Your browser doesn't support javascript.
loading
Testing for coronavirus (SARS-CoV-2) infection in populations with low infection prevalence: the largely ignored problem of false positives and the value of repeat testing
Cathie Sudlow; Peter Diggle; Oliver Warlow; David Seymour; Ben Gordon; Rhos Walker; Charles Warlow.
Afiliação
  • Cathie Sudlow; BHF Data Science Centre, Health Data Research UK; Usher Institute, University of Edinburgh
  • Peter Diggle; University of Lancaster; Health Data Research UK
  • Oliver Warlow; Ventient Energy
  • David Seymour; Health Data Research UK
  • Ben Gordon; Health Data Research UK
  • Rhos Walker; Health Data Research UK
  • Charles Warlow; University of Edinburgh
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20178137
ABSTRACT
BackgroundCalls are increasing for widespread SARS-CoV-2 infection testing of people from populations with a very low prevalence of infection. We quantified the impact of less than perfect diagnostic test accuracy on populations, and on individuals, in low prevalence settings, focusing on false positives and the role of confirmatory testing. MethodsWe developed a simple, interactive tool to assess the impact of different combinations of test sensitivity, specificity and infection prevalence in a notional population of 100,000. We derived numbers of true positives, true negatives, false positives and false negatives, positive predictive value (PPV - the percentage of test positives that are true positives) and overall test accuracy for three testing strategies (1) single test for all; (2) add repeat testing in test positives; (3) add further repeat testing in those with discrepant results. We also assessed the impact on test results for individuals having one, two or three tests under these three strategies. ResultsWith sensitivity of 80%, infection prevalence of 1 in 2,000, and specificity 99.9% on all tests, PPV in the tested population of 100,000 will be only 29% with one test, increasing to > 99.5% (100% when rounded to the nearest %) with repeat testing in strategies 2 or 3. More realistically, if specificity is 95% for the first and 99.9% for subsequent tests, single test PPV will be only 1%, increasing to 86% with repeat testing in strategy 2, or 79% with strategy 3 (albeit with 6 fewer false negatives than strategy 2). In the whole population, or in particular individuals, PPV increases as infection becomes more common in the population but falls to unacceptably low levels with lower test specificity. ConclusionTo avoid multiple unnecessary restrictions on whole populations, and in particular individuals, from widespread population testing for SARS-CoV-2, the crucial roles of extremely high test specificity and of confirmatory testing must be fully appreciated and incorporated into policy decisions.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo diagnóstico / Estudo observacional / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo diagnóstico / Estudo observacional / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
...