Problem/Condition: Coccidioidomycosis, histoplasmosis, and blastomycosis are underdiagnosed fungal diseases that often mimic bacterial or viral pneumonia and can cause disseminated disease and death. These diseases are caused by inhalation of fungal spores that have distinct geographic niches in the environment (e.g., soil or dust), and distribution is highly susceptible to climate changes such as expanding arid regions for coccidioidomycosis, the northward expansion of histoplasmosis, and areas like New York reporting cases of blastomycosis previously thought to be nonendemic. The national incidence of coccidioidomycosis, histoplasmosis, and blastomycosis is poorly characterized. Reporting Period: 2019. Description of System: The National Notifiable Diseases Surveillance System (NNDSS) tracks cases of coccidioidomycosis, a nationally notifiable condition reported to CDC by 26 states and the District of Columbia. Neither histoplasmosis nor blastomycosis is a nationally notifiable condition; however, histoplasmosis is voluntarily reported in 13 states and blastomycosis in five states. Health departments classify cases based on the definitions established by the Council of State and Territorial Epidemiologists. Results: In 2019, a total of 20,061 confirmed coccidioidomycosis, 1,124 confirmed and probable histoplasmosis, and 240 confirmed and probable blastomycosis cases were reported to CDC. Arizona and California reported 97% of coccidioidomycosis cases, and Minnesota and Wisconsin reported 75% of blastomycosis cases. Illinois reported the greatest percentage (26%) of histoplasmosis cases. All three diseases were more common among males, and the proportion for blastomycosis (70%) was substantially higher than for histoplasmosis (56%) or coccidioidomycosis (52%). Coccidioidomycosis incidence was approximately four times higher for non-Hispanic American Indian or Alaska Native (AI/AN) persons (17.3 per 100,000 population) and almost three times higher for Hispanic or Latino persons (11.2) compared with non-Hispanic White (White) persons (4.1). Histoplasmosis incidence was similar across racial and ethnic categories (range: 0.9-1.3). Blastomycosis incidence was approximately six times as high among AI/AN persons (4.5) and approximately twice as high among non-Hispanic Asian and Native Hawaiian or other Pacific Islander persons (1.6) compared with White persons (0.7). More than one half of histoplasmosis (54%) and blastomycosis (65%) patients were hospitalized, and 5% of histoplasmosis and 9% of blastomycosis patients died. States in which coccidioidomycosis is not known to be endemic had more cases in spring (March, April, and May) than during other seasons, whereas the number of cases peaked slightly in autumn (September, October, and November) for histoplasmosis and in winter (December, January, and February) for blastomycosis. Interpretation: Coccidioidomycosis, histoplasmosis, and blastomycosis are diseases occurring in geographical niches within the United States. These diseases cause substantial illness, with approximately 20,000 coccidioidomycosis cases reported in 2019. Although substantially fewer histoplasmosis and blastomycosis cases were reported, surveillance was much more limited and underdiagnosis was likely, as evidenced by high hospitalization and death rates. This suggests that persons with milder symptoms might not seek medical evaluation and the symptoms self-resolve or the illnesses are misdiagnosed as other, more common respiratory diseases. Public Health Action: Improved surveillance is necessary to better characterize coccidioidomycosis severity and to improve detection of histoplasmosis and blastomycosis. These findings might guide improvements in testing practices that enable timely diagnosis and treatment of fungal diseases. Clinicians and health care professionals should consider coccidioidomycosis, histoplasmosis, and blastomycosis in patients with community-acquired pneumonia or other acute infections of the lower respiratory tract who live in or have traveled to areas where the causative ungi are known to be present in the environment. Culturally appropriate tailored educational messages might help improve diagnosis and treatment. Public health response to these three diseases is hindered because information gathered from states' routine surveillance does not include data on populations at risk and sources of exposure. Broader surveillance that includes expansion to other states and more detail about potential exposures and relevant host factors can describe epidemiologic trends, populations at risk, and disease prevention strategies.

