This article explores the implications for human health of local interactions between disease, ecosystems and livelihoods. Five interdisciplinary case studies addressed zoonotic diseases in African settings: Rift Valley fever (RVF) in Kenya, human African trypanosomiasis in Zambia and Zimbabwe, Lassa fever in Sierra Leone and henipaviruses in Ghana. Each explored how ecological changes and human–ecosystem interactions affect pathogen dynamics and hence the likelihood of zoonotic spillover and transmission, and how socially differentiated peoples’ interactions with ecosystems and animals affect their exposure to disease. Cross-case analysis highlights how these dynamics vary by ecosystem type, across a range from humid forest to semi-arid savannah; the significance of interacting temporal and spatial scales; and the importance of mosaic and patch dynamics. Ecosystem interactions and services central to different people's livelihoods and well-being include pastoralism and agro-pastoralism, commercial and subsistence crop farming, hunting, collecting food, fuelwood and medicines, and cultural practices. There are synergies, but also tensions and trade-offs, between ecosystem changes that benefit livelihoods and affect disease. Understanding these can inform ‘One Health’ approaches towards managing ecosystems in ways that reduce disease risks and burdens.This article is part of the themed issue ‘One Health for a changing world: zoonoses, ecosystems and human well-being’.

Salinity gradient power (or blue energy) is a renewable energy source mentioned in the literature since the 1950s. It refers to the production of electricity by mixing of two solutions with different salt concentrations, for example river and sea water. The global potential of salinity power has been estimated in the 1970s as substantial, but the state of membrane technology at that time-crucial for energy recovery-did not permit the practical use of this resource. More recently, the interest in salinity power has been growing because of the need for carbon neutral, renewable sources of electricity. This study aims to assess the potential of salinitygradient power for reducing emissions of CO 2 and non-CO 2 greenhouse gases. First, we discuss the global technical potential for blue energy, i.e. the maximum amount of energy that could be retrieved at the current state of technology. We focus on rivers as source of fresh water and seas as source of saline water. The analysis is based on global datasets of annual river discharges for more than 5000 world rivers. The resulting estimates of global and regional potentials for salinity gradient power are used to estimate the potential for reducing greenhouse gases, assuming that salinity power would reduce the need for fossil fuels. The results are shown for global totals, regional totals and selected rivers.

Background: Previous analyses have shown the individual correlations between poverty, health and satellitederived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI.Methods: In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa.Results: This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. Conclusions:These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality.

BackgroundThis paper presents a new agent-based model (ABM) for investigating T. b. rhodesiense human African trypanosomiasis (rHAT) disease dynamics, produced to aid a greater understanding of disease transmission, and essential for development of appropriate mitigation strategies.MethodsThe ABM was developed to model rHAT incidence at a fine spatial scale along a 75 km transect in the Luangwa Valley, Zambia. The method offers a complementary approach to traditional compartmentalised modelling techniques, permitting incorporation of fine scale demographic data such as ethnicity, age and gender into the simulation.ResultsThrough identification of possible spatial, demographic and behavioural characteristics which may have differing implications for rHAT risk in the region, the ABM produced output that could not be readily generated by other techniques. On average there were 1.99 (S.E. 0.245) human infections and 1.83 (S.E. 0.183) cattle infections per 6 month period. The model output identified that the approximate incidence rate (per 1000 person-years) was lower amongst cattle owning households (0.079, S.E. 0.017), than those without cattle (0.134, S.E. 0.017). Immigrant tribes (e.g. Bemba I.R. = 0.353, S.E.0.155) and school-age children (e.g. 5–10 year old I.R. = 0.239, S.E. 0.041) were the most at-risk for acquiring infection. These findings have the potential to aid the targeting of future mitigation strategies.ConclusionABMs provide an alternative way of thinking about HAT and NTDs more generally, offering a solution to the investigation of local-scale questions, and which generate results that can be easily disseminated to those affected. The ABM can be used as a tool for scenario testing at an appropriate spatial scale to allow the design of logistically feasible mitigation strategies suggested by model output. This is of particular importance where resources are limited and management strategies are often pushed to the local scale.

Difficulties accessing homeownership and reduced rates of owner-occupation among recent birth cohorts are a major concern for Global North policymakers. However, surprisingly little is known about how patterns of entry into homeownership have varied spatially across the early lives of recent birth cohorts. Using life course perspectives and survey data, this study examines how regional disparities in homeownership trajectories and transitions have varied across the life courses of four birth cohorts who entered the British housing system after 1990. The results show a nonlinear pattern of postponed homeownership across cohorts which has not varied greatly across regions. London is the most distinctive area and delayed homeownership transitions have long been a feature of the capital's housing market. Taken together, the findings illustrate the value of more thoroughly examining how place intersects with biographical and historical time in nuanced ways to shape housing careers.