Internet-based surveillance of Influenza-like-illness in the UK during the 2009 H1N1 influenza pandemic

Abstract

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.

Rapid assessment of influenza vaccine effectiveness: analysis of an internet-based cohort

“…The participants were a self-selecting sample with potential biases, and in particular the youngest and oldest age groups were underrepresented. ILI was determined using a symptom-based case definition, and therefore influenza was not laboratory confirmed ; however, ILI as determined here has been shown to provide a good match to patterns of influenza incidence [10][11][12] and the difference in estimated effectiveness of vaccination against ILI compared to effectiveness against MRI suggests that ILI is capturing true influenza infections. In those individuals who did not report ILI, H1N1v vaccination offered some protection against MRI, suggesting that some MRI cases were actually mild doses of influenza.…”

“…Each week, participants were prompted by email to complete a survey documenting any symptoms experienced, onset date, use of health services, and whether the episode resulted in absenteeism. Further details can be found in Tilston et al [11]. Participants were able to update their reported vaccination status throughout the season, and were periodically reminded of this in the weekly email.…”

Smallpox: New Perspectives Regarding Risk Assessment & Management

“…During week 30 (late July), there can be up to 70,000 cases of ILI in a given country (e.g. UK) [27]. The 2,000 additional cases linked to smallpox are responsible for a 2% increase only (doubtfully detectable at this step, figures are the same for the other countries).…”

Effectiveness of 2012–2013 influenza vaccine against influenza-like illness in general population

“…Self-report of influenza vaccination status, 33,34 and symptoms of infectious illness, including respiratory illnesses 35 has been shown to be acceptably accurate and valid, and monthly and weekly follow-up intervals have been used in other studies assessing occurrences of ILI. 36,37 Even if selfreport of vaccination could be subject to recall bias and overestimation of rates (especially in the elderly and social desirability bias in the answers provided), 38 in contrast to telephone surveys, the web self-report is less involved by the social desirability bias in the answers provided because of absence of a personal contact with the inquiring.…”