Dataset Information

Awareness of Appropriate Antibiotic Use in Primary Care for Influenza-Like Illness: Evidence of Improvement from UK Population-Based Surveys.

ABSTRACT: Influenza-like illnesses (ILI) account for a significant portion of inappropriate antibiotic use. Patient expectations for antibiotics for ILI are likely to play a substantial role in 'unnecessary' antibiotic consumption. This study aimed to investigate trends in awareness of appropriate antibiotic use and antimicrobial resistance (AMR). Three sequential online surveys of independent representative samples of adults in the United Kingdom investigated expectations for, and consumption of, antibiotics for ILI (May/June 2015 (n = 2064); Oct/Nov 2016 (n = 4000); Mar 2017 (n = 4000)). Respondents were asked whether they thought antibiotics were effective for ILI and about their antibiotic use. Proportions and 95% confidence intervals (CI) were calculated for each question and interactions with respondent characteristics were tested using logistic regression. Over the three surveys, the proportion of respondents who believed antibiotics would "definitely/probably" help an ILI fell from 37% (95% CI 35-39%) to 28% (95% CI 26-29%). Those who would "definitely/probably" visit a doctor in this situation fell from 48% (95% CI 46-50%) to 36% (95% CI 34-37%), while those who would request antibiotics during a consultation fell from 39% (95% CI 37-41%) to 30% (95% CI 29-32%). The percentage of respondents who found the information we provided about AMR "new/surprising" fell from 34% (95% CI 32-36%) to 28% (95% CI 26-31%). Awareness improved more among black, Asian and minority ethnic (BAME) than white people, with little other evidence of differences in improvements between subgroups. Whilst a degree of selection bias is unavoidable in online survey samples, the results suggest that awareness of AMR and appropriate antibiotic use has recently significantly improved in the United Kingdom, according to a wide range of indicators.

SUBMITTER: Pouwels KB

PROVIDER: S-EPMC7601947 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Awareness of Appropriate Antibiotic Use in Primary Care for Influenza-Like Illness: Evidence of Improvement from UK Population-Based Surveys.

Pouwels Koen B KB Roope Laurence S J LSJ Buchanan James J Morrell Liz L Tonkin-Crine Sarah S Peters Michele M Jones Leah F LF Castro-Sánchez Enrique E Crook Derrick W DW Peto Tim T Butler Christopher C CC Robotham Julie V JV Walker A Sarah AS Wordsworth Sarah S

Antibiotics (Basel, Switzerland) 20201013 10

Influenza-like illnesses (ILI) account for a significant portion of inappropriate antibiotic use. Patient expectations for antibiotics for ILI are likely to play a substantial role in 'unnecessary' antibiotic consumption. This study aimed to investigate trends in awareness of appropriate antibiotic use and antimicrobial resistance (AMR). Three sequential online surveys of independent representative samples of adults in the United Kingdom investigated expectations for, and consumption of, antibio ...[more]

PMID: 33066092

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Project description:PURPOSE:To assess the utility of "influenza-like illness" (ILI) and whether it appropriately tests influenza vaccine effectiveness. PRINCIPAL RESULTS:The WHO and CDC definitions of "influenza-like illness" are similar. However many studies use other definitions, some not specifying a temperature and requiring specific respiratory and/or systemic symptoms, making many samples non-comparable. Most ILI studies find less than 25% of cases are RT-PCR-positive, those which test for other viruses and bacteria usually find multiple other pathogens, and most identify no pathogen in about 50% of cases. ILI symptom and symptom combinations do not have high sensitivity or specificity in identifying PCR-positive influenza cases. Rapid influenza diagnostic tests are increasingly used to screen ILI cases and they have low sensitivity and high specificity when compared to RT-PCR in identifying influenza. MAIN CONCLUSIONS:The working diagnosis of ILI presumes influenza may be involved until proven otherwise. Health care workers would benefit by renaming the WHO and CDC ILI symptoms and signs as "acute respiratory illness" and also using the WHO acute severe respiratory illness definition if the illness is severe and meets this criterion. This renaming would shift attention to identify the viral and bacterial pathogens in cases and epidemics, identify new pathogens, implement vaccination plans appropriate to the identified pathogens, and estimate workload during the viral season. Randomised controlled trials testing the effectiveness of influenza vaccine require all participants to be assessed by a gold standard (RT-PCR). ILI has no role in measuring influenza vaccine effectiveness. ILI is well established in the literature and in the operational definition of many surveillance databases and its imprecise definition may be inhibiting progress in research and treatment. The current ILI definition could with benefit be renamed "acute respiratory illness," with additional definitions for "severe acute respiratory illness" (SARI) with RT-PCR testing for pathogens to facilitate prevention and treatment.

