Constructing and adjusting estimates for household transmission of SARS-CoV-2 from prior studies, widespread-testing and contact-tracing data
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Abstract
Background
With reduced community mobility, household infections may become increasingly important in SARS-CoV-2 transmission dynamics.
Methods
We investigate the intra-household transmission of COVID-19 through the secondary-attack rate (SAR) and household reproduction number (Rh). We estimate these using (i) data from 29 prior studies (February–August 2020), (ii) epidemiologically linked confirmed cases from Singapore (January–April 2020) and (iii) widespread-testing data from Vo’ (February–March 2020). For (i), we use a Bayesian random-effects model that corrects for reverse transcription–polymerase chain reaction (RT–PCR) test sensitivity and asymptomatic cases. We investigate the robustness of Rh with respect to community transmission rates and mobility patterns.
Results
The corrected pooled estimates from prior studies for SAR and Rh are 24% (20–28%) and 0.34 (0.30–0.38), respectively. Without corrections, the pooled estimates are: SAR = 18% (14–21%) and Rh = 0.28 (0.25–0.32). The corrected estimates line up with direct estimates from contact-tracing data from Singapore [Rh = 0.32 (0.22–0.42)] and population testing data from Vo’ [SAR = 31% (28–34%) and Rh = 0.37 (0.34–0.40)]. The analysis of Singapore data further suggests that the value of Rh (0.22–0.42) is robust to community-spread dynamics; our estimate of Rh stays constant whereas the fraction of infections attributable to household transmission (Rh/Reff) is lowest during outbreaks (5–7%) and highest during lockdowns and periods of low community spread (25–30%).
Conclusions
The three data-source types yield broadly consistent estimates for SAR and Rh. Our study suggests that household infections are responsible for a large fraction of infections and so household transmission may be an effective target for intervention.
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SciScore for 10.1101/2020.05.23.20111559: (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: Thank you for sharing your code and data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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 …
SciScore for 10.1101/2020.05.23.20111559: (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: Thank you for sharing your code and data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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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