ArticleTropical medicine and infectious disease2019
Accounting for Healthcare-Seeking Behaviours and Testing Practices in Real-Time Influenza Forecasts.
Article in Tropical medicine and infectious disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- The tale of two assumptions: incorporating healthcare-seeking behaviour in epidemic forecasting.BMC infectious diseases · 2025Article
- Biases in Routine Influenza Surveillance Indicators Used to Monitor Infection Incidence and Recommendations for Improvement.Influenza and other respiratory viruses · 2024Article
- Challenges in the case-based surveillance of infectious diseases.Royal Society open science · 2024Article
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- Article
- Key Challenges for Respiratory Virus Surveillance while Transitioning out of Acute Phase of COVID-19 Pandemic.Emerging infectious diseases · 2024Article
- Near-term forecasting of Covid-19 cases and hospitalisations in Aotearoa New Zealand.PLoS computational biology · 2024Article
- The re-emergence of influenza following the COVID-19 pandemic in Victoria, Australia, 2021 to 2022.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023Article
- Forecasting COVID-19 activity in Australia to support pandemic response: May to October 2020.Scientific reports · 2023Article
- Design of effective outpatient sentinel surveillance for COVID-19 decision-making: a modeling study.BMC infectious diseases · 2023Article
- Drivers of SARS-CoV-2 testing behaviour: a modelling study using nationwide testing data in England.Nature communications · 2023Article
- Designing Digital COVID-19 Screening: Insights and Deliberations.International journal of environmental research and public health · 2023Article
- Tracking changes in SARS-CoV-2 transmission with a novel outpatient sentinel surveillance system in Chicago, USA.Nature communications · 2022Article
- A computationally tractable birth-death model that combines phylogenetic and epidemiological data.PLoS computational biology · 2022Article
- Resurgence of SARS-CoV-2: Detection by community viral surveillance.Science (New York, N.Y.) · 2021Article
- Spatial Inequality Hides the Burden of Dog Bites and the Risk of Dog-Mediated Human Rabies.The American journal of tropical medicine and hygiene · 2020Article
- Article
- Commentary on "Transparent modeling of influenza incidence": Because the model said so.International journal of forecastingArticle
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Authors and funding
4 authors.
Funding
Abstract
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.
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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.