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-economic,　and　weather　variables.　The　results　suggested　the　following:　(1)　The　COVID-19　pandemic　has　a　significantly　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　understanding　the　usage　of　metro　systems　in　the　outbreak　and　new-normal　phases　and　provide　transit　operators　with　guidance　to　adjust　services.　©　2022　Elsevier　Ltd