Last updated: 2020-09-14

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Rmd 4c36b15 Damon Bayer 2020-09-14 History of R0 estimation
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Rmd dbab6de vnminin 2020-09-13 fixed some R0 subscripts, but many are left
html dbab6de vnminin 2020-09-13 fixed some R0 subscripts, but many are left
Rmd 246fc9c vnminin 2020-09-13 fixed cachign issue with prevalence plot and rounded off prevalence a bit
html 246fc9c vnminin 2020-09-13 fixed cachign issue with prevalence plot and rounded off prevalence a bit
Rmd e819db9 Damon Bayer 2020-09-13 Adde prevalence numbers to summary
html e819db9 Damon Bayer 2020-09-13 Adde prevalence numbers to summary
Rmd 3554527 Damon Bayer 2020-09-13 Positivity Fraction -> Positivity Percent
Rmd cd4e651 igoldsteinh 2020-09-13 actually updating jul 28 sept 1
html cd4e651 igoldsteinh 2020-09-13 actually updating jul 28 sept 1
Rmd b5a0ae4 igoldsteinh 2020-09-13 Merge branch ‘master’ of https://github.com/vnminin/uci_covid_modeling
Rmd 2ae9065 igoldsteinh 2020-09-13 jul28 to sep 1 update
html 2ae9065 igoldsteinh 2020-09-13 jul28 to sep 1 update
html 2b665a5 vnminin 2020-09-12 tried to add google analytics unsuccessfully yet
Rmd 0f11928 Damon Bayer 2020-09-09 Positivity Fraction as %
html 0f11928 Damon Bayer 2020-09-09 Positivity Fraction as %
html 5cbf476 vnminin 2020-09-08 got rid of caching warnings in the most recent archived report
html ab9898a Damon Bayer 2020-09-08 jul 24-aug 28 update 2
Rmd e4e122f igoldsteinh 2020-09-08 jul 24 - aug 28 update
html e4e122f igoldsteinh 2020-09-08 jul 24 - aug 28 update
Rmd 8b62aff Damon Bayer 2020-09-08 Fix x-axis spacing in appendix plots
html 8b62aff Damon Bayer 2020-09-08 Fix x-axis spacing in appendix plots
Rmd 7922317 igoldsteinh 2020-09-08 forgot some arxiv links
html 7922317 igoldsteinh 2020-09-08 forgot some arxiv links
Rmd 82a701b vnminin 2020-09-04 added caching to index rmd
html 82a701b vnminin 2020-09-04 added caching to index rmd
Rmd 349da66 vnminin 2020-09-04 merge conflict
html 349da66 vnminin 2020-09-04 merge conflict
Rmd 22fb043 vnminin 2020-09-04 some edits
html 22fb043 vnminin 2020-09-04 some edits
Rmd 416b006 Damon Bayer 2020-09-03 Automatic date labeling and fixed y-axis for cumulative plots
html 416b006 Damon Bayer 2020-09-03 Automatic date labeling and fixed y-axis for cumulative plots
Rmd e7bdeeb igoldsteinh 2020-09-02 new report Jul 18 - Aug 22
html e7bdeeb igoldsteinh 2020-09-02 new report Jul 18 - Aug 22
html 5586873 vnminin 2020-09-01 and now with rebuilding
Rmd b56de81 vnminin 2020-09-01 fixing typos
Rmd dbb4f14 vnminin 2020-09-01 added one more horizontal bar
html dbb4f14 vnminin 2020-09-01 added one more horizontal bar
Rmd 5a2ae54 vnminin 2020-09-01 small edits
html 5a2ae54 vnminin 2020-09-01 small edits
Rmd d3179ba vnminin 2020-08-31 forgot to rebuild
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Rmd 660bde6 vnminin 2020-08-31 resolved conflict
html 660bde6 vnminin 2020-08-31 resolved conflict
Rmd f67a6e2 vnminin 2020-08-31 reformatted report to be ore digestable, hopefully
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Rmd e5e49c0 igoldsteinh 2020-08-31 fixed a typo that was buggin me
html e5e49c0 igoldsteinh 2020-08-31 fixed a typo that was buggin me
Rmd dbf4f20 vnminin 2020-08-31 playing with text
html dbf4f20 vnminin 2020-08-31 playing with text
Rmd 5fd3a50 igoldsteinh 2020-08-31 fixed issue 1, updated report with new pop size calculation
html 5fd3a50 igoldsteinh 2020-08-31 fixed issue 1, updated report with new pop size calculation
Rmd 800b9bc igoldsteinh 2020-08-31 Update index.Rmd
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Rmd 3857e0a vnminin 2020-08-30 started to rearrange figures in situation report
html 3857e0a vnminin 2020-08-30 started to rearrange figures in situation report
Rmd c762f18 igoldsteinh 2020-08-28 added software to about, made vladimir the contact
Rmd 2eb7b73 vnminin 2020-08-27 added some text with effexctive reproductive number
html 2eb7b73 vnminin 2020-08-27 added some text with effexctive reproductive number
Rmd 7c5be6a Damon Bayer 2020-08-27 Add R_eff to executive summary
Rmd 33f234e vnminin 2020-08-27 some formatting
html 33f234e vnminin 2020-08-27 some formatting
html 6698589 igoldsteinh 2020-08-27 change jun 20 - jul25 so that it looks like current report
Rmd 4ca76fb igoldsteinh 2020-08-27 Updating website, also adding latest report Jul 11 - Aug 15
html 4ca76fb igoldsteinh 2020-08-27 Updating website, also adding latest report Jul 11 - Aug 15
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
html 8d52b42 igoldsteinh 2020-08-26 more updates to website
Rmd 79a6fd6 igoldsteinh 2020-08-26 updating about and license, experimenting with figure size
Rmd ddbef62 igoldsteinh 2020-08-26 changing website layout
html ddbef62 igoldsteinh 2020-08-26 changing website layout
Rmd 64adfeb igoldsteinh 2020-08-20 cleaning up helper functions and index
Rmd 8abe830 igoldsteinh 2020-08-06 fixed figure length, updated, tried a readme
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.

