Cities are complex adaptive systems whose responses to policy initiatives emerge from feedback interactions between their parts. Urban policy makers must routinely deal with both detail and dynamic complexity, coupled with high levels of diversity, uncertainty and contingency. In such circumstances, it is difficult to generate reliable predictions of health-policy outcomes. In this paper we explore the potential for low-order system dynamics (LOSD) models to make a contribution towards meeting this challenge. By definition, LOSD models have few state variables (≤5), illustrate the non-linear effects caused by feedback and accumulation, and focus on endogenous dynamics generated within well-defined boundaries. We suggest that experience with LOSD models can help practitioners to develop an understanding of basic principles of system dynamics, giving them the ability to 'see with new eyes'. Because efforts to build a set of LOSD models can help a transdisciplinary group to develop a shared, coherent view of the problems that they seek to tackle, such models can also become the foundations of 'powerful ideas'. Powerful ideas are conceptual metaphors that provide the members of a policy-making group with the a priori shared context required for effective communication, the co-production of knowledge, and the collaborative development of effective public health policies.
As human populations become more and more urban, decision-makers at all levels face new challenges related to both the scale of service provision and the increasing complexity of cities and the networks that connect them. These challenges may take on unique aspects in cities with different cultures, political and institutional frameworks, and at different levels of development, but they frequently have in common an origin in the interaction of human and environmental systems and the feedback relationships that govern their dynamic evolution. Accordingly, systems approaches are becoming recognized as critical to understanding and addressing such complex problems, including those related to human health and wellbeing. Management of water resources in and for cities is one area where such approaches hold real promise.
The term "co-benefits" refers to positive outcomes accruing from a policy beyond the intended outcome, often or usually in other sectors. In the urban context, policies implemented in particular sectors (such as transport, energy or waste) often generate multiple co-benefits in other areas. Such benefits may be related to the reduction of local or global environmental impacts and also extend into the area of public health. A key to identifying and realising co-benefits is the adoption of systems approaches to understand inter-sectoral linkages and, in particular, the translation of this understanding to improved sector-specific and city governance. This paper reviews a range of policies which can yield health and climate co-benefits across different urban sectors and illustrates, through a series of cases, how taking a systems approach can lead to innovations in urban governance which aid the development of healthy and sustainable cities.
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.
Cities are currently experiencing serious, multifaceted impacts from global environmental change, especially climate change, and the degree to which they will need to cope with and adapt to such challenges will continue to increase. A complex systems approach inspired by evolutionary theory can inform strategies for policies and interventions to deal with growing urban vulnerabilities. Such an approach would guide the design of new (and redesign of existing) urban structures, while promoting innovative integration of grey, green and blue infrastructure in service of environmental and health objectives. Moreover, it would contribute to more flexible, effective policies for urban management and the use of urban space. Four decades ago, in a seminal paper in Science, the French evolutionary biologist and philosopher Francois Jacob noted that evolution differs significantly in its characteristic modes of action from processes that are designed and engineered de novo (Jacob in Science 196(4295):1161-1166, 1977). He labeled the evolutionary process "tinkering", recognizing its foundation in the modification and molding of existing traits and forms, with occasional dramatic shifts in function in the context of changing conditions. This contrasts greatly with conventional engineering and design approaches that apply tailor-made materials and tools to achieve well-defined functions that are specified a priori. We here propose that urban tinkering is the application of evolutionary thinking to urban design, engineering, ecological restoration, management and governance. We define urban tinkering as:A mode of operation, encompassing policy, planning and management processes, that seeks to transform the use of existing and design of new urban systems in ways that diversify their functions, anticipate new uses and enhance adaptability, to better meet the social, economic and ecological needs of cities under conditions of deep uncertainty about the future.This approach has the potential to substantially complement and augment conventional urban development, replacing predictability, linearity and monofunctional design with anticipation of uncertainty and non-linearity and design for multiple, potentially shifting functions. Urban tinkering can function by promoting a diversity of small-scale urban experiments that, in aggregate, lead to large-scale often playful innovative solutions to the problems of sustainable development. Moreover, the tinkering approach is naturally suited to exploring multi-functional uses and approaches (e.g., bricolage) for new and existing urban structures and policies through collaborative engagement and analysis. It is thus well worth exploring as a means of delivering co-benefits for environment and human health and wellbeing. Indeed, urban tinkering has close ties to systems approaches, which often are recognized as critical to sustainable development. We believe this concept can help forge much-closer, much-needed ties among engineers, architects, evolutionary ecologists, health specialists, and numerous other urban stakeholders in developing innovative, widely beneficial solutions for society and contribute to successful implementation of SDG11 and the New Urban Agenda.