Identifiability of parameters in mathematical models of SARS-CoV-2 infections in humans
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Abstract
Determining accurate estimates for the characteristics of the severe acute respiratory syndrome coronavirus 2 in the upper and lower respiratory tracts, by fitting mathematical models to data, is made difficult by the lack of measurements early in the infection. To determine the sensitivity of the parameter estimates to the noise in the data, we developed a novel two-patch within-host mathematical model that considered the infection of both respiratory tracts and assumed that the viral load in the lower respiratory tract decays in a density dependent manner and investigated its ability to match population level data. We proposed several approaches that can improve practical identifiability of parameters, including an optimal experimental approach, and found that availability of viral data early in the infection is of essence for improving the accuracy of the estimates. Our findings can be useful for designing interventions.
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SciScore for 10.1101/2022.04.26.22274345: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our study has several limitations. First, we considered a density dependent clearance term for the URT virus that saturates at around 1-2×103 RNA copies per ml, in order to explain the viral RNA persistence in the LRT at 30 days following infection reported in the Wolfle et al. [44]. While in public health setting a SARS-CoV-2 diagnostic …
SciScore for 10.1101/2022.04.26.22274345: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our study has several limitations. First, we considered a density dependent clearance term for the URT virus that saturates at around 1-2×103 RNA copies per ml, in order to explain the viral RNA persistence in the LRT at 30 days following infection reported in the Wolfle et al. [44]. While in public health setting a SARS-CoV-2 diagnostic is determined by PCR assays, long-term RNA levels are not a reliable measurement of infectiousness, with the measured RNA values indicating the presence of genomic fragments, immune-complexed or neutralised virus, rather than replicationcompetent virus [1,21,34]. Further work is needed to separate the presence of infectious versus noninfectious viral RNA in the lower respiratory tract. Secondly, we did not consider an eclipse phase in the virus infectiousness (usually assumed to be around 6 hours [21, 24]). This simplification may be the leading reason for larger estimates for the death rate of infected cell in our study compared to other studies [22, 24]. Thirdly, due to the novelty of the model, we have no information on parameter priors. Therefore, we fitted the within-host model to the patient A and population data, and used those estimates as a mean in the prior distributions. However, since the resulting means fall within ranges observed for other acute infections [2–4, 6, 31, 32], and since we consider large standard deviations around the prior means, we are confident that we are covering a large search space that does not exclude viab...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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