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OBJECTIVE To determine whether empirical antibiotic initiation and selection for children with pneumonia was associated with procalcitonin (PCT) levels when results were blinded to clinicians. METHODS We enrolled children RESULTS We enrolled 488 children (median PCT, 0.37 ng/mL; interquartile range [IQR], 0.11–2.38); 85 (17%) received no antibiotics (median PCT, 0.32; IQR, 0.09–1.33). Among the 403 children receiving antibiotics, 95 (24%) received narrow-spectrum therapy (median PCT, 0.24; IQR, 0.08–2.52) and 308 (76%) received broad-spectrum (median PCT, 0.46; IQR, 0.12–2.83). In adjusted analyses, PCT values were not associated with antibiotic initiation (odds ratio [OR], 1.02, 95% confidence interval [CI], 0.97%–1.06%) or empirical antibiotic selection (OR 1.07; 95% CI, 0.97%–1.17%). Of those with noncritical illness, 246 (69%) were identified as potential targets for antibiotic stewardship interventions. CONCLUSION Neither antibiotic initiation nor empirical antibiotic selection were associated with PCT values. Whereas other factors may inform antibiotic treatment decisions, the observed discordance between objective likelihood of bacterial etiology and antibiotic use suggests important opportunities for stewardship.

OBJECTIVES: To determine if serum procalcitonin, an indicator of bacterial etiology in pneumonia in all ages and a predictor of severe pneumonia in adults, is associated with disease severity in children with community-acquired pneumonia. METHODS: We prospectively enrolled children 2 months to RESULTS: The study included 488 children with pneumonia; 30 (6%) were classified as very severe, 106 (22%) as severe, 327 (67%) as moderate, and 25 (5%) as mild. Median procalcitonin in the very severe group was 5.06 (interquartile range [IQR] 0.90–16.83), 0.38 (IQR 0.11–2.11) in the severe group, 0.29 (IQR 0.09–1.90) in the moderate group, and 0.21 (IQR 0.12–1.2) in the mild group. Increasing procalcitonin was associated with increasing severity (range of aORs: 1.03–1.25) and increased LOS (range of aORs: 1.04–1.36). All comparisons were statistically significant. CONCLUSIONS: Higher procalcitonin was associated with increased severity and LOS. Procalcitonin may be useful in helping clinicians evaluate pneumonia severity.

Background Respiratory Syncytial Virus (RSV) is one of the most common causes of childhood lower respiratory tract infection (LRTI) leading to hospitalization worldwide. Readmissions following viral LRTI hospitalization are common, however rates, timing and causes of readmission following RSV LRTI hospitalization are understudied. We evaluated readmissions occurring during 1-year post-discharge of RSV hospitalization. Methods We prospectively identified children < 5 years of age hospitalized with laboratory-confirmed RSV LRTI at Primary Children’s and Riverton hospitals in Salt Lake City, Utah during the 2019-2020 RSV season. An electronic alert system identified all-cause readmission between November 2019 and April 2021. Discharge diagnoses of readmissions were reviewed by two pediatricians. We calculated the incidence rate of all-cause and respiratory-related readmission. Results A total of 297 children had laboratory-confirmed RSV LRTI hospitalizations during the 2019-2020 RSV season, with 24% admitted to the intensive care unit (ICU) during index RSV hospitalization and 24% having a chronic medical condition. During the 1-year follow-up period, 59 readmissions occurred among 47 patients (Table 1). The incidence rate of all-cause and respiratory-related readmission was 19.9 (95%CI 15.5-24.9) and 13.1 (95%CI 9.5-17.5) per 100 patients, respectively. Median age of readmitted patients was 11 months (interquartile range 5.9-11 months). Median number of readmissions was 1 (range: 1-4), with initial readmissions occurring within 28 days (median) of index admission; most (74%) due to a respiratory-related illness. Second and 3rd admissions were less common and occurred at 67 (median) and 160 (median) days respectively. During all readmissions, 19% of children required ICU admission and 25% had chronic medical conditions. Conclusion All cause and respiratory readmission after Initial hospitalization with RSV LRTI commonly occurred among children < 5 years. These data support the need for RSV vaccines and immunoprophylaxis to prevent RSV hospitalization. A further study with a control group is needed to determine the role of RSV in readmission. Disclosures Yoonyoung Choi, PhD, MS, RPh, Merck (Employee) Lyn Finelli, DrPH, MS, Merck (Employee)

