Communities on the move: community participation in health in rural territories of Buenaventura District in Colombia.

BACKGROUND: Social and community participation is a fundamental component of the development of renewed primary healthcare (PHC). With the recognition of health as a right, such participation is a significant part of the design of public policies aimed at this sector. These policies contribute not only to overcoming inequity in the provision of this type of services but also to a reduction in social inequalities as a whole. Through a comparative analysis, this study aimed to explain the conditions through which ethnic-rural territories of the Colombian Pacific coast participate in health to contribute to the generation of policies and programs in territories with similar conditions. METHODS: The work was developed through the use of multiple techniques and strategies for information collection and analysis. These include several semi-structured interviews, multiple observation exercises and analysis based on a set theory, i.e., qualitative comparative analysis (QCA). The latter aims to develop a model that provides a count of the main causal combinations that allow high community participation in health. RESULTS: Key findings include how the trajectory of social mobilization and existence of a robust community social fabric became two critical conditions for community participation in the context of social exclusion. The presence of variables such as the implementation of PHC, guarantee of social rights, and trust in institutions, is underestimated as sufficient causal conditions for obtaining this result. Therefore, it is essential to recognize the existence, validity, and importance of processes, experiences, and resourcefulness of political natures, which aim at transforming the daily reality of the inhabitants of these communities. These also set a potential space and scenario for managing the communities' main problems, including health, in the absence of institutionality that guarantees access to their social rights. CONCLUSION: This study points out the importance of understanding community participation as a political activity, expanding exchange dynamics and dialogs between institutions, rulers, and communities to provide social responses in health and well-being to communities and to understand local realities and their own community dynamics.

A network-based analysis to assess COVID-19 disruptions in the Bogotá BRT system.

The global COVID-19 crisis has severely affected mass transit in the cities of the global south. Fear of widespread propagation in public spaces and the dramatic decrease in human mobility due to lockdowns have resulted in a significant reduction of public transport options. We analyze the case of TransMilenio in Bogotá, a massive Bus Rapid Transit system that is the main mode of transport for an urban area of roughly 10 million inhabitants. Concerns over social distancing and new health regulations reduced the number of trips to under 20% of its historical values during extended periods of time during the lockdowns. This has sparked a renewed interest in developing innovative data-driven responses to COVID-19 resulting in large corpora of TransMilenio data being made available to the public. In this paper we use a database updated daily with individual passenger card swipe validation microdata including entry time, entry station, and a hash of the card's ID. The opportunity of having daily detailed minute-to-minute ridership information and the challenge of extracting useful insights from the massive amount of raw data (∼1,000,000 daily records) require the development of tailored data analysis approaches. Our objective is to use the natural representation of urban mobility offered by networks to make pairwise quantitative similarity measurements between daily commuting patterns and then use clustering techniques to reveal behavioral disruptions as well as the most affected geographical areas due to the different pandemic stages. This method proved to be efficient for the analysis of large amount of data and may be used in the future to make temporal analysis of similarly large datasets in urban contexts.

Differences in the spatial landscape of urban mobility: Gender and socioeconomic perspectives.

Many of our routines and activities are linked to our ability to move; be it commuting to work, shopping for groceries, or meeting friends. Yet, factors that limit the individuals' ability to fully realise their mobility needs will ultimately affect the opportunities they can have access to (e.g. cultural activities, professional interactions). One important aspect frequently overlooked in human mobility studies is how gender-centred issues can amplify other sources of mobility disadvantages (e.g. socioeconomic inequalities), unevenly affecting the pool of opportunities men and women have access to. In this work, we leverage on a combination of computational, statistical, and information-theoretical approaches to investigate the existence of systematic discrepancies in the mobility diversity (i.e. the diversity of travel destinations) of (1) men and women from different socioeconomic backgrounds, and (2) work and non-work travels. Our analysis is based on datasets containing multiple instances of large-scale, official, travel surveys carried out in three major metropolitan areas in South America: Medellín and Bogotá in Colombia, and São Paulo in Brazil. Our results indicate the presence of general discrepancies in the urban mobility diversities related to the gender and socioeconomic characteristics of the individuals. Lastly, this paper sheds new light on the possible origins of gender-level human mobility inequalities, contributing to the general understanding of disaggregated patterns in human mobility.

Using demand mapping to assess the benefits of urban green and blue space in cities from four continents.

The benefits of urban green and blue infrastructure (UGI) are widely discussed, but rarely take into account local conditions or contexts. Although assessments increasingly consider the demand for the ecosystem services that UGI provides, they tend to only map the spatial pattern of pressures such as heat, or air pollution, and lack a wider understanding of where the beneficiaries are located and who will benefit most. We assess UGI in five cities from four continents with contrasting climate, socio-political context, and size. For three example services (air pollution removal, heat mitigation, accessible greenspace), we run an assessment that takes into account spatial patterns in the socio-economic demand for ecosystem services and develops metrics that reflect local context, drawing on the principles of vulnerability assessment. Despite similar overall levels of UGI (from 35 to 50% of urban footprint), the amount of service provided differs substantially between cities. Aggregate cooling ranged from 0.44 °C (Leicester) to 0.98 °C (Medellin), while pollution removal ranged from 488 kg PM2.5/yr (Zomba) to 48,400 kg PM2.5/yr (Dhaka). Percentage population with access to nearby greenspace ranged from 82% (Dhaka) to 100% (Zomba). The spatial patterns of pressure, of ecosystem service, and of maximum benefit within a city do not necessarily match, and this has implications for planning optimum locations for UGI in cities.

Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes.

We analyse the urban mobility in the cities of Medellín and Manizales (Colombia). Each city is represented by six mobility networks, each one encoding the origin-destination trips performed by a subset of the population corresponding to a particular socio-economic status. The nodes of each network are the different urban locations whereas links account for the existence of a trip between two different areas of the city. We study the main structural properties of these mobility networks by focusing on their spatio-temporal patterns. Our goal is to relate these patterns with the partition into six socio-economic compartments of these two societies. Our results show that spatial and temporal patterns vary across these socio-economic groups. In particular, the two datasets show that as wealth increases the early-morning activity is delayed, the midday peak becomes smoother and the spatial distribution of trips becomes more localized.