ArticleNature communications2023
Drivers of SARS-CoV-2 testing behaviour: a modelling study using nationwide testing data in England.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The association of overweight, obesity, and long-term obesity with SARS-CoV-2 infection: a meta-analysis of 9 population-based cohorts from the Netherlands Cohorts Consortium.International journal of obesity (2005) · 2025Pooled it
- Employment type and non-compliance with SARS-CoV-2 diagnostic testing: insights from a nationwide seroprevalence study in South Korea.BMJ open · 2026Article
- Behavioural determinants of testing behaviour during a hypothetical human-to-human avian influenza outbreak: an interview study.BMC public health · 2026Article
- The impact of human behavioral adaptation stratified by immune status on COVID-19 spread with application to South Korea.PloS one · 2026Article
- Age and clinical spectrum of COVID-19 are associated with safety of transarterial chemoembolization in hepatocellular carcinoma: a retrospective cohort study.Journal of gastrointestinal oncology · 2024Article
- Observational
- High prevalence group testing in epidemiology with geometrically inspired algorithms.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
During the COVID-19 pandemic, national testing programmes were conducted worldwide on unprecedented scales. While testing behaviour is generally recognised as dynamic and complex, current literature demonstrating and quantifying such relationships is scarce, despite its importance for infectious disease surveillance and control. Here, we characterise the impacts of SARS-CoV-2 transmission, disease susceptibility/severity, risk perception, and public health measures on SARS-CoV-2 PCR testing behaviour in England over 20 months of the pandemic, by linking testing trends to underlying epidemic trends and contextual meta-data within a systematic conceptual framework. The best-fitting model describing SARS-CoV-2 PCR testing behaviour explained close to 80% of the total deviance in NHS test data. Testing behaviour showed complex associations with factors reflecting transmission level, disease susceptibility/severity (e.g. age, dominant variant, and vaccination), public health measures (e.g. testing strategies and lockdown), and associated changes in risk perception, varying throughout the pandemic and differing between infected and non-infected people.
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Registered trials
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