As of April 19, 2021, 21.6 million COVID-19 cases had been reported among U.S. adults, most of whom had mild or moderate disease that did not require hospitalization (1). Health care needs in the months after COVID-19 diagnosis among nonhospitalized adults have not been well studied. To better understand longer-term health care utilization and clinical characteristics of nonhospitalized adults after COVID-19 diagnosis, CDC and Kaiser Permanente Georgia (KPGA) analyzed electronic health record (EHR) data from health care visits in the 28-180 days after a diagnosis of COVID-19 at an integrated health care system. Among 3,171 nonhospitalized adults who had COVID-19, 69% had one or more outpatient visits during the follow-up period of 28-180-days. Compared with patients without an outpatient visit, a higher percentage of those who did have an outpatient visit were aged ≥50 years, were women, were non-Hispanic Black, and had underlying health conditions. Among adults with outpatient visits, 68% had a visit for a new primary diagnosis, and 38% had a new specialist visit. Active COVID-19 diagnoses* (10%) and symptoms potentially related to COVID-19 (3%-7%) were among the top 20 new visit diagnoses; rates of visits for these diagnoses declined from 2-24 visits per 10,000 person-days 28-59 days after COVID-19 diagnosis to 1-4 visits per 10,000 person-days 120-180 days after diagnosis. The presence of diagnoses of COVID-19 and related symptoms in the 28-180 days following acute illness suggests that some nonhospitalized adults, including those with asymptomatic or mild acute illness, likely have continued health care needs months after diagnosis. Clinicians and health systems should be aware of post-COVID conditions among patients who are not initially hospitalized for acute COVID-19 disease.

We compared the characteristics of hospitalized and nonhospitalized patients who had coronavirus disease in Atlanta, Georgia, USA. We found that risk for hospitalization increased with a patient's age and number of concurrent conditions. We also found a potential association between hospitalization and high hemoglobin A1c levels in persons with diabetes.

OBJECTIVES: To obtain timely and detailed data on COVID-19 cases in the United States, the Centers for Disease Control and Prevention (CDC) uses 2 data sources: (1) aggregate counts for daily situational awareness and (2) person-level data for each case (case surveillance). The objective of this study was to describe the sensitivity of case ascertainment and the completeness of person-level data received by CDC through national COVID-19 case surveillance. METHODS: We compared case and death counts from case surveillance data with aggregate counts received by CDC during April 5-September 30, 2020. We analyzed case surveillance data to describe geographic and temporal trends in data completeness for selected variables, including demographic characteristics, underlying medical conditions, and outcomes. RESULTS: As of November 18, 2020, national COVID-19 case surveillance data received by CDC during April 5-September 30, 2020, included 4 990 629 cases and 141 935 deaths, representing 72.7% of the volume of cases (n = 6 863 251) and 71.8% of the volume of deaths (n = 197 756) in aggregate counts. Nationally, completeness in case surveillance records was highest for age (99.9%) and sex (98.8%). Data on race/ethnicity were complete for 56.9% of cases; completeness varied by region. Data completeness for each underlying medical condition assessed was <25% and generally declined during the study period. About half of case records had complete data on hospitalization and death status. CONCLUSIONS: Incompleteness in national COVID-19 case surveillance data might limit their usefulness. Streamlining and automating surveillance processes would decrease reporting burdens on jurisdictions and likely improve completeness of national COVID-19 case surveillance data.

We report a fatal case of Rhizopus azygosporus pneumonia in a 56-year-old man hospitalized for COVID-19 who had received methylprednisolone and tocilizumab. Although COVID-associated pulmonary aspergillosis has been widely documented, mucormycosis has been rarely reported. In this patient, receipt of two commonly used immunosuppressants likely contributed to mucormycosis risk, suggesting the need for vigilance in hospitalized patients with COVID-19.

BACKGROUND: The epidemiological features and outcomes of hospitalized adults with coronavirus disease 2019 (COVID-19) have been described; however, the temporal progression and medical complications of disease among hospitalized patients require further study. Detailed descriptions of the natural history of COVID-19 among hospitalized patients are paramount to optimize health care resource utilization, and the detection of different clinical phenotypes may allow tailored clinical management strategies. METHODS: This was a retrospective cohort study of 305 adult patients hospitalized with COVID-19 in 8 academic and community hospitals. Patient characteristics included demographics, comorbidities, medication use, medical complications, intensive care utilization, and longitudinal vital sign and laboratory test values. We examined laboratory and vital sign trends by mortality status and length of stay. To identify clinical phenotypes, we calculated Gower's dissimilarity matrix between each patient's clinical characteristics and clustered similar patients using the partitioning around medoids algorithm. RESULTS: One phenotype of 6 identified was characterized by high mortality (49%), older age, male sex, elevated inflammatory markers, high prevalence of cardiovascular disease, and shock. Patients with this severe phenotype had significantly elevated peak C-reactive protein creatinine, D-dimer, and white blood cell count and lower minimum lymphocyte count compared with other phenotypes (P < .01, all comparisons). CONCLUSIONS: Among a cohort of hospitalized adults, we identified a severe phenotype of COVID-19 based on the characteristics of its clinical course and poor prognosis. These findings need to be validated in other cohorts, as improved understanding of clinical phenotypes and risk factors for their development could help inform prognosis and tailored clinical management for COVID-19.