Project description:BackgroundInternet-based surveillance systems to monitor influenza-like illness (ILI) have advantages over traditional (physician-based) reporting systems, as they can potentially monitor a wider range of cases (i.e. including those that do not seek care). However, the requirement for participants to have internet access and to actively participate calls into question the representativeness of the data. Such systems have been in place in a number of European countries over the last few years, and in July 2009 this was extended to the UK. Here we present results of this survey with the aim of assessing the reliability of the data, and to evaluate methods to correct for possible biases.MethodsInternet-based monitoring of ILI was launched near the peak of the first wave of the UK H1N1v influenza pandemic. We compared the recorded ILI incidence with physician-recorded incidence and an estimate of the true number of cases over the course of the epidemic. We also compared overall attack rates. The effect of using different ILI definitions and alternative denominator assumptions on incidence estimates was explored.ResultsThe crude incidence measured by the internet-based system appears to be influenced by individuals who participated only once in the survey and who appeared more likely to be ill. This distorted the overall incidence trend. Concentrating on individuals who reported more than once results in a time series of ILI incidence that matches the trend of case estimates reasonably closely, with a correlation of 0.713 (P-value: 0.0001, 95% CI: 0.435, 0.867). Indeed, the internet-based system appears to give a better estimate of the relative height of the two waves of the UK pandemic than the physician-recorded incidence. The overall attack rate is, however, higher than other estimates, at about 16% when compared with a model-based estimate of 6%.ConclusionInternet-based monitoring of ILI can capture the trends in case numbers if appropriate weighting is used to correct for differential response. The overall level of incidence is, however, difficult to measure. Internet-based systems may be a useful adjunct to existing ILI surveillance systems as they capture cases that do not necessarily contact health care. However, further research is required before they can be used to accurately assess the absolute level of incidence in the community.

Project description:BackgroundInfluenza and Influenza-like-illness (ILI) represents a substantial public health problem, but it is difficult to measure the overall burden as many cases do not access health care. Community cohorts have the advantage of not requiring individuals to present at hospitals and surgeries and therefore can potentially monitor a wider variety of cases. This study reports on the incidence and risk factors for ILI in the UK as measured using Flusurvey, an internet-based open community cohort.MethodsUpon initial online registration participants were asked background characteristics, and every week were asked to complete a symptoms survey. We compared the representativeness of our sample to the overall population. We used two case definitions of ILI, which differed in whether fever/chills was essential. We calculated ILI incidence week by week throughout the season, and investigated risk factors associated with ever reporting ILI over the course of the season. Risk factor analysis was conducted using binomial regression.Results5943 participants joined the survey, and 4532 completed the symptoms survey at least twice. Participants who filled in symptoms surveys at least twice filled in a median of nine symptoms surveys over the course of the study. 46.1% of participants reported at least one episode of ILI, and 6.0% of all reports were positive for ILI. Females had slightly higher incidence, and individuals over 65 had the lowest incidence. Incidence peaked just before Christmas and declined dramatically during school holidays. Multivariate regression showed that, for both definitions of ILI considered, being female, unvaccinated, having underlying health issues, having contact with children, being aged between 35 and 64, and being a smoker were associated with the highest risk of reporting an ILI. The use of public transport was not associated with an increased risk of ILI.ConclusionsOur results show that internet based surveillance can be used to measure ILI and understand risk factors. Vaccination is shown to be linked to a reduced risk of reporting ILI. Taking public transport does not increase the risk of reporting ILI. Flusurvey and other participatory surveillance techniques can be used to provide reliable information to policy makers in nearly real-time.

Dataset Information

Awareness of Appropriate Antibiotic Use in Primary Care for Influenza-Like Illness: Evidence of Improvement from UK Population-Based Surveys.

Publications

Awareness of Appropriate Antibiotic Use in Primary Care for Influenza-Like Illness: Evidence of Improvement from UK Population-Based Surveys.

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