Representative threats for research in public health surveillance

Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization

Syndromic Surveillance aims at analyzing medical data to detect clusters of illness or forecast disease outbreaks. Although the research in this field is flourishing in terms of publications, an insight of the global research output has been overlooked. This paper aims at analyzing the global scientific output of the research from 1993 to 2017. To this end, the paper uses bibliometric analysis and visualization to achieve its goal. Particularly, a data processing framework was proposed based on citation datasets collected from Scopus and Clarivate Analytics’ Web of Science Core Collection (WoSCC). The bibliometric method and Citespace were used to analyze the institutions, countries, and research areas as well as the current hotspots and trends. The preprocessed dataset includes 14,680 citation records. The analysis uncovered USA, England, Canada, France and Australia as the top five most productive countries publishing about Syndromic Surveillance. On the other hand, at the Pinnacle of academic institutions are the US Centers for Disease Control and Prevention (CDC). The reference co-citation analysis uncovered the common research venues and further analysis of the keyword cooccurrence revealed the most trending topics. The findings of this research will help in enriching the field with a comprehensive view of the status and future trends of the research on Syndromic Surveillance.

Nano/micromotors for security/defense applications. A review

The new capabilities of man-made micro/nanomotors open up considerable opportunities for diverse security and defense applications. This review highlights new micromotor-based strategies for enhanced security monitoring and detoxification of chemical and biological warfare agents (CBWA). The movement of receptor-functionalized nanomotors offers great potential for sensing and isolating target bio-threats from complex samples. New mobile reactive materials based on zeolite or activated carbon offer considerable promise for the accelerated removal of chemical warfare agents. A wide range of proof-of-concept motor-based approaches, including the detection and destruction of anthrax spores, 'on-off' nerve-agent detection or effective neutralization of chemical warfare agents have thus been demonstrated. The propulsion of micromotors and their corresponding bubble tails impart significant mixing that greatly accelerates such detoxification processes. These nanomotors will thus empower sensing and destruction where stirring large quantities of decontaminating reagents and controlled mechanical agitation are impossible or undesired. New technological breakthroughs and greater sophistication of micro/nanoscale machines will lead to rapid translation of the micromotor research activity into practical defense applications, addressing the escalating threat of CBWA.

Attomole sensitivity of staphylococcal enterotoxin B detection using an aptamer-modified surface-enhanced Raman scattering probe

In this report, we present a new homogeneous detection method for staphylococcal enterotoxin B (SEB) utilizing core-shell-structured iron-gold magnetic nanoparticles and a gold nanorod surface-enhanced Raman scattering (SERS) probe in solution. Peptide ligand (aptamer) functionalized magnetic gold nanorod particles were used as scavengers for target SEB. After the SEB molecules were separated from the matrix, the sandwich assay procedure was tested by gold nanorod particles that act as SERS probes. The binding constant between SEB and peptide-nanoparticle complex was determined as 8.0 × 10(7) M(-1). The correlation between the SEB concentration and SERS signal was found to be linear within the range of 2.5 fM to 3.2 nM. The limit of detection for the homogeneous assay was determined as 224 aM (ca. 2697 SEB molecules/20 μL sample volume). Also, gold-coated surfaces were used as capture substrates and performances of the two methods were compared. Furthermore, the developed method was evaluated for investigating the SEB specificity on bovine serum albumin (BSA) and avidin and detecting SEB in artificially contaminated milk, blood, and urine.

Laboratory-Guided Detection of Disease Outbreaks: Three Generations of Surveillance Systems

Context.—Traditional biothreat surveillance systems are vulnerable to incomplete and delayed reporting of public health threats.

Objective.—To review current and emerging approaches to detection and monitoring of biothreats enabled by laboratory methods of diagnosis and to identify trends in the biosurveillance research.

Data Sources.—PubMed (1995 to December 2007) was searched with the combined search terms “surveillance” and “infectious diseases.” Additional articles were identified by hand searching the bibliographies of selected papers. Additional search terms were “public health,” “disease monitoring,” “cluster,” “outbreak,” “laboratory notification,” “molecular,” “detection,” “evaluation,” “genomics,” “communicable diseases,” “geographic information systems,” “bioterrorism,” “genotyping,” and “informatics.” Publication language was restricted to English. The bibliographies of key references were later hand searched to identify articles missing in the database search. Three approaches to infectious disease surveillance that involve clinical laboratories are contrasted: (1) laboratory-initiated infectious disease notifications, (2) syndromic surveillance based on health indicators, and (3) genotyping based surveillance of biothreats. Advances in molecular diagnostics enable rapid genotyping of biothreats and investigations of genes that were not previously identifiable by traditional methods. There is a need for coordination between syndromic and laboratory-based surveillance. Insufficient and delayed decision support and inadequate integration of surveillance signals into action plans remain the 2 main barriers to efficient public health monitoring and response. Decision support for public health users of biosurveillance alerts is often lacking.

