Digital Transformations and Urban Health: Current Challenges and Opportunities

Key messages: a profound digital urban transformation

Introduction: Digital urban transformations as a determinant of urban health

Digital technologies have become the backbone for most urban technological innovation in the 21^st century, but also a close companion of socio-economic and in many cases political or cultural change. We can confidently argue that today access to digital technologies is a key determinant of urban health. This reality has been in the works for a long time. The two decades since the turn of the millennium have seen a progressive shift from more technology-driven ‘smart city’ discussions to a more holistic appreciation of the defining impacts of digital shifts and digital infrastructures on urban life, livelihoods, and governance. The progress and ongoing challenges of urban health are now inextricably entwined with the digitalisation of urban settlements and urbanisation processes. Twin trends have seen urban-based ICT hardware become more ubiquitous and accurate, while digital software focused on cities has rapidly improved and substantially expanded.

These developments present sizeable opportunities, and efforts to seize them are already underway. Digitalisation and advancements in ICTs have provided urban health stakeholders and policymakers with powerful tools for planning, decision-making and evidence generation. Massive increases in the digitally powered dissemination of public health data in many countries, along with strategies to communicate key metrics and evidentiary standards, have improved awareness and solidified public expectations that such data will be prompt, reliable, complete, and transparent. Meanwhile, the digital transformation agenda has driven the push for more innovative, holistic, and integrated care, and this is progressively happening in and through urban areas. A growth in the capacity to leverage urban data and digitally enabled wellness approaches is making cities a key fulcrum of the current digital health revolution, side by side with an ever-greater digital propensity in urban health management.

The most recent pandemic, for the most part, has driven this transformation. The COVID-19 response provides a common reference point for grappling with the digital transformation of urban health in diverse urban contexts worldwide.¹ It underscored the pervasiveness of ICTs at the heart of urban life and, in most contexts, stimulated a greater appetite toward mainstreaming digital transformational agendas, not least out of an everyday necessity to assess, control and respond to a globally shared health challenge. Since the early 2020s, this common referent has also featured prominently within global debates surrounding the rapid advancement of artificial intelligence (AI) and AI-powered urban systems, particularly in the context of growing concerns about the risks of digital transformation, highlighted by the rapid expansion of disinformation and misinformation in urban settlements.²

In this new frame of reference, it has become commonplace to note how digital technology can transform urban health across a vast variety of urban policy sectors. First, digital transformations have a proven—and increasingly ‘real-time’—capability to support the monitoring and analysis of urban health and to support critical interventions in times of crisis. Second, the proliferation of urban health data and digital systems has generated feedback loops with urban dwellers that can promote greater well-being and support the timely assessment of primary health threats. Third, digital advancements are allowing us to pay more targeted attention to the determinants of urban health.

These developments present a range of positive opportunities for the urban health community, whether in research, practice, or across both. For instance, a few key areas where this is taking place are:

Rapidly deployed digital solutions and services have the potential to support essential advances in urban health, but they also spotlight continuing inequalities, as we detail more in-depth below.⁴

In the meantime, digital transformation is revolutionising existing systems and conditions for urban management, and it shows no sign of slowing down. AI-powered tools are becoming increasingly embedded in legacy technologies, sometimes replacing existing processes through automation and sometimes promising sizeable leaps in technological innovation. Nonetheless, key questions remain as to their potential, applicability, and effectiveness.

The expanding digital economy that underpins digital transformation is also increasingly entrenched in urban governance in general and urban health mechanisms more specifically. This reality tightly links digital changes in health with action toward other global urban agendas, including climate, inequality and resilience, to name but a few. For example, the digital economy pervades and mediates crisis response, as underscored not only by COVID-19 but also by pressing issues around housing affordability, air quality and natural hazards. The digital economy shapes how the public responds to healthcare crises, complies with national public health strategy, maintains livelihoods, and makes decisions about consumption. Digital transfer systems speed up social safety net payments and remuneration of healthcare workers for crisis response. In some contexts, digital health records facilitate access to essential services, such as public sector offices and transit hubs, by validating immunisation status. These are not just features of larger and more ‘global’ cities: much of this transformation is taking place, as a recent review by the World Economic Forum noted, in small and medium-sized towns and predominantly in the Global South.⁵ In short, the change—an opportunity but also a challenge—is truly ‘global’ in span.

