A Prediction Tool to Identify the Causative Agent of Enteric Disease Outbreaks Using Outbreak Surveillance Data.

Information on the causative agent in an enteric disease outbreak can be used to generate hypotheses about the route of transmission and possible vehicles, to guide environmental assessments, and to target outbreak control measures. However, only about 40% of outbreaks reported in the United States include a confirmed etiology. The goal of this project was to identify clinical and demographic characteristics that can be used to predict the causative agent in an enteric disease outbreak and to use these data to develop an online tool for investigators to use during an outbreak when hypothesizing about the causative agent. Using data on enteric disease outbreaks from all transmission routes (animal contact, environmental contamination, foodborne, person-to-person, waterborne, unknown) reported to the U.S. Centers for Disease Control and Prevention, we developed random forest models to predict the etiology of an outbreak based on aggregated clinical and demographic characteristics at both the etiology category (i.e., bacteria, parasites, toxins, viruses) and individual etiology (Clostridium perfringens, Campylobacter, Cryptosporidium, norovirus, Salmonella, Shiga toxin-producing Escherichia coli, and Shigella) levels. The etiology category model had a kappa of 0.85 and an accuracy of 0.92, whereas the etiology-specific model had a kappa of 0.75 and an accuracy of 0.86. The highest sensitivities in the etiology category model were for bacteria and viruses; all categories had high specificities (>0.90). For the etiology-specific model, norovirus and Salmonella had the highest sensitivity and all etiologies had high specificities. When laboratory confirmation is unavailable, information on the clinical signs and symptoms reported by people associated with the outbreak, with other characteristics including case demographics and illness severity, can be used to predict the etiology or etiology category. An online publicly available tool was developed to assist investigators in their enteric disease outbreak investigations.

Power Law for Estimating Underdetection of Foodborne Disease Outbreaks, United States.

We fit a power law distribution to US foodborne disease outbreaks to assess underdetection and underreporting. We predicted that 788 fewer than expected small outbreaks were identified annually during 1998-2017 and 365 fewer during 2018-2019, after whole-genome sequencing was implemented. Power law can help assess effectiveness of public health interventions.

Preliminary Incidence and Trends of Infections Caused by Pathogens Transmitted Commonly Through Food - Foodborne Diseases Active Surveillance Network, 10 U.S. Sites, 2016-2021.

To evaluate progress toward prevention of enteric infections in the United States, the Foodborne Diseases Active Surveillance Network (FoodNet) conducts active population-based surveillance for laboratory-diagnosed infections caused by Campylobacter, Cyclospora, Listeria, Salmonella, Shiga toxin-producing Escherichia coli (STEC), Shigella, Vibrio, and Yersinia at 10 U.S. sites. This report summarizes preliminary 2021 data and describes changes in annual incidence compared with the average annual incidence for 2016-2018, the reference period for the U.S. Department of Health and Human Services' (HHS) Healthy People 2030 goals for some pathogens (1). During 2021, the incidence of infections caused by Salmonella decreased, incidence of infections caused by Cyclospora, Yersinia, and Vibrio increased, and incidence of infections caused by other pathogens did not change. As in 2020, behavioral modifications and public health interventions implemented to control the COVID-19 pandemic might have decreased transmission of enteric infections (2). Other factors (e.g., increased use of telemedicine and continued increase in use of culture-independent diagnostic tests [CIDTs]) might have altered their detection or reporting (2). Much work remains to achieve HHS Healthy People 2030 goals, particularly for Salmonella infections, which are frequently attributed to poultry products and produce, and Campylobacter infections, which are frequently attributed to chicken products (3).

Characteristics and Outcomes of US Children and Adolescents With Multisystem Inflammatory Syndrome in Children (MIS-C) Compared With Severe Acute COVID-19.

