Rとstanでベイズ統計ができるなら、以下のコードで実行可能。
パッケージ rstan　と　BEST(信頼区間グラフ描出用)が必要


library("BEST")
library("rstan")
rstan_options(auto_write = TRUE)
options(mc.cores = parallel::detectCores())
options(scipen = 5)

model.string='
data{
int n; // sample size
int x; // number of positive test
real<lower=0,upper=1> sen; // sensitivity 0.7
real<lower=0,upper=1> spc; // specificity 0.9
real<lower=0,upper=1> ul; // uniform(0,ul)
}

parameters{
real<lower=0,upper=1> prev; // prevalence
}

transformed parameters{
real<lower=0,upper=1> p;
p = prev*sen + (1-prev)*(1-spc) ; // probability of positive test result
}

model{
x ~ binomial(n,p);
prev ~ uniform(0,ul);
}

'
writeLines( model.string , con='model.stan' )
corona1.model=stan_model('model.stan')
# saveRDS(corona1.model,file='corona1.rds')
# corona1.model=readRDS('corona1.rds')

PCRs <- function(N=1000,X=10,UL=1,SEN=0.7,SPC=0.9,verbose=FALSE,...){
data = list(n=N,x=X,sen=SEN,spc=SPC,ul=UL)
fit.corona = sampling(corona1.model, data=data,
seed=1234,control=list(adapt_delta=0.99),...)
if(verbose) print(fit.corona, prob=c(0.025,0.5,0.975),pars=c('prev'),digits=8)
ms=rstan::extract(fit.corona)
BEST::plotPost(ms$prev,showMode = T,xlab='prevalence') ; lines(density(ms$prev),col='skyblue')
c(mean=mean(ms$prev),HDInterval::hdi(ms$prev)[1:2])
}