Population Mobility Research Articles

Advanced Integration of Urban Street Greenery and Pedestrian Flow: A Multidimensional Analysis in Chengdu’s Central Urban District

As urbanization accelerates, urban greenery, particularly street greenery, emerges as a vital strategy for enhancing residents’ quality of life, demanding attention for its alignment with pedestrian flows to foster sustainable urban development and ensure urban dwellers’ wellbeing. The advent of diverse urban data has significantly advanced this area of study. Focusing on Chengdu’s central urban district, this research assesses street greening metrics against pedestrian flow indicators, employing spatial autocorrelation techniques to investigate the interplay between street greenery and pedestrian flow over time and space. Our findings reveal a prevalent negative spatial autocorrelation between street greenery and pedestrian flow within the area, underscored by temporal disparities in greenery demands across various urban functions during weekdays versus weekends. This study innovatively incorporates mobile phone signal-based population heat maps into the mismatch analysis of street greenery for the first time, moving beyond the conventional static approach of space syntax topology in assessing pedestrian flow. By leveraging dynamic pedestrian flow data, it enriches our understanding of the disconnect between street greening plans and pedestrian circulation, highlighting the concept of urban flow and delving into the intricate nexus among time, space, and human activity. Moreover, this study meticulously examines multiple street usage scenarios, reflecting diverse behavior patterns, with the objective of providing nuanced and actionable strategies for urban renewal initiatives aimed at creating more inviting and sustainable urban habitats.

The Influence of the Construction of the Ocarina – Bengkong Bridge on Economic Aspects and Social Aspects In Bengkong District, Batam City

Infrastructure development has the potential to have an important influence on various aspects of regional development. One important piece of infrastructure is a bridge. This study aims to analyze the influence of the construction of the Ocarina - Bengkong Bridge on economic and social aspects in Bengkong sub-district. This research uses quantitative methods by distributing questionnaires to the community around the Bengkong bridge. In the economic aspect, the research results show that the construction of the bridge has made a positive contribution to economic growth in Bengkong sub-district. The availability of better accessibility between Ocarina and Bengkong has increased population mobility, enabled the growth of the trade sector, and supported the development of the tourism sector in the region. Apart from that, the construction of the bridge also triggers an increase in property values and investment around the area. In the social aspect, bridge construction has brought positive changes in people's lives. Better mobility increases social connectivity between regions, facilitates cultural exchange, and strengthens community integration. Apart from that, increasing accessibility also increases people's access to education and health services. However, this study also identified several challenges and negative influences, such as increased traffic flow which can cause congestion and environmental impacts that need to be managed well and wisely. This research provides important insights for policy makers, related parties and the general public about the importance of infrastructure such as bridges in improving the economic and social welfare of a region.

«Digital nomads» in the modern labor market

The purpose of the research: Analyze the economic situation of digital nomads, their infl uence on the labor market, taking into account that they differ in dynamism of geographic mobility. To study the problems of non-traditional employment in the context of digitalization of the economy. Methodology: The paper uses a comparative analysis between digital nomads, freelancers and self-employed citizens, which showed that they form overlapping sets with such common feature as remote non-standard employment. Study of digital nomads involves the use of a non-ethnographic approach, including methods such as online immersive interaction, content analysis of websites, forums, blogs, etc. Originality/value of the research: Despite many publications, there are still a number of diffi culties in studying the phenomenon of digital nomads. The article discusses defi nition of digital nomads, their essential characteristics, differences from self-employed citizens and freelancers. The article proves an important role of digital nomads in the modern labor market, who provide information, technological, managerial support, and various types of services. Findings: Increase in level of the population mobility stimulated emergence of a new form of employment on the labor market. Digital nomads are distinguished by a high level of education and professional training; considerable freedom in choosing the production sphere and provision of services in the fi eld of intangible production. In post-covid conditions, digital nomads can contribute to replacement of lost workers.

