PhilSci Archive

The epistemology of the SARS-CoV-2 test

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

WarningThere is a more recent version of this item available.
[img]
Preview
Text
Corona test article preprint.pdf

Download (852kB) | Preview

Abstract

We investigate the epistemological consequences of a positive SARS-CoV-2 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 sole cause of flu-like symptoms in a given patient. We ask two fundamental epistemological questions regarding each hypothesis: First, given a positive SARS-CoV-2 test, what should we believe about the hypothesis and to what degree? Second, how much evidence does a positive test provide for a 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 for realistic assumptions about the base rate of infected individuals, P(V)≲20%, positive tests having low specificity (75%) would not raise the posterior probability for V to more than 50%. Furthermore, if the test specificity is less than 88.1%, even a positive test having 95% sensitivity would only yield weak to moderate evidence for V against ¬V. We also find that in plausible scenarios, positive tests would only provide weak to moderate evidence for C unless the tests have a high specificity. One has thus to be careful in ascribing the symptoms or death of a positively tested patient to SARS-CoV-2, if the possibility exists that the disease has been caused by another pathogen.


Export/Citation: EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL
Social Networking:
Share |

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; Medical tests
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: 09 Apr 2020 02:59
Last Modified: 09 Apr 2020 02:59
Item ID: 17048
Subjects: General Issues > Confirmation/Induction
General Issues > Evidence
Specific Sciences > Medicine > Health and Disease
Specific Sciences > Probability/Statistics
Date: 7 April 2020
URI: https://philsci-archive.pitt.edu/id/eprint/17048

Available Versions of this Item

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item