We study the stationary distribution of the (spread-out) $d$-dimensional contact process from the point of view of site percolation. In this process, vertices of $mathbb{Z}^d$ can be healthy (state 0) or infected (state 1). With rate one infected sites recover, and with rate $lambda$ they transmit the infection to some other vertex chosen uniformly within a ball of radius $R$. The classical phase transition result for this process states that there is a critical value $lambda_c(R)$ such that the process has a non-trivial stationary distribution if and only if $lambda > lambda_c(R)$. In configurations sampled from this stationary distribution, we study nearest-neighbor site percolation of the set of infected sites; the associated percolation threshold is denoted $lambda_p(R)$. We prove that $lambda_p(R)$ converges to $1/(1-p_c)$ as $R$ tends to infinity, where $p_c$ is the threshold for Bernoulli site percolation on $mathbb{Z}^d$. As a consequence, we prove that $lambda_p(R) > lambda_c(R)$ for large enough $R$, answering an open question of Liggett and Steif in the spread-out case.
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