3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Does knowing the influenza epidemic threshold has been reached influence the performance of influenza case definitions?

      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

          Disease surveillance using adequate case definitions is very important. The objective of the study was to compare the performance of influenza case definitions and influenza symptoms in the first two epidemic weeks with respect to other epidemic weeks.

          Methods

          We analysed cases of acute respiratory infection detected by the network of sentinel primary care physicians of Catalonia for 10 seasons. We calculated the diagnostic odds ratio (DOR) and 95% confidence intervals (CI) for the first two epidemic weeks and for other epidemic weeks.

          Results

          A total of 4,338 samples were collected in the epidemic weeks, of which 2,446 (56.4%) were positive for influenza. The most predictive case definition for laboratory-confirmed influenza was the WHO case definition for influenza-like illness (ILI) in the first two epidemic weeks (DOR 2.10; 95% CI 1.57–2.81) and in other epidemic weeks (DOR 2.31; 95% CI 1.96–2.72). The most predictive symptom was fever. After knowing that epidemic threshold had been reached, the DOR of the ILI WHO case definition in children aged <5 years and cough and fever in this group increased (190%, 170% and 213%, respectively).

          Conclusions

          During influenza epidemics, differences in the performance of the case definition and the discriminative ability of symptoms were found according to whether it was known that the epidemic threshold had been reached or not. This suggests that sentinel physicians are stricter in selecting samples to send to the laboratory from patients who present symptoms more specific to influenza after rather than before an influenza epidemic has been declared.

          Related collections

          Most cited references23

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

            Does this patient have influenza?

            Influenza vaccination lowers, but does not eliminate, the risk of influenza. Making a reliable, rapid clinical diagnosis is essential to appropriate patient management that may be especially important during shortages of antiviral agents caused by high demand. To systematically review the precision and accuracy of symptoms and signs of influenza. A secondary objective was to review the operating characteristics of rapid diagnostic tests for influenza (results available in <30 min). Structured search strategy using MEDLINE (January 1966-September 2004) and subsequent searches of bibliographies of retrieved articles to identify articles describing primary studies dealing with the diagnosis of influenza based on clinical signs and symptoms. The MEDLINE search used the Medical Subject Headings EXP influenza or EXP influenza A virus or EXP influenza A virus human or EXP influenza B virus and the Medical Subject Headings or terms EXP sensitivity and specificity or EXP medical history taking or EXP physical examination or EXP reproducibility of results or EXP observer variation or symptoms.mp or clinical signs.mp or sensitivity.mp or specificity.mp. Of 915 identified articles on clinical assessment of influenza-related illness, 17 contained data on the operating characteristics of symptoms and signs using an independent criterion standard. Of these, 11 were eliminated based on 4 inclusion criteria and availability of nonduplicative primary data. Two authors independently reviewed and abstracted data for estimating the likelihood ratios (LRs) of clinical diagnostic findings. Differences were resolved by discussion and consensus. No symptom or sign had a summary LR greater than 2 in studies that enrolled patients without regard to age. For decreasing the likelihood of influenza, the absence of fever (LR, 0.40; 95% confidence interval [CI], 0.25-0.66), cough (LR, 0.42; 95% CI, 0.31-0.57), or nasal congestion (LR, 0.49; 95% CI, 0.42-0.59) were the only findings that had summary LRs less than 0.5. In studies limited to patients aged 60 years or older, the combination of fever, cough, and acute onset (LR, 5.4; 95% CI, 3.8-7.7), fever and cough (LR, 5.0; 95% CI, 3.5-6.9), fever alone (LR, 3.8; 95% CI, 2.8-5.0), malaise (LR, 2.6; 95% CI, 2.2-3.1), and chills (LR, 2.6; 95% CI, 2.0-3.2) increased the likelihood of influenza to the greatest degree. The presence of sneezing among older patients made influenza less likely (LR, 0.47; 95% CI, 0.24-0.92). Clinical findings identify patients with influenza-like illness but are not particularly useful for confirming or excluding the diagnosis of influenza. Clinicians should use timely epidemiologic data to ascertain if influenza is circulating in their communities, then either treat patients with influenza-like illness empirically or obtain a rapid influenza test to assist with management decisions.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Performance of influenza case definitions for influenza community surveillance: based on the French influenza surveillance network GROG, 2009-2014

