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Open AccessArticle

Accounting for Healthcare-Seeking Behaviours and Testing Practices in Real-Time Influenza Forecasts

1
Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville 3052, Australia
2
Department of Zoology, The University of Oxford, Oxford OX1 3SZ, UK
3
Hunter New England Population Health, Wallsend 2287, Australia
4
School of Mathematics and Statistics, The University of Melbourne, Parkville 3052, Australia
5
Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville 3052, Australia
6
Victorian Infectious Diseases Reference Laboratory Epidemiology Unit, Peter Doherty Institute for Infection and Immunity, The Royal Melbourne Hospital and The University of Melbourne, Melbourne 3000, Australia
*
Author to whom correspondence should be addressed.
Trop. Med. Infect. Dis. 2019, 4(1), 12; https://doi.org/10.3390/tropicalmed4010012
Received: 20 November 2018 / Revised: 8 January 2019 / Accepted: 8 January 2019 / Published: 11 January 2019
For diseases such as influenza, where the majority of infected persons experience mild (if any) symptoms, surveillance systems are sensitive to changes in healthcare-seeking and clinical decision-making behaviours. This presents a challenge when trying to interpret surveillance data in near-real-time (e.g., to provide public health decision-support). Australia experienced a particularly large and severe influenza season in 2017, perhaps in part due to: (a) mild cases being more likely to seek healthcare; and (b) clinicians being more likely to collect specimens for reverse transcription polymerase chain reaction (RT-PCR) influenza tests. In this study, we used weekly Flutracking surveillance data to estimate the probability that a person with influenza-like illness (ILI) would seek healthcare and have a specimen collected. We then used this estimated probability to calibrate near-real-time seasonal influenza forecasts at each week of the 2017 season, to see whether predictive skill could be improved. While the number of self-reported influenza tests in the weekly surveys are typically very low, we were able to detect a substantial change in healthcare seeking behaviour and clinician testing behaviour prior to the high epidemic peak. Adjusting for these changes in behaviour in the forecasting framework improved predictive skill. Our analysis demonstrates a unique value of community-level surveillance systems, such as Flutracking, when interpreting traditional surveillance data. These methods are also applicable beyond the Australian context, as similar community-level surveillance systems operate in other countries. View Full-Text
Keywords: influenza; epidemics; forecasting; public health; surveillance; ascertainment influenza; epidemics; forecasting; public health; surveillance; ascertainment
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Moss, R.; Zarebski, A.E.; Carlson, S.J.; McCaw, J.M. Accounting for Healthcare-Seeking Behaviours and Testing Practices in Real-Time Influenza Forecasts. Trop. Med. Infect. Dis. 2019, 4, 12.

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  • Externally hosted supplementary file 1
    Doi: 10.26188/5bf3d60c4ffae
    Description: Accounting for healthcare-seeking behaviours and testing practices in real-time influenza forecasts: supplementary materials
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