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The epistemology of a positive SARS-CoV-2 test

Klement, Rainer J. and Bandyopadhyay, Prasanta S. (2020) The epistemology of a positive SARS-CoV-2 test. [Preprint]

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Abstract

We investigate the epistemological consequences of a positive polymerase chain reaction SARS-CoV test for two relevant hypotheses: (i) V is the hypothesis that an individual has been infected with SARS-CoV-2; (ii) C is the hypothesis that SARS-CoV-2 is the cause of flu-like symptoms in a given patient. We ask two fundamental epistemological questions regarding each hypothesis: First, how much confirmation does a positive test lend to each hypothesis? Second, how much evidence does a positive test provide for each hypothesis against its negation? We respond to each question within a formal Bayesian framework. We construe degree of confirmation as the difference between the posterior probability of the hypothesis and its prior, and the strength of evidence for a hypothesis against its alternative in terms of their likelihood ratio. We find that test specificity – and coinfection probabilities when making inferences about C – were key determinants of confirmation and evidence. Tests with <87% specificity could not provide strong evidence (likelihood ratio >8) for V against ¬V regardless of sensitivity. Accordingly, low specificity tests could not provide strong evidence in favor of C in all plausible scenarios modeled. We also show how a positive influenza A test disconfirms C and provides weak evidence against C in dependence on the probability that the patient is influenza A infected given that her symptoms are not caused by SARS-CoV-2. Our analysis points out some caveats that should be considered when attributing symptoms or death of a positively tested patient to SARS-CoV-2.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Klement, Rainer J.rainer_klement@gmx.de0000-0003-1401-4270
Bandyopadhyay, Prasanta S.psb@montana.edu
Keywords: Bayesianism; Confirmation; COVID-19; Evidence; RT-qPCR
Subjects: General Issues > Confirmation/Induction
General Issues > Evidence
Specific Sciences > Medicine > Health and Disease
Specific Sciences > Probability/Statistics
Depositing User: Dr. Rainer Klement
Date Deposited: 14 Aug 2020 03:55
Last Modified: 14 Aug 2020 03:55
Item ID: 17982
Subjects: General Issues > Confirmation/Induction
General Issues > Evidence
Specific Sciences > Medicine > Health and Disease
Specific Sciences > Probability/Statistics
Date: 13 August 2020
URI: https://philsci-archive.pitt.edu/id/eprint/17982

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