Importance: Refinement of criteria for multisystem inflammatory syndrome in children (MIS-C) may inform efforts to improve health outcomes. Objective: To compare clinical characteristics and outcomes of children and adolescents with MIS-C vs those with severe coronavirus disease 2019 (COVID-19). Setting, Design, and Participants: Case series of 1116 patients aged younger than 21 years hospitalized between March 15 and October 31, 2020, at 66 US hospitals in 31 states. Final date of follow-up was January 5, 2021. Patients with MIS-C had fever, inflammation, multisystem involvement, and positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcriptase-polymerase chain reaction (RT-PCR) or antibody test results or recent exposure with no alternate diagnosis. Patients with COVID-19 had positive RT-PCR test results and severe organ system involvement. Exposure: SARS-CoV-2. Main Outcomes and Measures: Presenting symptoms, organ system complications, laboratory biomarkers, interventions, and clinical outcomes. Multivariable regression was used to compute adjusted risk ratios (aRRs) of factors associated with MIS-C vs COVID-19. Results: Of 1116 patients (median age, 9.7 years; 45% female), 539 (48%) were diagnosed with MIS-C and 577 (52%) with COVID-19. Compared with patients with COVID-19, patients with MIS-C were more likely to be 6 to 12 years old (40.8% vs 19.4%; absolute risk difference [RD], 21.4% [95% CI, 16.1%-26.7%]; aRR, 1.51 [95% CI, 1.33-1.72] vs 0-5 years) and non-Hispanic Black (32.3% vs 21.5%; RD, 10.8% [95% CI, 5.6%-16.0%]; aRR, 1.43 [95% CI, 1.17-1.76] vs White). Compared with patients with COVID-19, patients with MIS-C were more likely to have cardiorespiratory involvement (56.0% vs 8.8%; RD, 47.2% [95% CI, 42.4%-52.0%]; aRR, 2.99 [95% CI, 2.55-3.50] vs respiratory involvement), cardiovascular without respiratory involvement (10.6% vs 2.9%; RD, 7.7% [95% CI, 4.7%-10.6%]; aRR, 2.49 [95% CI, 2.05-3.02] vs respiratory involvement), and mucocutaneous without cardiorespiratory involvement (7.1% vs 2.3%; RD, 4.8% [95% CI, 2.3%-7.3%]; aRR, 2.29 [95% CI, 1.84-2.85] vs respiratory involvement). Patients with MIS-C had higher neutrophil to lymphocyte ratio (median, 6.4 vs 2.7, P < .001), higher C-reactive protein level (median, 152 mg/L vs 33 mg/L; P < .001), and lower platelet count (<150 ×103 cells/µL [212/523 {41%} vs 84/486 {17%}, P < .001]). A total of 398 patients (73.8%) with MIS-C and 253 (43.8%) with COVID-19 were admitted to the intensive care unit, and 10 (1.9%) with MIS-C and 8 (1.4%) with COVID-19 died during hospitalization. Among patients with MIS-C with reduced left ventricular systolic function (172/503, 34.2%) and coronary artery aneurysm (57/424, 13.4%), an estimated 91.0% (95% CI, 86.0%-94.7%) and 79.1% (95% CI, 67.1%-89.1%), respectively, normalized within 30 days. Conclusions and Relevance: This case series of patients with MIS-C and with COVID-19 identified patterns of clinical presentation and organ system involvement. These patterns may help differentiate between MIS-C and COVID-19.

Severe Respiratory Illness Associated with Human Metapneumovirus in Nursing Home, New Mexico, USA.

Human metapneumovirus is an emerging pathogen that causes upper and lower respiratory illness. Nursing home outbreaks of infection with this virus can cause severe illness and lead to poor patient outcomes. We report an outbreak investigation in a nursing home during 2018 and infection control guidelines to assist in disease control.

Middle East Respiratory Syndrome Coronavirus, Saudi Arabia, 2017-2018.

We characterized exposures and demographics of Middle East respiratory syndrome coronavirus cases reported to the Saudi Arabia Ministry of Health during July 1-October 31, 2017, and June 1-September 16, 2018. Molecular characterization of available specimens showed that circulating viruses during these periods continued to cluster within lineage 5.

Severe Respiratory Illness Outbreak Associated with Human Coronavirus NL63 in a Long-Term Care Facility.