Background Respiratory Syncytial Virus (RSV) is one of the most common causes of childhood lower respiratory tract infection (LRTI) worldwide. While financial burdens have been documented, there are few data on parental psychological stress associated with RSV hospitalizations. We evaluated the psychological stress and anxiety of parents whose children were hospitalized with RSV. Methods During the 2019-2020 RSV season, parents with children < 5 years of age hospitalized with laboratory-confirmed RSV LRTI at Primary Children’s and Riverton Hospitals in Salt Lake City, Utah, were surveyed in person, and online after discharge. As part of the survey, parents completed the State-Trait Anxiety Inventory for Adults (STAIAD) instrument (short form) and the parental stressor scale (PSS). We evaluated the difference in parental stress and anxiety reported during hospitalization and at 2-weeks post-discharge using a paired t-test. Results Among 284 Salt Lake County resident children < 5 years, and hospitalized with RSV LRTI, 75 (26%) and 57 (20%) parents completed both surveys on admission and at 2-weeks post-discharge respectively. In 11 of 20 STAIAD items gauging stress and anxiety, parents reported higher levels of stress and anxiety whilst their children were admitted compared to post-discharge (Table 1). Parents’ average score on several items associated with a “positive outlook,” e.g. I feel calm, significantly improved (p < 0.05) at 2-weeks post-discharge. Similarly, several items associated with a “negative outlook,” e.g. I am worried, significantly decreased (p < 0.05) at 2-weeks post-discharge (Table 1). For the PSS items, ≥ 50% of parents rated 15 out of 25 as being “very or extremely stressful”, including: feeling helpless about how to help my baby; my baby’s unusual or abnormal breathing; and when my baby seemed to be in pain (Table 2). Estimates of Psychological Burden of RSV lower respiratory tract infection (LRTI) Hospitalization of Children Estimates of Psychological Burden of RSV lower respiratory tract infection (LRTI) Hospitalization of Children Conclusion RSV LRTI hospitalization among children < 5 years of age, imposed a significant psychological stress and anxiety on parents, which generally persisted up to 2-weeks post-discharge. Prevention of RSV infection through vaccines and immunoprophylaxis will help ease parental psychological burden associated with RSV hospitalization. Disclosures Krow Ampofo, MBChB, Merck (Grant/Research Support) Yoonyoung Choi, PhD, MS, RPh, Merck (Employee) Lyn Finelli, DrPH, MS, Merck & Co Inc, (Employee)

The 2017-18 U.S. influenza season was notable for its high severity, with approximately 45 million illnesses and 810,000 influenza-associated hospitalizations throughout the United States (1). The purpose of the investigation reported here was to create a state-level estimate of the number of persons in Utah who became ill with influenza disease during this severe national seasonal influenza epidemic and to create a sustainable system for making timely updates in future influenza seasons. Knowing the extent of influenza-associated illness can help public health officials, policymakers, and clinicians tailor influenza messaging, planning, and responses for seasonal influenza epidemics or during pandemics. Using national methods and existing influenza surveillance and testing data, the influenza burden (number of influenza illnesses, medical visits for influenza, and influenza-associated hospitalizations) in Utah during the 2016-17 and 2017-18 influenza seasons was estimated. During the 2016-17 season, an estimated 265,000 symptomatic illnesses affecting 9% of Utah residents occurred, resulting in 125,000 medically attended illnesses and 2,700 hospitalizations. During the 2017-18 season, an estimated 338,000 symptomatic illnesses affecting 11% of Utah residents occurred, resulting in 160,000 medically attended illnesses and 3,900 hospitalizations. Other state or county health departments could adapt similar methods in their jurisdictions to estimate the burden of influenza locally and support prompt public health activities.

