Post-project assessment and follow-up support for community managed rural water systems in Panama

The Environmental Health (EH) program of Peace Corps (PC) Panama and a non-governmental organization (NGO) Waterlines have been assisting rural communities in Panama gain access to improved water sources through the practice of community management (CM) model and participatory development. Unfortunately, there is little information available on how a water system is functioning once the construction is complete and the volunteer leaves the community. This is a concern when the recent literature suggests that most communities are not able to indefinitely maintain a rural water system (RWS) without some form of external assistance (Sara and Katz, 1997; Newman et al, 2002; Lockwood, 2002, 2003, 2004; IRC, 2003; Schweitzer, 2009). Recognizing this concern, the EH program director encouraged the author to complete a postproject assessment of the past EH water projects. In order to carry out the investigation, an easy to use monitoring and evaluation tool was developed based on literature review and the author’s three years of field experience in rural Panama. The study methodology consists of benchmark scoring systems to rate the following ten indicators: watershed, source capture, transmission line, storage tank, distribution system, system reliability, willingness to pay, accounting/transparency, maintenance, and active water committee members. The assessment of 28 communities across the country revealed that the current state of physical infrastructure, as well as the financial, managerial and technical capabilities of water committees varied significantly depending on the community. While some communities are enjoying continued service and their water committee completing all of its responsibilities, others have seen their water systems fall apart and be abandoned. Overall, the higher score were more prevalent for all ten indicators. However, even the communities with the highest scores requested some form of additional assistance. The conclusion from the assessment suggests that the EH program should incorporate an institutional support mechanism (ISM) to its sector policy in order to systematically provide follow-up support to rural communities in Panama. A full-time circuit rider with flexible funding would be able to provide additional technical support, training and encouragement to those communities in need.

Genetic association studies under the population stratification, family pedigree and application to genome-wide association studies

This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.