Genomic surveillance of malaria parasites in an indigenous community in the Peruvian Amazon

Hard-to-reach communities represent Peru's main challenge for malaria elimination, but information about transmission in these areas is scarce. Here, we assessed Plasmodium vivax (Pv) and P. falciparum (Pf) transmission dynamics, resistance markers, and Pf hrp2/3 deletions in Nueva Jerusalén (NJ), a remote, indigenous community in the Peruvian Amazon with high population mobility. We collected samples from November 2019 to May 2020 by active (ACD) and passive case detection (PCD) in NJ. Parasites were identified with microscopy and PCR. Then, we analyzed a representative set of positive-PCR samples (Pv = 68, Pf = 58) using highly-multiplexed deep sequencing assays (AmpliSeq) and compared NJ parasites with ones from other remote Peruvian areas using population genetics indexes. The ACD intervention did not reduce malaria cases in the short term, and persistent malaria transmission was observed (at least one Pv infection was detected in 96% of the study days). In Nueva Jerusalen, the Pv population had modest genetic diversity (He = 0.27). Pf population had lower diversity (He = 0.08) and presented temporal clustering, one of these clusters linked to an outbreak in February 2020. Moreover, Pv and Pf parasites from NJ exhibited variable levels of differentiation (Pv Fst = 0.07–0.52 and Pf Fst = 0.11–0.58) with parasites from other remote areas. No artemisin resistance mutations but chloroquine (57%) and sulfadoxine-pyrimethamine (35–67%) were detected in NJ's Pf parasites. Moreover, pfhrp2/3 gene deletions were common (32–50% of parasites with one or both genes deleted). The persistent Pv transmission and the detection of a Pf outbreak with parasites genetically distinct from the local ones highlight the need for tailored interventions focusing on mobility patterns and imported infections in remote areas to eliminate malaria in the Peruvian Amazon.

A global perspective on social stratification in science

To study stratification among scientists, we reconstruct the career-long trajectories of 8.2 million scientists worldwide using 12 bibliometric measures of productivity, geographical mobility, collaboration, and research impact. While most previous studies examined these variables in isolation, we study their relationships using Multiple Correspondence and Cluster Analysis. We group authors according to their bibliometric performance and academic age across six macro fields of science, and analyze co-authorship networks and detect collaboration communities of different sizes. We found a stratified structure in terms of academic age and bibliometric classes, with a small top class and large middle and bottom classes in all collaboration communities. Results are robust to community detection algorithms used and do not depend on authors’ gender. These results imply that increased productivity, impact, and collaboration are driven by a relatively small group that accounts for a large share of academic outputs, i.e., the top class. Mobility indicators are the only exception with bottom classes contributing similar or larger shares. We also show that those at the top succeed by collaborating with various authors from other classes and age groups. Nevertheless, they are benefiting disproportionately from these collaborations which may have implications for persisting stratification in academia.

Defining indicators for disease burden, health outcomes, policies and barriers and facilitators to health services for migrant populations in the Middle East and North African region: a protocol for a suite of systematic reviews

IntroductionThe Middle East and North African (MENA) region is characterised by high and complex migration flows, yet little is known about the health of migrant populations, their levels of underimmunisation...

Mobility in a globalised world: How countries regulate mobility with passports and visas

Citizenship has a significant impact on migrants' freedom to travel. While citizens of the Global North can travel without major problems, citizens of the Global South have to queue at consulates to obtain a visa before they can travel. They may have to wait in long queues at the border or at the airport, where they may be subjected to unpleasant interrogations. The aim of this article is to uncover how a passport becomes powerful or weak depending on the country that issues it, and what impact this has on the (geographical and professional) mobility of passport holders. We explore why some countries impose visa restrictions while others allow visa‐free travel. We interviewed 32 people who had travelled on a number of occasions for professional reasons or as tourists. The externalities created by visa regulations may lead to an increase in the number of alternative destinations in lockstep, even if countries' policies remain unchanged. This study has critical policy implications for both source and destination countries.

