Results from FaME (Faecal Management Enterprises) - can dried faecal sludge fuel the sanitation service chain?

In Sub-Saharan Africa, sanitation needs for the majority of the urban population are met by onsite sanitation technologies. Cities grapple with management of faecal sludge (FS) once these technologies become full, while at the same time the urban economy is resource intensive. The FaME (Faecal Management Enterprises) project addressed both of these issues by identifying untapped markets for FS treatment products. Industries have a high fuel demand and FaME demonstrated that dried FS could be used as a solid combustible in industrial kilns. Existing treatment technologies were adapted for fuel production, and its application was demonstrated in two pilot kilns. Historically used as a soil conditioner, processing of FS to a solid biofuel could provide higher revenues, thereby providing a financial incentive for stakeholders to enhance FS management service along the entire sanitation chain

Swirl Flow Bioreactor coupled with Cu-alginate beads: A system for the eradication of Coliform and Escherichia coli from biological effluents.

It is estimated that approximately 1.1 billion people globally drink unsafe water. We previously reported both a novel copper-alginate bead, which quickly reduces pathogen loading in waste streams and the incorporation of these beads into a novel swirl flow bioreactor (SFB), of low capital and running costs and of simple construction from commercially available plumbing pipes and fittings. The purpose of the present study was to trial this system for pathogen reduction in waste streams from an operating Dewats system in Hinjewadi, Pune, India and in both simulated and real waste streams in Seattle, Washington, USA. The trials in India, showed a complete inactivation of coliforms in the discharged effluent (Mean Log removal Value (MLRV) = 3.51), accompanied by a total inactivation of E. coli with a MLRV of 1.95. The secondary clarifier effluent also showed a 4.38 MLRV in viable coliforms during treatment. However, the system was slightly less effective in reducing E. coli viability, with a MLRV of 1.80. The trials in Seattle also demonstrated the efficacy of the system in the reduction of viable bacteria, with a LRV of 5.67 observed of viable Raoultella terrigena cells (100%)

Patterns of multimorbidity in working Australians

Background: Multimorbidity is becoming more prevalent. Previously-used methods of assessing multimorbidity relied on counting the number of health conditions, often in relation to an index condition (comorbidity), or grouping conditions based on body or organ systems. Recent refinements in statistical approaches have resulted in improved methods to capture patterns of multimorbidity, allowing for the identification of nonrandomly occurring clusters of multimorbid health conditions. This paper aims to identify nonrandom clusters of multimorbidity.Methods: The Australian Work Outcomes Research Cost-benefit (WORC) study cross-sectional screening dataset (approximately 78,000 working Australians) was used to explore patterns of multimorbidity. Exploratory factor analysis was used to identify nonrandomly occurring clusters of multimorbid health conditions.Results: Six clinically-meaningful groups of multimorbid health conditions were identified. These were: factor 1: arthritis, osteoporosis, other chronic pain, bladder problems, and irritable bowel; factor 2: asthma, chronic obstructive pulmonary disease, and allergies; factor 3: back/neck pain, migraine, other chronic pain, and arthritis; factor 4: high blood pressure, high cholesterol, obesity, diabetes, and fatigue; factor 5: cardiovascular disease, diabetes, fatigue, high blood pressure, high cholesterol, and arthritis; and factor 6: irritable bowel, ulcer, heartburn, and other chronic pain. These clusters do not fall neatly into organ or body systems, and some conditions appear in more than one cluster.Conclusions: Considerably more research is needed with large population-based datasets and a comprehensive set of reliable health diagnoses to better understand the complex nature and composition of multimorbid health conditions