Contact tracing is increasingly used to combat COVID-19, and digital implementations are now being deployed, many based on Apple and Google’s Exposure Notification System. These systems utilize non-traditional smartphone-based technology, presenting challenges in understanding possible outcomes. In this work, we create individual-based models of three Washington state counties to explore how digital exposure notifications combined with other non-pharmaceutical interventions influence COVID-19 disease spread under various adoption, compliance, and mobility scenarios. In a model with 15% participation, we found that exposure notification could reduce infections and deaths by approximately 8% and 6% and could effectively complement traditional contact tracing. We believe this can provide health authorities in Washington state and beyond with guidance on how exposure notification can complement traditional interventions to suppress the spread of COVID-19.
Even with the availability of vaccines, therapeutic options for COVID-19 still remain
highly desirable, especially in hospitalized patients with moderate or severe disease.
Soluble ACE2 (sACE2) is a promising therapeutic candidate that neutralizes SARS CoV-2
infection by acting as a decoy. Using computational mutagenesis, we designed a number of
sACE2 derivatives carrying three to four mutations. The top-predicted sACE2 decoy based
on the
in silico
mutagenesis scan was subjected to molecular dynamics
and free-energy calculations for further validation. After illuminating the mechanism of
increased binding for our designed sACE2 derivative, the design was verified
experimentally by flow cytometry and BLI-binding experiments. The computationally
designed sACE2 decoy (ACE2-
FFWF
) bound the receptor-binding domain of
SARS-CoV-2 tightly with low nanomolar affinity and ninefold affinity enhancement over
the wild type. Furthermore, cell surface expression was slightly greater than wild-type
ACE2, suggesting that the design is well-folded and stable. Having an arsenal of
high-affinity sACE2 derivatives will help to buffer against the emergence of SARS CoV-2
variants. Here, we show that computational methods have become sufficiently accurate for
the design of therapeutics for current and future viral pandemics.
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