ArticleJournal of theoretical biology2023
Ascertainment rate of SARS-CoV-2 infections from healthcare and community testing in the UK.
Article in Journal of theoretical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Resolving parameter uncertainty in SIR models through population-level serological surveillance: A synthetic study.Infectious Disease Modelling · 2026Article
- Multivariable Behavioral Change Modeling of Epidemics in the Presence of Undetected Infections.Statistics in medicine · 2026Article
- The tale of two assumptions: incorporating healthcare-seeking behaviour in epidemic forecasting.BMC infectious diseases · 2025Article
- Identification of undetected SARS-CoV-2 infections by clustering of Nucleocapsid antibody trajectories.Nature communications · 2025Article
- Estimation of unconfirmed COVID-19 cases from a cross-sectional survey of >10 000 households and a symptom-based machine learning model in Gilgit-Baltistan, Pakistan.BMJ public health · 2025Article
- Modeling the burden of long COVID in California with quality adjusted life-years (QALYS).Scientific reports · 2024Article
- Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand.Communications medicine · 2024Article
- The effect of quarantine policy on pollution emission and the usage of private transportation in urban areas.Scientific reports · 2024Article
- Estimating the Burden and Distribution of Post-COVID-19 Condition in Washington State, March 2020-October 2023.Preventing chronic disease · 2024Article
- Drivers and impact of the early silent invasion of SARS-CoV-2 Alpha.Nature communications · 2024Article
- Vaccination against COVID-19 - risks and benefits in children.European journal of pediatrics · 2024Review
- Using early detection data to estimate the date of emergence of an epidemic outbreak.PLoS computational biology · 2024Article
- Routine Surveillance of SARS-CoV-2 Serostatus in Pediatrics Allows Monitoring of Humoral Response.Microorganisms · 2023Article
- Assessing the importance of demographic risk factors across two waves of SARS-CoV-2 using fine-scale case data.PLoS computational biology · 2023Article
- Dynamics of SARS-CoV-2 infection hospitalisation and infection fatality ratios over 23 months in England.PLoS biology · 2023Article
- Empirical distributions of time intervals between COVID-19 cases and more severe outcomes in Scotland.PloS one · 2023Article
- Reversal of the unique Q493R mutation increases the affinity of Omicron S1-RBD for ACE2.Computational and structural biotechnology journal · 2023Article
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4 authors.
Funding
Abstract
The proportion of SARS-CoV-2 infections ascertained through healthcare and community testing is generally unknown and expected to vary depending on natural factors and changes in test-seeking behaviour. Here we use population surveillance data and reported daily case numbers in the United Kingdom to estimate the rate of case ascertainment. We mathematically describe the relationship between the ascertainment rate, the daily number of reported cases, population prevalence, and the sensitivity of PCR and Lateral Flow tests as a function time since exposure. Applying this model to the data, we estimate that 20%-40% of SARS-CoV-2 infections in the UK were ascertained with a positive test with results varying by time and region. Cases of the Alpha variant were ascertained at a higher rate than the wild type variants circulating in the early pandemic, and higher again for the Delta variant and Omicron BA.1 sub-lineage, but lower for the BA.2 sub-lineage. Case ascertainment was higher in adults than in children. We further estimate the daily number of infections and compare this to mortality data to estimate that the infection fatality rate increased by a factor of 3 during the period dominated by the Alpha variant, and declined in line with the distribution of vaccines. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".
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