Traumatic brain injury is one of the most common pediatric injuries; totaling more than 500,000 emergency department visits per year. When the injury involves a skull fracture, sinus venous thrombosis and the risk of resultant increased intracranial pressure (ICP) are a concern. We describe a previously healthy 11-month-old female infant with nondepressed skull fracture who developed increased ICP in the absence of intracranial changes on imaging. Funduscopic examination revealed unilateral papilledema, and opening pressure on lumbar puncture was elevated at 35 cm of H2O. Computed tomography scan demonstrated a nondepressed occipital bone fracture. However, further imaging, including magnetic resonance imaging with angiogram/venogram, did not reveal any intracranial abnormalities. In particular, there was no evidence of sinus venous thrombosis. Given her presentation and signs of increased ICP, she was started on acetazolamide and improved dramatically. A thorough literature search was completed but yielded no information on infants with increased ICP after nondepressed skull fracture in the absence of radiographic findings to suggest a cause for the increase in pressure. Trauma alone can lead to increased ICP secondary to several processes, although this is expected in moderate to severe head trauma. Our case demonstrates that increased ICP can be present in infants with mild traumatic brain injury in the absence of intracranial pathology. This should be considered in patients who present with persistent vomiting that is refractory to antiemetics.

Background Respiratory Syncytial Virus (RSV) is one of the most common causes of childhood lower respiratory tract infection (LRTI) worldwide. Accurate data are critical to inform the rationale for RSV vaccine and immunoprophylaxis development. We evaluated the burden of laboratory-confirmed RSV from hospitalized children. Methods During the 2019-2020 RSV season, we prospectively identified children < 5 years of age hospitalized with laboratory-confirmed RSV LRTI at Primary Children’s and Riverton hospitals in Salt Lake City, Utah. Outcomes included Salt Lake county RSV hospitalization rates, adjusted for market share, health care resource utilization including intensive care unit (ICU) stays, mechanical ventilation, length of stay (LOS), and total hospital costs. Results A total of 284 children had laboratory-confirmed RSV LRTI hospitalizations during the 2019-2020 RSV season: 106 (37%) < 6 months of age; 67 (24%) had high-risk medical conditions (HMC); 70 (25%) children had an ICU stay; 18 (6%) required mechanical ventilation; 132 (46%) received antibiotics and median hospital LOS of 2.3 days (IQR 1.6- 3.6). Population-based incidence rates of RSV hospitalization were 4.6/1000 (range 0.7/1000 to 17/1000). The highest rates were in children < 6 months, and rates decreased with increasing age. The mean hospital cost was $12,974.6 (standard deviation: $19869.7), with a total for the cohort was $3.7 million; 42% was accounted for by children < 6 months. Median age of children with HMC’s were significantly older (18.7 mon vs. 12.7 mon; p=0.001) than healthy, but comparable mean hospital cost ($14208.5 vs. 12593.2) and median hospital LOS (2.4 vs. 2.3). Conclusion Hospitalized RSV LRTI among children < 5 years remains significant, and is associated with substantial HCRU, antibiotic use and morbidity. Nationwide, the mean hospital costs may total $1.1 billion. Our data support the need for RSV vaccines and immunoprophylaxis to prevent RSV hospitalization. Disclosures Krow Ampofo, MBChB, Merck (Grant/Research Support) Yoonyoung Choi, PhD, MS, RPh, Merck (Employee) Lyn Finelli, DrPH, MS, Merck & Co Inc, (Employee)

1AbstractThe prediction and characterization of outbreaks of infectious diseases such as influenza remains an open and important problem. This paper describes a framework for detecting and characterizing outbreaks of influenza and the results of testing it on data from ten outbreaks collected from two locations over five years. We model outbreaks with compartment models and explicitly model non-influenza influenza-like illnesses.

Nearly 60% of U.S. children live in counties with particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PMTo evaluate the association between ambient PMUsing an observational case-crossover design, subjects (n = 146,397) were studied if they had an ALRI diagnosis and resided on Utah's Wasatch Front. PMApproximately 77% (n = 112,467) of subjects were 0-2 years of age. The odds of ALRI encounter for these young children increased within 1 week of elevated PMIn this large sample of urban/suburban patients, short-term exposure to elevated PM

