Robert Kubinec 3/28/2020
This repository contains data and code to fit the model described in “A Retrospective Bayesian Model for Measuring Covariate Effects on Observed COVID-19 Test and Case Counts”, link here. The following is a brief list of the files in the repo relevant to the paper. There are also other files in the repo related to the collection of government policy data.
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corona_tscs_betab.stan: This Stan model contains a partially-identified model of COVID-19 that permits relative distinctions to be made between areas/countries/states’ infection rates. The parameter
num_infected_highindexes the infection rate by time point and country. As the latent process is on the logit scale, it must be converted via the inverse-logit function to a proportion. However, the resulting estimate should not be interpreted as the total infected in a country, but rather a relative ranking of which countries/areas are the most infected up to the current time point. -
corona_tscs_betab_scale.stan: This Stan model extends the partially-identified model with the 10% lower threshold for tests to infections ratio described in the paper. This model will produce an estimate for
num_infected_highthat when converted with the inverse-logit function will represent the proportion infected in a country conditional on the model’s prior concerning the tests to infections ratio. -
kubinec_model_preprint.Rmd: A copy of the paper draft with embedded R code. Because the fitted model objects are too large to put on Github, all Stan models must be re-fit to compile the paper. The process will take approximately 2 hours.
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kubinec_model_SI.Rmd: This file contains an Rmarkdown file with embedded R code showing how to simulate the model. It is the supplementary information for the paper. See the compiled .pdf version as well.
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data: The data folder contains CSVs of tests and cases for US states that were used to fit the models in the paper.
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BibTexDatabase.bib: This file contains the Bibtex bibliography for the paper.