Laboratory Data

The Influenza Division (ID) in the Centers for Disease Control and Prevention (CDC) maintains the WHO/NREVSS surveillance system, a network of laboratories in the U.S. that report influenza testing results. This system has seen many changes during the past 40 years, especially since the 2009 H1N1 pandemic. This was due in large part to increased adoption of HL7 messaging via PHLIP. PHLIP data is detailed, standardized influenza testing information, reported in near real-time. The data received through this and other report methods is published online in national and regional aggregate form in FluView, a weekly surveillance report prepared by CDC.

Objective

Describe the changes to the World Health Organization/National Respiratory and Enteric Virus Surveillance System (WHO/NREVSS) influenza surveillance system over time, with a focus on the Public Health Laboratory Interoperability Project (PHLIP) and how it has influenced the system

Numerous studies have demonstrated a causal relationship between human papillomavirus (HPV) and cervical cancer1. By 2007 two vaccines targeting HPV were available in the United States. Both vaccines have shown close to 100% efficacy against HPV types 16 and 18, the cause of 70% of all cervical cancers2. It is hypothesized that with routine vaccination the prevalence of HPV and HPV-associated cancers should decline3. A need exists for surveillance with national coverage2. The purpose of this study is to present a method to estimate rate of change of high-risk HPV in the United States since 2004 in women using national reference laboratory data.

Objective

To establish and evaluate an HPV surveillance protocol and determine the rate of change of high-risk HPV in the United States since 2004 using archived reference laboratory data.

Of the 13 million people in Malawi1 85% are rural and the country has high burden of under-five morbidity and mortality due to preventable infectious diseases. Respiratory, febrile and diarrhea diseases are the top 3 morbidity and mortality illnesses in most developing countries2. Acute medical care has greatly improved these conditions, but widespread and uncontrolled use of antibiotics threatens to reverse gains achieved so far. Drug sensitivity tests are a prerequisite to guide prescription practices.

Objective

Assessment of routine use of drug sensitivity test results to guide treatment choices in district hospitals in Malawi.

Calls to NHS Direct (a national UK telephone health advice line) which may be indicative of infection show marked seasonal variation, often peaking during winter or early spring. This variation may be related to the seasonality of common viruses. There is currently no routine microbiological confirmation of the cause of illness in NHS Direct callers. Modelling trends in NHS Direct syndromic call data against laboratory data may help by attributing the likely cause of these calls the and surveillance ‘signals’ generated by syndromic surveillance.

Multiple linear regression has been used previously to estimate the contribution of rotavirus and RSV to hospital admission for infectious intestinal disease and lower respiratory tract infections respectively. We applied a similar regression model to NHS Direct syndromic surveillance data and laboratory reports.

Objective

To provide weekly estimates of the proportions of NHS Direct respiratory calls attributable to common infectious disease pathogens.

A number of syndromic surveillance systems include tools that quickly identify potentially large disease outbreak events. However, the high falsepositive rate continues to be a problem in all of these systems. Our earlier work has showed that multi-source information fusion can improve specificity of the syndromic surveillance systems. However, an anomalous health event that presents as only a few cases may remain undetected because the chief complaint data does not contain enough details. New linked data sources need to be used to enhance detection capabilities. The focus of this project examining the incorporation of laboratory, prescription medications and radiology data linked to the patient encounter within syndromic surveillance systems. These data source linkings may enhance the sensitivity of syndromic surveillance.

An outbreak of dengue fever has occured in French Guiana since the end of November 2005 until July 2006. The dengue serotype circulating was DEN-2, responsible of more than 2 000 confirmed cases and 4 deaths. The previous surveillance system was only based on the laboratories data, and didn’t permit to assess the real situation of dengue infection within the population of French Guiana. Actually, the dengue fever being a viral infection for which no etiological treatments nor immunization were available, a lot of general practioners didn’t send their patients to laboratories but prescribed only a symptomatic treatment. A survey made on the field during February 2006 in a town of 5000 inhabitants in the West of French Guiana showed that the real situation within the population was really more important than the one evaluated by the current surveillance system (135 suspected cases for only 13 confirmed cases reported by the network of laboratories). For that reason, it was decided to put in place a syndromic surveillance system, which can permit to have a better knowledge of the situation for dengue fever. The objectives of this new system were i) to detect earlier the beginning of an outbreak ii) to have a better estimation of the impact of the outbreak within the population and iii) to permit the evaluation of the Public Health strategy set up.