Digital access must now be considered, as underscored by the recent Lancet and Financial Times Commission on Governing Health Futures 2030,⁶ a social determinant of health.⁷ The shape, resilience and inclusivity of digital systems underpinning urban health in cities are a central driver of urban dwellers’ well-being in both North and South contexts.⁸ For instance, ‘digital rights’ are a growing critical urban health issue in cities worldwide, not least when tied to other key determinants of health.

Cities are not standing idly in the face of this challenge. For example, the Cities Coalition for Digital Rights, launched in 2018, incorporates more than 50 cities internationally. It engages across a diverse spectrum of issues, advocating for stronger rights for urban dwellers, for example, through establishing a Global Observatory of Urban Artificial Intelligence (although with limited health engagement to date).

At the same time, urban dwellers and local governments are increasingly demanding the right to digital access and data accessibility, along with widespread open-source data, citizen science, data transparency, and democratised IoT experiments.

The role of digital access as a social determinant of health can be articulated with increasing confidence. Yet, access itself is underpinned by deep urban inequalities, creating potentially self-perpetuating feedback cycles. On the one hand, access to digital transformation is deeply problematic from both technological-infrastructural and socio-economic standpoints. Access to the infrastructure underpinning digitalisation (e.g., state-of-the-art ICT, broadband) and health data itself is inequitable, contributing to a significant digital divide. Indeed, “health data poverty”⁹ is a key piece of the puzzle described here.

On the other hand, the unequal progress of digital transformation among different groups and contexts leads to even greater splintering and health inequities among urban dwellers. As with many of the challenges in this paper, much of this is not novel and has been developing for quite some time. Nor is it all bad news: even in extreme poverty, digital transformation offers unique potential for leapfrogging urban development and creating more inclusive urban services and communities. ITCs have become more affordable and accessible, and 20^th-century information technology that has been hard and costly to access is increasingly bypassed by newer, cheaper, and more widespread digital solutions. Likewise, a momentous expansion in computing capabilities and AI tools has great potential to enhance predictive and foresight analysis of urban data. Unfortunately, skills deficits and supplier limitations often hamper wider and more inclusive uptake of digital innovation. Therefore, in our view, the way forward urgently depends on step changes in research (and thus policy advice) and practical action—but only if coupled with leapfrogging in infrastructure and capacity.

Addressing urban digital divides

The ‘digital gap’, defined as unequal access to digital technology, is now a well-recognised challenge for innovation in cities and, consequently, for delivering better and more equitable urban health outcomes. Central to this is the issue of literacy. Indeed, digital literacy and capacity gaps within and between cities remain sizable, and in many cases, they have been widened or worsened by COVID-19-accelerated inequalities. Recent years have revealed significant gaps in the public sector across cities of all sizes and geographies. For instance, over 3 million new data professionals in the social impact sector will be needed worldwide to deliver on our current needs.¹⁰ In many (but not all) instances, intermediary cities and towns are falling further behind their larger national counterparts, creating digital divides between cities within countries, whilst similar differences have also emerged starkly at an international scale.

Additionally, action and investment gaps remain sizable, a pressing issue for all health policymakers leveraging digital transformations. For example, more than $20 billion in additional funding is estimated to be needed by 2030 to implement and operate digital health programs in low- and middle-income countries. Yet, at the same time, over 70% of the more than £1 trillion invested in enterprise digital transformation may be underperforming or be wasted altogether.¹¹ Sectoral siloes, shadow and informal work, inefficiencies related to the splintering of digital systems across diverse urban systems—missing out on the essential co-benefits of coordination—and sustained privatisation of digital transformations—as against the pursuit of more open digital goods—have tended to limit the potential for truly transformative investment.

Rapid evolution in the capacities and affordability of data, computing facilities, and computing power continues to inform new approaches to understanding and monitoring the contexts that shape urban health. The potential power of this digital step change can be seen, for instance, in recent initiatives in informal settlement mapping, gridded population mapping between censuses, urban health outcomes analysis, monitoring of web searches and social media for potential infectious disease outbreaks, and advances in digital wastewater surveillance of COVID-19, among others.¹²