Geo-Phenomenology: A Qualitative and Humanistic GIS Approach to Exploring Lived Experience

Critical discussions are developing to combine geographic information systems (GIS) and qualitative methods as an alternative approach to traditional quantitative GIS, but the possibility of integrating spatial information technology and phenomenology is still unknown. This study explores a new qualitative and humanistic GIS approach called geo-phenomenology. It attempts to improve the ability to validate and authenticate findings and to gain a holistic understanding of the complex interplay among space, place, and human emotion through a combination of phenomenology, natural language processing methods, and GIS. To illustrate this approach, this study focuses on international students and examines the effects of geographic mobility on individuals’ sense of attachment and belonging. Importantly, it allows for a more sensitive approach to the spatial scale of material culture as a mediator of sense of place. The overlay of emotional mapping and land use provided a perspective for narrative interpretation and hypothesis building, ultimately leading to the discovery of key evidence determining the main themes of international students’ sense of place attachment and belonging. By combining quantitative emotion detection with qualitative phenomenological interpretation in GIS, this study concludes that geo-phenomenology can help us consider the rich nuances of lifeworlds from multiple perspectives.

Bangladesh Ship Breaking Industry: Is it an Opportunity or Obstacles for Out-Migrant Workers?

The ship breaking industry flourished in Bangladesh after the liberation war in 1971. Since then Bangladesh is leading in this ship breaking sector around the globe. The rapid growth of this industry is specially driven by national iron demands, income generation, and the easy opportunity of employment for the poor people. As most of the workers working here are poor and hail from underdeveloped regions of the country hence this study was designed to find out the obstacles and opportunities that need to encounter when they leave this industry after extensive working years. The instrument used for this research was semi close ended questionnaires, in depth interviews, ethnographic analysis and secondary research. The respondents are from southern and northern parts of Bangladesh, aged 18 years and above. This study revealed that a majority portion of the out migrant workers are sufferings from numerous challenges such as health issue, social stigma, psychological trauma, restricted employment opportunities, limited geographical mobility and so on. Conversely, only a minority of the out migrators are benefited from this industry, specifically those employed in technical or supervisory roles. Overall, this industry has proven detrimental, creating more obstacles rather than opportunities for out-migrant workers lives.

The heterogeneous impact of population mobility on the influent characteristics of wastewater treatment facilities

Improving the resilience of wastewater treatment facilities (WWTFs) has never been more important with rising risks of disasters under climate change. Beyond physical damages, non-physical shocks induced by disasters warrant attention. Human mobility is a vital mediator in transferring the stresses from extreme events into tangible challenges for urban sewage systems by reshaping influent characteristics. However, the impact path remains inadequately explored. Leveraging the stay-at-home orders during the COVID-19 pandemic as a natural experiment, this study aims to quantify and interpret the heterogeneous impacts of mobility reduction on the influent characteristics of WWTFs with different socio-economic, infrastructural, and climatic conditions. To achieve this goal, we developed a research framework integrating causal inference and interpretable machine learning techniques. Based on the empirical data from China, we find that 79.1% of the studied WWTFs, typically located in cities with well-developed drainage infrastructures and low per capita water usage, exhibited resilience against drastic mobility reduction. In contrast, 20.9% of the studied WWTFs displayed significant variations in influent characteristics. Large-capacity WWTFs in subtropical regions encountered challenges with low-load operations, and small-capacity facilities in suburban areas grappled with nutrient imbalances. This study provides valuable insights to equip WWTFs in anticipating and adapting potential variations in influent characteristics triggered by mobility reduction.

Analysis of determinants of elderly welfare in Karangasem District, Karangasem Regency, Bali

Increasing population mobility has resulted in many elderly individuals being left alone. This study aims to: 1) analyze the simultaneous and partial effects of income, health access, environmental conditions, and the perception of menama braya activities on the well-being of the elderly; 2) analyze the role of the perception of menama braya activities in moderating the influence of environmental conditions on the well-being of the elderly. This study uses a quantitative approach with an associative explanatory level. The population in this study consists of residents aged 60 and above in the Karangasem District, totaling 100 individuals. The sampling technique was conducted using accidental sampling combined with snowball sampling, with data collection methods including observation, structured interviews, and in-depth interviews. Data analysis was performed using moderated regression analysis. The results of the study show that: 1) income, health access, environmental conditions, and the perception of menama braya activities simultaneously have a significant effect on the well-being of the elderly; 2) income, health access, environmental conditions, and the perception of equalizing activities partially have a significant positive effect on the well-being of the elderly; 3) the perception of equalizing activities moderates (weakens) the influence of environmental conditions on the well-being of the elderly.