BACKGROUND Health care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are comprehensive and specific with respect to the pathogen but are rapid in reporting the data. It has proven difficult to implement these requirements on a large scale while maintaining patient privacy. OBJECTIVE The aim of this study was to demonstrate the automated export, aggregation, and analysis of infectious disease diagnostic test results from clinical laboratories across the United States in a manner that protects patient confidentiality. We hypothesized that such a system could aid in monitoring the seasonal occurrence of respiratory pathogens and may have advantages with regard to scope and ease of reporting compared with existing surveillance systems. METHODS We describe a system, BioFire Syndromic Trends, for rapid disease reporting that is syndrome-based but pathogen-specific. Deidentified patient test results from the BioFire FilmArray multiplex molecular diagnostic system are sent directly to a cloud database. Summaries of these data are displayed in near real time on the Syndromic Trends public website. We studied this dataset for the prevalence, seasonality, and coinfections of the 20 respiratory pathogens detected in over 362,000 patient samples acquired as a standard-of-care testing over the last 4 years from 20 clinical laboratories in the United States. RESULTS The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks, and adenovirus and the bacterial pathogens show constant detection over the year. The dataset can also be considered in an ecological framework; the viruses and bacteria detected by this test are parasites of a host (the human patient). Interestingly, the rate of pathogen codetections, on average 7.94% (28,741/362,101), matches predictions based on the relative abundance of organisms present. CONCLUSIONS Syndromic Trends preserves patient privacy by removing or obfuscating patient identifiers while still collecting much useful information about the bacterial and viral pathogens that they harbor. Test results are uploaded to the database within a few hours of completion compared with delays of up to 10 days for other diagnostic-based reporting systems. This work shows that the barriers to establishing epidemiology systems are no longer scientific and technical but rather administrative, involving questions of patient privacy and data ownership. We have demonstrated here that these barriers can be overcome. This first look at the resulting data stream suggests that Syndromic Trends will be able to provide high-resolution analysis of circulating respiratory pathogens and may aid in the detection of new outbreaks.

Health-care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are pathogen-specific. We describe a system, FilmArray®Trend, for rapid disease reporting that is syndrome-based but pathogen-specific. Results from a multiplex molecular diagnostic test are sent directly to a cloud database.www.syndromictrends.compresents these data in near real-time. Trend preserves patient privacy by removing or obfuscating patient identifiers. We summarize the respiratory pathogen results, for 20 organisms from 344,000 patient samples acquired as standard of care testing over the last four years from 20 clinical laboratories in the United States. The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks and adenovirus and bacterial pathogens show constant detection over the year. Interestingly, the rate of pathogen co-detections, on average 7.7%, matches predictions based on the relative abundance of organisms present.

Poison control centers (PCCs) and emergency departments (EDs) rely upon telephone communication to collaborate. PCCs and EDs each create electronic records for the same patient during the course of collaboration, but those electronic records are not shared.The purpose of this study was to describe the current, telephone based process of PCC-ED communication as the basis for potential process improvement.This study was conducted at one PCC and two tertiary care EDs. We developed workflow diagrams to depict clinician descriptions of the current process, descriptions obtained through interviews of key informants. We also analyzed transcripts of phone calls between emergency departments and the poison control center, corresponding to a random sample of 120 PCC cases occurring January 1-December 31, 2011.Collaboration between the ED and PCC takes place during multiple telephone calls, and the process is unsupported by shared documentation. The process occurs in three phases: notification, collaborative care, and ongoing consultation. In the ED, multiple care providers may communicate with the PCC, but only one ED care provider communicates with the poison control center specialist at a time. Handoffs occur for both ED and PCC. Collaborative care planning is common and most cases involve some type of request for information, whether vital signs, laboratory results, or verification that a treatment was administered. We found evidence of inefficiencies and safety vulnerabilities, including the inability of PCC specialists to reach ED care providers, telephone calls routed through multiple ED staff members in an attempt to reach the appropriate care provider, and exchange of clinical information with non-clinical staff. In 55% of cases, the patient was discharged prior to any synchronous telephone communication between the ED care provider and a PCC specialist. Ambiguous communication of information was observed in 22% of cases. In 12% of cases, a PCC specialist was unable to obtain requested information from the ED.Inefficiencies and vulnerabilities occur in telephone-based PCC-ED communication. Prudence begs consideration of alternative processes and models of ED-PCC communication and information sharing, including a process that supports collaboration with health information exchange.