During February 12-October 15, 2020, the coronavirus disease 2019 (COVID-19) pandemic resulted in approximately 7,900,000 aggregated reported cases and approximately 216,000 deaths in the United States.* Among COVID-19-associated deaths reported to national case surveillance during February 12-May 18, persons aged ≥65 years and members of racial and ethnic minority groups were disproportionately represented (1). This report describes demographic and geographic trends in COVID-19-associated deaths reported to the National Vital Statistics System(†) (NVSS) during May 1-August 31, 2020, by 50 states and the District of Columbia. During this period, 114,411 COVID-19-associated deaths were reported. Overall, 78.2% of decedents were aged ≥65 years, and 53.3% were male; 51.3% were non-Hispanic White (White), 24.2% were Hispanic or Latino (Hispanic), and 18.7% were non-Hispanic Black (Black). The number of COVID-19-associated deaths decreased from 37,940 in May to 17,718 in June; subsequently, counts increased to 30,401 in July and declined to 28,352 in August. From May to August, the percentage distribution of COVID-19-associated deaths by U.S. Census region increased from 23.4% to 62.7% in the South and from 10.6% to 21.4% in the West. Over the same period, the percentage distribution of decedents who were Hispanic increased from 16.3% to 26.4%. COVID-19 remains a major public health threat regardless of age or race and ethnicity. Deaths continued to occur disproportionately among older persons and certain racial and ethnic minorities, particularly among Hispanic persons. These results can inform public health messaging and mitigation efforts focused on prevention and early detection of infection among disproportionately affected groups.

OBJECTIVES: Aspergillus coinfection in coronavirus disease 2019 patients has rarely been described but may be occurring among coronavirus disease 2019 patients admitted to ICUs. Previous reports of viral coinfections with Aspergillus, including influenza-associated pulmonary aspergillosis, suggest that coronavirus disease 2019-associated aspergillosis is plausible. This report aims to summarize what is known about coronavirus disease 2019 complicated by Aspergillus, introduces coronavirus disease 2019-associated pulmonary aspergillosis as a possible clinical entity, and describes reasons clinical suspicion of Aspergillus is warranted in the critical care setting. DATA SOURCES: We summarize the available evidence suggesting the existence of Aspergillus coinfection among severe coronavirus disease 2019 patients. This includes published coronavirus disease 2019 patient case series, a case description, and a review of potential biologic mechanisms. STUDY SELECTION: Reports of coronavirus disease 2019 patient attributes were selected if they included clinical, microbiologic, or radiologic signs of invasive fungal infection. DATA EXTRACTION: Data included in summary tables were identified through a literature search for coronavirus disease 2019-associated pulmonary aspergillosis. DATA SYNTHESIS: We present descriptive data extracted from coronavirus disease 2019-associated pulmonary aspergillosis case series current at the time of article submission. DISCUSSION: Pulmonary aspergillosis is known to occur among influenza patients requiring intensive care and is associated with increased mortality. If Aspergillus coinfections are occurring among coronavirus disease 2019 patients, early clinical suspicion and testing are needed to understand the epidemiology of these infections and prevent associated mortality. As the coronavirus disease 2019 pandemic unfolds, reports on the existence of this coinfection are needed, and opportunities to contribute cases of Aspergillus coinfection among coronavirus disease 2019 patients to an ongoing registry are described.

