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Climate change is increasing the severity and the frequency of natural hazards and associated disasters worldwide, yet there is little data tracking how and whether it is being addressed by humanitarian assistance initiatives. Drawing on publicly available United Nations programme data and vulnerability indexes, this study pilots a novel approach to identifying and quantifying the prevalence of climate change-related humanitarian programmes from 2016-18 in five disaster-affected countries. The funding levels of proposed and undertaken interventions were analysed within specific programmatic sub-areas and across clusters. The study found that 1.8 per cent (99 of 5,558) of projects included in humanitarian proposals reviewed during the research have a climate change-related component. Of 1,361 funded projects, 40 of these were climate change-related and received funding. The methodologies tested here to assess and classify climate change-related humanitarian programmes could be expanded to support further tracking of humanitarian responses to climate change across operational contexts.

This report is a synthesis of the technical assistance (TA) and recommendations, carried out by the World Bank water and sanitation program (WSP) since September 2014. To achieve the target of 100 percent improved sanitation, there is a national drive to improve fecal sludge management (FSM). This TA recognizes that to achieve the goals it is necessary to support the development of national FSM policies, regulations, and guidelines, while also improving capacity at the local level by supporting the implementation of improved FSM models in target cities. The objective of the TA was to provide government with tested advice on how to scale up improved septage management nationwide through: (i) improvement of septage management in three cities through the application of new management models (local level); and (ii) assistance to national government in training and capacity building and the formulation of policies and regulations to improve septage management at scale (national level). This report is structured as follows: chapter one is the executive summary; chapter two gives the background to sanitation in Indonesia and to fecal sludge management in particular; chapter three provides an overview of the TA approach; chapter four gives details of the implementation of the TA; chapter five summarizes the lessons learned; and chapter six outlines the recommendations and next steps.

This paper analyzes the socioeconomic, fiscal, and governance impact of gold mining in Mali. The analysis finds that, at the national level, mining plays an important role by contributing to export earnings and overall government fiscal revenue. In 2013, the mining sector represented 7 percent of gross domestic product, contributed 1.5 percent to growth in total gross domestic product, and accounted for 65 percent of total export earnings and 25 percent of total government budget revenues. At the local level, despite higher population growth, there is some evidence that outcomes (poverty and infrastructure services) are marginally better in mining communes compared with non-mining communes. Local governments receive fiscal windfalls that are spent significantly on education capital expenditures and current expenditures (salaries and non-salaries). Non-salary current expenditures are 10 times higher in mining areas. Analysis of the political economy of public service provision at the local level suggests that technical or absorptive capacities may be the bottleneck to increasing the local benefit of mining instead of corruption or accountability.

The study reported here describes the links between non-farm employment and child nutritional status in rural coastal Kenya using a model adapted from an operational model commonly used in nutrition planning. Four studies were conducted in 1994 and 1995 in a community in Kwale district. Three of these studies were nonfarm employment and subsistence food production, household income and food accessibility, and maternal employment and child care and house health environment. The findings of these three studies were used in the design of the fourth study which assessed the whole model.Households which combined both NFE and agricultural sources of income had higher total incomes than those which depended on only one source. The relation between non-farm employment and nutritional status was weak. There was a positive relation between household income and the level of household food expenditure, which, in turn, was positively associated with long-term nutritional status of children. Higher energy intake was associated with food diversity and increased with income level. The sources of differences in food diversity within income groups were not sought. Household income and time spent in the non-farm activities per woman had no direct linear effects on the components of child care. However, income did affect housing quality, while time affected household sanitation/hygiene. Maternal employment had no effect on the components of child care and household-living conditions when controlling for the age of the youngest child, mother's education and household income. This is attributed to the fact that the mother had a lot of "spare time". Hence, this analysis suggests that non-farm employment can open an opportunity to provide for enhanced child's long-term nutritional status through the effect of total income on nutrient intake and through purchased goods that improve housing quality. Women's time in non-farm employment, although affecting house sanitation/hygiene, does not have to compromise the nutritional status of children. It is concluded that the framework used by households to allocate their resources of time and income is different from the framework used for programming and policy development. The role of non-economic factors in the difference between two frameworks is suggested as a focus for future research.

The study reported here describes the links between non-farm employment and child nutritional status in rural coastal Kenya using a model adapted from an operational model commonly used in nutrition planning. Four studies were conducted in 1994 and 1995 in a community in Kwale district. Three of these studies were nonfarm employment and subsistence food production, household income and food accessibility, and maternal employment and child care and house health environment. The findings of these three studies were used in the design of the fourth study which assessed the whole model.Households which combined both NFE and agricultural sources of income had higher total incomes than those which depended on only one source. The relation between non-farm employment and nutritional status was weak. There was a positive relation between household income and the level of household food expenditure, which, in turn, was positively associated with long-term nutritional status of children. Higher energy intake was associated with food diversity and increased with income level. The sources of differences in food diversity within income groups were not sought. Household income and time spent in the non-farm activities per woman had no direct linear effects on the components of child care. However, income did affect housing quality, while time affected household sanitation/hygiene. Maternal employment had no effect on the components of child care and household-living conditions when controlling for the age of the youngest child, mother's education and household income. This is attributed to the fact that the mother had a lot of "spare time". Hence, this analysis suggests that non-farm employment can open an opportunity to provide for enhanced child's long-term nutritional status through the effect of total income on nutrient intake and through purchased goods that improve housing quality. Women's time in non-farm employment, although affecting house sanitation/hygiene, does not have to compromise the nutritional status of children. It is concluded that the framework used by households to allocate their resources of time and income is different from the framework used for programming and policy development. The role of non-economic factors in the difference between two frameworks is suggested as a focus for future research.