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My research interests include policy informatics and decision making, modeling in policy analysis and management decisions, public health management and policy, and the role of public value in policy development. I am particularly interested in less mainstream approaches to modeling that account for learning, feedback, and other systems dynamics. I include Bayesian inference, agent-based models, and behavioral assumptions in both my research and teaching.
In my dissertation research, I conceptualize state Medicaid programs as complex adaptive systems characterized by diverse actors, behaviors, relationships, and objectives. These systems reproduce themselves through both strategic and emergent mechanisms of program management. I focus on the mechanism by which citizens are sorted into or out of the system: program enrollment. Using Bayesian regression and agent-based models, I explore the role of administrative practices (such as presumptive eligibility and longer continuous eligibility periods) in increasing enrollment of eligible citizens into Medicaid programs.
I received my BSc, MSc, and PhD from the University of Nottingham. My PhD focuses on the Agent-Based Modelling and Simulation (ABMS) of Public Goods Game (PGG) in Economics. In my thesis, a development framework was developed using software-engineering methods to provide a structured approach to the development process of agent-based social simulations. Also as a case study, the framework was used to design and implement a simulation of PGG in the continuous-time setting which is rarely considered in Economics.
In 2017, I joined international, inter-disciplinary project CASCADE (Calibrated Agent Simulations for Combined Analysis of Drinking Etiologies) to further pursue my research interest in strategic modelling and simulation of human-centred complex systems. CASCADE, funded by the US National Institutes of Health (NIH), aims to develop agent-based models and systems-based models of the UK and US populations for the sequential and linked purposes of testing theories of alcohol use behaviors, predicting population alcohol use patterns, predicting population-level alcohol outcomes and evaluating the impacts of policy interventions on alcohol use patterns and harmful outcomes.
Aniruddha Belsare is a disease ecologist with a background in veterinary medicine, interspecific transmission, pathogen modeling and conservation research. Aniruddha received his Ph.D. in Wildlife Science (Focus: Disease Ecology) from the University of Missouri in 2013 and subsequently completed a postdoctoral fellowship there (University of Missouri, May 2014 – June 2017). He then was a postdoctoral fellow in the Center for Modeling Complex Interactions at the University of Idaho (June 2017 - March 2019) and later a Research Associate with the Boone and Crockett Quantitative Wildlife Center, Michigan State University (March 2019 - Jan 2021). He was a Research Scientist in the Civitello Disease Ecology Lab at Emory University from Jan 2021 to Jan 2023. Currently, Aniruddha is an Assistant Professor of Disease Ecology at the College of Forestry, Wildlife & Environment / College of Veterinary Medicine at Auburn University.
My research interests primarily lie at the interface of ecology and epidemiology, and include host-pathogen systems that are of public health or conservation concern. I use ecologic, epidemiologic and model-based investigations to understand how pathogens spread through, persist in, and impact host populations. Animal disease systems that I am currently working on include canine rabies, leptospirosis, chronic wasting disease, bighorn sheep pneumonia, raccoon roundworm (Baylisascaris procyonis), chytridiomycosis, and Lyme disease.
Ms. Stringfellow is a PhD candidate whose goal is to identify ways to build and leverage the natural support systems of people who are experiencing problems related to their illicit drug use. Her current interest is in how these support systems operate in small towns with limited formal resources for quitting. To that end, she recently began conducting in-depth qualitative interviews for her dissertation in a semi-rural county in eastern Missouri. These interviews will be used to build an agent-based model, a type of dynamic simulation modeling that can be used to represent heterogeneous actors with multiple goals and perceptions. As a research assistant and dissertation fellow with the Social System Design Lab, she has also been trained in system dynamics, an aggregate-level dynamic simulation modeling method.
Prior to joining the PhD program, she worked as a research associate at the Boston Health Care for the Homeless Program from 2008-2012. BHCHP is an exemplar model of providing patient-centered care for people who have experienced homelessness. There, she gained significant experience in managing research projects, collecting qualitative and quantitative data, and program evaluation. She earned her MSW from the University of Michigan in 2007, with a focus on policy and evaluation in community and social systems, and a BA in sociology in 2005, also at the University of Michigan. Ms. Stringfellow was born and raised in a small town in Michigan.
Dr. Kimberly G. Rogers studies the coupled human-natural processes shaping coastal environments. She obtained a B.Sc. in Geological Sciences from the University of Texas at Austin and began her graduate studies on Long Island at Stony Brook University’s School of Marine and Atmospheric Sciences. Rogers completed her Ph.D. at Vanderbilt University, where she specialized in nearshore and coastal sediment transport. She was a postdoctoral scholar and research associate at the Institute for Arctic and Alpine Research at the University of Colorado Boulder. In 2014, her foundation in the physical sciences was augmented by training in Environmental Anthropology at Indiana University Bloomington through an NSF Science, Engineering, and Education for Sustainability (SEES) Fellowship.
