Disease severity determines health-seeking behaviour amongst individuals with influenza-like illness in an internet-based cohort.

Peppa, M; Edmunds, WJ; Funk, S; (2017) Disease severity determines health-seeking behaviour amongst individuals with influenza-like illness in an internet-based cohort. BMC infectious diseases, 17 (1). p. 238. ISSN 1471-2334 DOI: https://doi.org/10.1186/s12879-017-2337-5

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Seasonal influenza epidemics place considerable strain on health services. Robust systems of surveillance are therefore required to ensure preparedness. Sentinel surveillance does not accurately capture the community burden of epidemics as it misses cases that do not present to health services. In this study, Flusurvey (an internet-based community surveillance tool) was used to examine how severity of disease influences health-seeking behaviour in the UK. Logistic regression with random effects was used to investigate the association between health-seeking and symptom severity, duration of illness and reduction in self-reported health-score over four flu seasons between 2011 and 2015. The majority of individuals did not seek care. In general, there was very strong evidence for an association between all severity indicators and visiting a health service (p < 0.0001). Being female (OR 1.62, 95% CI 1.23-2.14, p = 0.0003) and a self-diagnosis of the flu (OR 3.39, 95% CI 2.38-4.83, p < 0.0001) were also associated with increased likelihood of visiting a health service. During the 2012-13 and 2014-15 flu seasons, there was a significantly larger proportion of individuals with more severe sets of symptoms and a longer duration of illness. Despite this, the proportion of individuals with particular sets of symptoms visiting a health service showed only very slight variation across years. Traditional surveillance systems capture only the more severe episodes of illness. However, in spite of variation in flu activity, the proportion of individuals visiting a health service remains relatively stable within specific sets of symptoms across years. These data could be used in combination with data on consultation rates to provide better estimates of community burden.

Item Type: Article
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology
Research Centre: EHR Research Group
Related URLs:
PubMed ID: 28359335
Web of Science ID: 397730000001
URI: http://researchonline.lshtm.ac.uk/id/eprint/3716655


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