SummaryObjectives: This study evaluates the accuracy and portability of a natural language processing (NLP) tool for extracting clinical findings of influenza from clinical notes across two large healthcare systems. Effectiveness is evaluated on how well NLP supports downstream influenza case-detection for disease surveillance.Methods: We independently developed two NLP parsers, one at Intermountain Healthcare (IH) in Utah and the other at University of Pittsburgh Medical Center (UPMC) using local clinical notes from emergency department (ED) encounters of influenza. We measured NLP parser performance for the presence and absence of 70 clinical findings indicative of influenza. We then developed Bayesian network models from NLP processed reports and tested their ability to discriminate among cases of (1) influenza, (2) non-influenza influenza-like illness (NI-ILI), and (3) ‘other’ diagnosis.Results: On Intermountain Healthcare reports, recall and precision of the IH NLP parser were 0.71 and 0.75, respectively, and UPMC NLP parser, 0.67 and 0.79. On University of Pittsburgh Medical Center reports, recall and precision of the UPMC NLP parser were 0.73 and 0.80, respectively, and IH NLP parser, 0.53 and 0.80. Bayesian case-detection performance measured by AUROC for influenza versus non-influenza on Intermountain Healthcare cases was 0.93 (using IH NLP parser) and 0.93 (using UPMC NLP parser). Case-detection on University of Pittsburgh Medical Center cases was 0.95 (using UPMC NLP parser) and 0.83 (using IH NLP parser). For influenza versus NI-ILI on Intermountain Healthcare cases performance was 0.70 (using IH NLP parser) and 0.76 (using UPMC NLP parser). On University of Pisstburgh Medical Center cases, 0.76 (using UPMC NLP parser) and 0.65 (using IH NLP parser).Conclusion: In all but one instance (influenza versus NI-ILI using IH cases), local parsers were more effective at supporting case-detection although performances of non-local parsers were reasonable.Citation: Ferraro JP, Ye Y, Gesteland PH, Haug PJ, Tsui F(R), Cooper GF, Van Bree R, Ginter T, Nowalk AJ, Wagner M. The effects of natural language processing on cross-institutional portability of influenza case detection for disease surveillance. Appl Clin Inform 2017; 8: 560–580 https://doi.org/10.4338/ACI-2016-12-RA-0211

Outbreaks of infectious diseases such as influenza are a significant threat to human health. Because there are different strains of influenza which can cause independent outbreaks, and influenza can affect demographic groups at different rates and times, there is a need to recognize and characterize multiple outbreaks of influenza. This paper describes a Bayesian system that uses data from emergency department patient care reports to create epidemiological models of overlapping outbreaks of influenza. Clinical findings are extracted from patient care reports using natural language processing. These findings are analyzed by a case detection system to create disease likelihoods that are passed to a multiple outbreak detection system. We evaluated the system using real and simulated outbreaks. The results show that this approach can recognize and characterize overlapping outbreaks of influenza. We describe several extensions that appear promising.

Advances in surveillance science have supported public health agencies in tracking and responding to disease outbreaks. Increasingly, epidemiologists have been tasked with interpreting multiple streams of heterogeneous data arising from varied surveillance systems. As a result public health personnel have experienced an overload of plots and charts as information visualization techniques have not kept pace with the rapid expansion in data availability. This study sought to advance the science of public health surveillance data visualization by conceptualizing a visual paradigm that provides an 'epidemiological canvas' for detection, monitoring, exploration and discovery of regional infectious disease activity and developing a software prototype of an 'infectious disease weather map'. Design objectives were elucidated and the conceptual model was developed using cognitive task analysis with public health epidemiologists. The software prototype was pilot tested using retrospective data from a large, regional pediatric hospital, and gastrointestinal and respiratory disease outbreaks were re-created as a proof of concept.

Unnecessarily broad-spectrum antibiotic prescribing for ambulatory pediatric urinary tract infection may result from clinicians not having antibiograms specific to this population. Comparing an existing hospital-based with a proposed ambulatory uropathogen antibiogram for children in Utah, Escherichia coli accounted for a larger percentage and was more susceptible to narrower-spectrum antibiotics, demonstrating the potential need for ambulatory pediatric antibiograms.