We describe an outbreak of severe respiratory illness associated with human coronavirus NL63 in a long-term care facility in Louisiana in November 2017. Six of 20 case-patients were hospitalized with pneumonia, and 3 of 20 died. Clinicians should consider human coronavirus NL63 for patients in similar settings with respiratory disease.

Respiratory Syncytial Virus Seasonality - United States, 2014-2017.

Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infection in young children worldwide (1-3). In the United States, RSV infection results in >57,000 hospitalizations and 2 million outpatient visits each year among children aged <5 years (3). Recent studies have highlighted the importance of RSV in adults as well as children (4). CDC reported RSV seasonality nationally, by U.S. Department of Health and Human Services (HHS) regions* and for the state of Florida, using a new statistical method that analyzes polymerase chain reaction (PCR) laboratory detections reported to the National Respiratory and Enteric Virus Surveillance System (NREVSS) (https://www.cdc.gov/surveillance/nrevss/index.html). Nationally, across three RSV seasons, lasting from the week ending July 5, 2014 through July 1, 2017, the median RSV onset occurred at week 41 (mid-October), and lasted 31 weeks until week 18 (early May). The median national peak occurred at week 5 (early February). Using these new methods, RSV season circulation patterns differed from those reported from previous seasons (5). Health care providers and public health officials use RSV circulation data to guide diagnostic testing and to time the administration of RSV immunoprophylaxis for populations at high risk for severe respiratory illness (6). With several vaccines and other immunoprophlyaxis products in development, estimates of RSV circulation are also important to the design of clinical trials and future vaccine effectiveness studies.

Epidemiology and Antimicrobial Resistance of Campylobacter Infections in the United States, 2005-2018.

Background: Campylobacter is the most common cause of bacterial diarrhea in the United States; resistance to macrolides and fluoroquinolones limits treatment options. We examined the epidemiology of US Campylobacter infections and changes in resistance over time. Methods: The Foodborne Diseases Active Surveillance Network receives information on laboratory-confirmed Campylobacter cases from 10 US sites, and the National Antimicrobial Resistance Monitoring System receives a subset of isolates from these cases for antimicrobial susceptibility testing. We estimated trends in incidence of Campylobacter infection, adjusting for sex, age, and surveillance changes attributable to culture-independent diagnostic tests. We compared percentages of isolates resistant to erythromycin or ciprofloxacin during 2005-2016 with 2017-2018 and used multivariable logistic regression to examine the association of international travel with resistance. Results: Adjusted Campylobacter incidence remained stable or decreased for all groups analyzed since 2012. Among 2449 linked records in 2017-2018, the median patient age was 40.2 years (interquartile range, 21.6-57.8 years), 54.8% of patients were male, 17.2% were hospitalized, and 0.2% died. The percentage of resistant infections increased from 24.5% in 2005-2016 to 29.7% in 2017-2018 for ciprofloxacin (P < .001) and from 2.6% to 3.3% for erythromycin (P = .04). Persons with recent international travel had higher odds than nontravelers of having isolates resistant to ciprofloxacin (adjusted odds ratio [aOR] varied from 1.7 to 10.6 by race/ethnicity) and erythromycin (aOR = 1.7; 95% confidence interval, 1.3-2.1). Conclusions: Campylobacter incidence has remained stable or decreased, whereas resistance to antimicrobials recommended for treatment has increased. Recent international travel increased the risk of resistance.

Respiratory Syncytial Virus-Associated Hospitalizations in Children With Neurological Disorders, 2006-2015.

