Cities are central to achieving the 2030 Agenda for Sustainable Development, yet many remain disengaged from the process. This paper examines nine city and subnational pilot projects conducted between 2015 and 2019, to assess the role of a data-based approach to governance in improving decision-making for sustainable development. We consider to what extent a data-based approach to governance can help cities in (a) localizing the sustainable development goals (SDGs); (b) integrating national and local datasets; (c) increasing openness of data and enabling better accountability for outcomes; and (d) encouraging innovation in data gathering. We find that data is considered a useful entry point for local sustainable development conversations and employing a focus on data management is welcomed by nearly all local governments, however, few localities explicitly focus on data to improve their sustainable development outcomes. Critically, despite the excitement around big data, most cities are unable to access them due to capacity challenges, data ownership, and privacy concerns.

2015 was a seismic moment for urban stakeholders around the world. A coalition of policymakers, academics and practitioners came together to successfully advocate for an urban goal to be included in the UN Sustainable Development Goal framework. Although the value of a place-based approach to development has been demonstrated by a number of cities and countries worldwide, it was 2020–2022 (three years of cataclysmic global events) that highlighted the necessity for a universal place-based approach to planning in order to foster resilience and sustainability. In this article, three academic-practitioners reflect upon the transformative potential of the 2015–16 urban agendas.

Achieving routine immunization for all children remains a major challenge in many low- and middle-income countries. In 2021, 18.1 million children globally missed their first dose of the diphtheria-tetanus-pertussis vaccine (DTP1), highlighting gaps in immunization and healthcare services. The Global Immunization Agenda 2030 aims for 90% coverage of essential childhood and adolescent vaccines and a 50% reduction in zero-dose children by 2030. However, national level data often obscures subnational variations, hampering the identification of unvaccinated children. Geographic access to healthcare is a key factor in vaccine uptake, but global comparative studies at the subnational level are rare, limiting our understanding of local vaccination behaviours and dynamics. This study estimates and maps the number and distribution of zero-dose children and their geographic access to healthcare services across 99 low- and middle-income countries. Using geospatial modelling approaches, we assessed geographic access to the nearest facility through two scenarios: walking and taking motorised transport. We quantified spatial inequalities of immunization at 1km spatial resolution and compared the patterns with healthcare access. Results show substantial variations, both between and within countries. Among the estimated 15.7 million zero-dose children across the studied countries, 39% lived more than one hour’s walking from a health facility, with Afghanistan (84%), Papua New Guinea (83%), Sudan (81%), and Cambodia (78%) showing the highest proportions. When figures were disaggregated to the district level, 33% of the districts across all 99 countries had more than 50% of their unvaccinated children living more than 2 hours from a health facility by foot. At the same time, many zero-dose children overall lived within 30 minutes of a health facility under a motorised scenario, indicating that proximity alone does not ensure vaccine uptake and that additional non-geographic barriers contribute to persistent zero-dose status. We provide a foundation for targeted vaccination strategies and interventions to bridge vaccination gaps and ensure equitable access to essential healthcare services. Assessing walking and motorised travel times highlight where geographic barriers contribute to low vaccine uptake, while also pointing to settings where other factors play a larger role. These findings show where tailored interventions such as outreach services, mobile clinics or new facility placement may be required for locations that are difficult to reach. They also highlight the need to consider local contexts where conflict, insecurity or weak health system performance limit the availability or quality of services, even when geographic access is not a major barrier. Addressing both geographic and nongeographic barriers will help ensure that the children most in need are reached, reducing vaccination gaps and improving equitable access to essential healthcare.

Population data at small area scales are essential for effective decision-making, influencing public health, disaster response, and resource allocation, amongst others. While national censuses remain the cornerstone of population data, they are often constrained by high costs, infrequent collection cycles, and coverage gaps, which can hinder timely data availability. To address these challenges, geospatial statistical approaches using limited microcensus surveys have been demonstrated as a reliable source, but the field has advanced substantially in recent years, with significant developments in both data sources and modelling methodologies. New approaches now leverage routine health intervention campaign data, satellite-derived settlement maps, and bespoke modelling approaches to produce reliable small area population estimates where enumeration is difficult or outdated. Various countries are applying these techniques to support census operations, health program planning, and humanitarian response. This manuscript reviews recent advances in ‘bottom-up’ population mapping approaches, highlighting innovations in input data, modelling methods, and validation techniques. We examine ongoing challenges, including partial observation of buildings under forest canopy, population displacement, and institutional uptake. Finally, we discuss emerging opportunities to enhance these approaches through better integration with traditional data ecosystems, capacity strengthening, and co-production with national institutions.