Search

The Complex Urban Systems for Sustainability and Health (CUSSH) project is a global research programme on the complex systemic connections between urban development and health. Through transdisciplinary methods it will develop critical evidence on how to achieve the far-reaching transformation of cities needed to address vital environmental imperatives for planetary health in the 21st century. CUSSH’s core components include: (i) a review of evidence on the effects of climate actions (both mitigation and adaptation) and factors influencing their implementation in urban settings; (ii) the development and application of methods for tracking the progress of cities towards sustainability and health goals; (iii) the development and application of models to assess the impact on population health, health inequalities, socio-economic development and environmental parameters of urban development strategies, in order to support policy decisions; (iv) iterative in-depth engagements with stakeholders in partner cities in low-, middle- and high-income settings, using systems-based participatory methods, to test and support the implementation of the transformative changes needed to meet local and global health and sustainability objectives; (v) a programme of public engagement and capacity building. Through these steps, the programme will provide transferable evidence on how to accelerate actions essential to achieving population-level health and global climate goals through, amongst others, changing cities’ energy provision, transport infrastructure, green infrastructure, air quality, waste management and housing.

Cities produce more than 70% of global greenhouse gas emissions. Action by cities is therefore crucial for climate change mitigation as well as for safeguarding the health and wellbeing of their populations under climate change. Many city governments have made ambitious commitments to climate change mitigation and adaptation and implemented a range of actions to address them. However, a systematic record and synthesis of the findings of evaluations of the effect of such actions on human health and wellbeing is currently lacking. This, in turn, impedes the development of robust knowledge on what constitutes high-impact climate actions of benefit to human health and wellbeing, which can inform future action plans, their implementation and scale-up. The development of a systematic record of studies reporting climate and health actions in cities is made challenging by the broad landscape of relevant literature scattered across many disciplines and sectors, which is challenging to effectively consolidate using traditional literature review methods. This protocol reports an innovative approach for the systematic development of a database of studies of climate change mitigation and adaptation actions implemented in cities, and their benefits (or disbenefits) for human health and wellbeing, derived from peer-reviewed academic literature. Our approach draws on extensive tailored search strategies and machine learning methods for article classification and tagging to generate a database for subsequent systematic reviews addressing questions of importance to urban decision-makers on climate actions in cities for human health and wellbeing.

Climate change is already affecting health in populations around the world, threatening to undermine the past 50 years of global gains in public health. Health is not only affected by climate change via many causal pathways, but also by the emissions that drive climate change and their co-pollutants. Yet there has been relatively limited synthesis of key insights and trends at a global scale across fragmented disciplines. Compounding this, an exponentially increasing literature means that conventional evidence synthesis methods are no longer sufficient or feasible. Here, we outline a protocol using machine learning approaches to systematically synthesize global evidence on the relationship between climate change, climate variability, and weather (CCVW) and human health. We will use supervised machine learning to screen over 300,000 scientific articles, combining terms related to CCVW and human health. Our inclusion criteria comprise articles published between 2013 and 2020 that focus on empirical assessment of: CCVW impacts on human health or health-related outcomes or health systems; relate to the health impacts of mitigation strategies; or focus on adaptation strategies to the health impacts of climate change. We will use supervised machine learning (topic modeling) to categorize included articles as relevant to impacts, mitigation, and/or adaptation, and extract geographical location of studies. Unsupervised machine learning using topic modeling will be used to identify and map key topics in the literature on climate and health, with outputs including evidence heat maps, geographic maps, and narrative synthesis of trends in climate-health publishing. To our knowledge, this will represent the first comprehensive, semi-automated, systematic evidence synthesis of the scientific literature on climate and health.

Kristine Belesova and colleagues argue that recovery from the covid-19 pandemic must safeguard the health of current and future generations in the face of the climate emergency

Housing quality is crucially linked to health and sustainability goals, yet there is limited research on informal housing and settlements where housing quality is poor, and the health risks are expected to be greatest. This paper describes the investigation of housing conditions in a low-income resettlement colony in Delhi. A novel transdisciplinary methodology to evaluate multiple housing health hazards and establish intervention priorities in participation with the community was developed. Findings from housing surveys and indoor environmental monitoring were contrasted with a participatory self-assessment—revealing the widespread prevalence of hazards and suboptimal housing conditions as well as substantial differences in priorities, and thus perspectives, between participants and researchers. Focus group discussions explored the findings and built consensus on priorities. Our findings uncovered how poor housing conditions affect daily practices and thus are likely to adversely affect socio-economic development and gender equality. We highlight limitations in current frameworks to assess housing hazards and argue that a transdisciplinary approach is vital to provide a holistic understanding and to develop effective interventions. These insights are crucial to inform inclusive solutions for adequate housing and human settlements that can support improved health and help achieve the sustainable development goals. Electronic supplementary material The online version of this article (10.1007/s11524-020-00442-w) contains supplementary material, which is available to authorized users.

