Using smartphone geographical positioning systems (GPS) data for Japan, we show that travel within urban areas frequently occurs along trip chains, involving multiple stops as part of a single journey. Motivated by these empirical findings, we develop a tractable theoretical model of travel itineraries, in which agents choose a set and sequence of locations to visit each day. To overcome the resulting high dimensionality of the choice set, we develop an approach based on importance sampling. We show that trip chains introduce consumption externalities across locations. We show that these consumption externalities are central to explaining the collapse in foot traffic in downtown areas following the shift to remote working during the Covid-19 pandemic.