A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2.
The scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination...
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Public Library of Science (PLoS)
2021-03-01
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| Series: | PLoS Biology |
| Online Access: | https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.3001128&type=printable |
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| author | Kwang Su Kim Keisuke Ejima Shoya Iwanami Yasuhisa Fujita Hirofumi Ohashi Yoshiki Koizumi Yusuke Asai Shinji Nakaoka Koichi Watashi Kazuyuki Aihara Robin N Thompson Ruian Ke Alan S Perelson Shingo Iwami |
| author_facet | Kwang Su Kim Keisuke Ejima Shoya Iwanami Yasuhisa Fujita Hirofumi Ohashi Yoshiki Koizumi Yusuke Asai Shinji Nakaoka Koichi Watashi Kazuyuki Aihara Robin N Thompson Ruian Ke Alan S Perelson Shingo Iwami |
| author_sort | Kwang Su Kim |
| collection | DOAJ |
| description | The scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data, we compare within-host viral dynamics of SARS-CoV-2 with analogous dynamics of MERS-CoV and SARS-CoV. Our quantitative analyses using a mathematical model revealed that the within-host reproduction number at symptom onset of SARS-CoV-2 was statistically significantly larger than that of MERS-CoV and similar to that of SARS-CoV. In addition, the time from symptom onset to the viral load peak for SARS-CoV-2 infection was shorter than those of MERS-CoV and SARS-CoV. These findings suggest the difficulty of controlling SARS-CoV-2 infection by antivirals. We further used the viral dynamics model to predict the efficacy of potential antiviral drugs that have different modes of action. The efficacy was measured by the reduction in the viral load area under the curve (AUC). Our results indicate that therapies that block de novo infection or virus production are likely to be effective if and only if initiated before the viral load peak (which appears 2-3 days after symptom onset), but therapies that promote cytotoxicity of infected cells are likely to have effects with less sensitivity to the timing of treatment initiation. Furthermore, combining a therapy that promotes cytotoxicity and one that blocks de novo infection or virus production synergistically reduces the AUC with early treatment. Our unique modeling approach provides insights into the pathogenesis of SARS-CoV-2 and may be useful for development of antiviral therapies. |
| format | Article |
| id | doaj-art-e9a5c985132245c49a544053dcc871c1 |
| institution | OA Journals |
| issn | 1544-9173 1545-7885 |
| language | English |
| publishDate | 2021-03-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Biology |
| spelling | doaj-art-e9a5c985132245c49a544053dcc871c12025-08-20T02:01:00ZengPublic Library of Science (PLoS)PLoS Biology1544-91731545-78852021-03-01193e300112810.1371/journal.pbio.3001128A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2.Kwang Su KimKeisuke EjimaShoya IwanamiYasuhisa FujitaHirofumi OhashiYoshiki KoizumiYusuke AsaiShinji NakaokaKoichi WatashiKazuyuki AiharaRobin N ThompsonRuian KeAlan S PerelsonShingo IwamiThe scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data, we compare within-host viral dynamics of SARS-CoV-2 with analogous dynamics of MERS-CoV and SARS-CoV. Our quantitative analyses using a mathematical model revealed that the within-host reproduction number at symptom onset of SARS-CoV-2 was statistically significantly larger than that of MERS-CoV and similar to that of SARS-CoV. In addition, the time from symptom onset to the viral load peak for SARS-CoV-2 infection was shorter than those of MERS-CoV and SARS-CoV. These findings suggest the difficulty of controlling SARS-CoV-2 infection by antivirals. We further used the viral dynamics model to predict the efficacy of potential antiviral drugs that have different modes of action. The efficacy was measured by the reduction in the viral load area under the curve (AUC). Our results indicate that therapies that block de novo infection or virus production are likely to be effective if and only if initiated before the viral load peak (which appears 2-3 days after symptom onset), but therapies that promote cytotoxicity of infected cells are likely to have effects with less sensitivity to the timing of treatment initiation. Furthermore, combining a therapy that promotes cytotoxicity and one that blocks de novo infection or virus production synergistically reduces the AUC with early treatment. Our unique modeling approach provides insights into the pathogenesis of SARS-CoV-2 and may be useful for development of antiviral therapies.https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.3001128&type=printable |
| spellingShingle | Kwang Su Kim Keisuke Ejima Shoya Iwanami Yasuhisa Fujita Hirofumi Ohashi Yoshiki Koizumi Yusuke Asai Shinji Nakaoka Koichi Watashi Kazuyuki Aihara Robin N Thompson Ruian Ke Alan S Perelson Shingo Iwami A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2. PLoS Biology |
| title | A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2. |
| title_full | A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2. |
| title_fullStr | A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2. |
| title_full_unstemmed | A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2. |
| title_short | A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2. |
| title_sort | quantitative model used to compare within host sars cov 2 mers cov and sars cov dynamics provides insights into the pathogenesis and treatment of sars cov 2 |
| url | https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.3001128&type=printable |
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