Conclusions.—The merger of the 3 scientific fields of surveillance, genomics, and informatics offers an opportunity for the development of effective and rapid biosurveillance methods and tools.

Detection of disease outbreaks by the use of oral manifestations

Oral manifestations of diseases caused by bioterrorist agents could be a potential data source for biosurveillance. This study had the objectives of determining the oral manifestations of diseases caused by bioterrorist agents, measuring the prevalence of these manifestations in emergency department reports, and constructing and evaluating a detection algorithm based on them. We developed a software application to detect oral manifestations in free text and identified positive reports over three years of data. The normal frequency in reports for oral manifestations related to anthrax (including buccal ulcers-sore throat) was 7.46%. The frequency for tularemia was 6.91%. For botulism and smallpox, the frequencies were 0.55% and 0.23%. We simulated outbreaks for these bioterrorism diseases and evaluated the performance of our system. The detection algorithm performed better for smallpox and botulism than for anthrax and tularemia. We found that oral manifestations can be a valuable tool for biosurveillance.

Trends in detection of warfare agents. Detection methods for ricin, staphylococcal enterotoxin B and T-2 toxin

An overview of the different detection methods available for ricin, staphylococcal enterotoxin B (SEB) and T-2 toxin is presented here. These toxins are potential biological warfare agents (BWA). The aim of this review is not to cover all the papers that had been published but rather to give an overall picture of the trend in the detection methodologies for potential biological warfare agents as we do see the emerging threats from these three toxins. The advantages and disadvantages of each methodology as well as the detection limit will be reviewed. It seems that mass spectrometry has created a niche for analysis of proteinaceous toxins, ricin and SEB as well as molecular toxin, T-2 toxin given its high sensitivity, high selectivity, high specificity and capability to identify and quantify unknown agents simultaneously in a short time frame. But its main drawbacks are its sophisticated instrumentation and its high cost. Improvised immunoassay may be an alternative.

Can syndromic surveillance data detect local outbreaks of communicable disease? A model using a historical cryptosporidiosis outbreak

A national UK surveillance system currently uses data from a health helpline (NHS Direct) in an attempt to provide early warning of a bio-terrorist attack, or an outbreak caused by a more common infection. To test this syndromic surveillance system we superimposed data from a historical outbreak of cryptosporidiosis onto a statistical model of NHS Direct call data. We modelled whether calls about diarrhoea (a proxy for cryptosporidiosis) exceeded a statistical threshold, thus alerting the surveillance team to the outbreak. On the date that the public health team were first notified of the outbreak our model predicted a 4% chance of detection when we assumed that one-twentieth of cryptosporidiosis cases telephoned the helpline. This rose to a 72% chance when we assumed nine-tenths of cases telephoned. The NHS Direct surveillance system is currently unlikely to detect an event similar to the cryptosporidiosis outbreak used here and may be most suited to detecting more widespread rises in syndromes in the community, as previously demonstrated. However, the expected rise in NHS Direct call rates, should improve early warning of outbreaks using call data.

Generating a reliable reference standard set for syndromic case classification

OBJECTIVE

To generate and measure the reliability for a reference standard set with representative cases from seven broad syndromic case definitions and several narrower syndromic definitions used for biosurveillance.

DESIGN

From 527,228 eligible patients between 1990 and 2003, we generated a set of patients potentially positive for seven syndromes by classifying all eligible patients according to their ICD-9 primary discharge diagnoses. We selected a representative subset of the cases for chart review by physicians, who read emergency department reports and assigned values to 14 variables related to the seven syndromes.

MEASUREMENTS

(1) Positive predictive value of the ICD-9 diagnoses; (2) prevalence of the syndromic definitions and related variables; (3) agreement between physician raters demonstrated by kappa, kappa corrected for bias and prevalence, and Finn's r; and (4) reliability of the reference standard classifications demonstrated by generalizability coefficients.