Orange County, CA COVID-19 Situation Report, Jul 28 - Sep 01

The goal of this report is to inform interested parties about dynamics of SARS-CoV-2 spread in Orange County, CA and to predict epidemic trajectories. Methodological details are provided below and in the accompanying manuscript.

Version Author Date
246fc9c vnminin 2020-09-13
2ae9065 igoldsteinh 2020-09-13
ab9898a Damon Bayer 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04

Version Author Date
246fc9c vnminin 2020-09-13
e819db9 Damon Bayer 2020-09-13
cd4e651 igoldsteinh 2020-09-13
2ae9065 igoldsteinh 2020-09-13
0f11928 Damon Bayer 2020-09-09
ab9898a Damon Bayer 2020-09-08
e4e122f igoldsteinh 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04

Version Author Date
dbab6de vnminin 2020-09-13
e819db9 Damon Bayer 2020-09-13
2ae9065 igoldsteinh 2020-09-13
ab9898a Damon Bayer 2020-09-08
e4e122f igoldsteinh 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04

Summary (statements are made assuming 95% credibility levels)


Abbreviated technical details (optional)

Our approach is based on fitting a mechanistic model of SARS-CoV-2 spread to multiple sources of surveillance data. More flashed out method description is in the manuscript.

Model inputs

Our method takes three time series as input: daily new tests, case counts, and deaths. However, we find daily resolution to be too noisy due to delay in testing reports, weekend effect, etc. So we aggregated/binned the three types of counts in 3 day intervals. These aggregated time series are shown below.

Version Author Date
e819db9 Damon Bayer 2020-09-13
2ae9065 igoldsteinh 2020-09-13
ab9898a Damon Bayer 2020-09-08
e4e122f igoldsteinh 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04

Model structure

We assume that all individuals in Orange County, CA can be split into 6 compartments: S = susceptible individuals, E = infected, but not yet infectious individuals, \(\text{I}_\text{e}\) = individuals at early stages of infection, \(\text{I}_\text{p}\) = individuals at progressed stages of infection (assumed 20% less infectious than individuals at the early infection stage), R = recovered individuals, D = individuals who died due to COVID-19. Possible progressions of an individual through the above compartments are depicted in the diagram below.

Version Author Date
4ca76fb igoldsteinh 2020-08-27

Mathematically, we assume that dynamics of the proportions of individuals in each compartment follow a set of ordinary differential equations corresponding to the above diagram. These equations are controlled by the following parameters:

  • Basic reproductive number (\(R_0\))
  • mean duration of the latent period
  • mean duration of the early infection period
  • mean duration of the progressed infection period
  • probability of transitioning from progressed infection to death, rather than to recovery (i.e., IFR)

We fit this model to data by assuming that case counts are noisy realizations of the actual number of individuals progressing from \(\text{I}_\text{e}\) compartment to \(\text{I}_\text{p}\) compartment. Similarly we assume that observed deaths are noisy realizations of the actual number of individuals progressing from \(\text{I}_\text{p}\) compartment to \(\text{D}\) compartment. A priori, we assume that death counts are significantly less noisy than case counts. We use a Bayesian estimation framework, which means that all estimated quantities receive credible intervals (e.g., 80% or 95% credible intervals). Width of these credible intervals encode the amount of uncertainty that we have in the estimated quantities.


