The　outbreak　of　coronavirus　disease　2019　(COVID-19)　has　had　severely　disruptive　impacts　on　transportation,　particularly　public　transit.　To　understand　metro　ridership　changes　due　to　the　COVID-19　pandemic,　this　study　conducts　an　in-depth　analysis　of　two　Chinese　megacities　from　January　1,　2020,　to　August　31,　2021.　Generalized　linear　models　are　used　to　explore　the　impact　of　the　COVID-19　pandemic　on　metro　ridership.　The　dependent　variable　is　the　relative　change　in　metro　ridership,　and　the　independent　variables　include　COVID-19,　socio-eco-nomic,　and　weather　variables.　The　results　suggested　the　following:　(1)　The　COVID-19　pandemic　has　a　signifi-cantly　negative　effect　on　the　relative　change　in　metro　ridership,　and　the　number　of　cumulative　confirmed　COVID-19　cases　within　14　days　performs　better　in　regression　models,　which　reflects　the　existence　of　the　time　lag　effect　of　the　COVID-19　pandemic.　(2)　Emergency　responses　are　negatively　associated　with　metro　system　usage　according　to　severity　and　duration.　(3)　The　marginal　effects　of　the　COVID-19　variables　and　emergency　responses　are　larger　on　weekdays　than　on　weekends.　(4)　The　number　of　imported　confirmed　COVID-19　cases　only　significantly　affects　metro　ridership　in　the　weekend　and　new-normal-phase　models　for　Beijing.　In　addition,　the　daily　gross　domestic　product　and　weather　variables　are　significantly　associated　with　metro　ridership.　These　findings　can　aid　in　un-derstanding　the　usage　of　metro　systems　in　the　outbreak　and　new-normal　phases　and　provide　transit　operators　with　guidance　to　adjust　services.