Large deviations, asymptotic bounds on the number of positive individuals in a Bernoulli sample via the number of positive pool samples drawn on the bernoulli sample

In this paper we define for a Bernoulli samples the \emph{ empirical infection measure}, which counts the number of positives (infections) in the Bernoulli sample and for the \emph{ pool samples} we define the empirical pool infection measure, which counts the number of positive (infected) pool samples. For this empirical measures we prove a joint large deviation principle for Bernoulli samples. We also found an asymptotic relationship between the \emph{ proportion of infected individuals } with respect to the samples size, $n$ and the \emph{ proportion of infected pool samples} with respect to the number of pool samples, $k(n)\mathrm{.}$ All rate functions are expressed in terms of relative entropies.