1
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Betancourt F, Riascos AP, Mateos JL. Temporal visitation patterns of points of interest in cities on a planetary scale: a network science and machine learning approach. Sci Rep 2023; 13:4890. [PMID: 36966183 PMCID: PMC10039356 DOI: 10.1038/s41598-023-32074-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 03/22/2023] [Indexed: 03/27/2023] Open
Abstract
We aim to study the temporal patterns of activity in points of interest of cities around the world. In order to do so, we use the data provided by the online location-based social network Foursquare, where users make check-ins that indicate points of interest in the city. The data set comprises more than 90 million check-ins in 632 cities of 87 countries in 5 continents. We analyzed more than 11 million points of interest including all sorts of places: airports, restaurants, parks, hospitals, and many others. With this information, we obtained spatial and temporal patterns of activities for each city. We quantify similarities and differences of these patterns for all the cities involved and construct a network connecting pairs of cities. The links of this network indicate the similarity of temporal visitation patterns of points of interest between cities and is quantified with the Kullback-Leibler divergence between two distributions. Then, we obtained the community structure of this network and the geographic distribution of these communities worldwide. For comparison, we also use a Machine Learning algorithm-unsupervised agglomerative clustering-to obtain clusters or communities of cities with similar patterns. The main result is that both approaches give the same classification of five communities belonging to five different continents worldwide. This suggests that temporal patterns of activity can be universal, with some geographical, historical, and cultural variations, on a planetary scale.
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Affiliation(s)
- Francisco Betancourt
- Instituto de Física, Universidad Nacional Autónoma de México, Ciudad Universitaria, 04510, Mexico City, Mexico.
| | - Alejandro P Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Ciudad Universitaria, 04510, Mexico City, Mexico
| | - José L Mateos
- Instituto de Física, Universidad Nacional Autónoma de México, Ciudad Universitaria, 04510, Mexico City, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, 04510, Mexico City, Mexico
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2
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Chen H, Ye Y. Random walks on complex networks under time-dependent stochastic resetting. Phys Rev E 2022; 106:044139. [PMID: 36397577 DOI: 10.1103/physreve.106.044139] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 10/05/2022] [Indexed: 06/16/2023]
Abstract
We study discrete-time random walks on networks subject to a time-dependent stochastic resetting, where the walker either hops randomly between neighboring nodes with a probability 1-ϕ(a) or is reset to a given node with a complementary probability ϕ(a). The resetting probability ϕ(a) depends on the time a since the last reset event (also called a, the age of the walker). Using the renewal approach and spectral decomposition of the transition matrix, we formulate the stationary occupation probability of the walker at each node and the mean first passage time between two arbitrary nodes. Concretely, we consider two different time-dependent resetting protocols that are both exactly solvable. One is that ϕ(a) is a step-shaped function of a and the other one is that ϕ(a) is a rational function of a. We demonstrate the theoretical results on several different networks, also validated by numerical simulations, and find that the time-modulated resetting protocols can be more advantageous than the constant-probability resetting in accelerating the completion of a target search process.
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Affiliation(s)
- Hanshuang Chen
- School of Physics and Optoelectronic Engineering, Anhui University, Hefei 230601, China
| | - Yanfei Ye
- School of Physics and Optoelectronic Engineering, Anhui University, Hefei 230601, China
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3
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Hidalgo Calva CS, Riascos AP. Optimal exploration of random walks with local bias on networks. Phys Rev E 2022; 105:044318. [PMID: 35590568 DOI: 10.1103/physreve.105.044318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 03/23/2022] [Indexed: 06/15/2023]
Abstract
We propose local-biased random walks on general networks where a Markovian walker is defined by different types of biases in each node to establish transitions to its neighbors depending on their degrees. For this ergodic dynamics, we explore the capacity of the random walker to visit all the nodes characterized by a global mean first passage time. This quantity is calculated using eigenvalues and eigenvectors of the transition matrix that defines the dynamics. In the first part, we illustrate how our framework leads to optimal exploration for small-size graphs through the analysis of all the possible bias configurations. In the second part, we study the most favorable configurations in each node by using simulated annealing. This heuristic algorithm allows obtaining approximate solutions of the optimal bias in different types of networks. The results show how the local bias can optimize the exploration of the network in comparison with the unbiased random walk. The methods implemented in this research are general and open the doors to a broad spectrum of tools applicable to different random walk strategies and dynamical processes on networks.