Yet, these advances have also come with a wealth of challenges.¹³ For example, there is now a sizeable opportunity for policymakers and the multilateral sector to improve urban health by unlocking privately-held data—but this process raises many ethical and procedural questions.¹⁴ Bridging gaps and scaling up investments (including in capacity building) for digital public infrastructure (DPI) is critical and a core meeting point for local, multilateral, public and private influences, with significant potential for fostering more collaborative and internationalizable knowledge experimentation. This area is witnessing a flurry of activity both on the ground and in the multilateral context. Locally, key examples include digital payment systems like Mojaloop¹⁵; open-source software; digital health records; validation protocols; health-applicable universal IDs like the Modular Open Source Identity Platform (MOSIP), and others. In the multilateral sphere, coalitions and transnational initiatives are intensifying. For example, the new Co-Develop financing facility has recently been launched by the Digital Public Goods Alliance to support the procurement of open-source DPI solutions for LMICs. In short, there are opportunities and activities. Still, a more concerted effort is needed to concretise the promise of digital transformations for urban health and overcome the pressing challenges that remain evident.

Stepping up our capacity to leverage digital transformations to improve urban health requires overcoming several current challenges; these call equally for greater, more effective evidence generation and analysis and coordinated action and policymaking.

Contextualising transformative urban innovations remains an urgent priority: blanket transformations may not equitably bridge the digital gaps described above. To address inclusivity concerns head-on, digital transformations in urban health must provide urban dwellers with choice. Urban health equity is only truly embedded here if digital transformation leads to the right to choose and is not based on single services and unavoidably pre-determined systems. This can happen both in the health sector, specifically with greater integration in urban management, for instance, via better integrating equitable and inclusive telemedicine and e-health systems to bridge splintered urban inequalities, as well as in urban management and planning more generally, as with greater emphasis on digital health linked into the provision of a variety of culturally-sensitive modes of wellbeing in the ‘15 minute’ city.

Similarly, the pandemic has highlighted both the value and the limits of digital capacity to make accurate predictions in complex urban systems, for instance, in contexts of urban informality,¹⁶ and the still lingering limits of AI are re-stressing this. While data regulations and policies around the world are advancing, the realities of data governance and management remain challenging, leading to data siloes, quality issues and the inability to drive real-world insights in a rapid and replicable manner. A central challenge for practitioners and scholars alike is to acknowledge and tackle the inherent technological limitations in the digital revolution for urban health, with a more public and open discussion as to where we are not yet at pace with the change needed or where the technology is still lagging.

From this point of view, AI is an attractive option for modelling and predicting human behaviours and outcomes, especially in complex urban settings where rapid/early warning knowledge is emphasised. However, the complexity of AI methods, inputs, and error metrics limits their use by urban decision-makers due to a lack of ‘explainability’ and understandability¹⁷ (i.e. “black box” decisions made by models). Furthermore, many AI models are known to reproduce human biases based on the biased data with which they are presented. In turn, both urban governance and health systems around the world have varying levels of maturity and readiness to leverage AI. Nonetheless, if implemented appropriately, AI is currently the technology with the highest potential to drive health equity impacts thanks to its ability to derive real-world insights from health and non-health data.¹⁸

Lastly, urban governance confronts critical issues regarding the ownership of and access to data created in the digital urban transformation. Legal and technical considerations will both shape solutions in this area, yet, particularly in low-income and middle-income countries, many of the urban governance processes needed to empower urban dwellers to benefit fairly from this wealth of digital transformation are still missing. Critical, in our view, are processes of localisation and civil society engagement. All urban dwellers must be given a seat at the table to decide how their data is used, not just the residents who can access or afford a voice in local government. Relevant data may include an individual’s interaction with services or the operations of a taxpayer-funded service, even if private sector data benefits from local public infrastructure. For at least two decades, digital transformation in cities has predominantly been ‘supply-side’ driven and often sector-specific, with the private sector leading much of the advocacy for ‘smarter’ cities, yet modern digital innovation in urban health heralds more balanced growth coalitions and a more proactive role for the public and multilateral sectors. A recent World Economic Forum review¹⁹ underscored the need to confront urban digital gaps head-on by investing in capacity alongside technology and supporting cities to become ‘mature customers’, avoiding over-dependence on single suppliers or datasets and learning to navigate the pitfalls of AI-led data analytics.