Background: Health care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are comprehensive and specific with respect to the pathogen but are rapid in reporting the data. It has proven difficult to implement these requirements on a large scale while maintaining patient privacy. Objective: The aim of this study was to demonstrate the automated export, aggregation, and analysis of infectious disease diagnostic test results from clinical laboratories across the United States in a manner that protects patient confidentiality. We hypothesized that such a system could aid in monitoring the seasonal occurrence of respiratory pathogens and may have advantages with regard to scope and ease of reporting compared with existing surveillance systems. Methods: We describe a system, BioFire Syndromic Trends, for rapid disease reporting that is syndrome-based but pathogen-specific. Deidentified patient test results from the BioFire FilmArray multiplex molecular diagnostic system are sent directly to a cloud database. Summaries of these data are displayed in near real time on the Syndromic Trends public website. We studied this dataset for the prevalence, seasonality, and coinfections of the 20 respiratory pathogens detected in over 362,000 patient samples acquired as a standard-of-care testing over the last 4 years from 20 clinical laboratories in the United States. Results: The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks, and adenovirus and the bacterial pathogens show constant detection over the year. The dataset can also be considered in an ecological framework; the viruses and bacteria detected by this test are parasites of a host (the human patient). Interestingly, the rate of pathogen codetections, on average 7.94% (28,741/362,101), matches predictions based on the relative abundance of organisms present. Conclusions: Syndromic Trends preserves patient privacy by removing or obfuscating patient identifiers while still collecting much useful information about the bacterial and viral pathogens that they harbor. Test results are uploaded to the database within a few hours of completion compared with delays of up to 10 days for other diagnostic-based reporting systems. This work shows that the barriers to establishing epidemiology systems are no longer scientific and technical but rather administrative, involving questions of patient privacy and data ownership. We have demonstrated here that these barriers can be overcome. This first look at the resulting data stream suggests that Syndromic Trends will be able to provide high-resolution analysis of circulating respiratory pathogens and may aid in the detection of new outbreaks.

Please cite this paper as: Allison et al. (2010) Feasibility of elementary school children’s use of hand gel and facemasks during influenza season. Influenza and Other Respiratory Viruses 4(4), 223–229. Background The feasibility of non-pharmacologic interventions to prevent influenza’s spread in schools is not well known. Objectives To determine the acceptability of, adherence with, and barriers to the use of hand gel and facemasks in elementary schools. Patients and Methods Intervention: We provided hand gel and facemasks to 20 teachers and their students over 4 weeks. Gel use was promoted for the first 2 weeks; mask use was promoted for the second 2 weeks. Outcomes: Acceptability, adherence, and barriers were measured by teachers’ responses on weekly surveys. Mask use was also measured by observation. Results The weekly survey response rate ranged from 70% to 100%. Averaged over 2 weeks, 89% of teachers thought gel use was not disruptive (week 1 – 17/20, week 2 – 16/17), 95% would use gel next winter (week 1 – 19/20, week 2 – 16/17), and 97% would use gel in a pandemic (week 1 – 20/20, week 2 – 16/17). Averaged over 2 weeks, 39% thought mask use was not disruptive (week 1 – 6/17, week 2 – 6/14), 35% would use masks next winter (week 1 – 5/17, week 2 – 6/14), and 97% would use masks in a pandemic (week 1 – 16/17, week 2 – 14/14). About 70% estimated that their students used hand gel ≥4×/day for both weeks (week 1 – 14/20, week 2 – 13/17). Students’ mask use declined over time with 59% of teachers (10/17) estimating regular mask use during week 1 and 29% (4/14) during week 2. By observation, 30% of students wore masks in week 1, while 15% wore masks in week 2. Few barriers to gel use were identified; barriers to mask use were difficulty reading facial expressions and physical discomfort. Conclusions Hand gel use is a feasible strategy in elementary schools. Acceptability and adherence with facemasks was low, but some students and teachers did use facemasks for 2 weeks, and most teachers would use masks in their classroom in a pandemic.

