In　spite　of　the　extensive　previous　efforts　on　traffic　dynamics　and　epidemic　spreading　in　complex　networks,　the　problem　of　traffic-driven　epidemic　spreading　on　correlated　networks　has　not　been　addressed.　Interestingly,　we　find　that　the　epidemic　threshold,　a　fundamental　quantity　underlying　the　spreading　dynamics,　exhibits　a　nonmonotonic　behavior　in　that　it　can　be　minimized　for　some　critical　value　of　the　assortativity　coefficient,　a　parameter　characterizing　the　network　correlation.　To　understand　this　phenomenon,　we　use　the　degree-based　mean-field　theory　to　calculate　the　traffic-driven　epidemic　threshold　for　correlated　networks.　The　theory　predicts　that　the　threshold　is　inversely　proportional　to　the　packet-generation　rate　and　the　largest　eigenvalue　of　the　betweenness　matrix.　We　obtain　consistency　between　theory　and　numerics.　Our　results　may　provide　insights　into　the　important　problem　of　controlling　and/or　harnessing　real-world　epidemic　spreading　dynamics　driven　by　traffic　flows.