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There are three efforts we are working on.

The first effort is to continuously profile the patients screened for SARS-CoV-2 in our health system. Using anonymized data, we watch trends in presenting symptoms of patients, test positivity rates, the age distribution of positive cases and hospitalization rates as well as monitor length of stay. This work as yielded a few insights already such as:

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.

  1. How data science can ease the COVID-19 pandemic, in the Brookings Institute's TechStream

The third effort is about answering specific questions by participating in network studies on COVID-19 in the OHDSI collaborative.

  1. Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS). Study Package and, Shiny App
  2. A networked study investigating the association of ACEis and ARBSs on COVID-19 incidence and complications. Protcol

5 min clip on how we need to improve the quality of the inputs to our COVID-19 models.

A talk about Stanford's data science efforts at COVID-19 and AI: A Virtual Conference by Stanford HAI.

covid19.txt · Last modified: 2020/12/10 11:25 by nigam