This article describes the origins and characteristics of an interdisciplinary multinational collaboration aimed at promoting and disseminating actionable evidence on the drivers of health in cities in Latin America and the Caribbean: The Network for Urban Health in Latin America and the Caribbean and the Wellcome Trust funded SALURBAL (Salud Urbana en América Latina, or Urban Health in Latin America) Project. Both initiatives have the goals of supporting urban policies that promote health and health equity in cities of the region while at the same time generating generalizable knowledge for urban areas across the globe. The processes, challenges, as well as the lessons learned to date in launching and implementing these collaborations, are described. By leveraging the unique features of the Latin American region (one of the most urbanized areas of the world with some of the most innovative urban policies), the aim is to produce generalizable knowledge about the links between urbanization, health, and environments and to identify effective ways to organize, design, and govern cities to improve health, reduce health inequalities, and maximize environmental sustainability in cities all over the world.
Area-level indicators of the determinants of health are vital to plan and monitor progress toward targets such as the Sustainable Development Goals (SDGs). Tools such as the Urban Health Equity Assessment and Response Tool (Urban HEART) and UN-Habitat Urban Inequities Surveys identify dozens of area-level health determinant indicators that decision-makers can use to track and attempt to address population health burdens and inequalities. However, questions remain as to how such indicators can be measured in a cost-effective way. Area-level health determinants reflect the physical, ecological, and social environments that influence health outcomes at community and societal levels, and include, among others, access to quality health facilities, safe parks, and other urban services, traffic density, level of informality, level of air pollution, degree of social exclusion, and extent of social networks. The identification and disaggregation of indicators is necessarily constrained by which datasets are available. Typically, these include household- and individual-level survey, census, administrative, and health system data. However, continued advancements in earth observation (EO), geographical information system (GIS), and mobile technologies mean that new sources of area-level health determinant indicators derived from satellite imagery, aggregated anonymized mobile phone data, and other sources are also becoming available at granular geographic scale. Not only can these data be used to directly calculate neighborhood- and city-level indicators, they can be combined with survey, census, administrative and health system data to model household- and individual-level outcomes (e.g., population density, household wealth) with tremendous detail and accuracy. WorldPop and the Demographic and Health Surveys (DHS) have already modeled dozens of household survey indicators at country or continental scales at resolutions of 1 × 1 km or even smaller. This paper aims to broaden perceptions about which types of datasets are available for health and development decision-making. For data scientists, we flag area-level indicators at city and sub-city scales identified by health decision-makers in the SDGs, Urban HEART, and other initiatives. For local health decision-makers, we summarize a menu of new datasets that can be feasibly generated from EO, mobile phone, and other spatial data-ideally to be made free and publicly available-and offer lay descriptions of some of the difficulties in generating such data products.
Readers should note an additional Acknowledgment for this article: Dana Thomson is funded by the Economic and Social Research Council grant number ES/5500161/1.