              International case definitions recommended by the Centers for Disease Control and Prevention (CDC), the European Centre for Disease Prevention and Control (ECDC), and the World Health Organization (WHO) are commonly used for influenza surveillance. We evaluated clinical factors associated with the laboratory-confirmed diagnosis of influenza and the performance of these influenza case definitions by using a complete dataset of 14,994 patients with acute respiratory infection (ARI) from whom a specimen was collected between August 2009 and April 2014 by the Groupes Régionaux d’Observation de la Grippe (GROG), a French national influenza surveillance network. Cough and fever ≥ 39 °C most accurately predicted an influenza infection in all age groups. Several other symptoms were associated with an increased risk of influenza (headache, weakness, myalgia, coryza) or decreased risk (adenopathy, pharyngitis, shortness of breath, otitis/otalgia, bronchitis/ bronchiolitis), but not throughout all age groups. The WHO case definition for influenza-like illness (ILI) had the highest specificity with 21.4%, while the ECDC ILI case definition had the highest sensitivity with 96.1%. The diagnosis among children younger than 5 years remains challenging. The study compared the performance of clinical influenza definitions based on outpatient surveillance and will contribute to improving the comparability of data shared at international level.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: ValidationRole: Writing – original draft
                Role: ConceptualizationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: ValidationRole: Writing – original draft
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                1 July 2022
                2022
                : 17
                : 7
                : e0270740
                Affiliations
                [1 ] CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
                [2 ] Departament de Medicina, Universitat de Barcelona, Barcelona, Spain
                [3 ] Agència de Salut Pública de Catalunya, Generalitat de Catalunya, Barcelona, Spain
                [4 ] Agència de Salut Pública de Barcelona, Barcelona, Spain
                ISI Foundation: Fondazione ISI - Istituto per l’lnterscambio Scientifico, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                ¶ Membership of the PIDIRAC Sentinel Surveillance Program of Catalonia is listed in the Acknowledgments.

                Author information
                https://orcid.org/0000-0002-1353-5325
                https://orcid.org/0000-0003-0143-5295
                https://orcid.org/0000-0003-0219-1907
                Article
                PONE-D-21-23664
                10.1371/journal.pone.0270740
                9249166
                35776716
                202b908a-8648-4e95-b098-d152b717a5f6
                © 2022 Soldevila 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
                : 21 July 2021
                : 16 June 2022
                Page count
                Figures: 3, Tables: 2, Pages: 12
                Funding
                Funded by: program of prevention, surveillance, and control of transmissible diseases (previcet); ciber de epidemiología y salud pública (ciberesp); instituto de salud carlos iii
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003030, agència de gestió d’ajuts universitaris i de recerca;
                Award ID: 2017/SGR 1342
                Award Recipient :
                This study was supported by the Program of Prevention, Surveillance, and Control of Transmissible Diseases (PREVICET); CIBER de Epidemiología y Salud Pública (CIBERESP); Instituto de Salud Carlos III, Madrid; and the Catalan Agency for the Management of Grants for University Research (AGAUR Grant Number 2017/SGR 1342). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Influenza
                Medicine and Health Sciences
                Clinical Medicine
                Signs and Symptoms
                Fevers
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Coughing
                Medicine and Health Sciences
                Clinical Medicine
                Signs and Symptoms
                Coughing
                Medicine and Health Sciences
                Health Care
                Health Care Providers
                Physicians
                People and Places
                Population Groupings
                Professions
                Medical Personnel
                Physicians
                Medicine and Health Sciences
                Epidemiology
                Disease Surveillance
                Infectious Disease Surveillance
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Infectious Disease Control
                Infectious Disease Surveillance
                Biology and life sciences
                Organisms
                Viruses
                RNA viruses
                Orthomyxoviruses
                Influenza Viruses
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Viral Pathogens
                Orthomyxoviruses
                Influenza Viruses
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Viral Pathogens
                Orthomyxoviruses
                Influenza Viruses
                Biology and Life Sciences
                Organisms
                Viruses
                Viral Pathogens
                Orthomyxoviruses
                Influenza Viruses
                People and Places
                Population Groupings
                Age Groups
                Medicine and Health Sciences
                Clinical Medicine
                Signs and Symptoms
                Headaches
                Custom metadata
                Data set is available in the Supporting Information files.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article