BACKGROUND: We quantified the risk of respiratory syncytial virus (RSV) hospitalizations and severe outcomes among children with neurological disorders. METHODS: We estimated RSV-specific and RSV-associated hospitalization rates using International Classification of Diseases, Ninth Revision (ICD-9) codes from 2 insurance claims IBM MarketScan Research Databases (Commercial and Multi-State Medicaid) from July 2006 through June 2015. For comparison, a simple random sample of 10% of all eligible children was selected to represent the general population. Relative rates (RRs) of RSV hospitalization were calculated by dividing rates for children with neurological disorders by rates for children in the general population by age group and season. RESULTS: The RSV-specific hospitalization rate for children with any neurological condition was 4.2 (95% confidence interval [CI]: 4.1, 4.4) per 1000 person-years, and the RSV-associated hospitalization rate was 7.0 (95% CI: 6.9, 7.2) per 1000 person-years among children <19 years of age. Among privately insured children, the overall RR of RSV hospitalization in children with neurological disorders compared with the general population was 10.7 (95% CI: 10.0, 11.4) for RSV-specific hospitalization and 11.1 (95% CI: 10.5, 11.7) for RSV-associated hospitalizations. Among children in Medicaid, the RSV-specific hospitalization RR was 6.1 (95% CI: 5.8, 6.5) and the RSV-associated hospitalization RR was 6.4 (95% CI: 6.2, 6.7) compared with the general population. CONCLUSIONS: Our population-based study of children with neurological disorders found that the risk of RSV hospitalization was 6 to 12 times higher among children with neurological disorders than among the general pediatric population. These findings should be considered when determining who should be targeted for current and future RSV interventions.

Multiple Respiratory Syncytial Virus Introductions Into a Neonatal Intensive Care Unit.

BACKGROUND: Outbreaks of respiratory syncytial virus (RSV) in neonatal intensive care units (NICUs) are of concern because of the risk of severe disease in young infants. We describe an outbreak of RSV in a NICU and use whole genome sequencing (WGS) to better understand the relatedness of viruses among patients. METHODS: An investigation was conducted to identify patients and describe their clinical course. Infection control measures were implemented to prevent further spread. Respiratory specimens from outbreak-related patients and the community were tested using WGS. Phylogenetic trees were constructed to understand relatedness of the viruses. RESULTS: Seven patients developed respiratory symptoms within an 11-day span in December 2017 and were diagnosed with RSV; 6 patients (86%) were preterm and 1 had chronic lung disease. Three patients required additional respiratory support after symptom onset, and none died. Six of 7 patients were part of the same cluster based on > 99.99% nucleotide agreement with each other and 3 unique single-nucleotide polymorphisms were identified in viruses sequenced from those patients. The seventh patient was admitted from the community with respiratory symptoms and had a genetically distinct virus that was not related to the other 6. Implementation of enhanced infection control measures likely limited the spread. CONCLUSIONS: Using WGS, we found 2 distinct introductions of RSV into a NICU, highlighting the risk of healthcare-associated infections during RSV season. Early recognition and infection control measures likely limited spread, emphasizing the importance of considering RSV in the differential diagnosis of respiratory infections in healthcare settings.

Respiratory syncytial virus seasonality in three epidemiological zones of Kenya.

Understanding respiratory syncytial virus (RSV) circulation patterns is necessary to guide the timing of limited-duration interventions such as vaccines. We describe RSV circulation over multiple seasons in three distinct counties of Kenya during 2006-2018. Kilifi and Siaya counties each had consistent but distinct RSV seasonality, lasting on average 18-22 weeks. Based on data from available years, RSV did not have a clear pattern of circulation in Nairobi. This information can help guide the timing of vaccines and immunoprophylaxis products that are under development.

Risk maps for cities: Incorporating streets into geostatistical models.

Vector-borne diseases commonly emerge in urban landscapes, and Gaussian field models can be used to create risk maps of vector presence across a large environment. However, these models do not account for the possibility that streets function as permeable barriers for insect vectors. We describe a methodology to transform spatial point data to incorporate permeable barriers, by distorting the map to widen streets, with one additional parameter. We use Gaussian field models to estimate this additional parameter, and develop risk maps incorporating streets as permeable barriers. We demonstrate our method on simulated datasets and apply it to data on Triatoma infestans, a vector of Chagas disease in Arequipa, Peru. We found that the transformed landscape that best fit the observed pattern of Triatoma infestans infestation, approximately doubled the true Euclidean distance between neighboring houses on different city blocks. Our findings may better guide control of re-emergent insect populations.