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seir_covid19_dev's Introduction

SEIR_COVID19_Dev

(Developer's version) SEIR model for COVID-19 infection, including different clinical trajectories of infection, interventions to reduce transmission, and comparisons to healthcare capacity.

The code that produces the interface and functionality of the Shiny App is in files

  • server.R
  • ui.R

Files used in the explanatory sections of the app are

  • SEIR.Rmd
  • www/Parameters.nb.html

All the functions that actually run the model and process the parameters are in the code/functions.R file

If you want to run the code to produce the same outputs as Shiny but without dealing with the app structure, you can use the R scripts

  • runSpread.R
  • runInterventions.R
  • runCapacity.R

When trying out new model structures or plots, it is much easier to work with scripts instead of directly with the app. If you're adding a new feature, please add it via the functions.R file and a new script, so other can test it easily. Once troubleshooting is done, we can figure out how to integrated with the app

seir_covid19_dev's People

Contributors

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seir_covid19_dev's Issues

Intervention Compliance

I am wondering if there is models or implementations on how to account for the differences in policy intervention compliance across different countries. Comparing China and USA, the strictness of the policy varies significantly. In addition, USA lifted the lock down earlier than anticipated. It would be interesting to incorporate this feature in the intervention package.

Thanks.

Age structured model

We would like to create an age structured model that can pull in country-specific age distributions, country-specific age mixing matrices, and age-specific COVIDV19 death rates

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