FoodNet 2024 Preliminary Data

Since 1996, FoodNet has been counting cases and tracking trends for infections transmitted commonly through food.

Information gathered on which illnesses are decreasing, and which are increasing, provides a foundation for food safety policy and prevention efforts.

FoodNet's surveillance data show where efforts are needed to reduce foodborne illnesses.

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Abbreviations: CIDT = culture-independent diagnostic test; CrI = credible interval; IRR = incidence rate ratio; NA = not applicable; STEC = Shiga toxin-producing Escherichia coli.

*When FoodNet was founded in 1995, the catchment included Minnesota and Oregon and counties in California (two), Connecticut (two), and Georgia (eight). The catchment expanded consistently during 1996–2004; it remained stable during 2004–2022. The historic catchment includes sites under surveillance since 2004, including Connecticut, Georgia, Maryland, Minnesota, New Mexico, Oregon, and Tennessee, and counties in California (three), Colorado (seven), and New York (34). To facilitate comparability with past FoodNet reports, data for the historic catchment are presented in-text.

^† Case data for 2024 are preliminary.

^§ Bacterial infections were diagnosed using culture or culture-independent diagnostic tests. Cyclospora infections were diagnosed using microscopy or polymerase chain reaction.

^¶ Admission to an inpatient unit or an observation stay of >24 hours ≤7 days before or after specimen collection or determined to be related to the infection if beyond this time frame. The average percentage of infections resulting in hospitalizations during 2016–2018, by pathogen, were Campylobacter (20%), Salmonella (27%), STEC (22%), Shigella (24%), Yersinia (26%), Vibrio (30%), Listeria (96%), Cyclospora (6%), and overall (24%). Infections with unknown hospitalization status (9% of infections during 2024 and 4% during 2016–2018) were included in the denominator only.

** Attributed to infection when death occurred during hospitalization or ≤7 days after specimen collection from nonhospitalized patients. The average percentage of infections resulting in death during 2016–2018 were, by pathogen, Campylobacter (0.4%), Salmonella (0.4%), STEC (0.4%), Shigella (0.1%), Yersinia (1.2%), Vibrio (2.1%), Listeria (18.6%), Cyclospora (0.2%), and overall (0.5%). Infections with unknown death status (2% of infections during 2024 and 3% during 2016–2018) were included in the denominator only.

^††Generally defined as two or more cases of similar illness associated with a common exposure; some sites also stipulate illnesses be from one or more households. The average percentage of outbreak-associated infections during 2016–2018 were, by pathogen, Campylobacter (<1%), Salmonella (7%), STEC (4%), Shigella (5%), Yersinia (<1%), Vibrio (4%), Listeria (5%), Cyclospora (24%), and overall (4%).

^§§Cases per 100,000 persons.

^¶¶Crude incidence is unadjusted and is calculated as cases of infection per 100,000 persons.

*** A Bayesian, negative binomial model with penalized thin plate splines adjusting for state-specific trends was used to quantify adjusted incidence in 2024 and the IRR in 2024 compared with average incidence during 2016–2018. Incidence during 2024 was described as increased or decreased compared with 2016–2018 if the 95% CrI for the IRR did not include 1. A 95% CrI is analogous to a 95% Confidence Interval (CI) in frequentist statistics and can be interpreted similarly, meaning a 95% probability of the true IRR for incidence in 2024 compared with average annual incidence during 2016–2018 is within the 95% CrI.

^††† Includes both international travel–associated infections and domestically acquired infections.

^§§§ Starting in 2024, only Campylobacter infections diagnosed by culture were collected by FoodNet. This is a change to previous years in which infections diagnosed by culture or CIDT test results were collected. Due to this change, the number of Campylobacter infections during 2024 are not comparable to previous years and could not be included in trend modeling to calculate incidence rates for 2024.

^¶¶¶Salmonella infections that were not serotyped include all cases that were diagnosed by CIDT only, CIDT-diagnosed cases that failed to yield an isolate during culture, and cases that yielded an isolate (both culture and CIDT-diagnosed) where the isolate was partially serotyped or not serotyped. IRRs were not calculated for Salmonella serotypes.

**** Dashes indicate that the given data point was unknown, not reported, otherwise missing from the FoodNet data, or was not quantified.

^†††† Incidences for STEC O157 and overall STEC non-O157 represent only a proportion of the total STEC incidence because 1,373 (38%) infections yielded an isolate, and only 1,342 (37%) were fully serogrouped and classified as STEC O157 or STEC non-O157 during 2024. IRRs were not calculated for STEC serogroups.

^§§§§ The most frequently detected non-O157 serogroups were O103 (210) and O26 (148).

^¶¶¶¶ Includes only domestically acquired infections (those for which the patient had no history of international travel or unknown travel history).

Abbreviations: CIDT = culture-independent diagnostic test; STEC = Shiga toxin-producing Escherichia coli.