Although children and young adults are reportedly at lower risk for severe disease and death from infection with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), than are persons in other age groups (1), younger persons can experience infection and subsequently transmit infection to those at higher risk for severe illness (2-4). Although at lower risk for severe disease, some young adults experience serious illness, and asymptomatic or mild cases can result in sequelae such as myocardial inflammation (5). In the United States, approximately 45% of persons aged 18-22 years were enrolled in colleges and universities in 2019 (6). As these institutions reopen, opportunities for infection increase; therefore, mitigation efforts and monitoring reports of COVID-19 cases among young adults are important. During August 2-September 5, weekly incidence of COVID-19 among persons aged 18-22 years rose by 55.1% nationally; across U.S. Census regions,* increases were greatest in the Northeast, where incidence increased 144.0%, and Midwest, where incidence increased 123.4%. During the same period, changes in testing volume for SARS-CoV-2 in this age group ranged from a 6.2% decline in the West to a 170.6% increase in the Northeast. In addition, the proportion of cases in this age group among non-Hispanic White (White) persons increased from 33.8% to 77.3% during May 31-September 5. Mitigation and preventive measures targeted to young adults can likely reduce SARS-CoV-2 transmission among their contacts and communities. As colleges and universities resume operations, taking steps to prevent the spread of COVID-19 among young adults is critical (7).

BACKGROUND: Coronavirus disease (COVID-19) can cause severe illness and death. Predictors of poor outcome collected on hospital admission may inform clinical and public health decisions. METHODS: We conducted a retrospective observational cohort investigation of 297 adults admitted to eight academic and community hospitals in Georgia, United States, during March 2020. Using standardized medical record abstraction, we collected data on predictors including admission demographics, underlying medical conditions, outpatient antihypertensive medications, recorded symptoms, vital signs, radiographic findings, and laboratory values. We used random forest models to calculate adjusted odds ratios (aORs) and 95% confidence intervals (CI) for predictors of invasive mechanical ventilation (IMV) and death. RESULTS: Compared with age <45 years, ages 65-74 years and ≥75 years were predictors of IMV (aOR 3.12, CI 1.47-6.60; aOR 2.79, CI 1.23-6.33) and the strongest predictors for death (aOR 12.92, CI 3.26-51.25; aOR 18.06, CI 4.43-73.63). Comorbidities associated with death (aORs from 2.4 to 3.8, p <0.05) included end-stage renal disease, coronary artery disease, and neurologic disorders, but not pulmonary disease, immunocompromise, or hypertension. Pre-hospital use vs. non-use of angiotensin receptor blockers (aOR 2.02, CI 1.03-3.96) and dihydropyridine calcium channel blockers (aOR 1.91, CI 1.03-3.55) were associated with death. CONCLUSIONS: After adjustment for patient and clinical characteristics, older age was the strongest predictor of death, exceeding comorbidities, abnormal vital signs, and laboratory test abnormalities. That coronary artery disease, but not chronic lung disease, was associated with death among hospitalized patients warrants further investigation, as do associations between certain antihypertensive medications and death.

The recent emergence of a multidrug-resistant yeast, Candida auris, has drawn attention to the closely related species from the Candida haemulonii complex that include C. haemulonii, Candida duobushaemulonii, Candida pseudohaemulonii, and the recently identified Candida vulturna. Here, we used antifungal susceptibility testing and whole-genome sequencing (WGS) to investigate drug resistance and genetic diversity among isolates of C. haemulonii complex from different geographic areas in order to assess population structure and the extent of clonality among strains. Although most isolates of all four species were genetically distinct, we detected evidence of the in-hospital transmission of C. haemulonii and C. duobushaemulonii in one hospital in Panama, indicating that these species are also capable of causing outbreaks in healthcare settings. We also detected evidence of the rising azole resistance among isolates of C. haemulonii and C. duobushaemulonii in Colombia, Panama, and Venezuela linked to substitutions in ERG11 gene as well as amplification of this gene in C. haemulonii in isolates in Colombia suggesting the presence of evolutionary pressure for developing azole resistance in this region. Our results demonstrate that these species need to be monitored as possible causes of outbreaks of invasive infection.

