

@mastersthesis {6638,
	title = {Evaluating population-level effects of water, sanitation, and hygiene interventions: {Methods} and applications},
	year = {2014},
	note = {3640354},
	school = {University of California, Berkeley},
	type = {phdPh.{D}.},
	address = {Ann Arbor},
	abstract = {Background: Scientists and development stakeholders argue that health interventions proven effective in randomized efficacy trials should be translated into large-scale programs to benefit public health. Substantive evidence supports the scale-up of numerous health interventions, such as water, sanitation, and deworming interventions, and since the establishment of the Millennium Development Goals (MDGs) the funding and motivation for such scale-up has grown. In the field of water and sanitation, numerous interventions have been demonstrated to be efficacious in the reduction of diarrhea and soil-transmitted helminth infection. However, scaling up these interventions to regional or national levels frequently presents implementation challenges, and systematically studying the reasons for scale-up success or failure is essential to refine and sustain public health programs. Another important feature of scaling up interventions is determining how best to integrate interventions at scale and whether intervention delivery should be focused at the individual, household, or community level. Population attributable fraction (PAF) parameters and a new class of parameters which build upon the PAF can be used to estimate the effect of large-scale programs on population health. Evaluation of interventions at scale poses unique questions, and epidemiologic designs and analyses need to be tailored to answer these particular questions. Modern approaches to PAF estimation allow for parameter definition to be tailored one{\textquoteright}s particular research question and are well suited to the evaluation of population-level effects of large-scale health interventions. Methods: In this dissertation, I illustrate and apply methods to evaluate population-level effects of water, sanitation, and hygiene interventions. I specifically focus on methods for and applications with observational, cross-sectional data, and I discuss generalizations to other study designs. In the first chapter, I quantify the association between deworming, improved sanitation, and hygiene interventions and soil-transmitted helminths in a population in rural Bangladesh. I assess the potential for interactions between these interventions and explore associations at both the individual and village level. In the second chapter I assess the quality of implementation of a large-scale water, sanitation, and hygiene intervention implemented by UNICEF and the Government of Bangladesh in rural Bangladesh. It was found that this intervention did not meet most of its health and behavior targets in an interim evaluation. To help understand why, I envision a scenario in which implementation had been better in all areas, and I estimate how much outcomes may have changed under this scenario compared to the outcomes that were observed. In the third chapter, I discuss parameters appropriate for estimating population-level effects of health interventions. Specifically, I describe the estimation of the PAF and two modern parameters which build upon the PAF: the population intervention model and stochastic intervention model parameters. I provide a didactic description of the estimation of these parameters. Significance: This dissertation illustrates the use of rigorous methods to systematically evaluate the effect of individual and combined interventions at scale. Rigorous assessment of water, sanitation, and hygiene interventions is difficult, even for small-scale interventions, and very few large-scale WASH interventions have been evaluated rigorously. The parameters I illustrated and estimated in this dissertation have broad applicability to similar assessments of other large-scale public health programs. My findings contribute to the growing empirical evidence base describing best practices for and barriers to delivering interventions at scale. This evidence may contribute to improvements in design, delivery, and prioritization of interventions which in turn could increase the health impact of such interventions when delivered at scale.},
	keywords = {0308:Biostatistics, 0573:Public health, 0595:Water Resource Management, 0766:Epidemiology, Biological sciences, Biostatistics, Earth sciences, epidemiology, Health and environmental sciences, Helminths, Hygiene interventions:, Public health, Sanitation interventions:, Water interventions, Water Resource Management},
	url = {http://search.proquest.com/docview/1615412438?accountid=14270},
	author = {Benjamin-Chung, Jade De-Rong}
}
