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covid19 [2020/08/20 11:47]
nigam
covid19 [2020/12/10 11:25] (current)
nigam
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   - [[https://www.nature.com/articles/s41746-020-0300-0|Estimating the feasibility of symptom based screening of COVID19]],// in npj Digital Medicine //   - [[https://www.nature.com/articles/s41746-020-0300-0|Estimating the feasibility of symptom based screening of COVID19]],// 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 the 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//
 +  - [[https://immunology.sciencemag.org/content/5/54/eabe0240 | Defining the Features and Duration of Antibody Responses to SARS-CoV- 2 Infection ...]] // Science Immunology //
  
 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.
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 The **third**  effort is about answering specific questions by participating in network studies on COVID-19 in the OHDSI collaborative. The **third**  effort is about answering specific questions by participating in network studies on COVID-19 in the OHDSI collaborative.
  
-  - [[https://www.medrxiv.org/content/10.1101/2020.04.22.20074336v1|An international characterisation of patients hospitalised with COVID-19 and a comparison with those hospitalised with influenza]], [[https://github.com/ohdsi-studies/Covid19HospitalizationCharacterization| Protocol]] and, [[https://data.ohdsi.org/Covid19CharacterizationHospitalization/| Shiny App]]+  - [[https://www.nature.com/articles/s41467-020-18849-z|Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study]], [[https://github.com/ohdsi-studies/Covid19HospitalizationCharacterization| Protocol]] and, [[https://data.ohdsi.org/Covid19CharacterizationHospitalization/| Shiny App]]
   - Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS). [[https://github.com/ohdsi-studies/Covid19CharacterizationCharybdis|Study Package]] and, [[https://data.ohdsi.org/Covid19CharacterizationCharybdis/| Shiny App]]   - Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS). [[https://github.com/ohdsi-studies/Covid19CharacterizationCharybdis|Study Package]] and, [[https://data.ohdsi.org/Covid19CharacterizationCharybdis/| Shiny App]]
   - A networked study investigating the association of ACEis and ARBSs on COVID-19 incidence and complications. [[https://github.com/ohdsi-studies/Covid19EstimationRasInhibitors|Protcol]]   - A networked study investigating the association of ACEis and ARBSs on COVID-19 incidence and complications. [[https://github.com/ohdsi-studies/Covid19EstimationRasInhibitors|Protcol]]
covid19.txt · Last modified: 2020/12/10 11:25 by nigam