Calculating incidence of Influenza-like and COVID-like symptoms from Flutracking participatory survey data.

Emily P Harvey, Joel A Trent, Frank Mackenzie, Steven M Turnbull, Dion R J O'Neale

Abstract read

In one paragraph

Article in MethodsX, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it

0cells of the map it votes in

4citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

Monitoring influenza-like symptoms in the UK through participatory surveillance: Insights from FluSurvey over two winter seasons (2023-24 and 2024-25).PLOS digital health · 2026
Article
Increasing Underrepresentation of Pacific Peoples in Community-Based Respiratory Surveillance in Aotearoa New Zealand, 2018-2024.Journal of the Royal Society of New Zealand · 2026
Article
A Framework for Evaluating the Use of Surveillance Systems for Short-Term Influenza Forecasting.Influenza and other respiratory viruses · 2025
Article
Exploring influenza vaccination determinants through digital participatory surveillance.BMC public health · 2025
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Emily P HarveyCOVID Modelling Aotearoa, The University of Auckland, 38 Princes Street, Auckland CBD, Auckland 1010, New Zealand.

Joel A TrentCOVID Modelling Aotearoa, The University of Auckland, 38 Princes Street, Auckland CBD, Auckland 1010, New Zealand.

Frank MackenzieCOVID Modelling Aotearoa, The University of Auckland, 38 Princes Street, Auckland CBD, Auckland 1010, New Zealand.

Steven M TurnbullCOVID Modelling Aotearoa, The University of Auckland, 38 Princes Street, Auckland CBD, Auckland 1010, New Zealand.

Dion R J O'NealeCOVID Modelling Aotearoa, The University of Auckland, 38 Princes Street, Auckland CBD, Auckland 1010, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article describes a new method for estimating weekly incidence (new onset) of symptoms consistent with Influenza and COVID-19, using data from the Flutracking survey. The method mitigates some of the known self-selection and symptom-reporting biases present in existing approaches to this type of participatory longitudinal survey data. The key novel steps in the analysis are:

Indexed as

COVID-19FlutrackingIncidenceInfluenza-like illnessLogistic regressionParticipatory epidemiologyReporting biasSurvey analysisSurvey re-weightingSyndromic surveillance

Identifiers

PMID35993031

DOI10.1016/j.mex.2022.101820

PMCPMC9381980

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.