Appendix

Sensitivity to Prior for \(R_0\)

We examine how sensitive our conclusions about \(R_0\) are to our prior assumptions by repeating estimation of all model parameters under different priors for this parameter. The priors are listed in the titles of the figures. Although the prior distribution of \(R_0\) does have some effect on its posterior (as it should), the our results and conclusions are not too sensitive to a particular specification of this prior.

Version Author Date
e819db9 Damon Bayer 2020-09-13
2ae9065 igoldsteinh 2020-09-13
ab9898a Damon Bayer 2020-09-08
e4e122f igoldsteinh 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04

Version Author Date
dbab6de vnminin 2020-09-13
e819db9 Damon Bayer 2020-09-13
2ae9065 igoldsteinh 2020-09-13
ab9898a Damon Bayer 2020-09-08
e4e122f igoldsteinh 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04
349da66 vnminin 2020-09-04
22fb043 vnminin 2020-09-04
416b006 Damon Bayer 2020-09-03
e7bdeeb igoldsteinh 2020-09-02
f67a6e2 vnminin 2020-08-31
5fd3a50 igoldsteinh 2020-08-31
3857e0a vnminin 2020-08-30
33f234e vnminin 2020-08-27
4ca76fb igoldsteinh 2020-08-27
8abe830 igoldsteinh 2020-08-06
99d68f7 igoldsteinh 2020-07-29

Version Author Date
e819db9 Damon Bayer 2020-09-13
2ae9065 igoldsteinh 2020-09-13
ab9898a Damon Bayer 2020-09-08
e4e122f igoldsteinh 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04
349da66 vnminin 2020-09-04
22fb043 vnminin 2020-09-04
416b006 Damon Bayer 2020-09-03
e7bdeeb igoldsteinh 2020-09-02
f67a6e2 vnminin 2020-08-31
5fd3a50 igoldsteinh 2020-08-31
3857e0a vnminin 2020-08-30
33f234e vnminin 2020-08-27
4ca76fb igoldsteinh 2020-08-27
a07b913 igoldsteinh 2020-08-26

Version Author Date
dbab6de vnminin 2020-09-13
e819db9 Damon Bayer 2020-09-13
2ae9065 igoldsteinh 2020-09-13
ab9898a Damon Bayer 2020-09-08
e4e122f igoldsteinh 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04
349da66 vnminin 2020-09-04
a07b913 igoldsteinh 2020-08-26
8abe830 igoldsteinh 2020-08-06
99d68f7 igoldsteinh 2020-07-29

Sensitivity to prior for fraction initially infected

We examine how sensitive our conclusions about \(R_0\) are to our prior assumptions by repeating estimation of all model parameters under different priors for the parameter controlling how many people are infected initially. This prior changes depending on the time period, so we adjust by changing the prior mean to be twice as large or one half as large as the default prior.

Version Author Date
e819db9 Damon Bayer 2020-09-13
2ae9065 igoldsteinh 2020-09-13
ab9898a Damon Bayer 2020-09-08
e4e122f igoldsteinh 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04
349da66 vnminin 2020-09-04
22fb043 vnminin 2020-09-04
416b006 Damon Bayer 2020-09-03
e7bdeeb igoldsteinh 2020-09-02
f67a6e2 vnminin 2020-08-31
5fd3a50 igoldsteinh 2020-08-31
33f234e vnminin 2020-08-27
4ca76fb igoldsteinh 2020-08-27
8abe830 igoldsteinh 2020-08-06
99d68f7 igoldsteinh 2020-07-29

Version Author Date
dbab6de vnminin 2020-09-13
e819db9 Damon Bayer 2020-09-13
2ae9065 igoldsteinh 2020-09-13
ab9898a Damon Bayer 2020-09-08
e4e122f igoldsteinh 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04
349da66 vnminin 2020-09-04
22fb043 vnminin 2020-09-04
416b006 Damon Bayer 2020-09-03
e7bdeeb igoldsteinh 2020-09-02
f67a6e2 vnminin 2020-08-31
5fd3a50 igoldsteinh 2020-08-31
33f234e vnminin 2020-08-27
4ca76fb igoldsteinh 2020-08-27
a07b913 igoldsteinh 2020-08-26

