Abstract
The within-host viral kinetics of SARS-CoV-2 infection and how they relate to a person's infectiousness are not well understood. This limits our ability to quantify the impact of interventions on viral transmission. Here, we develop viral dynamic models of SARS-CoV-2 infection and fit them to data to estimate key within-host parameters such as the infected cell half-life and the within-host reproductive number. We then develop a model linking viral load (VL) to infectiousness and show a person's infectiousness increases sublinearly with VL and that the logarithm of the VL in the upper respiratory tract is a better surrogate of infectiousness than the VL itself. Using data on VL and the predicted infectiousness, we further incorporated data on antigen and RT-PCR tests and compared their usefulness in detecting infection and preventing transmission. We found that RT-PCR tests perform better than antigen tests assuming equal testing frequency; however, more frequent antigen testing may perform equally well with RT-PCR tests at a lower cost but with many more false-negative tests. Overall, our models provide a quantitative framework for inferring the impact of therapeutics and vaccines that lower VL on the infectiousness of individuals and for evaluating rapid testing strategies.
Highlights
ATheoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545; bNew Mexico Consortium, Los Alamos, NM 87544; and cAaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032
We develop a model linking viral load (VL) to infectiousness and show a person’s infectiousness increases sublinearly with VL and that the logarithm of the VL in the upper respiratory tract is a better surrogate of infectiousness than the VL itself
There were large uncertainties in model parameter estimates because in almost all studies, viral dynamic models were fit to data that were taken after symptom onset without knowledge of the patients’ infection dates and early VL dynamics
Summary
ATheoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545; bNew Mexico Consortium, Los Alamos, NM 87544; and cAaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032. As administration of vaccines may lead to lowered VLs in breakthrough infections [10,11,12], a quantitative understanding will inform how these reductions in VL impact infectiousness and allow better predictions of how much transmission vaccinated individuals with breakthrough infection cause It would provide better insight into a person’s infectiousness throughout the course of infection and inform testing strategies for work/school reopening, travel, etc. There were large uncertainties in model parameter estimates because in almost all studies, viral dynamic models were fit to data that were taken after symptom onset without knowledge of the patients’ infection dates and early VL dynamics We resolve this issue by using two unique datasets and by using clinical and epidemiological data to inform the quantitative relationship between VL and infectiousness. We further evaluate the effectiveness of testing strategies using either antigen or RT-PCR tests at different testing frequencies
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