The first reported U.S. case of coronavirus disease 2019 (COVID-19) was detected in January 2020 (1). As of June 15, 2020, approximately 2 million cases and 115,000 COVID-19-associated deaths have been reported in the United States.* Reports of U.S. patients hospitalized with SARS-CoV-2 infection (the virus that causes COVID-19) describe high proportions of older, male, and black persons (2-4). Similarly, when comparing hospitalized patients with catchment area populations or nonhospitalized COVID-19 patients, high proportions have underlying conditions, including diabetes mellitus, hypertension, obesity, cardiovascular disease, chronic kidney disease, or chronic respiratory disease (3,4). For this report, data were abstracted from the medical records of 220 hospitalized and 311 nonhospitalized patients aged >/=18 years with laboratory-confirmed COVID-19 from six acute care hospitals and associated outpatient clinics in metropolitan Atlanta, Georgia. Multivariable analyses were performed to identify patient characteristics associated with hospitalization. The following characteristics were independently associated with hospitalization: age >/=65 years (adjusted odds ratio [aOR] = 3.4), black race (aOR = 3.2), having diabetes mellitus (aOR = 3.1), lack of insurance (aOR = 2.8), male sex (aOR = 2.4), smoking (aOR = 2.3), and obesity (aOR = 1.9). Infection with SARS-CoV-2 can lead to severe outcomes, including death, and measures to protect persons from infection, such as staying at home, social distancing (5), and awareness and management of underlying conditions should be emphasized for those at highest risk for hospitalization with COVID-19. Measures that prevent the spread of infection to others, such as wearing cloth face coverings (6), should be used whenever possible to protect groups at high risk. Potential barriers to the ability to adhere to these measures need to be addressed.

SARS-CoV-2, the novel coronavirus that causes coronavirus disease 2019 (COVID-19), was first detected in the United States during January 2020 (1). Since then, >980,000 cases have been reported in the United States, including >55,000 associated deaths as of April 28, 2020 (2). Detailed data on demographic characteristics, underlying medical conditions, and clinical outcomes for persons hospitalized with COVID-19 are needed to inform prevention strategies and community-specific intervention messages. For this report, CDC, the Georgia Department of Public Health, and eight Georgia hospitals (seven in metropolitan Atlanta and one in southern Georgia) summarized medical record-abstracted data for hospitalized adult patients with laboratory-confirmed* COVID-19 who were admitted during March 2020. Among 305 hospitalized patients with COVID-19, 61.6% were aged <65 years, 50.5% were female, and 83.2% with known race/ethnicity were non-Hispanic black (black). Over a quarter of patients (26.2%) did not have conditions thought to put them at higher risk for severe disease, including being aged >/=65 years. The proportion of hospitalized patients who were black was higher than expected based on overall hospital admissions. In an adjusted time-to-event analysis, black patients were not more likely than were nonblack patients to receive invasive mechanical ventilation(dagger) (IMV) or to die during hospitalization (hazard ratio [HR] = 0.63; 95% confidence interval [CI] = 0.35-1.13). Given the overrepresentation of black patients within this hospitalized cohort, it is important for public health officials to ensure that prevention activities prioritize communities and racial/ethnic groups most affected by COVID-19. Clinicians and public officials should be aware that all adults, regardless of underlying conditions or age, are at risk for serious illness from COVID-19.

Whole-genome sequencing confirmed the presence of a Malassezia pachydermatis outbreak among neonates in a neonatal intensive care unit. This technology supports the importance of adhering to infection prevention measures.

Candida auris is an emerging multidrug-resistant yeast first described in 2009 that has since caused healthcare-associated outbreaks of severe human infections around the world. In some hospitals, it has become a leading cause of invasive candidiasis. C. auris is markedly different from most other pathogenic Candida species in its genetics, antifungal resistance, and ability to spread between patients. The reasons why this fungus began spreading widely in the last decade remain a mystery. We examine available data on C. auris and related species, including genomic epidemiology, phenotypic characteristics, and sites of detection, to put forth hypotheses on its possible origins. C. auris has not been detected in the natural environment; related species have been detected in in plants, insects, and aquatic environments, as well as from human body sites. It can tolerate hypersaline environments and higher temperatures than most Candida species. We explore hypotheses about the pre-emergence niche of C. auris, whether in the environmental or human microbiome, and speculate on factors that might have led to its spread, including the possible roles of healthcare, antifungal use, and environmental changes, including human activities that might have expanded its presence in the environment or caused increased human contact.