RESULTS

Positive predictive value for ICD-9 classification ranged from 0.33 for botulinic to 0.86 for gastrointestinal. We generated between 80 and 566 positive cases for six of the seven syndromic definitions. Rash syndrome exhibited low prevalence (34 cases). Agreement between physician raters was high, with kappa > 0.70 for most variables. Ratings showed no bias. Finn's r was >0.70 for all variables. Generalizability coefficients were >0.70 for all variables but three.

CONCLUSION

Of the 27 syndromes generated by the 14 variables, 21 showed high enough prevalence, agreement, and reliability to be used as reference standard definitions against which an automated syndromic classifier could be compared. Syndromic definitions that showed poor agreement or low prevalence include febrile botulinic syndrome, febrile and nonfebrile rash syndrome, respiratory syndrome explained by a nonrespiratory or noninfectious diagnosis, and febrile and nonfebrile gastrointestinal syndrome explained by a nongastrointestinal or noninfectious diagnosis.

Classification of emergency department chief complaints into 7 syndromes: a retrospective analysis of 527,228 patients

STUDY OBJECTIVE

Electronic surveillance systems often monitor triage chief complaints in hopes of detecting an outbreak earlier than can be accomplished with traditional reporting methods. We measured the accuracy of a Bayesian chief complaint classifier called CoCo that assigns patients 1 of 7 syndromic categories (respiratory, botulinic, gastrointestinal, neurologic, rash, constitutional, or hemorrhagic) based on free-text triage chief complaints.

METHODS

We compared CoCo's classifications with criterion syndromic classification based on International Classification of Diseases, Ninth Revision (ICD-9) discharge diagnoses. We assigned the criterion classification to a patient based on whether the patient's primary diagnosis was a member of a set of ICD-9 codes associated with CoCo's 7 syndromes. We tested CoCo's performance on a set of 527,228 chief complaints from patients registered at the University of Pittsburgh Medical Center emergency department (ED) between 1990 and 2003. We performed a sensitivity analysis by varying the ICD-9 codes in the criterion standard. We also tested CoCo on chief complaints from EDs in a second location (Utah).

RESULTS

Approximately 16% (85,569/527,228) of the patients were classified according to the criterion standard into 1 of the 7 syndromes. CoCo's classification performance (number of cases by criterion standard, sensitivity [95% confidence interval (CI)], and specificity [95% CI]) was respiratory (34,916, 63.1 [62.6 to 63.6], 94.3 [94.3 to 94.4]); botulinic (1,961, 30.1 [28.2 to 32.2], 99.3 [99.3 to 99.3]); gastrointestinal (20,431, 69.0 [68.4 to 69.6], 95.6 [95.6 to 95.7]); neurologic (7,393, 67.6 [66.6 to 68.7], 92.7 [92.6 to 92.8]); rash (2,232, 46.8 [44.8 to 48.9], 99.3 [99.3 to 99.3]); constitutional (10,603, 45.8 [44.9 to 46.8], 96.6 [96.6 to 96.7]); and hemorrhagic (8,033, 75.2 [74.3 to 76.2], 98.5 [98.4 to 98.5]). The sensitivity analysis showed that the results were not affected by the choice of ICD-9 codes in the criterion standard. Classification accuracy did not differ on chief complaints from the second location.

CONCLUSION

Our results suggest that, for most syndromes, our chief complaint classification system can identify about half of the patients with relevant syndromic presentations, with specificities higher than 90% and positive predictive values ranging from 12% to 44%.

How outbreaks of infectious disease are detected: a review of surveillance systems and outbreaks

To learn how outbreaks of infectious disease are detected and to describe the entities and information systems that together function to identify outbreaks in the U.S., the authors drew on multiple sources of information to create a description of existing surveillance systems and how they interact to detect outbreaks. The results of this analysis were summarized in a system diagram. The authors reviewed a sample of recent outbreaks to determine how they were detected, with reference to the system diagram. The de facto U.S. system for detection of outbreaks consists of five components: the clinical health care system, local/state health agencies, federal agencies, academic/professional organizations, and collaborating governmental organizations. Primary data collection occurs at the level of clinical health care systems and local health agencies. The review of a convenience sample of outbreaks showed that all five components of the system participated in aggregating, analyzing, and sharing data. The authors conclude that the current U.S. approach to detection of disease outbreaks is complex and involves many organizations interacting in a loosely coupled manner. State and local health departments and the health care system are major components in the detection of outbreaks.