In this retrospective cohort study, a clinical and administrative database of children hospitalized at Primary Children's Medical Center, Salt Lake City, Utah, between January 1, 2002, and December 31, 2006, was used to identify those with laboratory-confirmed rotavirus infections and at least one seizure. In all, 59 children were identified, 34 of whom (58%) had no other potential medical explanation for their seizures. Of these 34 children, 23 (68%) were afebrile at seizure onset and 11 were febrile. Electroencephalography was performed for 21 of the 34 children (62%); all findings were normal, except for a child with slowing related to cerebral edema. Twenty-six of the 34 children (76%) had neuroimaging studies; all findings were normal, except for the child with cerebral edema and a child with an incidental arachnoid cyst. Twenty of the 34 children (59%) had a lumbar puncture; again, all findings were normal. All 34 children recovered uneventfully, including the 6 children who spent at least 1 day in an intensive care unit. Follow-up data on 27 of these children identified 2 children (7%) who required chronic anticonvulsant therapy. The results indicate that seizures associated with rotavirus infection are a relatively benign neurologic condition in young children. With few exceptions, neurodiagnostic studies do not influence management or outcome.

We evaluated the presentation, outcomes, and the risk of serious bacterial infection (SBI) in infants3 months old with influenza virus infection.We identified demographic, hospitalization, and microbiologic data from computerized medical records for all infants and children24 months of age, with laboratory confirmed influenza infection cared for at a tertiary care children's hospital during 4 winter seasons (2004-2008). We compared those3 months of age with older groups.We identified 833 children24 months of age with laboratory-confirmed influenza. Of those, 218 were3 months old. Influenza accounted for 3.6% of all evaluations of febrile infants and 12% of febrile infant encounters during winter. Infants3 months of age were less likely to have a high risk chronic medical condition, but were more likely to be hospitalized than children 3 to24 months old (P0.005). Infants3 months with influenza had fewer prolonged hospital stays than those 3 to6 months old [P = 0.056; OR: 0.5 (0.24-1.0)] and 6 to12 months old [P = 0.011; OR: 0.43 (0.24-0.83)]. Five (2.3%) infants3 months old had SBI.Infants3 months of age with influenza virus infection often present with fever alone. Although they are more likely to be hospitalized than those 3 to24 months old, hospital stays are short and outcomes generally good. Infants with influenza virus infection have a low risk of concomitant SBI.

BACKGROUND The surveillance case definition for confirmed pertussis requires that an individual with a positive polymerase chain reaction (PCR) result for Bordetella pertussis have 2 weeks or more of cough and at least one of the following: paroxysmal coughing, inspiratory "whoop," or posttussive vomiting. OBJECTIVES Determine (1) proportion of individuals with a positive PCR result who met additional criteria for surveillance confirmed pertussis, (2) whether the likelihood of PCR-positive individuals meeting additional elements of surveillance case definition varied by age or vaccination status, and (3) whether elements of the current case definition influence the likelihood of pertussis confirmation in PCR-positive individuals. METHODS Pertussis PCR results were compared with case investigation data. RESULTS Eighty-eight percent (165/188) of PCR-positive individuals met requirements for confirmed pertussis. Sixty-one percent (14/23) of PCR-positive individuals who had less than 2 weeks but more than 1 week of cough had at least one other reported sign or symptom. Fourteen (100%) reported paroxysmal coughing, 7 (50%) "whoop," and 7 (50%) posttussive vomiting. Infants who met case definition were more likely to have reported apnea than were older individuals (15/17 vs 45/86, OR = 6.8, 95% CI = 1.4-64.2). CONCLUSIONS Decreasing cough duration from 2 weeks or more to more than 1 week would result in 95 percent of those with positive PCR results meeting confirmation criteria for pertussis. Apnea should be considered an additional sign for pertussis confirmation in infants.

Viral respiratory tract diseases pose serious public health problems. Our ability to predict and thus, be able to prepare for outbreaks is strained by the complex factors driving the prevalence and severity of these diseases. The abundance of diseases and transmission dynamics of strains are not only affected by external factors, such as weather, but also driven by interactions among viruses mediated by human behavior and immunity. To untangle the complex out-of-phase annual and biennial pattern of three common paramyxoviruses, Respiratory Syncytial Virus (RSV), Human Parainfluenza Virus (HPIV), and Human Metapneumovirus (hMPV), we adopt a theoretical approach that integrates ecological and immunological mechanisms of disease interactions. By estimating parameters from multiyear time series of laboratory-confirmed cases from the intermountain west region of the United States and using statistical inference, we show that models of immune-mediated interactions better explain the data than those based on ecological competition by convalescence. The strength of cross-protective immunity among viruses is correlated with their genetic distance in the phylogenetic tree of the paramyxovirus family.