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Affiliation(s)
| | - Alejandro P Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, Mexico City 01000, Mexico
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4
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Bestehorn M, Michelitsch TM, Collet BA, Riascos AP, Nowakowski AF. Simple model of epidemic dynamics with memory effects. Phys Rev E 2022; 105:024205. [PMID: 35291108 DOI: 10.1103/physreve.105.024205] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 02/08/2022] [Indexed: 06/14/2023]
Abstract
We introduce a compartment model with memory for the dynamics of epidemic spreading in a constant population of individuals. Each individual is in one of the states S=susceptible, I=infected, or R=recovered (SIR model). In state R an individual is assumed to stay immune within a finite-time interval. In the first part, we introduce a random lifetime or duration of immunity which is drawn from a certain probability density function. Once the time of immunity is elapsed an individual makes an instantaneous transition to the susceptible state. By introducing a random duration of immunity a memory effect is introduced into the process which crucially determines the epidemic dynamics. In the second part, we investigate the influence of the memory effect on the space-time dynamics of the epidemic spreading by implementing this approach into computer simulations and employ a multiple random walker's model. If a susceptible walker meets an infectious one on the same site, then the susceptible one gets infected with a certain probability. The computer experiments allow us to identify relevant parameters for spread or extinction of an epidemic. In both parts, the finite duration of immunity causes persistent oscillations in the number of infected individuals with ongoing epidemic activity preventing the system from relaxation to a steady state solution. Such oscillatory behavior is supported by real-life observations and not captured by the classical standard SIR model.
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Affiliation(s)
- Michael Bestehorn
- Brandenburgische Technische Universität Cottbus-Senftenberg, Institut für Physik, Erich-Weinert-Straße 1, 03046 Cottbus, Germany
| | - Thomas M Michelitsch
- Sorbonne Université, Institut Jean le Rond d'Alembert, CNRS UMR 7190, 4 place Jussieu, 75252 Paris cedex 05, France
| | - Bernard A Collet
- Sorbonne Université, Institut Jean le Rond d'Alembert, CNRS UMR 7190, 4 place Jussieu, 75252 Paris cedex 05, France
| | - Alejandro P Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, 01000 Ciudad de México, México
| | - Andrzej F Nowakowski
- Department of Mechanical Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, United Kingdom
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5
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Martínez-González JU, Riascos AP. Activity of vehicles in the bus rapid transit system Metrobús in Mexico City. Sci Rep 2022; 12:98. [PMID: 34997045 PMCID: PMC8742109 DOI: 10.1038/s41598-021-04037-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 12/10/2021] [Indexed: 12/27/2022] Open
Abstract
In this paper, we analyze a massive dataset with registers of the movement of vehicles in the bus rapid transit system Metrobús in Mexico City from February 2020 to April 2021. With these records and a division of the system into 214 geographical regions (segments), we characterize the vehicles' activity through the statistical analysis of speeds in each zone. We use the Kullback-Leibler distance to compare the movement of vehicles in each segment and its evolution. The results for the dynamics in different zones are represented as a network where nodes define segments of the system Metrobús and edges describe similarity in the activity of vehicles. Community detection algorithms in this network allow the identification of patterns considering different levels of similarity in the distribution of speeds providing a framework for unsupervised classification of the movement of vehicles. The methods developed in this research are general and can be implemented to describe the activity of different transportation systems with detailed records of the movement of users or vehicles.
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Affiliation(s)
- Jaspe U Martínez-González
- Instituto de Física, Universidad Nacional Autónoma de México, Ciudad Universitaria, 04510, Mexico City, Mexico
| | - Alejandro P Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Ciudad Universitaria, 04510, Mexico City, Mexico.
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6
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Leng Y, Santistevan D, Pentland A. Understanding collective regularity in human mobility as a familiar stranger phenomenon. Sci Rep 2021; 11:19444. [PMID: 34593831 PMCID: PMC8484593 DOI: 10.1038/s41598-021-98475-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 08/30/2021] [Indexed: 11/16/2022] Open
Abstract
Beyond the physical structures that contain daily routines, urban city dwellers repeatedly encounter strangers that similarly shape their environments. Familiar strangers are neither formal acquaintances nor completely anonymous faces in daily urban life. Due to data limitations, there is a lack of research focused on uncovering the structure of the “Familiar Stranger” phenomenon at a large scale while simultaneously investigating the social relationships between such strangers. Using countrywide mobile phone records from Andorra, we empirically show the existence of such a phenomenon as well as details concerning these strangers’ relative social relations. To understand the social and spatial components of familiar strangers more deeply, we study the temporal regularity and spatial structure of collective urban mobility to shed light on the mechanisms that guide these interactions. Furthermore, we explore the relationship between social distances and the number of encounters to show that more significant physical encounters correspond to a shorter social distance. Understanding these social and physical networks has essential implications for epidemics spreading, urban planning, and information diffusion.