The effect of transport parameters on regional economic development: The case of the Ural Federal District

The transport has a special role to play in the regional socioeconomic development, which changes depending on the prevailing trends for population mobility, introduction of advanced technologies, extension of economic connections, and growth in regional production. The study explores the problem of the interface between transport and regional economy on the example of the Ural Federal District. Methodologically, it relies on the theories of spatial development and regional economics. The main method of research is correlation and regression analysis. The evidence is the socioeconomic data on transport as well as values of gross regional product of the Ural Federal District for 2010–2020 sourced from the Federal State Statistics Service of the Russian Federation. The paper develops a model for forecasting GRP. The analysis indicates the presence of the relationship between the socioeconomic metrics of the transport sector and gross regional product of the Ural Federal District. In particular, there is the correlation between the indicators “density of public roads with hard surface”, “deaths in road accidents per 100,000 population” and gross regional product of the Ural Federal District. The paper concludes about the need to develop a composite indicator for assessing the transport sector that will reflect the ongoing digital modernisation and introduction of innovations.

Spatiotemporal dynamics of epidemiology diseases: mobility based risk and short-term prediction modeling of COVID-19.

Nowadays, epidemiological modeling is applied to a wide range of diseases, communicable and non-communicable, namely AIDS, Ebola, influenza, Dengue, Malaria, Zika. More recently, in the context of the last pandemic declared by the World Health Organization (WHO), several studies applied these models to SARS-CoV-2. Despite the increasing number of researches using spatial analysis, some constraints persist that prevent more complex modeling such as capturing local epidemiological dynamics or capturing the real patterns and dynamics. For example, the unavailability of: (i) epidemiological information such as the frequency with which it is made available; (ii) sociodemographic and environmental factors (e.g., population density and population mobility) at a finer scale which influence the evolution patterns of infectious diseases; or (iii) the number of cases information that is also very dependent on the degree of testing performed, often with severe territorial disparities and influenced by context factors. Moreover, the delay in case reporting and the lack of quality control in epidemiological information is responsible for biases in the data that lead to many results obtained being subject to the ecological fallacy, making it difficult to identify causal relationships. Other important methodological limitations are the control of spatiotemporal dependence, management of non-linearity, ergodicy, among others, which can impute inconsistencies to the results. In addition to these issues, social contact, is still difficult to quantify in order to be incorporated into modeling processes. This study aims to explore a modeling framework that can overcome some of these modeling methodological limitations to allow more accurate modeling of epidemiological diseases. Based on Geographic Information Systems (GIS) and spatial analysis, our model is developed to identify group of municipalities where population density (vulnerability) has a stronger relationship with incidence (hazard) and commuting movements (exposure). Specifically, our framework shows how to operate a model over data with no clear trend or seasonal pattern which is suitable for a short-term predicting (i.e., forecasting) of cases based on few determinants. Our tested models provide a good alternative for when explanatory data is few and the time component is not available, once they have shown a good fit and good short-term forecast ability.

Examining the Impact of Urban Connectivity on Urban Innovation Efficiency: An Empirical Study of Yangtze River Delta in China

Innovation serves as a vital catalyst for sustainable urban development, with the enhancement of urban innovation efficiency representing a critical strategy to bolster cities’ innovative capacity. Rigorous scientific measurement of urban innovation efficiency and thorough investigation into the key factors influencing it are imperative for advancing urban innovation capacity. Despite this significance, prior research has largely overlooked the impact of urban connections on urban innovation efficiency. Therefore, this paper undertakes the task of measuring the innovation efficiency of 27 cities within China’s Yangtze River Delta (YRD) region using an improved DEA model, while also examining the associated influencing factors. The primary findings are as follows: (1) The comprehensive efficiency of the 27 cities in the YRD remains relatively low, with pure technical efficiency representing a notable constraint, while scale efficiency demonstrates higher overall performance. (2) The cities can be classified into four distinct categories: innovation-leading, innovation-optimizing, innovation-breaking, and innovation-improving cities. (3) The urban innovation efficiency within the YRD exhibits negative spatial spillover effects. (4) And notably, local economic and social characteristics such as human capital and degree of openness play a positive role in enhancing innovation efficiency in YRD cities. Conversely, factors such as economic foundation and government involvement exhibit negative contributions to innovation efficiency enhancement in YRD cities. Additionally, population mobility between cities is identified as a significant contributor to urban innovation efficiency. This study sheds light on the complex dynamics shaping urban innovation efficiency and underscores the importance of leveraging urban connections to bolster innovation capacity in the YRD and beyond.

