Models to understand dynamics of test positivity under epidemic dynamics and biased testing
fitode or RTMBodeRelated projects. It’s not super-clear we have any of sufficient interest, but JD is willing to share. We have a mathy publication with an earlier post-doc (Ali Gharouni, nice guy, now at PHO); Mike Li did some stuff during Covid which probably had some ideas but will be hard to figure out; JD advised some South African students who have a public repo, but it’s not clear how far they got.
Notes_Nov10.Rmd: @RichardSichengZhao ‘s summary notes for progresscorrCheck.R: numerical calculations of correlation showing non-monotonicityExpected_Test_positivity_figure.R: beta model’s test positivity as a function of testing focus/dispersion \phi, testing proportion t, prevalence isimple.md: basic notes on multiplex testing and cross-effects of diseases on each others’ positivity/number of positive teststesting_funs.R: basic machinery for computing expected positivity based on the Beta model and Hazard Ratio Modeltesting_distrib.rmd: description and exploration of properties of testing_funs.RLogspace_comparing_methods.R: the file used to generate the pictures for log-space comparing 4 different methods of calculating positivity for Beta model.Qbeta_Issues.R: investigation of the Qbeta & qbeta issues.Single_variable_SIR.R: a numerical simulation of simple version SIR trajectory (fitODE later).inc_testing_positivity-ratio.R: As discussed, this file is used to generate figures for ratio of inc/test_positivity_proportion under different combination of inc, phi and testing_proportion.Average_i-phi_idea.R: @RichardSichengZhao ‘s Unsuccessful experiments. Will try something else but please ignore this for now.HR_Test_positivity_figure: Hazard Ratio model’s test positivity curves as a function of testing Risk offsets \Phi, testing proportion T, prevalence V(TO DO)