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Affiliation(s)
- Yan Leng
- McCombs School of Business, The University of Texas at Austin, Austin, 78712, USA.
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7
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Wang S, Chen H, Huang F. Random walks on complex networks with multiple resetting nodes: A renewal approach. CHAOS (WOODBURY, N.Y.) 2021; 31:093135. [PMID: 34598469 DOI: 10.1063/5.0064791] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 09/02/2021] [Indexed: 06/13/2023]
Abstract
Due to wide applications in diverse fields, random walks subject to stochastic resetting have attracted considerable attention in the last decade. In this paper, we study discrete-time random walks on complex networks with multiple resetting nodes. Using a renewal approach, we derive exact expressions of the occupation probability of the walker in each node and mean first-passage time between arbitrary two nodes. All the results can be expressed in terms of the spectral properties of the transition matrix in the absence of resetting. We demonstrate our results on circular networks, stochastic block models, and Barabási-Albert scale-free networks and find the advantage of the resetting processes to multiple resetting nodes in a global search on such networks. Finally, the distribution of resetting probabilities is optimized via a simulated annealing algorithm, so as to minimize the mean first-passage time averaged over arbitrary two distinct nodes.
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Affiliation(s)
- Shuang Wang
- School of Physics Optoelectronics Engineering, Anhui University, Hefei 230601, China
| | - Hanshuang Chen
- School of Physics Optoelectronics Engineering, Anhui University, Hefei 230601, China
| | - Feng Huang
- Key Laboratory of Advanced Electronic Materials and Devices & School of Mathematics and Physics, Anhui Jianzhu University, Hefei 230601, China
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8
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Huang F, Chen H. Random walks on complex networks with first-passage resetting. Phys Rev E 2021; 103:062132. [PMID: 34271762 DOI: 10.1103/physreve.103.062132] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 06/01/2021] [Indexed: 11/07/2022]
Abstract
We study discrete-time random walks on arbitrary networks with first-passage resetting processes. To the end, a set of nodes are chosen as observable nodes, and the walker is reset instantaneously to a given resetting node whenever it hits either of observable nodes. We derive exact expressions of the stationary occupation probability, the average number of resets in the long time, and the mean first-passage time between arbitrary two nonobservable nodes. We show that all the quantities can be expressed in terms of the fundamental matrix Z=(I-Q)^{-1}, where I is the identity matrix and Q is the transition matrix between nonobservable nodes. Finally, we use ring networks, two-dimensional square lattices, barbell networks, and Cayley trees to demonstrate the advantage of first-passage resetting in global search on such networks.
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Affiliation(s)
- Feng Huang
- Key Laboratory of Advanced Electronic Materials and Devices & School of Mathematics and Physics, Anhui Jianzhu University, Hefei, 230601, China.,Key Laboratory of Architectural Acoustic Environment of Anhui Higher Education Institutes, Hefei, 230601, China
| | - Hanshuang Chen
- Department of Physics, Anhui University, Hefei, 230601, China
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9
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González FH, Riascos AP, Boyer D. Diffusive transport on networks with stochastic resetting to multiple nodes. Phys Rev E 2021; 103:062126. [PMID: 34271672 DOI: 10.1103/physreve.103.062126] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 05/27/2021] [Indexed: 01/30/2023]
Abstract
We study the diffusive transport of Markovian random walks on arbitrary networks with stochastic resetting to multiple nodes. We deduce analytical expressions for the stationary occupation probability and for the mean and global first passage times. This general approach allows us to characterize the effect of resetting on the capacity of random walk strategies to reach a particular target or to explore the network. Our formalism holds for ergodic random walks and can be implemented from the spectral properties of the random walk without resetting, providing a tool to analyze the efficiency of search strategies with resetting to multiple nodes. We apply the methods developed here to the dynamics with two reset nodes and derive analytical results for normal random walks and Lévy flights on rings. We also explore the effect of resetting to multiple nodes on a comb graph, Lévy flights that visit specific locations in a continuous space, and the Google random walk strategy on regular networks.
