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Global sustainable development goals call for universal access to safely managed sanitation by 2030. Here, we demonstrate methods to estimate the financial requirements for meeting this commitment in urban settings of low-income countries. Our methods considered two financial requirements: (i) the subsidies needed to bridge the gap between the willingness-to-pay of low-income households and actual market prices of toilets and emptying services and (ii) the amounts needed to expand the municipal waste management infrastructure for unserved populations. We applied our methods in five cities- Kisumu, Malindi, Nakuru in Kenya; Kumasi in Ghana; and Rangpur in Bangladesh and compared three to five sanitation approaches in each city. We collected detailed cost data on the sanitation infrastructure, products, and services from 76 key informants across the five cities, and we surveyed a total of 2381 low-income households to estimate willingness-to-pay. We found that the total financial requirements for achieving universal sanitation in the next 10 years and their breakdown between household subsidies and municipal infrastructure varied greatly between sanitation approaches. Across our study cities, sewerage was the costliest approach (total financial requirements of 16-24 USD/person/year), followed by container-based sanitation (10-17 USD/person/year), onsite sanitation (2-14 USD/person/year), and mini-sewers connecting several toilets to communal septic tanks (3-5 USD/person/year). Further applications of our methods can guide sanitation planning in other cities.

Information about microbial water quality is critical for managing water safety and protecting public health. In low-income countries, monitoring all drinking water supplies is impractical because financial resources and capacity are insufficient. Data sets derived from satellite imagery, census, and hydrological models provide an opportunity to examine relationships between a suite of environmental risk factors and microbial water quality over large geographical scales. We investigated the relationships between groundwater fecal contamination and different environmental parameters in Uganda and Bangladesh. In Uganda, groundwater contamination was associated with high population density ( p < 0.001; OR = 1.27), high cropland coverage ( p < 0.001; OR = 1.47), high average monthly precipitation ( p < 0.001; OR = 1.14), and high surface runoff ( p < 0.001; OR = 1.37), while low groundwater contamination was more likely in areas further from cities ( p < 0.001; OR = 0.66) and with higher forest coverage ( p < 0.001; OR = 0.70). In Bangladesh, contamination was associated with higher weekly precipitation ( p < 0.001; OR = 1.44) and higher livestock density (p = 0.05; OR = 1.11), while low contamination was associated with low forest coverage ( p < 0.001; OR = 1.23) and high cropland coverage ( p < 0.001; OR = 0.80). We developed a groundwater contamination index for each country to help decision-makers identify areas where groundwater is most prone to fecal contamination and prioritize monitoring activities. Our approach demonstrates how to harness satellite-derived data to guide water safety management.