Epidemic spreading on spatial higher-order network

Higher-order interactions exist widely in mobile populations and are extremely important in spreading epidemics, such as influenza. However, research on high-order interaction modeling of mobile crowds and the propagation dynamics above is still insufficient. Therefore, this study attempts to model and simulate higher-order interactions among mobile populations and explore their impact on epidemic transmission. This study simulated the spread of the epidemic in a spatial high-order network based on agent-based model modeling. It explored its propagation dynamics and the impact of spatial characteristics on it. Meanwhile, we construct state-specific rate equations based on the uniform mixing assumption for further analysis. We found that hysteresis loops are an inherent feature of high-order networks in this space under specific scenarios. The evolution curve roughly presents three different states with the initial value change, showing different levels of the endemic balance of low, medium, and high, respectively. Similarly, network snapshots and parameter diagrams also indicate these three types of equilibrium states. Populations in space naturally form components of different sizes and isolations, and higher initial seeds generate higher-order interactions in this spatial network, leading to higher infection densities. This phenomenon emphasizes the impact of high-order interactions and high-order infection rates in propagation. In addition, crowd density and movement speed act as protective and inhibitory factors for epidemic transmission, respectively, and depending on the degree of movement weaken or enhance the effect of hysteresis loops.

PRISE EN CHARGE DES PERSONNES ATTEINTES DE TROUBLES MUSCULO SUELETTIQUES ET DE MALADIES CHRONIQUES NON TRANSMISSIBLES PAR DES ACTIVITES PHYSIQUES ADAPTEES SANTE (APS) DURANT LE CONFINEMENT EN PERIODE DE COVID 19 AU SENEGAL

The appearance of the coronavirus (COVID-19) in China, and more specifically in Wuhan, triggered a pandemic, declared by the World Health Organization (WHO) on March 11, 2020, which rapidly spread around the world, causing several thousand deaths. All countries have taken preventive measures, including containment, which reduces the mobility of populations. Consequently, inactivity among individuals, especially the elderly and women suffering from certain pathologies, further increases the risk of certain non-transmissible chronic diseases, as well as musculoskeletal and cardiovascular disorders. Thus, our study consisted in providing a remedy during the period of relief from restrictive measures or decontainment through a health adapted physical activity program (APAS). Anthropometric variables and musculoskeletal disorders in 11 Senegalese women, all suffering from musculoskeletal disorders and some from chronic non-transmissible diseases (diabetes, sickle-cell anemia AS, osteoarthritis) aged between 31 and 55, were measured before and at the end of a month-long program consisting of treadmill walking combined with muscle-strengthening exercises. Students t-tests performed to compare the mean values of variables measured in our sample before and at the end of the physical activity program revealed no statistically significant differences, although the women showed an absolute reduction in weight, body fat and Body Mass Index, a remarkable reduction in musculoskeletal disorders and a stabilization of chronic non-transmissible diseases.

Spatiotemporal analysis of imported and local dengue virus and cases in a metropolis in Southwestern China, 2013–2022

