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covid19 [2020/06/10 17:59] nigam |
covid19 [2020/06/16 17:54] nigam |
- [[https://www.sciencedirect.com/science/article/pii/S1386653220302195|Persistent detection of SARS-CoV-2 RNA in patients and healthcare workers with COVID-19]], // in the Journal of Clinical Virology// | - [[https://www.sciencedirect.com/science/article/pii/S1386653220302195|Persistent detection of SARS-CoV-2 RNA in patients and healthcare workers with COVID-19]], // in the Journal of Clinical Virology// |
- [[https://www.medrxiv.org/content/10.1101/2020.05.03.20089151v1|Frequency of discordant SARS-CoV-2 test results among initially negative patients]]// in Clinical Infectious Diseases // | - [[https://www.medrxiv.org/content/10.1101/2020.05.03.20089151v1|Frequency of discordant SARS-CoV-2 test results among initially negative patients]]// in Clinical Infectious Diseases // |
- [[https://docs.google.com/document/d/1b4QCweo6EmLYqsVSdnaTW0AJMmoPM-of3cO5yTpIOxg/edit#heading=h.gjdgxs|Estimating the feasibility of symptom based screening of COVID19]], //under review at npj Digital Medicine // | - [[https://docs.google.com/document/d/1b4QCweo6EmLYqsVSdnaTW0AJMmoPM-of3cO5yTpIOxg/edit#heading=h.gjdgxs|Estimating the feasibility of symptom based screening of COVID19]], //accepted in npj Digital Medicine // |
- [[https://doi.org/10.1016/j.jcv.2020.104502 | A predictive tool for identification of SARS-CoV-2 PCR-negative patients using routine test results]], // in Journal of Clinical Virology// | - [[https://doi.org/10.1016/j.jcv.2020.104502|A predictive tool for identification of SARS-CoV-2 PCR-negative patients using routine test results]], // in the Journal of Clinical Virology// |
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The **second** effort is to help others in creating better models of the COVID-19 pandemic. Existing predictions of the pandemic are highly uncertain due to lack of accurate input data. We are trying to help in the efforts of multiple scientists to obtain more accurate estimates of the parameters that feed into computer models of the COVID-19 pandemic. | The **second** effort is to help others in creating better models of the COVID-19 pandemic. Existing predictions of the pandemic are highly uncertain due to lack of accurate input data. We are trying to help in the efforts of multiple scientists to obtain more accurate estimates of the parameters that feed into computer models of the COVID-19 pandemic. |