Version Author Date
e819db9 Damon Bayer 2020-09-13
2ae9065 igoldsteinh 2020-09-13
ab9898a Damon Bayer 2020-09-08
e4e122f igoldsteinh 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04
349da66 vnminin 2020-09-04
22fb043 vnminin 2020-09-04
416b006 Damon Bayer 2020-09-03
e7bdeeb igoldsteinh 2020-09-02
f67a6e2 vnminin 2020-08-31
5fd3a50 igoldsteinh 2020-08-31
33f234e vnminin 2020-08-27
4ca76fb igoldsteinh 2020-08-27
a07b913 igoldsteinh 2020-08-26
8abe830 igoldsteinh 2020-08-06
99d68f7 igoldsteinh 2020-07-29

Version Author Date
dbab6de vnminin 2020-09-13
e819db9 Damon Bayer 2020-09-13
2ae9065 igoldsteinh 2020-09-13
ab9898a Damon Bayer 2020-09-08
e4e122f igoldsteinh 2020-09-08
8b62aff Damon Bayer 2020-09-08
7922317 igoldsteinh 2020-09-08
f21abf7 vnminin 2020-09-04
349da66 vnminin 2020-09-04
22fb043 vnminin 2020-09-04
416b006 Damon Bayer 2020-09-03
e7bdeeb igoldsteinh 2020-09-02
f67a6e2 vnminin 2020-08-31
5fd3a50 igoldsteinh 2020-08-31
33f234e vnminin 2020-08-27
6698589 igoldsteinh 2020-08-27
4ca76fb igoldsteinh 2020-08-27
a07b913 igoldsteinh 2020-08-26
8abe830 igoldsteinh 2020-08-06
99d68f7 igoldsteinh 2020-07-29

Last updated on 2020-09-14.


R version 4.0.0 (2020-04-24)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.4

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] glue_1.4.1      patchwork_1.0.1 scales_1.1.1    tidybayes_2.1.1
 [5] forcats_0.5.0   stringr_1.4.0   dplyr_1.0.0     purrr_0.3.4    
 [9] readr_1.3.1     tidyr_1.1.0     tibble_3.0.3    ggplot2_3.3.2  
[13] tidyverse_1.3.0 fs_1.4.2        here_0.1        lubridate_1.7.9
[17] workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] matrixStats_0.56.0   RColorBrewer_1.1-2   httr_1.4.1          
 [4] rprojroot_1.3-2      rstan_2.21.1         tools_4.0.0         
 [7] backports_1.1.8      utf8_1.1.4           R6_2.4.1            
[10] DBI_1.1.0            colorspace_1.4-1     ggdist_2.1.1        
[13] withr_2.2.0          tidyselect_1.1.0     gridExtra_2.3       
[16] prettyunits_1.1.1    processx_3.4.3       curl_4.3            
[19] compiler_4.0.0       git2r_0.27.1         cli_2.0.2           
[22] rvest_0.3.5          arrayhelpers_1.1-0   xml2_1.3.2          
[25] labeling_0.3         callr_3.4.3          digest_0.6.25       
[28] StanHeaders_2.21.0-5 rmarkdown_2.3        pkgconfig_2.0.3     
[31] htmltools_0.5.0      dbplyr_1.4.4         rlang_0.4.7         
[34] readxl_1.3.1         rstudioapi_0.11      farver_2.0.3        
[37] generics_0.0.2       svUnit_1.0.3         jsonlite_1.7.0      
[40] inline_0.3.15        magrittr_1.5         loo_2.3.0           
[43] Rcpp_1.0.5           munsell_0.5.0        fansi_0.4.1         
[46] lifecycle_0.2.0      stringi_1.4.6        whisker_0.4         
[49] yaml_2.2.1           pkgbuild_1.0.8       plyr_1.8.6          
[52] grid_4.0.0           blob_1.2.1           parallel_4.0.0      
[55] promises_1.1.1       crayon_1.3.4         lattice_0.20-41     
[58] haven_2.3.1          hms_0.5.3            knitr_1.29          
[61] ps_1.3.3             pillar_1.4.6         codetools_0.2-16    
[64] stats4_4.0.0         reprex_0.3.0         evaluate_0.14       
[67] V8_3.2.0             RcppParallel_5.0.2   modelr_0.1.8        
[70] vctrs_0.3.1          httpuv_1.5.4         cellranger_1.1.0    
[73] gtable_0.3.0         assertthat_0.2.1     xfun_0.15           
[76] broom_0.7.0          coda_0.19-3          later_1.1.0.1       
[79] ellipsis_0.3.1