Human mobility plays a key role in the dissemination of infectious diseases around the world. However, the complexity introduced by commuting patterns in the daily life of cities makes such a role unclear, especially at the intracity scale. Here, we propose a multiplex network fed with 9 months of mobility data with more than 107 million public bus validations in order to understand the relation between urban mobility and the spreading of COVID-19 within a large city, namely, Fortaleza in the northeast of Brazil. Our results suggest that the shortest bus rides in Fortaleza, measured in the number of daily rides among all neighborhoods, decreased $$\approx 25$$ ≈ 25 % more than the longest ones after an epidemic wave. Such a result is the opposite of what has been observed at the intercity scale. We also find that mobility changes among the neighborhoods are synchronous and geographically homogeneous. Furthermore, we find that the most central neighborhoods in mobility are the first targets for infectious disease outbreaks, which is quantified here in terms of the positive linear relation between the disease arrival time and the average of the closeness centrality ranking. These central neighborhoods are also the top neighborhoods in the number of reported cases at the end of an epidemic wave as indicated by the exponential decay behavior of the disease arrival time in relation to the number of accumulated reported cases with decay constant $$\lambda \approx 33$$ λ ≈ 33 days. We believe that these results can help in the development of new strategies to impose restriction measures in the cities guiding decision-makers with smart actions in public health policies, as well as supporting future research on urban mobility and epidemiology.
A criação do Bitcoin vem impactando o mercado digital global devido à sua tecnologia descentralizada e segura. Neste mesmo sentido, o meio digital incentiva o surgimento de influenciadores digitais de criptomoedas. Haveria alguma forma de identificar estes influenciadores digitais de criptomoedas, levando-se em consideração o grande número de usuários de mídias e redes sociais online? Neste artigo, descrevemos um método para realizar a coleta e o tratamento de textos de uma rede social online com o objetivo de identificar estes influenciadores, visando descobrir influenciadores digitais da criptomoeda Bitcoin.
Human mobility plays a key role in the dissemination of infectious diseases around the world. However, the complexity introduced by commuting patterns in the daily life of cities makes such a role unclear, especially at the intracity scale. Here, we propose a multiplex network fed with 9 months of mobility data with more than 107 million public bus validations in order to understand the relation between urban mobility and the spreading of COVID-19 within a large city, namely, Fortaleza in the northeast of Brazil. Our results suggest that the shortest bus rides in Fortaleza changed ≈ 25% more than the longest ones after an epidemic wave. Such a result is the opposite of what has been observed at the intercity scale. We also find that mobility changes among the neighborhoods are synchronous and geographically homogeneous. Furthermore, we find that the most central neighborhoods in mobility are the primary targets for infectious disease outbreaks, which is quantified here in terms of the linear relation between the disease arrival time and the average of the closeness centrality ranking. These central neighborhoods are also the top neighborhoods in the number of reported cases at the end of an epidemic wave as indicated by the exponential decay behavior of the disease arrival time in relation to the number of accumulated reported cases with decay constant λ ≈ 33 days. We believe that these results can help in the development of new strategies to impose restriction measures in the cities guiding decision-makers with smart actions in public health policies, as well as supporting future research on urban mobility and epidemiology.
Diffusive properties of colloidal crystals in a quasi-one-dimensional channel are studied using numerical simulations. In order to study the influence of the attractive interaction between particles, it was introduced as an artificial dimensionless parameter β in the attractive term of the interaction potential. Changing the value of β, we can tune the effect of attraction between particles. We show that charged particles can change their mobility and the diffusion exponent of a one-chain like system. Variation on exponent diffusion can be induced by tuning the attractive part of interaction potential, making possible the existence of diffusive regimes between single-file diffusion (SFD) and normal diffusion, without changing confinement strength. System stoichiometry was changed, imposing particles in different arrangements in small clusters, which varies the diffusive behaviour. If stoichiometry is different from 1:1, it is possible to have particles with equal charges but with different mobilities. Another important observation is that mean-square displacement (MSD) for different charges is different for different values.
The Covid-19 outbreak changed the dynamic in cities around the world. To avoid the collapse in the healthcare system, several cities restricted or forbid people’s mobility to diminish the Covid-19 contagion. Meanwhile, a number of researchers developed online initiatives such as websites, apps and chatbots, to inform and guide people about the Covid-19 and its effects. In this paper, we combine data gathered from a dialogue chatbot that indicates healthcare facilities to individuals, with Covid-19 daily reports on new cases and mortality and demographic and socioeconomic factors to carry out analysis on geography and Covid-19 healthcare facilities in a major metropolitan city in Brazil. Results show that less wealthier areas are more populous, report high Covid-19 contagion level and request healthcare facilities locations more often. These findings shed light on Covid-19 healthcare facilities mobility patterns, which is influenced by area features and can be used to design and plan more equitable and accessible cities.
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