Food safety outbreak & recall intelligence dashboard

Track foodborne illness outbreaks, food recalls, emerging food hazards, and fraud-prone commodities from official global sources — with role-specific actions for consumers, importers, and food processors.

Data mode LiveAuto-refresh Every 60sCoverage Global commoditiesUpdating… —

Data notice: Figures below reflect only the recall, import-alert, laboratory, research, and regulatory sources currently connected. Sections marked Sample datashow illustrative baselines until live feeds are wired in — do not treat them as public health advice.

Date rangeCommodityHazard typeRegionEvidence

TRTotal risk signals476+12%

HRHigh-risk signals44+18%

HZHazard events44+9%

FRFraud signals45+15%

COAffected countries24-5%

ALActive alerts47+22%

Overview risk trend

Signals by severity across hazards, fraud, import risk, and research findings.

HighMediumLowTotal

Hazards and risks in foods

Likelihood and severity matrix for monitored signals.

RareUnlikelyPossibleLikelyAlmost certainSevere25122836Major37184152Moderate614376165Minor821415547Negligible1223384231

Alerts by audience

Role-specific actions for consumer, importer, and processor teams.

high
Ready-to-eat foods with pathogen risk signals
Watch Listeria and Salmonella patterns in prepared salads, deli items, soft cheeses, and frozen vegetables.
high
Undeclared allergen risk in multi-ingredient products
Focus on sesame, milk, peanut, soy, and tree nut labeling on snacks, bakery, sauces, and protein bars.
medium
Foreign material and packaging integrity alerts
Check brand notices for glass, plastic, metal fragments, damaged seals, or tamper indicators.
low
Consumer reporting reminder
Report illness, unusual odors, swelling packages, or labeling mismatch to the seller and local authority.

Global outbreak watch

Latest foodborne illness clusters tracked across CDC, ECDC, RASFF, INFOSAN, WHO and PAHO.

View all outbreaks →

Salmonella Enteritidis · Shell eggs
criticalUnited States·CDC / FDA·214 cases
Jul 2
Avian Influenza (H5N1) · Poultry
criticalVietnam·WHO / FAO·4 cases
Jul 1
Botulinum toxin · Home-canned vegetables (commercial mislabel)
criticalItaly·ISS / RASFF·6 cases
May 22
Salmonella Typhimurium · Chocolate products
highBelgium·RASFF·56 cases
Jul 5
Salmonella spp. · Powdered infant formula
highSouth Africa·NICD·22 cases
Jul 4
Listeria monocytogenes · Deli meat
highCanada·PHAC / CFIA·31 cases
Jun 28

Foodborne source attribution, food fraud & disease burden

Foodborne source attribution estimates which food categories contribute to illnesses caused by specific hazards. Disability-adjusted life years (DALYs) measure the healthy years of life lost through illness and premature death. Published estimates, observed records from this platform, and modeled values are kept strictly apart.

HazardFood categoryGeographyStudy period

Published estimate · IFSAC — Foodborne Illness Source Attribution Estimates for Salmonella, Escherichia coli O157 and Listeria monocytogenes, United States, 2022. Percentages, intervals, population, period and method are reproduced as published; nothing is recalculated here.

