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The availability of cellphone geolocation data provides a remarkable opportunity to study human mobility patterns and how these patterns are affected by the recent pandemic. Two simple centrality metrics allow us to measure two different…
Mexico City, the largest city in Mexico, is also one of the largest cities in the world. It has over 9 million inhabitants and concentrates the vast majority of government and business centers. In this work we describe algorithms that use…
During outbreaks of emerging infectious diseases, internationally connected cities often experience large and early outbreaks, while rural regions follow after some delay. This hierarchical structure of disease spread is influenced…
Mexico, like the rest of the world, is currently facing the The COVID-19 pandemic. Given the size of its territory, the efforts to contain the disease have involved both national and regional measures. For this work, the curves of daily new…
The COVID-19 pandemic has impacted the national systems of population movement around the world. Existing work has focused on countries of the Global North and restricted to the immediate effects of COVID-19 data during 2020. Data have…
It is often necessary to introduce the main characteristics of population mobility dynamics to model critical social phenomena such as the economy, violence, transmission of information, or infectious diseases. In this work, we focus on…
Urban mobility is central to economic activity, social inclusion, and access to essential services. COVID-19 caused disruptions to mobility globally, yet its long-term impacts in less developed countries remain poorly understood. Using over…
Commuting patterns are a central component of urban dynamics and many societal activities. Exogenous shocks, such as a pandemic, might drastically modify them inducing heterogeneous variations across socioeconomic strata. Here, we quantify…
Understanding human mobility during disastrous events is crucial for emergency planning and disaster management. We develop a methodology to construct time-varying, multilayer networks where edges encode observed movements between spatial…
Human mobility is crucial to understand the transmission pattern of COVID-19 on spatially embedded geographic networks. This pattern seems unpredictable, and the propagation appears unstoppable, resulting in over 350,000 death tolls in the…
The use of mobile phone call detail records and device location data for the calling patterns, movements, and social contacts of individuals, has proven to be valuable for devising models and understanding of their mobility and behaviour…
The COVID-19 pandemic brought unprecedented levels of disruption to the local and regional transportation networks throughout the United States, especially the Motor City: Detroit. That was mainly a result of swift restrictive measures such…
Short-horizon epidemic forecasts guide near-term staffing, testing, and messaging. Mobility data are now routinely used to improve such forecasts, yet work diverges on whether the volume of mobility or the structure of mobility networks…
Without a vaccine, the fight against the spreading of the coronavirus has focused on maintaining physical distance. To study the impact of such measures on inter-municipality traffic, we analyze a mobile dataset with the daily flow of…
We examine how violence affects migration flows and, crucially, how it reshapes the strength of migration networks -- measured by the intensity of migration between areas, accounting for the fact that some routes become more prominent or…
During the 2020 pandemic caused by the COVID-19 virus, many countries implemented stay-at-home measures, which led to many businesses and schools moving from in-person to online mode of operation. We analyze sampled Netflow records at a…
The worldwide outbreak of COVID-19 has posed a dire threat to the public. Human mobility has changed in various ways over the course of the pandemic. Despite current studies on common mobility metrics, research specifically on…
The urban spatial structure represents the distribution of public and private spaces in cities and how people move within them. While it usually evolves slowly, it can change fast during large-scale emergency events, as well as due to urban…
COVID-19 has deeply affected daily life and travel behaviors. Understanding these changes is crucial, prompting an investigation into socio-demographic and socio-economic factors. This study used large-scale mobile device location data in…
The COVID19 pandemic highlighted the importance of non-traditional data sources, such as mobile phone data, to inform effective public health interventions and monitor adherence to such measures. Previous studies showed how socioeconomic…