Causal, Bayesian, & non-parametric modeling of the SARS-CoV-2 viral load distribution vs. patient's age.

ABSTRACT: The viral load of patients infected with SARS-CoV-2 varies on logarithmic scales and possibly with age. Controversial claims have been made in the literature regarding whether the viral load distribution actually depends on the age of the patients. Such a dependence would have implications for the COVID-19 spreading mechanism, the age-dependent immune system reaction, and thus for policymaking. We hereby develop a method to analyze viral-load distribution data as a function of the patients' age within a flexible, non-parametric, hierarchical, Bayesian, and causal model. The causal nature of the developed reconstruction additionally allows to test for bias in the data. This could be due to, e.g., bias in patient-testing and data collection or systematic errors in the measurement of the vira

SUBMITTER: Guardiani M 

PROVIDER: S-EPMC9534394 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature