Comparison of governance approaches for the control of antimicrobial resistance: Analysis of three European countries

Policy makers and governments are calling for coordination to address the crisis emerging from the ineffectiveness of current antibiotics and stagnated pipe-line of new ones – antimicrobial resistance (AMR). Wider contextual drivers and mechanisms are contributing to shifts in governance strategies in health care, but are national health system approaches aligned with strategies required to tackle antimicrobial resistance? This article provides an analysis of governance approaches within healthcare systems including: priority setting, performance monitoring and accountability for AMR prevention in three European countries: England, France and Germany. Advantages and unresolved issues from these different experiences are reported, concluding that mechanisms are needed to support partnerships between healthcare professionals and patients with democratized decision-making and accountability via collaboration. But along with this multi-stakeholder approach to governance, a balance between regulation and persuasion is needed

Improving public health preparedness : strengthening biosurveillance systems for enhanced situational awareness

This report is designed to aid state, territorial, tribal, and local public health leaders as they improve their capacity to achieve situational awareness during a public health emergency. We intend this report to serve as a concise reference work public health leaders can use to help design and manage biosurveillance systems to be used during an anticipated public health emergency. We hope public health staff will find it helpful in answering the question, \u201cWhat information do I need to support decision making during a public health emergency and how do I get this information?\u201d To address this question, we focused on information needs for situational awareness using three scenarios: a mass gathering, a natural disaster, or a large outbreak.During these events, information on population health status, health risks, and health services must be readily available to those managing the public health response to the event (Figure 1). This report lists \u201ccore\u201d information needed to effectively manage the public health aspects of an event such as an outbreak, a natural disaster, or a mass gathering. Furthermore, the report describes guiding principles and system capabilities that assure surveillance information systems meet relevant standards, while addressing the need for flexibility to adapt to unique and changing circumstances.We intend for the report\u2019s findings and recommendations to be used by CDC grantees to prioritize activities related to the use of Public Health Emergency Preparedness (PHEP) funding (as well as funding from other CDC cooperative agreements) in the development, maintenance, and optimization of biosurveillance systems. In particular, we intend that our findings and recommendations will delineate specific action steps which will complement and supplement existing guidance contained in the recently developed PHEP capabilities.This research was carried out by the North Carolina Preparedness and Emergency Response Research Center (NCPERRC) at the University of North Carolina at Chapel Hill\u2019s Gillings School of Global Public Health and was supported by the Centers for Disease Control and Prevention (CDC) Grant 1PO1 TP 000296.BiosurvReport_092013.pdfgrant 1PO1 TP00029

Doctor of Philosophy

dissertationPublic health surveillance systems are crucial for the timely detection and response to public health threats. Since the terrorist attacks of September 11, 2001, and the release of anthrax in the following month, there has been a heightened interest in public health surveillance. The years immediately following these attacks were met with increased awareness and funding from the federal government which has significantly strengthened the United States surveillance capabilities; however, despite these improvements, there are substantial challenges faced by today's public health surveillance systems. Problems with the current surveillance systems include: a) lack of leveraging unstructured public health data for surveillance purposes; and b) lack of information integration and the ability to leverage resources, applications or other surveillance efforts due to systems being built on a centralized model. This research addresses these problems by focusing on the development and evaluation of new informatics methods to improve the public health surveillance. To address the problems above, we first identified a current public surveillance workflow which is affected by the problems described and has the opportunity for enhancement through current informatics techniques. The 122 Mortality Surveillance for Pneumonia and Influenza was chosen as the primary use case for this dissertation work. The second step involved demonstrating the feasibility of using unstructured public health data, in this case death certificates. For this we created and evaluated a pipeline iv composed of a detection rule and natural language processor, for the coding of death certificates and the identification of pneumonia and influenza cases. The second problem was addressed by presenting the rationale of creating a federated model by leveraging grid technology concepts and tools for the sharing and epidemiological analyses of public health data. As a case study of this approach, a secured virtual organization was created where users are able to access two grid data services, using death certificates from the Utah Department of Health, and two analytical grid services, MetaMap and R. A scientific workflow was created using the published services to replicate the mortality surveillance workflow. To validate these approaches, and provide proofs-of-concepts, a series of real-world scenarios were conducted

The Infectious Disease Ontology in the Age of COVID-19

The Infectious Disease Ontology (IDO) is a suite of interoperable ontology modules that aims to provide coverage of all aspects of the infectious disease domain, including biomedical research, clinical care, and public health. IDO Core is designed to be a disease and pathogen neutral ontology, covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is then extended by a collection of ontology modules focusing on specific diseases and pathogens. In this paper we present applications of IDO Core within various areas of infectious disease research, together with an overview of all IDO extension ontologies and the methodology on the basis of which they are built. We also survey recent developments involving IDO, including the creation of IDO Virus; the Coronaviruses Infectious Disease Ontology (CIDO); and an extension of CIDO focused on COVID-19 (IDO-CovID-19).We also discuss how these ontologies might assist in information-driven efforts to deal with the ongoing COVID-19 pandemic, to accelerate data discovery in the early stages of future pandemics, and to promote reproducibility of infectious disease research

