82
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Thermal Image Scanning for Influenza Border Screening: Results of an Airport Screening Study

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Infrared thermal image scanners (ITIS) appear an attractive option for the mass screening of travellers for influenza, but there are no published data on their performance in airports.

          Methods

          ITIS was used to measure cutaneous temperature in 1275 airline travellers who had agreed to tympanic temperature measurement and respiratory sampling. The prediction by ITIS of tympanic temperature (37.8°C and 37.5°C) and of influenza infection was assessed using Receiver Operating Characteristic (ROC) curves and estimated sensitivity, specificity and positive predictive value (PPV).

          Findings

          Using front of face ITIS for prediction of tympanic temperature ≥37.8°C, the area under the ROC curve was 0.86 (95%CI 0.75–0.97) and setting sensitivity at 86% gave specificity of 71%. The PPV in this population of travellers, of whom 0.5% were febrile using this definition, was 1.5%. We identified influenza virus infection in 30 travellers (3 Type A and 27 Type B). For ITIS prediction of influenza infection the area under the ROC curve was 0.66 (0.56–0.75), a sensitivity of 87% gave specificity of 39%, and PPV of 2.8%. None of the 30 influenza-positive travellers had tympanic temperature ≥37.8°C at screening (95%CI 0% to 12%); three had no influenza symptoms.

          Conclusion

          ITIS performed moderately well in detecting fever but in this study, during a seasonal epidemic of predominantly influenza type B, the proportion of influenza-infected travellers who were febrile was low and ITIS were not much better than chance at identifying travellers likely to be influenza-infected. Although febrile illness is more common in influenza A infections than influenza B infections, many influenza A infections are afebrile. Our findings therefore suggest that ITIS is unlikely to be effective for entry screening of travellers to detect influenza infection with the intention of preventing entry of the virus into a country.

          Related collections

          Most cited references17

          • Record: found
          • Abstract: found
          • Article: not found

          Clinical signs and symptoms predicting influenza infection.

          New antiviral drugs are available for the treatment of influenza type A and type B infections. In clinical practice, antiviral use has rarely been guided by antecedent laboratory diagnosis. Defined clinical predictors of an influenza infection can help guide timely therapy and avoid unnecessary antibiotic use. To examine which clinical signs and symptoms are most predictive of influenza infection in patients with influenza-like illness using a large data set derived from clinical trials of zanamivir. This analysis is a retrospective, pooled analysis of baseline signs and symptoms from phase 2 and 3 clinical trial participants. It was conducted in mainly unvaccinated (mean age, 35 years) adults and adolescents who had influenza-like illness, defined as having fever or feverishness plus at least 2 of the following influenza-like symptoms: headache, myalgia, cough, or sore throat who underwent laboratory testing for influenza. Clinical signs and symptoms were evaluated in statistical models to identify those best predicting laboratory confirmation of influenza. Of 3744 subjects enrolled with baseline influenza-like symptoms, and included in this analysis, 2470 (66%) were confirmed to have influenza. Individuals with influenza were more likely to have cough (93% vs 80%), fever (68% vs 40%), cough and fever together (64% vs 33%), and/or nasal congestion (91% vs 81%) than those without influenza. The best multivariate predictors of influenza infections were cough and fever with a positive predictive value of 79% (P<. 001). The positive predictive value rose with the increase in the temperature at the time of recruitment. When influenza is circulating within the community, patients with an influenza-like illness who have both cough and fever within 48 hours of symptom onset are likely to have influenza and the administration of influenza antiviral therapy may be appropriate to consider. Arch Intern Med. 2000;160:3243-3247.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Clinical features of the initial cases of 2009 pandemic influenza A (H1N1) virus infection in China.