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Affiliation(s)
- Fernanda H González
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, 01000 Ciudad de México, México
| | - Alejandro P Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, 01000 Ciudad de México, México
| | - Denis Boyer
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, 01000 Ciudad de México, México
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10
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Riascos AP, Sanders DP. Mean encounter times for multiple random walkers on networks. Phys Rev E 2021; 103:042312. [PMID: 34005853 DOI: 10.1103/physreve.103.042312] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 03/23/2021] [Indexed: 01/18/2023]
Abstract
We introduce a general approach for the study of the collective dynamics of noninteracting random walkers on connected networks. We analyze the movement of R independent (Markovian) walkers, each defined by its own transition matrix. By using the eigenvalues and eigenvectors of the R independent transition matrices, we deduce analytical expressions for the collective stationary distribution and the average number of steps needed by the random walkers to start in a particular configuration and reach specific nodes the first time (mean first-passage times), as well as global times that characterize the global activity. We apply these results to the study of mean first-encounter times for local and nonlocal random walk strategies on different types of networks, with both synchronous and asynchronous motion.
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Affiliation(s)
- Alejandro P Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Ciudad Universitaria, Ciudad de México 04510, Mexico
| | - David P Sanders
- Departamento de Física, Facultad de Ciencias, Universidad Nacional Autónoma de México, Ciudad Universitaria, Ciudad de México 04510, Mexico and Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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11
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Pérez-Méndez D, Gershenson C, Lárraga ME, Mateos JL. Modeling adaptive reversible lanes: A cellular automata approach. PLoS One 2021; 16:e0244326. [PMID: 33395415 PMCID: PMC7781372 DOI: 10.1371/journal.pone.0244326] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 12/07/2020] [Indexed: 12/05/2022] Open
Abstract
Dealing with traffic congestion is one of the most pressing challenges for cities. Transport authorities have implemented several strategies to reduce traffic jams with varying degrees of success. The use of reversible lanes is a common approach to improve traffic congestion during rush hours. A reversible lane can change its direction during a time interval to the more congested direction. This strategy can improve traffic congestion in specific scenarios. Most reversible lanes in urban roads are fixed in time and number; however, traffic patterns in cities are highly variable and unpredictable due to this phenomenon’s complex nature. Therefore, reversible lanes may not improve traffic flow under certain circumstances; moreover, they could worsen it because of traffic fluctuations. In this paper, we use cellular automata to model adaptive reversible lanes(aka dynamic reversible lanes). Adaptive reversible lanes can change their direction using real-time information to respond to traffic demand fluctuations. Using real traffic data, our model shows that adaptive reversible lanes can improve traffic flow up to 40% compared to conventional reversible lanes. Our results show that there are significant fluctuations in traffic flow even during rush hours, and thus cities would benefit from implementing adaptive reversible lanes.
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Affiliation(s)
- Dante Pérez-Méndez
- Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Ciudad de México, México
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, México
- * E-mail:
| | - Carlos Gershenson
- Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Ciudad de México, México
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, México
- Lakeside Labs GmbH, Klagenfurt am, Wörthersee, Austria
| | - María Elena Lárraga
- Instituto de Ingeniería, Universidad Nacional Autónoma de México, Ciudad de México, México
| | - José L. Mateos
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, México
- Instituto de Física, Universidad Nacional Autónoma de México, Ciudad de México, México
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12
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Bestehorn M, Riascos AP, Michelitsch TM, Collet BA. A Markovian random walk model of epidemic spreading. CONTINUUM MECHANICS AND THERMODYNAMICS 2021; 33:1207-1221. [PMID: 34776647 PMCID: PMC7811397 DOI: 10.1007/s00161-021-00970-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 01/04/2021] [Indexed: 05/07/2023]
Abstract
We analyze the dynamics of a population of independent random walkers on a graph and develop a simple model of epidemic spreading. We assume that each walker visits independently the nodes of a finite ergodic graph in a discrete-time Markovian walk governed by his specific transition matrix. With this assumption, we first derive an upper bound for the reproduction numbers. Then, we assume that a walker is in one of the states: susceptible, infectious, or recovered. An infectious walker remains infectious during a certain characteristic time. If an infectious walker meets a susceptible one on the same node, there is a certain probability for the susceptible walker to get infected. By implementing this hypothesis in computer simulations, we study the space-time evolution of the emerging infection patterns. Generally, random walk approaches seem to have a large potential to study epidemic spreading and to identify the pertinent parameters in epidemic dynamics.
