Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

One of the major consequences of Africa's rapid urbanisation is the worsening air pollution, especially in urban centres. However, existing societal challenges such as recovery from the COVID-19 pandemic, poverty, intensifying effects of climate change are making prioritisation of addressing air pollution harder. We undertook a scoping review of strategies developed and/or implemented in Africa to provide a repository to stakeholders as a reference that could be applied for various local contexts. The review includes strategies assessed for effectiveness in improving air quality and/or health outcomes, co-benefits of the strategies, potential collaborators, and pitfalls. An international multidisciplinary team convened to develop well-considered research themes and scope from a contextual lens relevant to the African continent. From the initial 18,684 search returns, additional 43 returns through reference chaining, contacting topic experts and policy makers, 65 studies and reports were included for final analysis. Three main strategy categories obtained from the review included technology (75%), policy (20%) and education/behavioural change (5%). Most strategies (83%) predominantly focused on household air pollution compared to outdoor air pollution (17%) yet the latter is increasing due to urbanisation. Mobility strategies were only 6% compared to household energy strategies (88%) yet motorised mobility has rapidly increased over recent decades. A cost effective way to tackle air pollution in African cities given the competing priorities could be by leveraging and adopting implemented strategies, collaborating with actors involved whilst considering local contextual factors. Lessons and best practices from early adopters/implementers can go a long way in identifying opportunities and mitigating potential barriers related to the air quality management strategies hence saving time on trying to "reinvent the wheel" and prevent pitfalls. We suggest collaboration of various stakeholders, such as policy makers, academia, businesses and communities in order to formulate strategies that are suitable and practical to various local contexts.

Health Impact Assessments (HIAs) motivate effective measures for safeguarding public health. There is consensus that HIAs in low and middle-income countries (LMICs) are lacking, but no study systematically focuses on those that have been successfully conducted across all regions of the world, nor do they highlight factors that may enable or hinder their implementation. Our objectives are to (1) systematically review, geographically map, and characterize HIA activity in LMICs; and (2) apply a process evaluation method to identify factors which are important to improve HIA implementation in LMICs. A systematic review of peer-reviewed HIAs in 156 LMICs was performed in Scopus, Medline, Web of Science, Sociological abstracts, and LILACs (Latin American and Caribbean Health Sciences) databases. The search used PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and covered HIAs across all type of interventions, topics, and health outcomes. HIAs were included if they reported a clear intervention and health outcome to be assessed. No time restriction was applied, and grey literature was not included. The eligible studies were subjected to six process evaluation criteria. The search yielded 3178 hits and 57 studies were retained. HIAs were conducted in 26 out of 156 countries. There was an unequal distribution of HIAs across regions and within LMICs countries. The leading topics of HIA in LMICs were air pollution, development projects, and urban transport planning. Most of the HIAs reported quantitative approaches (72%), focused on air pollution (46%), appraised policies (60%), and were conducted at the city level (36%). The process evaluation showed important variations in the way HIAs have been conducted and low uniformity in the reporting of six criteria. No study reported the time, money, and staff used to perform HIAs. Only 12% of HIAs were based on participatory approaches; 92% of HIAs considered multiple outcomes; and 61% of HIAs provided recommendations and fostered cross-national collaboration. The limited transparency in process, weak participation, and inconsistent delivery of recommendations were potential limitations to HIA implementation in low and middle-income countries. Scaling and improving HIA implementation in low and middle-income countries in the upcoming years will depend on expanding geographically by increasing HIA governance, adapting models and tools in quantitative methods, and adopting better reporting practices.