            The first case of 2009 pandemic influenza A (H1N1) virus infection in China was documented on May 10. Subsequently, persons with suspected cases of infection and contacts of those with suspected infection were tested. Persons in whom infection was confirmed were hospitalized and quarantined, and some of them were closely observed for the purpose of investigating the nature and duration of the disease. During May and June 2009, we observed 426 persons infected with the 2009 pandemic influenza A (H1N1) virus who were quarantined in 61 hospitals in 20 provinces. Real-time reverse-transcriptase-polymerase-chain-reaction (RT-PCR) testing was used to confirm infection, the clinical features of the disease were closely monitored, and 254 patients were treated with oseltamivir within 48 hours after the onset of disease. The mean age of the 426 patients was 23.4 years, and 53.8% were male. The diagnosis was made at ports of entry (in 32.9% of the patients), during quarantine (20.2%), and in the hospital (46.9%). The median incubation period of the virus was 2 days (range, 1 to 7). The most common symptoms were fever (in 67.4% of the patients) and cough (69.5%). The incidence of diarrhea was 2.8%, and the incidence of nausea and vomiting was 1.9%. Lymphopenia, which was common in both adults (68.1%) and children (92.3%), typically occurred on day 2 (range, 1 to 3) and resolved by day 7 (range, 6 to 9). Hypokalemia was observed in 25.4% of the patients. Duration of fever was typically 3 days (range, 1 to 11). The median length of time during which patients had positive real-time RT-PCR test results was 6 days (range, 1 to 17). Independent risk factors for prolonged real-time RT-PCR positivity included an age of less than 14 years, male sex, and a delay from the onset of symptoms to treatment with oseltamivir of more than 48 hours. Surveillance of the 2009 H1N1 virus in China shows that the majority of those infected have a mild illness. The typical period during which the virus can be detected with the use of real-time RT-PCR is 6 days (whether or not fever is present). The duration of infection may be shortened if oseltamivir is administered. 2009 Massachusetts Medical Society
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Predicting influenza infections during epidemics with use of a clinical case definition.

              Combined pharyngeal and nasal swab specimens were collected from 100 subjects who presented with a flu-like illness (fever >37.8 degrees C plus 2 of 4 symptoms: cough, myalgia, sore throat, and headache) of or =38.2 degrees C as well as 3 or 4 of the symptoms in the clinical case definition. Stepwise logistic regression showed that cough (odds ratio [OR], 6.7; 95% confidence interval [CI], 1.4-34.1; P=.02) and fever (OR, 3.1; 95% CI, 1.4-8.0; P=.01) were the only factors significantly associated with a positive PCR test for influenza. The positive predictive value, negative predictive value, sensitivity, and the specificity of a case definition including fever (temperature of >38 degrees C) and cough for the diagnosis of influenza infection during this flu season were 86.8%, 39.3%, 77.6%, and 55.0%, respectively.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                5 January 2011
                : 6
                : 1
                : e14490
                Affiliations
                [1 ]Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand
                [2 ]Planning and Funding, Canterbury District Health Board, Christchurch, New Zealand
                [3 ]Virology Section, Canterbury Health Laboratories, Christchurch, New Zealand
                [4 ]Department of Public Health, University of Otago Wellington, Wellington, New Zealand
                The University of Hong Kong, Hong Kong
                Author notes

                Conceived and designed the experiments: PCP ARD LCJ MB. Performed the experiments: ARD LCJ. Analyzed the data: PCP. Wrote the paper: PCP ARD LCJ MB.

                Article
                10-PONE-RA-20762R2
                10.1371/journal.pone.0014490
                3016318
                21245928
                186556a6-5f53-40d1-b259-e1394b415e11
                Priest et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 7 July 2010
                : 1 December 2010
                Page count
                Pages: 7
                Categories
                Research Article
                Infectious Diseases/Epidemiology and Control of Infectious Diseases
                Public Health and Epidemiology/Health Policy
                Public Health and Epidemiology/Infectious Diseases
                Public Health and Epidemiology/Screening

                Uncategorized
                Uncategorized

                Comments

                Comment on this article