Dengue fever is a viral illness, mainly transmitted by Aedes aegypti and Aedes albopictus. With climate change and urbanisation, more urbanised areas are becoming suitable for the survival and reproduction of dengue vector, consequently are becoming suitable for dengue transmission in China. Chongqing, a metropolis in southwestern China, has recently been hit by imported and local dengue fever, experiencing its first local outbreak in 2019. However, the genetic evolution dynamics of dengue viruses and the spatiotemporal patterns of imported and local dengue cases have not yet been elucidated. Hence, this study implemented phylogenetic analyses using genomic data of dengue viruses in 2019 and 2023 and a spatiotemporal analysis of dengue cases collected from 2013 to 2022. We sequenced a total of 15 nucleotide sequences of E genes. The dengue viruses formed separate clusters and were genetically related to those from Guangdong Province, China, and countries in Southeast Asia, including Laos, Thailand, Myanmar and Cambodia. Chongqing experienced a dengue outbreak in 2019 when 168 imported and 1,243 local cases were reported, mainly in September and October. Few cases were reported in 2013–2018, and only six were imported from 2020 to 2022 due to the COVID-19 lockdowns. Our findings suggest that dengue prevention in Chongqing should focus on domestic and overseas population mobility, especially in the Yubei and Wanzhou districts, where airports and railway stations are located, and the period between August and October when dengue outbreaks occur in endemic regions. Moreover, continuous vector monitoring should be implemented, especially during August–October, which would be useful for controlling the Aedes mosquitoes. This study is significant for defining Chongqing's appropriate dengue prevention and control strategies.

Optimal region-specific social distancing strategies in a complex multi-patch model through reinforcement learning

Although non-pharmaceutical interventions such as social distancing have proven effective in curbing outbreaks, they also carry economic consequences. This poses a dilemma for policymakers striving to find a balance between disease control and economic burden. This delicate balance varies regionally, influenced by non-epidemiological factors such as population movements, socio-demographic characteristics, and the intricacies of social distancing policies. These factors interact in intricate ways, shaping the transmission dynamics of COVID-19. To address this complexity, we propose an innovative approach utilizing deep reinforcement learning (RL). This method assists in tailoring intervention policies for diverse regions, taking into account their unique dynamics. We incorporate South Korea’s social distancing policies and their economic impact into a RL framework with a multi-region epidemic model, offering a comprehensive solution. We integrate official mobility data and GDP specific to each region, employing the proximity policy optimization algorithm to determine the most appropriate region-specific social distancing policy. The algorithm’s reward function considers both outbreak control and economic impacts, providing policymakers with the flexibility to fine-tune the balance between these two factors according to their preferences. This adjustment can be performed across three distinct cost scenarios: High, Base, and Low-cost scenarios. In scenarios with High-costs, social distancing measures are aimed at regions with extensive connectivity and higher transmission rates. When costs are moderate, policies center around the period of peak prevalence, illustrating adaptable strategies in areas characterized by high transmission rates, budget limitations, and population mobility. In situations with Low-costs, these measures encompass most regions, excluding those with low transmission rates. The study’s results support focused interventions in specific regions to balance outbreak control and economic impact mitigation.

The Evolution of Cooperation in a Mobile Population on Random Networks: Network Topology Matters Only for Low-Degree Networks

The Evolution of Cooperation in a Mobile Population on Random Networks: Network Topology Matters Only for Low-Degree Networks

Declining Incidence of Kawasaki Disease During the COVID-19 Pandemic: A Time Series Analysis.

In 2020, Taiwan experienced a dramatic disruption of daily life due to measures aimed at limiting the spread of coronavirus disease 2019 (COVID-19), although domestic COVID-19 cases were extremely rare. This provided a chance to investigate the change of incidence and possible triggers of Kawasaki disease (KD) without the interference of multisystem inflammatory syndrome in children. This population-based study used Taiwan's National Health Insurance Research Database. To detect the change in KD incidence in children less than 6 years old during the period of social distancing policy in 2020, the autoregressive integrated moving average model was used based on seasonal variation and the increasing trend of KD incidence over the past 10 years. The trends in population mobility and common infectious diseases were also analyzed to observe their effects on KD incidence. The predicted monthly incidence [95% confidence interval (CI)] of KD in April, May and June 2020 were 5.26 (3.58-6.94), 5.45 (3.70-7.20) and 5.41 (3.61-7.21) per 100,000 person-months. The actual observed incidences were 2.41, 2.67 and 2.60 per 100,000 person-months, respectively, representing a 51.2%, 51.0% and 51.9% reduction in incident rates in the 3-month period of stringent COVID-19 mitigation measures. The trend was not proportionate to the profound decline of common infectious cases. KD incidence decreased by approximately 50% during the period of stringent COVID-19 mitigation measures in 2020 in Taiwan. Human-to-human contact may be a potential KD trigger, but there are likely other contributing factors aside from infection.