Vegetable Row Crops63.69%

Beef21.43%

Dairy3.27%

Pork2.55%

Fruits1.92%

Other Meat or Poultry1.78%

Other Produce1.52%

Chicken0.91%

Sprouts0.87%

Seeded vegetables0.7%

Grains-Beans0.53%

Other Seafood0.37%

Game0.32%

Fish0.14%

Turkey0%

Hazard	Food category	Estimate	90% credible interval	Geography	Period	Method	Denominator	Source
Escherichia coli O157 (STEC)	Vegetable Row Crops	63.69%	53.28–72.31%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Beef	21.43%	14.9–29.7%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Dairy	3.27%	1.88–5.16%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Pork	2.55%	0.68–5.49%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Fruits	1.92%	0.73–3.95%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Other Meat or Poultry	1.78%	0.56–3.8%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Other Produce	1.52%	0.21–4.05%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Chicken	0.91%	0.06–2.8%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Sprouts	0.87%	0.07–2.59%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Seeded vegetables	0.7%	0.19–1.52%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Grains-Beans	0.53%	0.03–1.6%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Other Seafood	0.37%	0.02–1.11%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Game	0.32%	0.12–0.65%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Fish	0.14%	0.01–0.45%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report
Escherichia coli O157 (STEC)	Turkey	0%	0–0%	United States	1998–2022	Bayesian model of outbreak-associated illnesses, weighting the most recent five years (2018–2022) equally and earlier years exponentially less; each implicated food assigned to a single one of 17 IFSAC food categories.	Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories).	IFSAC 2022 report

Denominator: Model-estimated foodborne illnesses caused by the pathogen, distributed across the 17 IFSAC food categories (percentages sum to 100 across categories). Because the model distributes only illnesses whose implicated food could be assigned to a single category, these are shares among source-attributed illnesses.

Campylobacter spp.: IFSAC does not publish Campylobacter attribution percentages in this report: evidence suggests the sources of Campylobacter outbreaks differ considerably from the sources of non-outbreak illnesses, and an alternative method is still being developed.

Food fraud trends by commodity

Commodities with elevated adulteration, substitution, or mislabeling signals.

Rank	Commodity	Primary fraud pattern	30d
1	Seafood	Species substitution / origin risk	-21%
2	Meat & Poultry	Mixed authenticity and residue signals	-42%
3	Supplements	Undeclared ingredient / potency claims	+267%
4	Spices	Unauthorized colorants / fillers	+7%
5	Oils and fats	Dilution / origin claims	+35%
6	Honey	Syrup addition / mislabeling	+20%

Priority actions

Recommended next steps for risk teams.

Verify supplier COAs for high-risk spice lots
High
48h
Review allergen changeover records for bakery lines
High
72h
Audit seafood species labeling evidence
Medium
7d
Update importer hold criteria for residue signals
Medium
7d

Research risk signals

Hazard and fraud patterns elevated by literature and analytical testing.

86%
Aflatoxin risk clusters remain concentrated in nuts, maize, and spice chains.
Evidence: analytical testing, border rejections, supplier history.
64%
Undeclared allergens trend higher in multi-ingredient snacks and bakery products.
Evidence: recalls, label reviews, processor deviations.
58%
Olive oil and honey show persistent authenticity pressure under price volatility.
Evidence: fraud databases, market indicators, laboratory methods.

Geographic exposure

Country-level risk concentration for hazards, imports, and fraud signals.

Country	Risk	Events	Movement
India	High	142	+25%
United States	High	121	+13%
China	High	98	+17%
Brazil	Medium	76	+5%

Regulatory watch

Professional monitoring module for the first page.

US
Labeling and traceability checks
Track recall notices, import alerts, and facility inspection themes.
EU
Residue and contaminant limits
Monitor commodity-specific maximum limits and border notifications.
Codex
Global standards pipeline
Follow draft guidance on contaminants, additives, and analytical methods.

Extended intelligence modules

Additional coverage across regulatory, laboratory, and trade signals.

01
Evidence confidence
Separates verified findings from early signals.
02
Priority actions
Turns risk intelligence into tasks for teams.
03
Source health
Shows whether government, research, media, and import feeds are current.
04
Geographic exposure
Helps teams compare country and commodity risk concentration.

Source status

Ingestion overview across connected recall, laboratory, research, and regulatory feeds.

GAGovernment agenciesRecall and enforcement feedsOperational

IAInternational alertsRASFF, INFOSAN, national portalsOperational

SLScientific literatureResearch and testing studiesOperational

IMImport / export dataBorder and supplier signalsDelayed

IRIndustry reportsProcessor and supply chain dataOperational

CSCrowdsourced reportsConsumer and field submissionsNeeds review