While digital transformations in urban health have great potential for good, we should also be wary of how they are applied. For example, as satellite imagery and street-view images become higher-quality and more widely accessible to public health and development initiatives, risks can also increase, especially for the urban poor, as in the context of forced evictions and slum clearance. Organisations like Understanding Patient Data have facilitated bottom-up dialogue around these issues. Based on this type of advocacy, central governments have begun embracing critical digital transformation concepts, such as “fair value exchange,” to ensure that when public data is leveraged, mechanisms exist to return benefits to the local population.²⁰

Five key questions

Several key issues and related questions inevitably arise in a global agenda for digital transformations in urban health. First, how paradigmatic is digital transformation for cities? Is it, in fact, akin to the impact of innovation in municipal management in the 1800s? Are the changes that took place in and around COVID-19 the sanitary revolution of our time, providing a considerable step change in the way we manage not only urban health but cities in general?

Second, how should we understand the interplay between data, value, and public goods? The growing value of data is an essential factor in determining the direction of action in this context. The World Bank recently estimated that every dollar invested in data might generate, on average, over $ 32 of value.²¹ Evidence along these lines has prompted sizeable investments by public and private sectors in cities, but calls for data to be conceived as a public good have also become widespread and were further strengthened by the pandemic crisis. Is this a false dichotomy? How can we reconcile private sector innovation in urban health with the demands of digital rights coalitions and claims for technological sovereignty?²²

Third, can we address the ‘urban’ in urban health with greater nuance in the context of digital change? The ‘city’ may, in fact, often be the wrong scale descriptor and unit of analysis for urban health when it comes to digital transformation. The debate on the correct urban scale and the right urban systems we need to focus on is often mired in “methodological city-ism”,²³ and a greater capacity to apply urban sciences across diverse scales is critical today. We should be wary of replacing “methodological nationalism” (presuming the state as the reference point) with cities in urban health practice and research, and open up more directly to experimenting with diverse scales of action and urban viewpoints in our complex urban systems. Indeed, digital transformations have taken place at multiple interacting scales, both within the daily lives of individual urban dwellers and at the city-level, in the interactions among large systems of cities, and in urbanisation processes at scales ranging from local to global. This is a systems-oriented perspective. Whilst plenty of research and policy have focused on digital transformation as it relates to urban individuals, the underlying changes reshaping urban systems, urbanised societies, and interconnected urban neighbourhoods are equally crucial and perhaps represent even more impactful entry points for change.

Fourth, and relatedly, how do we manage the multi-scale interactions that are becoming increasingly essential to coordinating national, international, and transnational efforts? Multilevel coordination between urban innovation initiatives stemming from local, community and philanthropic levels is often dissociated from national systems and buy-in, creating problematic dynamics of central-local and local-multilateral coordination. Do nationalist, inward-looking responses to the pandemic and the rise of populist political divides represent a step back from the gains on cross-level integration? Examples of successful coordination in the climate domain—such as those presented by C40 Cities Climate Leadership Group or the Global Covenant of Mayors (GCoM)—abound and should provide a template for more explicit digital action in urban health, especially given long-standing city networking efforts by the health community like the various Healthy Cities Networks or the Partnership for Healthy Cities. We have ample evidence of the transformative impact that collaboration between cities can bring in terms of developing climate resilience, providing mutual support, and jointly representing a more powerful, coordinated voice on the world stage: how do we create a C40 for digital transformation in urban health?

Fifth, how can technology transformations work for the urban poor? Of the population added to the planet by 2050, 90% will live in African and Asian cities, and a majority will reside in deprived urban areas: how many will be left behind by current surveying methods and data? Passive data extraction (e.g., mobile phone location tracking, digital purchases, traffic movement, etc.) feeds Big Data sets which benefit political, social, and technological power-holders—rarely the urban poor. Open data initiatives such as OpenStreetMap have provided valuable platforms for the poorest to upload their data and thus articulate their existence and advocate for their needs. However, few slum dwellers possess the technical expertise or access to technology to utilise Big Data, or even common open-source datasets like OpenStreetMap. Thus, many feel exploited when it comes to data collection and use. While these issues are not restricted to the poor, they have the most profound impacts in this context; thus, as we work to ensure that digital transformation benefits the average urban dweller, we must seek especially to ensure that it works for the urban poor.

Conclusions: three priorities for digital transformations in urban health

Building on the above discussion, we identify three areas where well-orchestrated digital transformations can turn into sizeable wins for urban health. As noted above, these need to be tackled in an evidence-based way that enhances cities’ digital capacities and scales up relevant partnerships. We couch these as a practical agenda, not just to stress key areas needing greater investigation, but also to provide a tangible menu of opportunities the urban health community can directly build on through action research.