Background: Droughts affect around 52 million people globally each year, a figure that is likely to increase under climate change. Objectives: To assess the strength of empirical evidence on drought exposure as a risk factor for undernutrition in children

In subsistence farming populations of sub-Saharan Africa reliant on rainfed agriculture, years of low crop yields result in poorer child nutrition and survival. Estimates of such impacts are critical for their reduction and prevention. We developed a model to quantify such health impacts, and the degree to which they are attributable to weather variations, for a subsistence farming population in the Nouna district of Burkina Faso (89,000 people in 2010). The method combines data from a new weather-crop yield model with empirical epidemiological risk functions. We quantify the child mortality impacts for 1984-2012 using observed weather data and estimate potential future burdens in 2050 and 2100 using daily weather data generated by global climate models parameterized to simulate global warming of 1.5°C above pre-industrial levels. For 1984-2012, crop yields below 90% of the period average were estimated to result in the total of 109.8 deaths per 10,000 children

To tackle global challenges, research collaborations need to integrate multiple disciplinary perspectives and connect with local practices to find solutions that are sustainable and impactful. This paper discusses how participatory action research (PAR) is used as a framework for transdisciplinary collaboration to integrate different disciplines and identify healthy and sustainable housing solutions appropriate for local development practices and policy. By analyzing a transdisciplinary research collaboration investigating housing interventions for low‐income settlements in Delhi, reflections and recommendations are provided for other projects wishing to use a similar methodology. It is found that the PAR framework has successfully guided the integration of contrasting methods and improved the impact of research outcomes, resulting in the emergence of new shared practices. However, it proves to be challenging and requires heightened communication and engagement to achieve understanding between all disciplines and practices. It is recommended that focus is given to developing relationships and effective communication channels and that time should be preallocated for reflection. The work provides insights for integrating academic disciplines, the community, and relevant stakeholders in the cocreation of evidence that is paramount to formulate effective solutions to global challenges.

Background Private practitioners are the preferred first point of care in a majority of low and middle-income countries and in this position, best placed for the surveillance of diseases. However their contribution to routine surveillance data is marginal. This systematic review aims to explore evidence with regards to the role, contribution, and involvement of private practitioners in routine disease data notification. We examined the factors that determine the inclusion of, and the participation thereof of private practitioners in disease surveillance activities. Methods Literature search was conducted using the PubMed, Web of Knowledge, WHOLIS, and WHO-IRIS databases to identify peer-reviewed and gray full-text documents in English with no limits for year of publication or study design. Forty manuscripts were reviewed. Results The current participation of private practitioners in disease surveillance efforts is appalling. The main barriers to their participation are inadequate knowledge leading to unsatisfactory attitudes and misperceptions that influence their practices. Complicated reporting mechanisms with unclear guidelines, along with unsatisfactory attitudes on behalf of the government and surveillance program managers also contribute to the underreporting of cases. Infrastructural barriers especially the availability of computers and skilled human resources are critical to improving private sector participation in routine disease surveillance. Conclusion The issues identified are similar to those for underreporting within the Integrated infectious Disease Surveillance and Response systems (IDSR) which collects data mainly from public healthcare facilities. We recommend that surveillance program officers should provide periodic training, supportive supervision and offer regular feedback to the practitioners from both public as well as private sectors in order to improve case notification. Governments need to take leadership and foster collaborative partnerships between the public and private sectors and most importantly exercise regulatory authority where needed. Electronic supplementary material The online version of this article (doi:10.1186/s12913-017-2476-9) contains supplementary material, which is available to authorized users.

The Lancet Countdown: Tracking Progress on Health and Climate Change is an international, multi-disciplinary research collaboration between academic institutions and practitioners across the world. It follows on from the work of the 2015 Lancet Commission, which concluded that the response to climate change could be “the greatest global health opportunity of the 21st century”. The Lancet Countdown aims to track the health effects of climate change; health resilience and adaptation; health co-benefits of mitigation; climate economics and finance; and political and broader engagement. These focus areas form the five thematic working groups of the Lancet Countdown and represent different aspects of the complex relationships between health and climate change. These thematic groups will provide indicators for a global overview of health and climate change; national case studies highlighting countries leading the way or going against the trend; and engagement with a range of stakeholders. The Lancet Countdown ultimately aims to report annually on a series of indicators across these five working groups. This paper outlines these potential indicators and indicator domains to be tracked by the collaboration, with suggestions on the methodologies, and data sets available to achieve this end. The proposed indicator domains require further refinement, and mark the beginning of an ongoing consultation process – from November 2016 to early 2017 – to develop these domains, identify key areas not currently covered, and change indicators where necessary. It will actively seek to engage with existing monitoring processes, such as the UN Sustainable Development Goals, and the World Health Organization’s Climate and Health Country Profiles. Additionally, the indicators will evolve throughout their lifetime through ongoing collaboration with experts and a range of stakeholders, and dependent on the emergence of new evidence and knowledge. During the course of its work, the Lancet Countdown will adopt a collaborative and iterative process, which aims to complement existing initiatives, welcome engagement with new partners, and be open to developing new research projects on health and climate change.

Background Reduction of child undernutrition is one of the Sustainable Development Goals for 2030. Achievement of this goal may be made more difficult in some settings by climate change through adverse impact on agricultural productivity. However, there is only limited quantitative evidence on the link between household crop harvests and child nutrition. We examined this link in a largely subsistence farming population in rural Burkina Faso. Methods Data on the middle-upper arm circumference (MUAC) of 975 children ≤5 years of age, household crop yields, and other parameters were obtained from the Nouna Health and Demographic Surveillance System. Multilevel modelling was used to assess the relationship between MUAC and the household crop harvest in the year 2009 estimated in terms of kilocalories per adult equivalent per day (kcal/ae/d). Results Fourteen percent of children had a MUAC