A Comparison of Self-report and Health Care Provider Data to Assess Surveillance Definitions of Influenza-like Illness in Outpatients

Abstract

s part of most influenza surveillance systems, patients who meet specific symptom criteria will have culture samples taken for laboratory testing. 1,2 Several surveillance definitions of influenza-like illness (ILI) have been proposed. 2-6 The Centers for Disease Control and Prevention (CDC) in the United States defines ILI as the presence of fever (temperature of 38 degrees Celsius or greater) and one of either cough or sore throat or both, in the absence of a known cause other than influenza. 7 Health Canada's Flu Watch uses a variant of the CDC definition of ILI: fever and cough plus one or more of the following-sore throat, arthralgia, myalgia, or prostration (www.phac-aspc.gc.ca/fluwatch). Several studies have found that the grouping of high fever and cough is the best predictor of influenza. 8-11 What these ILI definitions have in common is the presence of fever plus one or more symptoms of respiratory illness. Data about influenza symptoms can be obtained from multiple sources. For example, symptoms can be reported by multiple informants, such as self-reports and health care providers; or by multiple methods, such as symptom checklists and medical record data. In prior work, we found that agreements between health record data and self-report varied for respiratory-related symptoms. 12 Therefore, factors that might influence the sensitivity, specificity and predictive values of ILI include the actual surveillance definition, but also the data source from which the symptom data contained in the ILI definition are taken. The impact of these factors will be relevant to both public health researchers and clinicians in determining choice of ILI definitions. Most studies evaluating the surveillance definitions of influenza have relied on physician or health record data. 3,8,13,14 Some also included a patient survey following entry into the study and physician examination or review of medical records. 15,16 Nicholson and colleagues (1997) had weekly phone surveillance for symptoms and then home visits for symptomatic patients. 17 Vaccine effectiveness studies have also used clinical data, as well as self-report from research participants. 18-20 The goal of the current study was to assess the utility of two sources of data in determining the surveillance definitions for ILI and their association with laboratory-confirmed influenza. Using data from the Hutterite Influenza Prevention Study, 18 we compared data collected retrospectively from medical record extraction, similar data collected prospectively from research participants, and the combined data from both sources.

The French Connection: The First Large Population-Based Contact Survey in France Relevant for the Spread of Infectious Diseases

“…Nonetheless, to the best of our knowledge, no previous study has ever presented contact matrices according to gender. So far, gender differences in infectious diseases epidemiology have been attributed only to hormonal differences[ 28 ] or to differences in risk assessment[ 29 ] leading to incomplete reporting[ 30 ]. We suggest that the higher participation of women in infectious diseases such as influenza[ 31 ] or pertussis[ 32 ] could also be attributed to behaviour.…”

Is influenza-like illness a useful concept and an appropriate test of influenza vaccine effectiveness?

“…Schnepf's study of French ILI patients found that patients with no virus detected were less likely to have a cough (77.8%) than those with H1N1v (89.5%, p = 0.01) and more likely to have pharyngitis (21%) compared to those with H1N1v (10%, p = 0.003), but Schnepf was not able to predict PCR-positivity [19]. The Hutterite colony study found that combinations of fever, cough, sore throat and muscle aches predicted PCR influenza positivity, but the confidence intervals were wide [27]. The Indian Council of Medical Research influenza surveillance network study found that only three symptoms correlated with influenza PCR-positivity: cough (p < 0.0034), fatigue (p < 0.001) and chills/rigours (p < 0.001).…”

Importance of History Taking and Physical Examination Before Rapid Laboratory Test for Seasonal Influenza Virus: A Single-Center Multiple Logistic Analysis

“…The current study found that combining interviews and physical examination was important for predicting influenza test results [12]. While similar studies have been available to date, they have focused solely on symptoms, with only a few studies having analyzed a combination of interviews and physical examination [12,13].…”