^*Bacterial infections could be diagnosed by culture-based methods only, by CIDTs only, or by CIDTs with culture. When diagnosed by CIDTs with culture, the culture could either yield an isolate or fail to yield an isolate. Because speciation and subtyping are only possible when an isolate is available, species and subtype data are only reported in the table for infections diagnosed by culture and by CIDTs with culture that yielded an isolate.

^† The historic catchment area includes those sites under surveillance since 2004, including Connecticut, Georgia, Maryland, Minnesota, New Mexico, Oregon, Tennessee, and selected counties in California (three), Colorado (seven), and New York (34).

^§2024 data are preliminary.

^¶ Includes cases diagnosed by CIDTs only or by CIDTs with either a positive or negative culture.

^** Denominator is total number of infections for the corresponding pathogen and time-period in the table's second column (Total infections, No.).

^†† Denominator is number of infections with culture performed following a positive CIDT, not shown in table.

– 2024: Campylobacter – 2,795, Salmonella –4,983, STEC – 2,818, Shigella – 2,813, Yersinia – 847, Vibrio – 395, Listeria – 40, Overall excluding Campylobacter – 11,896

– 2016–2018: Campylobacter – 2,953, Salmonella – 1,969, STEC – 2,311, Shigella – 854, Yersinia – 206, Vibrio – 145, Listeria – 6, Overall excluding Campylobacter – 5,492

^§§Starting in 2024, only Campylobacter infections diagnosed by culture were collected by FoodNet. This is a change to previous years in which infections diagnosed by culture or CIDT test results were collected. Because of this change, we cannot compare the number of Campylobacter infections reported to FoodNet during 2024 with previous years, did not calculate incidence, and did not perform trend analyses. We also excluded Campylobacter from the overall calculations in the bottom row of the table.

In the past, FoodNet collected data on Campylobacter infections diagnosed by

• Culture only
• CIDT and confirmed by culture
• CIDT only

As of 2024, FoodNet no longer collects data on Campylobacter infections diagnosed by CIDT only.

Because of this change, we cannot compare the number of Campylobacter infections reported to FoodNet during 2024 with previous years, did not calculate incidence, and did not perform trend analyses.

FoodNet's surveillance area expanded during 2023 to include all of Colorado.

The expansion increased representation for specific populations, including

• People identifying as Hispanic, American Indian/Alaska Native, Native Hawaiian/Pacific Islander, or as more than 1 race or ethnicity, and
• People living in rural counties.

Increased representation improves FoodNet's ability to monitor disease trends and makes FoodNet data more applicable to a larger population.

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Compared with 2016–2018, incidence of infection increased for some pathogens in 2024 and remained stable for others.

Although assessing various factors that affect incidence can be complicated, several factors are likely responsible for the changes, including

• More sick people might have been tested because CIDTs are fast and easy to use.
• Increased use of CIDTs might have allowed laboratories to detect infections that would have previously been missed.
• People might have had more exposure to some pathogens.

How CIDT use affected incidence of infections in 2024

Use of CIDTs continues to increase, leading to increased detection of infections.

Most of these are true infections that, without use of CIDTs, would have been missed. Some infections, including those caused by STEC, Vibrio, and Yersinia, are harder to detect by traditional methods (e.g., culture).

Before widespread use of CIDTs, many patient samples were not tested for these infections and, when they were tested, false negative results were frequent.

CIDTs are likely not the only factor that affected the number of reported infections in 2024. For infections caused by some pathogens, increases in incidence appear to outpace increased CIDT usage.

Why 2016–2018 is the reference period

FoodNet sets a reference period that can be used for many years to monitor progress toward food safety goals. FoodNet used 1996–1998 and 2006–2008 as reference periods in earlier reports. These specific reference periods were chosen to align with the HHS Healthy People initiative.

Data source

FoodNet conducts active, population-based surveillance for laboratory-diagnosed Campylobacter, Cyclospora, Listeria, Salmonella, Shigella, STEC, Vibrio, and Yersinia infections and pediatric HUS at 10 U.S. sites.

Laboratory testing and data collection

Bacterial infections were diagnosed by CIDT or culture. Cyclosporiasis was diagnosed by polymerase chain reaction or microscopy.

If the ill person did not report international travel or had an unknown travel history, the illness was considered to have been domestically acquired. A history of international travel was defined as travel ≤30 days before onset of listeriosis, typhoid fever, or paratyphoid fever; ≤14 days before onset of cyclosporiasis; and ≤7 days before onset of other illnesses.

Estimating changes in the incidence of infections

Incidence (cases per 100,000 persons) was calculated by dividing number of infections during 2024 by 2023 U.S. Census Bureau population estimates.

FoodNet uses a Bayesian model to estimate changes in the incidence of infections. The model uses the average annual incidence for 2016–2018 for comparisons. This model adjusts for site-specific trends, reduces sensitivity to single-year events (e.g., outbreaks), and reduces biases towards more populous sites.

Incidence in 2024 was considered substantially different from 2016–2018 incidence if the 95% credible interval (CrI) for the incidence rate ratio (IRR) did not include 1.0. In contrast to frequentist statistics, which use significance testing, in a Bayesian model, true significance testing is not done, and differences are described as substantial.