Syndromic surveillance refers to methods relying on detection of individual and population health indicators that are discernible before confirmed diagnoses are made. In particular, prior to the laboratory confirmation of an infectious disease, ill persons may exhibit behavioral patterns, symptoms, signs, or laboratory findings that can be tracked through a variety of data sources. Syndromic surveillance systems are being developed locally, regionally, and nationally. The efforts have been largely directed at facilitating the early detection of a covert bioterrorist attack, but the technology may also be useful for general public health, clinical medicine, quality improvement, patient safety, and research. This report, authored by developers and methodologists involved in the design and deployment of the first wave of syndromic surveillance systems, is intended to serve as a guide for informaticians, public health managers, and practitioners who are currently planning deployment of such systems in their regions.

The 2002 Olympic Winter Games were held in Utah from February 8 to March 16, 2002. Following the terrorist attacks on September 11, 2001, and the anthrax release in October 2001, the need for bioterrorism surveillance during the Games was paramount. A team of informaticists and public health specialists from Utah and Pittsburgh implemented the Real-time Outbreak and Disease Surveillance (RODS) system in Utah for the Games in just seven weeks. The strategies and challenges of implementing such a system in such a short time are discussed. The motivation and cooperation inspired by the 2002 Olympic Winter Games were a powerful driver in overcoming the organizational issues. Over 114,000 acute care encounters were monitored between February 8 and March 31, 2002. No outbreaks of public health significance were detected. The system was implemented successfully and operational for the 2002 Olympic Winter Games and remains operational today.

Objectives This study evaluates the accuracy and transferability of Bayesian case detection systems (BCD) that use clinical notes from emergency department (ED) to detect influenza cases. Methods A BCD uses natural language processing (NLP) to infer the presence or absence of clinical findings from ED notes, which are fed into a Bayesain network classifier (BN) to infer patients’ diagnoses. We developed BCDs at the University of Pittsburgh Medical Center (BCDUPMC) and Intermountain Healthcare in Utah (BCDIH). At each site, we manually built a rule-based NLP and trained a Bayesain network classifier from over 40,000 ED encounters between Jan. 2008 and May. 2010 using feature selection, machine learning, and expert debiasing approach. Transferability of a BCD in this study may be impacted by seven factors: development (source) institution, development parser, application (target) institution, application parser, NLP transfer, BN transfer, and classification task. We employed an ANOVA analysis to study their impacts on BCD performance. Results Both BCDs discriminated well between influenza and non-influenza on local test cases (AUCs > 0.92). When tested for transferability using the other institution’s cases, BCDUPMC discriminations declined minimally (AUC decreased from 0.95 to 0.94, p

Purpose Bronchiolitis is the most common cause of illness leading to hospitalization in young children. At present, many bronchiolitis management decisions are made subjectively, leading to significant practice variation among hospitals and physicians caring for children with bronchiolitis. To standardize care for bronchiolitis, researchers have proposed various models to predict the disease course to help determine a proper management plan. This paper reviews the existing state of the art of predictive modeling for bronchiolitis. Predictive modeling for respiratory syncytial virus (RSV) infection is covered whenever appropriate, as RSV accounts for about 70% of bronchiolitis cases. Methods A systematic review was conducted through a PubMed search up to April 25, 2014. The literature on predictive modeling for bronchiolitis was retrieved using a comprehensive search query, which was developed through an iterative process. Search results were limited to human subjects, the English language, and children (birth to 18 years). Results The literature search returned 2312 references in total. After manual review, 168 of these references were determined to be relevant and are discussed in this paper. We identify several limitations and open problems in predictive modeling for bronchiolitis, and provide some preliminary thoughts on how to address them, with the hope to stimulate future research in this domain. Conclusions Many problems remain open in predictive modeling for bronchiolitis. Future studies will need to address them to achieve optimal predictive models.