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Affiliation(s)
- Michael Bestehorn
- Institut für Physik, Brandenburgische Technische Universität Cottbus-Senftenberg, 03046 Cottbus, Germany
| | - Alejandro P. Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, 01000 Ciudad de Mexico, Mexico
| | - Thomas M. Michelitsch
- Institut Jean le Rond d’Alembert, Sorbonne Université, CNRS UMR 7190, 4 place Jussieu, 75252 Paris, cedex 05 France
| | - Bernard A. Collet
- Institut Jean le Rond d’Alembert, Sorbonne Université, CNRS UMR 7190, 4 place Jussieu, 75252 Paris, cedex 05 France
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13
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Merrill RD, Bah Chabi AI, McIntyre E, Kouassi JV, Alleby MM, Codja C, Tante O, Primous Martial GT, Kone I, Ward S, Agbeko TT, Kakaı CG. An approach to integrate population mobility patterns and sociocultural factors in communicable disease preparedness and response. HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS 2021; 8:1-11. [PMID: 38617731 PMCID: PMC11010577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Complex human movement patterns driven by a range of economic, health, social, and environmental factors influence communicable disease spread. Further, cross-border movement impacts disparate public health systems of neighboring countries, making an effective response to disease importation or exportation more challenging. Despite the array of quantitative techniques and social science approaches available to analyze movement patterns, there continues to be a dearth of methods within the applied public health setting to gather and use information about community-level mobility dynamics. Population Connectivity Across Borders (PopCAB) is a rapidly-deployable toolkit to characterize multisectoral movement patterns through community engagement using focus group discussions or key informant interviews, each with participatory mapping, and apply the results to tailor preparedness and response strategies. The Togo and Benin Ministries of Health (MOH), in collaboration with the Abidjan Lagos Corridor Organization and the US Centers for Disease Control and Prevention, adapted and applied PopCAB to inform cross-border preparedness and response strategies for multinational Lassa fever outbreaks. Initially, the team implemented binational, national-level PopCAB activities in March 2017, highlighting details about a circular migration pathway across northern Togo, Benin, and Nigeria. After applying those results to respond to a cross-border Lassa fever outbreak in February 2018, the team designed an expanded PopCAB initiative in April 2018. In eight days, they trained 54 MOH staff who implemented 21 PopCAB focus group discussions in 14 cities with 224 community-level participants representing six stakeholder groups. Using the newly-identified 167 points of interest and 176 routes associated with a circular migration pathway across Togo, Benin, and Nigeria, the Togo and Benin MOH refined their cross-border information sharing and collaboration processes for Lassa fever and other communicable diseases, selected health facilities with increased community connectivity for enhanced training, and identified techniques to better integrate traditional healers in surveillance and community education strategies. They also integrated the final toolkit in national- and district-level public health preparedness plans. Integrating PopCAB in public health practice to better understand and accommodate population movement patterns can help countries mitigate the international spread of disease in support of improved global health security and International Health Regulations requirements.
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Affiliation(s)
| | | | - Elvira McIntyre
- Perspecta and US Centers for Disease Control and Prevention, Atlanta, USA
| | | | | | | | | | | | - Idriss Kone
- Abidjan Lagos Corridor Organization, Benin, Nigeria
| | - Sarah Ward
- US Centers for Disease Control and Prevention, Atlanta, USA
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14
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Riascos AP, Michelitsch TM, Pizarro-Medina A. Nonlocal biased random walks and fractional transport on directed networks. Phys Rev E 2020; 102:022142. [PMID: 32942357 DOI: 10.1103/physreve.102.022142] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 08/13/2020] [Indexed: 06/11/2023]
Abstract
In this paper, we study nonlocal random walk strategies generated with the fractional Laplacian matrix of directed networks. We present a general approach to analyzing these strategies by defining the dynamics as a discrete-time Markovian process with transition probabilities between nodes expressed in terms of powers of the Laplacian matrix. We analyze the elements of the transition matrices and their respective eigenvalues and eigenvectors, the mean first passage times and global times to characterize the random walk strategies. We apply this approach to the study of particular local and nonlocal ergodic random walks on different directed networks; we explore circulant networks, the biased transport on rings and the dynamics on random networks. We study the efficiency of a fractional random walker with bias on these structures. Effects of ergodicity loss which occur when a directed network is not any more strongly connected are also discussed.