Rogers’s research is broadly interdisciplinary and examines evolving sediment dynamics at the land-sea boundary, principally within the rapidly developing river deltas of South Asia. As deltas are some of the most densely populated coastal regions on earth, she incorporates social science methods to examine how institutions — particularly those governing land use and built infrastructure — influence the flow of water and sediment in coastal areas. She integrates quantitative and qualitative approaches in her work, such as direct measurement and geochemical fingerprinting of sediment transport phenomena, agent-based modeling, institutional and geospatial analyses, and ethnographic survey techniques. Risk holder collaboration is an integral part of her research philosophy and she is committed to co-production and capacity building in her projects. Her work has gained recognition from policy influencers such as the World Bank, USAID, and the US Embassy Bangladesh and has been featured in popular media outlets such as Slate and Environmental Health Perspectives.
Sedar is a PhD student at the University of Leeds, department of Geography. He graduated in Computer Science at King’s College London 2018. From a very early stage of his degree, he focused on artificial intelligence planning implementations on drones in a search and rescue domain, and this was his first formal attempt to study artificial intelligence. He participated in summer school at Boğaziçi University in Istanbul working on programming techniques to reduce execution time. During his final year, he concentrated on how argumentation theory with natural language processing can be used to optimise political influence. In the midst of completing his degree, he applied to Professor Alison Heppenstall’s research proposal focusing on data analytics and society, a joint endeavour with the Alan Turing Institute and the Economic and Social Research Council. From 2018 - 2023 he will be working on his PhD at the Alan Turing Institute and Leeds Institute for Data Analytics.
Sedar will be focusing on data analytics and smart cities, developing a programming library to try simulate how policies can impact a small world of autonomous intelligent agents to try deduce positive or negative impact in the long run. If the impact is positive and this is conveyed collectively taking into consideration the agent’s health, happiness and other social characteristics then the policy can be considered. Furthermore, he will work on agent based modelling to solve and provide faster solutions to economic and social elements of society, establishing applied and theoretical answers. Some other interests are:
performance of urban water service provision, high levels of inequities and inefficiency persist. In terms of water distribution and cost, these undesirable patterns have a high impact on peri-urban areas usually populated by marginalized and poor populations. The high levels of Non-Revenue Water (NRW), together with the existence of corrupt practices and mismanagement of water utilities, remain a highly controversial issue.
This situation confronts rent-seeking theory directly, explaining the performance-corruption relationship (Repetto, 1986). The presumption is that low performance in water supply service provision results from corruption because rent-seeking occurs. Hence, the implementation of performance-oriented reforms in the water supply sector, such as regulation or private sector participation, will reduce corruption, increasing the efficiency of water service provision. Nevertheless, latest evidence shows that “key elements of good political governance have a positive effect on the access to water services in developing countries. In turn, private sector participation has little influence other than increasing internal efficiency of water providers” (Krausse, 2009).
Indeed the relation between governance, corruption and performance seems to be more complex than theory wants to acknowledge. It must be reviewed further than a simple cause-effect relationship. It appears that poor management of water utilities, evidenced by high levels of NRW, justifies new investments. Such practices can be encouraged by an “opportunistic management”, whilst at the same time maintaining an influential “hydrocratic elite” in the sphere of water control.
The present research proposal aims to understand the relation between mismanagement and corruption of water control practices in water supply service provision. The research examines how this relationship affects the performance of water service provision and relates to water supply governance models at municipal peri-urban level in three African countries.
To understand the mismanagement-corruption relationship, we look at different case studies of water supply service provision in Senegal, Ghana and Kenya. Each case represents a different governance model in terms of management practices, institutional and organizational settings, and the actors in place, which affects the performance of water service provision in terms of allocative efficiency and access to water (equity). Whether regulation, decentralization and private sector participation constitute possible ways to reduce corruption is examined in the context of water sector reform.
In a second step, we propose a theoretical model based on Agent Based Modelling (ABM) (Pahl-Wostl, 2007) to reproduce complex social networks under a Socio-Ecological System (SES) framework approach. The model will allow us to test whether collaborative governance in the form of collective action in a participatory and negotiated decision-making process for water control, can reduce corruption and increase performance.
The present research benefits from the project “Transparency and Integrity in Service Delivery in Sub-Saharan Africa”. This project, carried out by Transparency International (TI) in 8 Sub-Saharan countries, aims to increase access to education, health and water by improving transparency and integrity in basic service delivery. The proposal retains focus on Senegal, Ghana and Kenya in the water sector.
Key words: water control, mismanagement, corruption, performance, collaborative governance, modelling, collective action, negotiation, participation
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