The environmental mold Aspergillus fumigatus is the primary cause of invasive aspergillosis. In patients with high-risk conditions, including stem cell and organ transplant recipients, mortality exceeds 50%. Triazole antifungals have greatly improved survival (1); however, triazole-resistant A. fumigatus infections are increasingly reported worldwide and are associated with increased treatment failure and mortality (2). Of particular concern are resistant A. fumigatus isolates carrying either TR34/L98H or TR46/Y121F/T289A genetic resistance markers, which have been associated with environmental triazole fungicide use rather than previous patient exposure to antifungals (3,4). Reports of these triazole-resistant A. fumigatus strains have become common in Europe (2,3), but U.S. reports are limited (5). Because of the risk posed to immunocompromised patients, understanding the prevalence of such isolates in patients is important to guide clinical and public health decision-making. In 2011, CDC initiated passive laboratory monitoring for U.S. triazole-resistant A. fumigatus isolates through outreach to clinical laboratories. This system identified five TR34/L98H isolates collected from 2016 to 2017 (6), in addition to two other U.S. isolates collected in 2010 and 2014 and reported in 2015 (5). Four of these seven isolates were reported from Pennsylvania, two from Virginia, and one from California. Three isolates were collected from patients with invasive pulmonary aspergillosis, and four patients had no known previous triazole exposure. A. fumigatus resistant to all triazole medications is emerging in the United States, and clinicians and public health personnel need to be aware that resistant infections are possible even in patients not previously exposed to these medications.

Background: Candida auris is a multidrug-resistant yeast associated with hospital outbreaks worldwide. During 2015-2016, multiple outbreaks were reported in Colombia. We aimed to understand the extent of contamination in healthcare settings and to characterize the molecular epidemiology of C. auris in Colombia. Methods: We sampled patients, patient contacts, healthcare workers, and the environment in four hospitals with recent C. auris outbreaks. Using standardized protocols, people were swabbed at different body sites. Patient and procedure rooms were sectioned into four zones and surfaces were swabbed. We performed whole-genome sequencing (WGS) and antifungal susceptibility testing (AFST) on all isolates. Results: Seven (41%) of the 17 people swabbed were found to be colonized. C. auris was isolated from 37/322 (12%) environmental samples. These were collected from a variety of items in all four zones. WGS and AFST revealed that although isolates were similar throughout the country, isolates from the northern region were genetically distinct and more resistant to amphotericin B (AmB) than the isolates from central Colombia. Four novel non-synonymous mutations were found to be significantly associated with AmB resistance. Conclusions: Our results show that extensive C. auris contamination can occur and highlight the importance of adherence to appropriate infection control practices and disinfection strategies. Observed genetic diversity supports healthcare transmission and a recent expansion of C. auris within Colombia with divergent AmB susceptibility.

BACKGROUND: Candida auris, a multidrug-resistant yeast that causes invasive infections, was first described in 2009 in Japan and has since been reported from several countries. METHODS: To understand the global emergence and epidemiology of C. auris, we obtained isolates from 54 patients with C. auris infection from Pakistan, India, South Africa, and Venezuela during 2012-2015 and the type specimen from Japan. Patient information was available for 41 of the isolates. We conducted antifungal susceptibility testing and whole-genome sequencing (WGS). RESULTS: Available clinical information revealed that 41% of patients had diabetes mellitus, 51% had undergone recent surgery, 73% had a central venous catheter, and 41% were receiving systemic antifungal therapy when C. auris was isolated. The median time from admission to infection was 19 days (interquartile range, 9-36 days), 61% of patients had bloodstream infection, and 59% died. Using stringent break points, 93% of isolates were resistant to fluconazole, 35% to amphotericin B, and 7% to echinocandins; 41% were resistant to 2 antifungal classes and 4% were resistant to 3 classes. WGS demonstrated that isolates were grouped into unique clades by geographic region. Clades were separated by thousands of single-nucleotide polymorphisms, but within each clade isolates were clonal. Different mutations in ERG11 were associated with azole resistance in each geographic clade. CONCLUSIONS: C. auris is an emerging healthcare-associated pathogen associated with high mortality. Treatment options are limited, due to antifungal resistance. WGS analysis suggests nearly simultaneous, and recent, independent emergence of different clonal populations on 3 continents. Risk factors and transmission mechanisms need to be elucidated to guide control measures.

Listeria monocytogenes(Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all U.S.Lmisolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Whole-genome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens.