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Connecting surveillance and population-level influenza incidence

View ORCID ProfileRobert C. Cope, View ORCID ProfileJoshua V. Ross, View ORCID ProfileMonique Chilver, Nigel P. Stocks, View ORCID ProfileLewis Mitchell
doi: https://doi.org/10.1101/427708
Robert C. Cope
1School of Mathematical Sciences, The University of Adelaide, Adelaide, SA 5005, Australia
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  • For correspondence: robert.cope@adelaide.edu.au
Joshua V. Ross
1School of Mathematical Sciences, The University of Adelaide, Adelaide, SA 5005, Australia
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Monique Chilver
2Discipline of General Practice, The University of Adelaide, Adelaide, SA 5005, Australia
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Nigel P. Stocks
2Discipline of General Practice, The University of Adelaide, Adelaide, SA 5005, Australia
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Lewis Mitchell
2Discipline of General Practice, The University of Adelaide, Adelaide, SA 5005, Australia
3Stream Leader, Data to Decisions Cooperative Research Centre (D2D CRC), Adelaide, SA, Australia
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Abstract

There is substantial interest in estimating and forecasting influenza incidence. Surveillance of influenza is challenging as one needs to demarcate influenza from other respiratory viruses, and due to asymptomatic infections. To circumvent these challenges, surveillance data often targets influenza-like-illness, or uses context-specific normalisations such as test positivity or per-consultation rates. Specifically, influenza incidence itself is not reported. We propose a framework to estimate population-level influenza incidence, and its associated uncertainty, using surveillance data and hierarchical observation processes. This new framework, and forecasting and forecast assessment methods, are demonstrated for three Australian states over 2016 and 2017. The framework allows for comparison within and between seasons in which surveillance effort has varied. Implementing this framework would improve influenza surveillance and forecasting globally, and could be applied to other diseases for which surveillance is difficult.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted September 28, 2018.
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Connecting surveillance and population-level influenza incidence
Robert C. Cope, Joshua V. Ross, Monique Chilver, Nigel P. Stocks, Lewis Mitchell
bioRxiv 427708; doi: https://doi.org/10.1101/427708
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Connecting surveillance and population-level influenza incidence
Robert C. Cope, Joshua V. Ross, Monique Chilver, Nigel P. Stocks, Lewis Mitchell
bioRxiv 427708; doi: https://doi.org/10.1101/427708

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