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Affiliation(s)
- A P Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, 01000 Ciudad de México, México
| | - T M Michelitsch
- Sorbonne Université, Institut Jean le Rond d'Alembert, CNRS UMR 7190,4 place Jussieu, 75252 Paris cedex 05, France
| | - A Pizarro-Medina
- Departamento de Física, Facultad de Ciencias, Universidad Nacional Autónoma de México, Ciudad Universitaria, Ciudad de México 04510, México
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15
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Riascos AP, Boyer D, Herringer P, Mateos JL. Random walks on networks with stochastic resetting. Phys Rev E 2020; 101:062147. [PMID: 32688619 DOI: 10.1103/physreve.101.062147] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 06/12/2020] [Indexed: 06/11/2023]
Abstract
We study random walks with stochastic resetting to the initial position on arbitrary networks. We obtain the stationary probability distribution as well as the mean and global first passage times, which allow us to characterize the effect of resetting on the capacity of a random walker to reach a particular target or to explore a finite network. We apply the results to rings, Cayley trees, and random and complex networks. Our formalism holds for undirected networks and can be implemented from the spectral properties of the random walk without resetting, providing a tool to analyze the search efficiency in different structures with the small-world property or communities. In this way, we extend the study of resetting processes to the domain of networks.
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Affiliation(s)
- Alejandro P Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, 01000 Ciudad de México, México
| | - Denis Boyer
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, 01000 Ciudad de México, México
| | - Paul Herringer
- Department of Physics and Astronomy, University of Calgary, Calgary, Alberta, Canada T2N 1N4
| | - José L Mateos
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, 01000 Ciudad de México, México
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, 04510 Ciudad de México, México
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Riascos AP, Mateos JL. Networks and long-range mobility in cities: A study of more than one billion taxi trips in New York City. Sci Rep 2020; 10:4022. [PMID: 32132592 PMCID: PMC7055277 DOI: 10.1038/s41598-020-60875-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 02/07/2020] [Indexed: 11/16/2022] Open
Abstract
We analyze the massive data set of more than one billion taxi trips in New York City, from January 2009 to December 2015. With these records of seven years, we generate an origin-destination matrix that has information of a vast number of trips. The mobility and flow of taxis can be described as a directed weighted network that connects different zones of high demand for taxis. This network has in and out degrees that follow a stretched exponential and a power law with an exponential cutoff distributions, respectively. Using the origin-destination matrix, we obtain a rank, called "OD rank”, analogous to the page rank of Google, that gives the more relevant places in New York City in terms of taxi trips. We introduced a model that captures the local and global dynamics that agrees with the data. Considering the taxi trips as a proxy of human mobility in cities, it might be possible that the long-range mobility found for New York City would be a general feature in other large cities around the world.
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Affiliation(s)
- A P Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, 01000, Ciudad de México, Mexico.
| | - José L Mateos
- Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, 01000, Ciudad de México, Mexico. .,Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Apartado Postal 04510, Ciudad de México, Mexico.
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Loaiza-Monsalve D, Riascos AP. Human mobility in bike-sharing systems: Structure of local and non-local dynamics. PLoS One 2019; 14:e0213106. [PMID: 30840674 PMCID: PMC6402762 DOI: 10.1371/journal.pone.0213106] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 02/14/2019] [Indexed: 12/27/2022] Open
Abstract
The understanding of human mobility patterns in different transportation modes is an interdisciplinary research field with a direct impact in aspects as varied as urban planning, traffic optimization, sustainability, the reduction of operating costs as well as the mitigation of pollution in urban areas. In this paper, we study the global activity of users in bike-sharing systems operating in the cities of Chicago and New York. For this transportation mode, we explore the temporal and spatial characteristics of the mobility of cyclists. In particular, through the analysis of origin-destination matrices, we characterize the spatial structure of the displacements of users. We apply a mobility model for the global activity of the system that classifies the displacements between stations in local and non-local transitions. In local transitions, cyclists move in a region around each station whereas, in the non-local case, bike users travel with long-range displacements in a similar way to Lévy flights. We reproduce the spatial dynamics by using Monte Carlo simulations. The obtained results are similar to the observed in real data and reveal that the model implemented captures important characteristics of the global spatial dynamics in the systems analyzed.
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Affiliation(s)
- D. Loaiza-Monsalve
- Department of Civil Engineering, Universidad Mariana, San Juan de Pasto, Colombia
| | - A. P. Riascos
- Instituto de Física, Universidad Nacional Autónoma de México, Ciudad de México, México
- * E-mail:
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