were not recovered; only 17% cleaned the fridge monthly or more often
    Excerpt
    “[Paraphrase from abstract — full text paywalled] "Staphylococcus aureus was the most frequently isolated pathogen [...] Salmonella, Listeria monocytogenes, and Yersinia enterocolitica were not found [...] Correlations were found between microbial contamination and refrigerator cleaning frequency and/or method [...] Only 17% of the respondents cleaned their refrigerators monthly or more often, and this frequency was lower than that reported in other countries." ”
    Source data from
    2020-06-22
    Accessed
    2026-05-31
    Calculation
    The cleanest published evidence on the actual question. Yamaguchi et al. swabbed 100 home refrigerators in Japan, recovered Staph aureus as the most frequent pathogen and coliforms in multiple households, but did not recover Salmonella, Listeria, or Yersinia — the three classical refrigeration-relevant pathogens. Cleaning frequency was identified as a significant correlate of bioburden, while temperature alone was not. This documents the mechanism (less cleaning → more bacteria on surfaces) without translating it into an infection rate; the study measures what is on the fabric of the fridge, not whether residents of dirtier fridges got sick more often. This is exactly the gap that justifies the no_reliable_estimate flag for this entry.
    Independence
    Independent Japanese household survey, distinct in methodology and population from the US Listeria home-kitchen study (Beczkiewicz) and the Irish home-refrigerator survey (Kennedy).
  2. [2] Journal of Food Protection (Beczkiewicz ATC, Kowalcyk BB) — Listeria monocytogenes Contamination in Domestic Refrigerators in the United States
    Listeria monocytogenes Contamination in Domestic Refrigerators in the United States
    Statistic
    Listeria spp., including L. monocytogenes and L. innocua, present in 15% of US homes; contamination significantly associated with higher refrigerator temperatures; most often found in samples from refrigerator meat drawers
    Excerpt
    “[Paraphrase from abstract — full text paywalled] "Listeria spp., including L. monocytogenes and L. innocua, were present in 15% of homes [...] Contamination with Listeria was significantly associated with higher refrigerator temperatures [...] most often in samples from refrigerator meat drawers." ”
    Source data from
    2017-03-01
    Accessed
    2026-05-31
    Calculation
    Direct US prevalence data for the pathogen that most concerns regulators and the pregnancy-advice literature. Roughly one in seven US homes harbours Listeria somewhere in the refrigerator, concentrated in the meat drawer, with the temperature association doing most of the explanatory work rather than cleaning cadence per se. The crucial gap, again: 15% of homes carrying Listeria does not translate to 15% of households having a listeriosis case — invasive listeriosis incidence in the US is roughly 0.26 per 100,000 per year (CDC FoodNet) across the general population, several orders of magnitude below the home-prevalence number. Most household Listeria does not cause clinical disease in immunocompetent adults; this is what makes the pregnancy and immunocompromised carve-outs the entire story.
    Independence
    US national surveillance study, methodologically and editorially independent of the Japan and Ireland surveys; same outcome (fridge bioburden) measured against a different population.
  3. [3] US Centers for Disease Control and Prevention (CDC) — About Food Safety
    About Food Safety

    See all 4 Likelier entries citing this source →

    Statistic
    CDC estimates 48 million US foodborne illnesses, 128,000 hospitalizations, and 3,000 deaths per year
    Excerpt
    “"CDC estimates that each year 48 million people get sick from a foodborne illness, 128,000 are hospitalized, and 3,000 die." ”
    Source data from
    2024-08-13
    Accessed
    2026-05-31
    Calculation
    Frames the absolute burden of foodborne illness in the US: roughly one in seven Americans has a foodborne illness episode in a given year. This is the headline number the contamination-anxiety articles implicitly invoke. What it cannot do is attribute any fraction of that burden to refrigerator cleaning frequency. CDC's attribution work apportions illness across food categories (poultry, produce, dairy, deli) and pathogens (Salmonella, Norovirus, Campylobacter, Listeria); the "in-home refrigerator cleaning cadence" exposure is not a category the surveillance system tracks because the data needed to estimate it does not exist. Anchors the absolute scale of foodborne illness while making clear why no slice of it can be cleanly assigned to the question this entry asks.
    Independence
    Federal surveillance estimate, independent of all three peer-reviewed bioburden studies; provides denominator and population context rather than mechanism.
  4. [4] Journal of Food Protection (Kennedy J, Jackson V, Blair IS, McDowell DA, Cowan C, Bolton DJ) — Food safety knowledge and microbiological hygiene in domestic refrigerators on the island of Ireland
    Food safety knowledge and microbiological hygiene in domestic refrigerators on the island of Ireland
    Statistic
    Representative sample of 1,020 Irish households; Staphylococcus aureus in 41%, Salmonella enterica in 7%, Listeria monocytogenes in 6%, Escherichia coli in 6% of domestic refrigerators
    Excerpt
    “[Paraphrase from abstract — full text paywalled] "A representative sample of households (n = 1,020) throughout the island of Ireland [...] Staphylococcus aureus [...] 41% [...] Salmonella enterica [...] 7% [...] Listeria monocytogenes [...] 6% [...] Escherichia coli [...] 6% [...] consumers with stronger food safety knowledge demonstrated lower bacterial contamination in their refrigerators and reported fewer foodborne illnesses." ”
    Source data from
    2005-06-01
    Accessed
    2026-05-31
    Calculation
    Largest published household-refrigerator survey by sample size (n=1,020), useful for two reasons. First, it puts a number on each of the relevant pathogens in home fridges in a Western population, broadly consistent with the US Listeria figure (6% Irish vs 15% US — different sampling regimes, both single-digit-to- teens prevalence). Second, the authors report a correlation between consumer food safety knowledge and both refrigerator contamination and self-reported foodborne illness — the closest the literature comes to linking household hygiene practices to illness outcomes. The self-report on the illness side is the limit: it is not a measured clinical attack rate, it is what people remember when surveyed.
    Independence
    Independent Irish national survey; cited here for sample-size weight and the knowledge-contamination correlation rather than as a substitute for US-specific figures.

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