Related papers: Characterizing Human Mobility Patterns During COVI…
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…
The COVID-19 pandemic and related restrictions forced many to work, learn, and socialize from home over the internet. There appears to be consensus that internet infrastructure in the developed world handled the resulting traffic surge…
We investigate, through a data-driven contact tracing model, the transmission of COVID-19 inside buses during distinct phases of the pandemic in a large Brazilian city. From this microscopic approach, we recover the networks of close…
We aimed to explore the utility of the recently developed open-source mobile health platform RADAR-base as a toolbox to rapidly test the effect and response to NPIs aimed at limiting the spread of COVID-19. We analysed data extracted from…
Socio-economic constructs and urban topology are crucial drivers of human mobility patterns. During the coronavirus disease 2019 pandemic, these patterns were reshaped in their components: the spatial dimension represented by the daily…
Background: Studies have shown that human mobility is an important factor in dengue epidemiology. Changes in mobility resulting from COVID-19 pandemic set up a real-life situation to test this hypothesis. Our objective was to evaluate the…
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…
Mobile phone data have been widely used to model the spread of COVID-19, however, quantifying and comparing their predictive value across different settings is challenging. Their quality is affected by various factors and their relationship…
Mobile phone data have played a key role in quantifying human mobility during the COVID-19 pandemic. Existing studies on mobility patterns have primarily focused on regional aggregates in high-income countries, obfuscating the accentuated…
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…
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…
The COVID-19 crisis has shown that we can only prevent the risk of mass contagion through timely, large-scale, coordinated, and decisive actions. However, frequently the models used by experts [from whom decision-makers get their main…
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…
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…
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…
Countries and cities around the world have resorted to unprecedented mobility restrictions to combat Covid-19 transmission. Here we exploit a natural experiment whereby Colombian cities implemented varied lockdown policies based on ID…
During early 2020, the SARS-CoV-2 virus rapidly spread worldwide, forcing many governments to impose strict lockdown measures to tackle the pandemic. This significantly changed people's mobility and habits, subsequently impacting how they…
Epidemiological simulations as a method are used to better understand and predict the spreading of infectious diseases, for example of COVID-19. This paper presents an approach that combines person-centric data-driven human mobility…
We are currently living in a state of uncertainty due to the pandemic caused by the Sars-CoV-2 virus. There are several factors involved in the epidemic spreading such as the individual characteristics of each city/country. The true shape…
In response to the coronavirus disease 2019 (COVID-19) pandemic, governments have encouraged and ordered citizens to practice social distancing, particularly by working and studying at home. Intuitively, only a subset of people have the…