%0 Journal Article %1 klement2020epistemology %A Klement, Rainer Johannes %A Bandyopadhyay, Prasanta S. %D 2020 %J Acta Biotheoretica %K bayesian covid-19 pcr_test %R 10.1007/s10441-020-09393-w %T The Epistemology of a Positive SARS-CoV-2 Test %U https://doi.org/10.1007/s10441-020-09393-w %X 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 <þinspace87\% specificity could not provide strong evidence (likelihood ratioþinspace>þinspace8) 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 his/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.

@article{klement2020epistemology, 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 <{\thinspace}87{\%} specificity could not provide strong evidence (likelihood ratio{\thinspace}>{\thinspace}8) for V against {\textlnot}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 his/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.}, added-at = {2020-11-30T12:54:12.000+0100}, author = {Klement, Rainer Johannes and Bandyopadhyay, Prasanta S.}, biburl = {https://www.bibsonomy.org/bibtex/29e2013601aca0bb80472a473ee2f1f70/fordham1}, day = 04, description = {The Epistemology of a Positive SARS-CoV-2 Test | SpringerLink}, doi = {10.1007/s10441-020-09393-w}, interhash = {849e1bee53361459b8f8e843b66f75d6}, intrahash = {9e2013601aca0bb80472a473ee2f1f70}, issn = {1572-8358}, journal = {Acta Biotheoretica}, keywords = {bayesian covid-19 pcr_test}, month = sep, timestamp = {2020-11-30T12:54:12.000+0100}, title = {The Epistemology of a Positive SARS-CoV-2 Test}, url = {https://doi.org/10.1007/s10441-020-09393-w}, year = 2020 }