Inferring Timing of Infection Using Within-host SARS-CoV-2 Infection Dynamics Model: Are “Imported Cases” Truly Imported?
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Abstract
In countries/communities at risk of future outbreaks of COVID-19, ascertaining whether cases are imported or the result of local secondary transmission is important for government to shape appropriate public health strategies. In this study, we propose a novel approach to identify the timing of infection, whereby we developed a within-host model to capture viral load dynamics post-symptom onset. We submit our approach allow us to differentiate imported cases from local secondary cases. To illustrate our method, we use the initial reported cases in Singapore, where the first reported 18 cases were considered imported, as these individuals had recent travel history to Wuhan, China, which is a hotspot of COVID-19 outbreak. With additional information regarding day of entrance in Singapore, we were able to infer whether these were infected locally or prior to arriving in Singapore. Of all the cases, we identified 6 as likely evidence of ongoing secondary transmission within Singapore. In an early phase of outbreaks, collecting viral load data over time from cases from symptom onset is highly recommended.
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SciScore for 10.1101/2020.03.30.20040519: (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:There are limitations to our approach. Our approach requires viral load data over multiple time points; therefore, we may not be able to estimate the timing of infection immediately after symptom onset. Further, we need to note that both the boundaries and the day of infection establishment estimated using our approach could be …
SciScore for 10.1101/2020.03.30.20040519: (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:There are limitations to our approach. Our approach requires viral load data over multiple time points; therefore, we may not be able to estimate the timing of infection immediately after symptom onset. Further, we need to note that both the boundaries and the day of infection establishment estimated using our approach could be underestimated, because infection is established after exposure starts. For countries and communities at risk of future COVID-19 outbreak, which include second outbreaks after significant decreased transmission (i.e. China), we strongly recommend monitoring the viral load in the early phase of outbreaks. As such, the method we used may be critical to help shape a country’s early response to an outbreak.
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.
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