Objective

This paper describes a new syndromic surveillance system installed in French Guiana in April 2006 during an outbreak of dengue fever.

Previous reports from participating facilities in North Dakota illustrated that ILI syndrome data from syndromic surveillance data, which is based on chief complaints logs, had a close correlation to the traditional ILI surveillance and that frequency slope of the ILI syndrome was also closely correlated to that of the cases that tested positive for influenza. The facility used in this report submits ICD-9 codes to the North Dakota Department of Health (NDDoH). By comparing the NDDoH ILI syndrome to influenza laboratory testing data and ICD-9 code specific to influenza (487) we found that syndromic surveillance data for ILI closely followed the influenza testing trend as well as the ICD-9 code trend.

Objective

The objective of this report is to evaluate the correlation between influenza-like illness (ILI) syndrome classification using chief complaint data and discharge diagnosis International Classification of Disease, Ninth Revision (ICD-9) code for influenza with the laboratory data from one hospital in North Dakota over a period of three influenza seasons.

Clinical and public health microbiology laboratories of the world are a rich, underutilized resource in monitoring the changing epidemiology of microbial populations worldwide. Two areas of public health importance in which effective use of relevant local data are critical include: 1. guiding local treatment guidelines, informed by knowledge of local patterns of infection and antimicrobial resistance; and 2. the early identification and characterization of outbreaks.

Most laboratories in the developed world and many in the developing world have clinical databases designed to meet the day-to-day needs of clinical reporting, specimen processing, billing, and permanent information storage. Unfortunately, most such systems were not developed with the epidemiological needs of microbiologists, infection control staff, public health authorities, and policy-makers in mind. To address this critical gap, our group at the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance has developed the WHONET and BacLink softwares to support local, national, and international infectious disease surveillance programs.

Objective

This paper describes two free softwares developed for the automated and semi-automated capture, processing, and analysis of microbiology laboratory data. Applications include early detection of hospital and community outbreaks, guiding local treatment guidelines and public health policy, and immediate alert of important pathogens and potential errors in laboratory testing.

NC DETECT is the Web-based early event detection and timely public health surveillance system in the North Carolina Public Health Information Network. The reporting system also provides broader public health surveillance reports for emergency department visits related to hurricanes, injuries, asthma,  vaccine-preventable diseases, environmental health and others. NC DETECT receives data on at least a daily basis from four data sources: emergency departments, the statewide poison center, the statewide EMS data collection system, a regional wildlife center and laboratory data from the NC State College of Veterinary Medicine. Data from select urgent care centers are in pilot testing.

Objective

Managers of the NC DETECT surveillance system wanted to augment standard tabular Web-based access with a Web-based spatial-temporal interface to allow users to see spatial and temporal characteristics of the surveillance data. Users need to see spatial and temporal patterns in the data to help make decisions about events that require further investigation. The innovative solution using Adobe Flash and Web services to integrate the mapping component with the backend database will be described in this paper.

BioSense data includes Department of Defense and Veterans Affairs ambulatory care diagnoses and procedures, as well as Laboratory Corporation of America lab test orders. Data are mapped to eleven syndrome categories. SaTScan is a spatio-temporal technique that has previously been applied to surveillance at the metropolitan area level. Visualization of national results involves unique issues, including displaying cluster information that crosses jurisdictions, zip codes with highly variant data volume, and evaluating large multiple state clusters. SaTScan was first implemented in June 2005 in the BioSense application for daily monitoring at CDC’s BioIntelligence Center.

Objective

The objective is to describe the visualization and monitoring of the national spatio-temporal SaTScan results in the BioSense application. This is the first application of this algorithm to a national early event detection and situational awareness system.