In　this　paper,　we　propose　a　coronavirus　disease　(COVID-19)　epidemiological　model　called　SEIR-FMi　(Susceptible　-Exposed-Infectious-Recovery　with　Flow　and　Medical　investments)　to　study　the　effects　of　intra-city　population　movement,　inter-city　population　movement,　and　medical　resource　investment　on　the　spread　of　the　COVID-19　epidemic.　We　theoretically　derived　the　reproduction　number　of　the　SEIR-FMi　model　by　using　the　next　-generation　matrix　method　and　empirically　simulate　the　individual　impacts　of　population　movement　and　medi-cal　resource　investment　on　epidemic　control.　We　found　that　intra-and　inter-city　population　movements　will　increase　the　risk　of　epidemic　spread,　and　the　effect　of　inter-city　population　movement　on　low-risk　areas　is　higher　than　that　on　high-risk　areas.　Increasing　medical　resource　investment　can　not　only　speed　up　the　recover　rate　of　patients　but　also　reduce　the　growth　rate　of　infected　cases　and　shorten　the　spread　duration　of　the　epidemic.　We　collected　data　on　intra-city　population　movement,　inter-city　population　movement,　medical　resource　investment,　and　confirmed　cases　in　the　cities　of　Wuhan,　Jingzhou,　and　Xiangyang,　Hubei　Province,　China,　from　January　15　to　March　15,　2020.　Using　the　collected　data,　we　validated　that　the　proposed　SEIR-FMi　model　performs　well　in　simulating　the　spread　of　COVID-19　in　the　three　cities.　Meanwhile,　this　study　confirms　that　three　non　-pharmaceutical　interventions,　namely　community　isolation,　population　mobility　control,　and　medical　resource　aid,　applied　during　the　epidemic　period　are　indispensable　in　controlling　the　spread　of　COVID-19　in　the　three　cities.