Using contingent valuation to estimate willingness to pay for improved water source in rural Uganda

This research was conducted in August of 2011 in the villages of Kigisu and Rubona in rural Uganda while the author was serving as a community health volunteer with the U.S. Peace Corps. The study used the contingent valuation method (CVM) to estimate the populations’ willingness to pay (WTP) for the operation and maintenance of an improved water source. The survey was administered to 122 households out of 400 in the community, gathering demographic information, health and water behaviors, and using an iterative bidding process to estimate WTP. Households indicated a mean WTP of 286 Ugandan Shillings (UGX) per 20 liters for a public tap and 202 UGX per 20 liters from a private tap. The data were also analyzed using an ordered probit model. It was determined that the number of children in the home, and the distance from the existing source were the primary variables influencing households’ WTP.

Retrofitting boreholes contaminated with iron in rural Uganda

During my Peace Corps service as a community health liaison in rural Uganda I noticed that many improved water wells in our area had been abandoned. The communities described the water in these wells as being reddish in color, having a foul taste and odor, discoloring clothes and food, and not able to produce lather for washing. Personal investigations and an initial literature search suggested that the primary contaminant was iron. The water in these wells had a low pH and a rusty metallic smell. The water produced early in the morning appeared very red but the water became more transparent as pumping continued. The iron components of many of these wells experienced accelerated corrosion resulting in frequent pump failure. This rapid corrosion coupled with the timing of the onset of iron contamination (months to years after these wells were completed) suggests that the most likely cause of the poor quality water was iron related bacteria and/or sulphate reducing bacteria. This report describes a remedy for iron contamination employed at 5 wells. The remedy involved disinfecting the wells with chlorine and replacing iron pump components with plastic and stainless steel. Iron concentrations in the wells were less than 1 mg/L when the wells were drilled but ranged from 2.5 to 40 mg/L prior to the remedy. After the remedy was applied, the total iron concentrations returned to levels below 1 mg/L. The presence of iron related bacteria was measured in all of these wells using Biological Activity Reaction Tests. Although IRB are still present in all the wells, the dissolved iron concentrations remain less than 1 mg/L. This remedy is practical for rural areas because the work can be performed with only hand tools and costs less than US $850. Because the source of iron contamination is removed in this approach, substantial follow-up maintenance is not necessary.

POST-PROJECT ASSESSMENT OF PIT LATRINES IN RURAL PANAMA

In Panama, one of the Environmental Health (EH) Sector’s primary goals is to improve the health of rural Panamanians by helping them to adopt behaviors and practices that improve access to and use of sanitation systems. In complying with this goal, the EH sector has used participatory development models to improve hygiene and increase access to latrines through volunteer managed latrine construction projects. Unfortunately, there is little understanding of the long term sustainability of these interventions after the volunteers have completed their service. With the Peace Corps adapting their Monitoring, Reporting, and Evaluation procedures, it is appropriate to evaluate the sustainability of sanitation interventions offering recommendations for the adaptions of the EH training program, project management, and evaluation procedures. Recognizing the need for evaluation of past latrine projects, the author performed a post project assessment of 19 pit latrine projects using participatory analysis methodologies. First, the author reviewed volunteers’ perspectives of pit latrine projects in a survey. Then, for comparison, the author performed a survey of latrine projects using a benchmarking scoring system to rate solid waste management, drainage, latrine siting, latrine condition, and hygiene. It was observed that the Sanitation WASH matrix created by the author was an effective tool for evaluating the efficacy of sanitation interventions. Overall more than 75%, of latrines constructed were in use. However, there were some areas where improvements could be made for both latrine construction and health and hygiene. The latrines scored poorly on the indicators related to the privacy structure and seat covers. Interestingly those are the two items least likely to be included in project subsidies. Furthermore, scores for hygiene-related indicators were low; particularly those related to hand washing and cleanliness of the kitchen, indicating potential for improvement in hygiene education. Based on these outcomes, the EH sector should consider including subsidies and standardized designs for privacy structures and seat covers for latrines. In addition, the universal adoption of contracts and/or deposits for project beneficiaries is expected to improve the completion of latrines. In order to address the low scores in the health and hygiene indicators, the EH sector should adapt volunteer training, in addition to standardizing health and hygiene intervention procedures. In doing so, the sector should mimic the Community Health Club model that has shown success in improving health and hygiene indicators, as well as use a training session plan format similar to those in the Water Committee Seminar manual. Finally, the sector should have an experienced volunteer dedicated to program oversight and post-project monitoring and evaluation.

A cold blizzard was raging, but the light shone brightly' : social networks presented in stained glass within an industrial community

Historical stained glass in Calumet and Laurium revealed the complex structures of these industrial communities. Creating an Industrial Archaeology-focused approach, I examined stained glass as material culture. Sacred glass revealed ethnic and religious values of a congregation through the style, iconography, and quality of the glasswork. Residential glass showed how owners represented themselves within cultural settings by meeting social expectations. Commercial glass indicated community status of owners through discreet and artistic shows of wealth and taste. Corporate glass displayed prosperity and belonging through the superior quality and cost of the glasswork. Viewing stained glass as material culture opened new methods of looking at both stained glass and industrial communities. Findings from my research can teach the public about the importance of preserving and conserving stained glass, and that can lead to greater public appreciation for the material culture found within these industrial communities.

MODULARITY BASED FUZZY COMMUNITY DETECTION IN SOCIAL NETWORKS

Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.