MS

thesisThe early detection of infectious disease outbreaks is key to their management and initiation of mitigation strategies. This is true whether the disease is naturally occurring or due to intentional release as an act of terrorism. In recent times, this has become evident with the anthrax bioterrorism attacks of October 2001, the occurrence of emerging infections such as West Nile Virus and Severe Acute Respiratory Syndrome of the concern for a new pandemic of influenza based on H5N1 avian influenza. Public health surveillance efforts at the University of Utah have been place for several years and came to the forefront during the 2002 Winter Olympic Games. At that time, an electronic medical record-based system was developed and deployed to perform daily surveillance of patients visiting the clinics and emergency department of the University of Utah Health Care System. This effort was then followed by a detailed validation of the computer rules used in the surveillance system, with special emphasis on the early detection of central nervous system (CNS) syndromes such as meningitis and encephalitis. These syndromes are of importance to both emerging infections such as West Nile Virus and for NIH/CDC Category B threat agents such as Eastern and Western Equine Encephalitis. True CNS syndromes caused by infectious agents represent a small proportion of patients seen at the emergency department of a large tertiary hospital. "Reason for visit" chief complaint data were poor predictors for the early detection of CNS syndromes. Orders and early results from the laboratory testing of cerebro-spinal fluid were useful for the early detection of meningitis and encephalitis. Overall, computer-based surveillance methods have a role to play in the early detection of infectious diseases. In particular, this project has contributed to public health surveillance by moving the field beyond complaint data and has shown the validity of suing computer-based rules for the detection of meningitis and encephalitis

Syndromic Surveillance for Bioterrorism-related Inhalation Anthrax in an Emergency Department Population

Objective: To utilize clinical data from emergency department admissions and published clinical case reports from the 2001 bioterrorism-related inhalation anthrax (IA) outbreak to develop a detection algorithm for syndromic surveillance. Methods: A comprehensive review of case reports and medical charts was undertaken to identify clinical characteristics of IA. Eleven historical cases were compared to 160 patients meeting a syndromic case definition based on acute respiratory failure and the presence of mediastinal widening or lymphadenopathy on a chest radiograph. Results: The majority of syndromic group patients admitted were due to motor vehicle accident (52%), followed by fall (10%), or other causes (4%). Positive culture for a gram positive rod was the most predictive feature for anthrax cases. Among signs and symptoms, myalgias, fatigue, sweats, nausea, headache, cough, confusion, fever, and chest pain were found to best discriminate between IA and syndromic patients. When radiological findings were examined, consolidation and pleural effusions were both significantly higher among IA patients. A four step algorithm was devised based on combinations of the most accurate clinical features and the availability of data during the course of typical patient care. The sensitivity (91%) and specificity (96%) of the algorithm were found to be high. Conclusions: Surveillance based on late stage findings of IA can be used by clinicians to identify high risk patients in the Emergency Department using a simple decision tree. Implications for public health: Monitoring pre-diagnostic indicators of IA can provide enough credible evidence to initiate an epidemiological investigation leading to earlier outbreak detection and more effective public health response

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

International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance: Building the Future of Public Health Surveillance

Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-04204pubpub1117

Ready or Not? Protecting the Public's Health From Diseases, Disasters, and Bioterrorism, 2008

Examines ten indicators to assess progress in state readiness to respond to bioterrorism and other public health emergencies. Evaluates the federal government's and hospitals' preparedness. Makes suggestions for funding, restructuring, and other reforms

Can routinely collected electronic health data be used to develop novel healthcare associated infection surveillance tools?

Background: Healthcare associated infections (HCAI) pose a significant burden to health systems both within the UK and internationally. Surveillance is an essential component to any infection control programme, however traditional surveillance systems are time consuming and costly. Large amounts of electronic routine data are collected within the English NHS, yet these are not currently exploited for HCAI surveillance. Aim: To investigate whether routinely collected electronic hospital data can be exploited for HCAI surveillance within the NHS. Methods: This thesis made use of local linked electronic health data from Imperial College Healthcare NHS Trust, including information on patient admissions, discharges, diagnoses, procedures, laboratory tests, diagnostic imaging requests and traditional infection surveillance data. To establish the evidence base on surveillance and risks of HCAI, two literature reviews were carried out. Based on these, three types of innovative surveillance tools were generated and assessed for their utility and applicability. Results: The key findings were firstly the emerging importance of automated and syndromic surveillance in infection surveillance, but the lack of investigation and application of these tools within the NHS. Syndromic surveillance of surgical site infections was successful in coronary artery bypass graft patients; however it was an inappropriate methodology for caesarean section patients. Automated case detection of healthcare associated urinary tract infections, based on electronic microbiology data, demonstrated similar rates of infection to those recorded during a point prevalence survey. Routine administrative data demonstrated mixed utility in the creation of simplified risk scores or infection, with poorly performing risk models of surgical site infections but reasonable model fit for HCA UTI. Conclusion: Whilst in principle routine administrative data can be used to generate novel surveillance tools for healthcare associated infections; in reality it is not yet practical within the IT infrastructure of the NHS

Ready or Not? Protecting the Public\u27s Health from Diseases, Disasters, and Bioterrorism

While significant progress has been made to better protect the country from health emergencies, funding for essential programs has been cut, putting these improvements in jeopardy. Additionally, a number of critical areas of preparedness still have significant gaps, including surge capacity and biosurveillance systems, and these problems are less likely to be addressed as funding decreases