Evidence in Practice – A Pilot Study Leveraging Companion Animal and Equine Health Data from Primary Care Veterinary Clinics in New Zealand

Veterinary practitioners have extensive knowledge of animal health from their day-to-day observations of clinical patients. There have been several recent initiatives to capture these data from electronic medical records for use in national surveillance systems and clinical research. In response, an approach to surveillance has been evolving that leverages existing computerized veterinary practice management systems to capture animal health data recorded by veterinarians. Work in the United Kingdom within the VetCompass program utilizes routinely recorded clinical data with the addition of further standardized fields. The current study describes a prototype system that was developed based on this approach. In a 4-week pilot study in New Zealand, clinical data on presentation reasons and diagnoses from a total of 344 patient consults were extracted from two veterinary clinics into a dedicated database and analyzed at the population level. New Zealand companion animal and equine veterinary practitioners were engaged to test the feasibility of this national practice-based health information and data system. Strategies to ensure continued engagement and submission of quality data by participating veterinarians were identified, as were important considerations for transitioning the pilot program to a sustainable large-scale and multi-species surveillance system that has the capacity to securely manage big data. The results further emphasized the need for a high degree of usability and smart interface design to make such a system work effectively in practice. The geospatial integration of data from multiple clinical practices into a common operating picture can be used to establish the baseline incidence of disease in New Zealand companion animal and equine populations, detect unusual trends that may indicate an emerging disease threat or welfare issue, improve the management of endemic and exotic infectious diseases, and support research activities. This pilot project is an important step toward developing a national surveillance system for companion animals and equines that moves beyond emerging infectious disease detection to provide important animal health information that can be used by a wide range of stakeholder groups, including participating veterinary practices

Disease surveillance systems

Recent advances in information and communication technologies have made the development and operation of complex disease surveillance systems technically feasible, and many systems have been proposed to interpret diverse data sources for health-related signals. Implementing these systems for daily use and efficiently interpreting their output, however, remains a technical challenge. This thesis presents a method for understanding disease surveillance systems structurally, examines four existing systems, and discusses the implications of developing such systems. The discussion is followed by two papers. The first paper describes the design of a national outbreak detection system for daily disease surveillance. It is currently in use at the Swedish Institute for Communicable Disease Control. The source code has been licenced under GNU v3 and is freely available. The second paper discusses methodological issues in computational epidemiology, and presents the lessons learned from a software development project in which a spatially explicit micro-meso-macro model for the entire Swedish population was built based on registry data

Reliability and validity of EMS dispatch code-based categorization of emergency patients for syndromic surveillance.

A retrospective study involving the secondary analysis of public health surveillance records was undertaken to characterize the reliability and validity of an EMS dispatch data-based scheme for assigning emergency patients to surveillance syndromes in relation to two other schemes, one based on hospital ED clinicians\u27 manual categorization according to patients\u27 chief complaint and clinical presentation, and one based on ICD-9 coded hospital ED diagnoses. Comparisons of a sample of individual emergency patients\u27 syndrome assignments according to the EMS versus each of the two hospital categorization schemes were made by matching EMS run records to their corresponding emergency department patient encounter records. This new, linked dataset was analyzed to assess the level of agreement beyond chance between the three possible pairs of syndrome categorization schemes in assigning patients to a respiratory or non-respiratory syndrome and to a gastrointestinal or non-gastrointestinal syndrome. Cohen\u27s kappa statistics were used to measure chance-adjusted agreement between categorization schemes (raters). Z-tests and a chi-square-like test based on the variance of the kappa statistic were used to test the equivalence of kappa coefficients across syndromes, population subgroups and pairs of syndrome assignment schemes. The sensitivity, specificity, predictive value positive and predictive value negative of EMS dispatch and chief complaint-based categorization schemes were also calculated, using the ICD-9-coded ED diagnosis-based categorization scheme as the criterion standard. Comparisons of all performance characteristic (i.e. sensitivity, specificity, predictive value positive and predictive value negative) values were made across categorization schemes and surveillance syndromes to determine whether they were significantly different. The use of EMS dispatch codes for assigning emergency patients to surveillance syndromes was found to have limited but statistically significant reliability in relation to more commonly used syndrome grouping methods based on chief complaints or ICD-9 coded ED diagnoses. The reliability of EMS-based syndrome assignment varied significantly by syndrome, age group and comparison rater. When ICD-9 coded ED diagnosis-based grouping is taken as the criterion standard of syndrome definition, the validity of EMS-based syndrome assignment was limited but comparable to chief complaint-based assignment. The validity of EMS-based syndrome assignment varied significantly by syndrome

Evaluation of Syndromic Surveillance in the Netherlands: Its Added Value and Recommendations for Implementation

In the last decade, syndromic surveillance has increasingly been used worldwide for detecting increases or outbreaks of infectious diseases that might be missed by surveillance based on laboratory diagnoses and notifications by clinicians alone. There is, however, an ongoing debate about the feasibility of syndromic surveillance and its potential added value. Here we present our perspective on syndromic surveillance, based on the results of a retrospective analysis of syndromic data from six Dutch healthcare registries, covering 1999–2009 or part of this period. These registries had been designed for other purposes, but were evaluated for their potential use in signalling infectious disease dynamics and outbreaks. Our results show that syndromic surveillance clearly has added value in revealing the blind spots of traditional surveillance, in particular by detecting unusual, local outbreaks independently of diagnoses of specific pathogens, and by monitoring disease burden and virulence shifts of common pathogens. Therefore we recommend the use of syndromic surveillance for these applications

Syndromic surveillance: reports from a national conference, 2003

Overview of Syndromic Surveillance -- What is Syndromic Surveillance? -- Linking Better Surveillance to Better Outcomes -- Review of the 2003 National Syndromic Surveillance Conference - Lessons Learned and Questions To Be Answered -- -- System Descriptions -- New York City Syndromic Surveillance Systems -- Syndrome and Outbreak Detection Using Chief-Complaint Data - Experience of the Real-Time Outbreak and Disease Surveillance Project -- Removing a Barrier to Computer-Based Outbreak and Disease Surveillance - The RODS Open Source Project -- National Retail Data Monitor for Public Health Surveillance -- National Bioterrorism Syndromic Surveillance Demonstration Program -- Daily Emergency Department Surveillance System - Bergen County, New Jersey -- Hospital Admissions Syndromic Surveillance - Connecticut, September 2001-November 2003 -- BioSense - A National Initiative for Early Detection and Quantification of Public Health Emergencies -- Syndromic Surveillance at Hospital Emergency Departments - Southeastern Virginia -- -- Research Methods -- Bivariate Method for Spatio-Temporal Syndromic Surveillance -- Role of Data Aggregation in Biosurveillance Detection Strategies with Applications from ESSENCE -- Scan Statistics for Temporal Surveillance for Biologic Terrorism -- Approaches to Syndromic Surveillance When Data Consist of Small Regional Counts -- Algorithm for Statistical Detection of Peaks - Syndromic Surveillance System for the Athens 2004 Olympic Games -- Taming Variability in Free Text: Application to Health Surveillance -- Comparison of Two Major Emergency Department-Based Free-Text Chief-Complaint Coding Systems -- How Many Illnesses Does One Emergency Department Visit Represent? Using a Population-Based Telephone Survey To Estimate the Syndromic Multiplier -- Comparison of Office Visit and Nurse Advice Hotline Data for Syndromic Surveillance - Baltimore-Washington, D.C., Metropolitan Area, 2002 -- Progress in Understanding and Using Over-the-Counter Pharmaceuticals for Syndromic Surveillance -- -- Evaluation -- Evaluation Challenges for Syndromic Surveillance - Making Incremental Progress -- Measuring Outbreak-Detection Performance By Using Controlled Feature Set Simulations -- Evaluation of Syndromic Surveillance Systems - Design of an Epidemic Simulation Model -- Benchmark Data and Power Calculations for Evaluating Disease Outbreak Detection Methods -- Bio-ALIRT Biosurveillance Detection Algorithm Evaluation -- ESSENCE II and the Framework for Evaluating Syndromic Surveillance Systems -- Conducting Population Behavioral Health Surveillance by Using Automated Diagnostic and Pharmacy Data Systems -- Evaluation of an Electronic General-Practitioner-Based Syndromic Surveillance System -- National Symptom Surveillance Using Calls to a Telephone Health Advice Service - United Kingdom, December 2001-February 2003 -- Field Investigations of Emergency Department Syndromic Surveillance Signals - New York City -- Should We Be Worried? Investigation of Signals Generated by an Electronic Syndromic Surveillance System - Westchester County, New York -- -- Public Health Practice -- Public Health Information Network - Improving Early Detection by Using a Standards-Based Approach to Connecting Public Health and Clinical Medicine -- Information System Architectures for Syndromic Surveillance -- Perspective of an Emergency Physician Group as a Data Provider for Syndromic Surveillance -- SARS Surveillance Project - Internet-Enabled Multiregion Surveillance for Rapidly Emerging Disease -- Health Information Privacy and Syndromic Surveillance SystemsPapers from the second annual National Syndromic Surveillance Conference convened by the New York City Department of Health and Mental Hygiene, the New York Academy of Medicine, and the CDC in New York City during Oct. 23-24, 2003. Published as the September 24, 2004 supplement to vol. 53 of MMWR. Morbidity and mortality weekly report.1571461