Last updated: 2020-09-01
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Knit directory: uci_covid_modeling/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | 4be982d | igoldsteinh | 2020-08-28 | Update about.html |
| Rmd | c762f18 | igoldsteinh | 2020-08-28 | added software to about, made vladimir the contact |
| html | 33f234e | vnminin | 2020-08-27 | some formatting |
| html | 2780db7 | igoldsteinh | 2020-08-27 | updated about page with proper header |
| Rmd | a07b913 | igoldsteinh | 2020-08-26 | fixed model graphic, fixed legend sizes, fixed readme, added about |
| html | a07b913 | igoldsteinh | 2020-08-26 | fixed model graphic, fixed legend sizes, fixed readme, added about |
| Rmd | 8d52b42 | igoldsteinh | 2020-08-26 | more updates to website |
| html | 8d52b42 | igoldsteinh | 2020-08-26 | more updates to website |
| Rmd | 79a6fd6 | igoldsteinh | 2020-08-26 | updating about and license, experimenting with figure size |
| html | 79a6fd6 | igoldsteinh | 2020-08-26 | updating about and license, experimenting with figure size |
| html | 8abe830 | igoldsteinh | 2020-08-06 | fixed figure length, updated, tried a readme |
| Rmd | 99d68f7 | igoldsteinh | 2020-07-29 | bare bones report |
| html | 99d68f7 | igoldsteinh | 2020-07-29 | bare bones report |
| Rmd | 792b89a | vnminin | 2020-07-27 | Start workflowr project. |
This website provides reports on the dynamics and future trends of COVID-19 in Orange County, CA. Please visit the github for details on the code, and read the manuscript associated with this endeavor for further methodological details.
For questions please contact Prof. Vladimir Minin.
We use data provided by OCHCA. An aggregated version of our data is available in the github. Crucially, we exclude repeat tests given to patients who test positive (which happens when patients are hospitalized). Our data may not correspond with publicly available data.
We also do not analyze data in real time. This is because case, test, and death counts are often updated retroactively, and we wish to give data collectors time to provide complete results. Typically, there will be at least a ten day gap between the present day and the final date analyzed in the most recent report.
Our analysis relies on a six compartment mechanistic model of the pandemic. We then use Bayesian inference to provide inference on key disease dynamics and make predictions on future observed cases and deaths. Further descriptions of the methodology are available in the manuscript.