Researchers develop a causal model to assess the dependence of viral loads of patients infected with COVID-19 on age

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Researchers develop a causal model to assess the dependence of viral loads of patients infected with COVID-19 on age
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Researchers develop a causal model to assess the dependence of viral loads of patients infected with COVID-19 on age PLOSONE LMU_Muenchen COVID19 coronavirus covid age infection viralload

By Tarun Sai LomteOct 12 2022Reviewed by Danielle Ellis, B.Sc. In a recent study published in PLOS One, researchers developed a causal model to analyze severe acute respiratory syndrome coronavirus 2 viral load distribution as a function of patients’ age.

About the study The present study examined viral load as a proxy for SARS-CoV-2 infectivity and re-analyzed age-stratified data previously reported by another research group through a non-parametric, Bayesian, and causal model. Since the COVID-19 outbreak, efforts have been made to identify whether individuals of specific age groups are more susceptible to infection than others.

Findings Related StoriesThe authors observed, in general, a descending trend in viral load probability distribution for all datasets and age groups. The dC dataset showed significant differences in the viral load for different age groups. The distribution had a distinct maximum for viral loads equal to or above 8 for patients older than 60. The researchers noted that this was not a consequence of an over-fit of sample noise but was triggered by data.

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