Policy decisions and urban governance are being influenced by an emergence of data from internet of things (IoT), which forms the backbone of Smart Cities, giving rise to Big Data which is processed and analyzed by Artificial Intelligence models at speeds unknown to mankind decades ago. This is providing new ways of understanding how well cities perform, both in terms of economics as well as in health. However, even though cities have been increasingly digitalized, accelerated by the concept of Smart Cities, the exploration of urban health has been limited by the interpretation of sensor data from IoT devices, omitting the inclusion of data from human anatomy and the emergence of biological data in various forms. This paper advances the need for expanding the concept of Big Data beyond infrastructure to include that of urban health through human anatomy; thus, providing a more cohesive set of data, which can lead to a better knowledge as to the relationship of people with the city and how this pertains to the thematic of urban health. Coupling both data forms will be key in supplementing the contemporary notion of Big Data for the pursuit of more contextualized, resilient, and sustainable Smart Cities, rendering more liveable fabrics, as outlined in the Sustainable Development Goal (SDG) 11 and the New Urban Agenda.

The GoGreenRoutes project aims to introduce co-created nature-based solutions (NBS) to enhance environmental quality in six medium-sized cities (Burgas, Lahti, Limerick, Tallinn, Umeå, and Versailles). We estimated the mortality and economic impacts attributed to suboptimal exposure to green space and air pollution, economic impacts, and the distribution thereof the adult population by socioeconomic status. We retrieved data from publicly accessible databases on green space (NDVI and % Green Area), air pollution (NO₂ and PM_2.5) and population (≥20 years, n = 804,975) at a 250m × 250m grid-cell level, and mortality for each city for 2015. We compared baseline exposures at the grid-cell to World Health Organization's recommendations and guidelines. We applied a comparative risk assessment to estimate the mortality burden attributable to not achieving the recommendations and guidelines. We estimated attributable mortality distributions and the association with income levels. We found high variability in air pollution and green spaces levels. Around 60% of the population lacked green space and 90% were exposed to harmful air pollution. Overall, we estimated age-standardized mortality rates varying from 10 (Umeå) to 92 (Burgas) deaths per 100,000 persons attributable to low NDVI levels; 3 (Lahti) to 38 (Burgas) per 100,000 persons to lack of % Green Area; 1 (Umeå) to 88 (Tallinn) per 100,000 persons to exceedances of NO₂ guidelines; and 1 (Umeå) to 206 (Burgas) per 100,000 persons to exceedances of PM_2.5 guidelines. Lower income associated with higher or lower mortality impacts depending on whether deprived populations lived in the densely constructed, highly-trafficked city centre or greener, less polluted outskirts. We attributed a considerable mortality burden to lack of green spaces and higher air pollution, which was unevenly distributed across different social groups. NBS and health-promoting initiatives should consider socioeconomic aspects to regenerate urban areas while providing equally good environments.

The increasing availability and capabilities of mobile phones make them a feasible means of data collection. Electronic Data Capture (EDC) systems have been used widely for public health monitoring and surveillance activities, but documentation of their use in complicated research studies requiring multiple systems is limited. This paper shares our experiences of designing and implementing a complex multi-component EDC system for a community-based four-armed cluster-Randomised Controlled Trial in the rural plains of Nepal, to help other researchers planning to use EDC for complex studies in low-income settings. We designed and implemented three interrelated mobile phone data collection systems to enrol and follow-up pregnant women (trial participants), and to support the implementation of trial interventions (women’s groups, food and cash transfers). 720 field staff used basic phones to send simple coded text messages, 539 women’s group facilitators used Android smartphones with Open Data Kit Collect, and 112 Interviewers, Coordinators and Supervisors used smartphones with CommCare. Barcoded photo ID cards encoded with participant information were generated for each enrolled woman. Automated systems were developed to download, recode and merge data for nearly real-time access by researchers. The systems were successfully rolled out and used by 1371 staff. A total of 25,089 pregnant women were enrolled, and 17,839 follow-up forms completed. Women’s group facilitators recorded 5717 women’s groups and the distribution of 14,647 food and 13,482 cash transfers. Using EDC sped up data collection and processing, although time needed for programming and set-up delayed the study inception. EDC using three interlinked mobile data management systems (FrontlineSMS, ODK and CommCare) was a feasible and effective method of data capture in a complex large-scale trial in the plains of Nepal. Despite challenges including prolonged set-up times, the systems met multiple data collection needs for users with varying levels of literacy and experience.