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Schistosomiasis is still prevalent in seven provinces in China despite several decades of continuous effort. Suppression of transmission in low-infection areas proves to be extremely difficult, and re-emergence of the disease in areas it was previously controlled or eliminated further complicates the situation. New surveillance and control strategies based on a better understanding of current transmission patterns are therefore crucial to the achievement of disease elimination. This dissertation explores these questions with the focus on the hilly and mountainous regions in Sichuan Province.

The main contents of this dissertation are centered on the development and simulation of a stochastic individually-based model. Focused on two cohorts representing the post-equilibrium and re-emerging environments, respectively, survey protocols and data description on human demographics, infection status, snail density, and cercarial mouse bioassay are presented and compared. A health education intervention was also introduced as an example of how individual data could be used for hypothesis testing related to model component determination. Upon development of the model, Monte-Carlo simulations were conducted to account for randomness from multiple sources including parasite acquisition, worm development, egg shedding and infection testing.

Surveillance results in the re-emerging villages indicated low sensitivity of current techniques for low infection-intensity environment. The distribution of individual susceptibility to S. japonicum infection appeared to be log-normally distributed with a high skewness. Given the cercarial density and water contact magnitude distributions of the surveyed populations, a considerable fraction of people had susceptibility levels that would not lead to infection. For infection surveillance purposes, sampling individuals with high susceptibility has markedly greater efficiency than other indices focused on either water or cercarial exposure. Based on these findings, priorities should be given to the development of more sensitive environmental monitoring and infection testing methods and exploration of an appropriate and quantifiable index for susceptibility. Environmental and economic modifications in addition to the traditional control methods need to be conceptualized and implemented to further conquer the disease and achieve comprehensive elimination.

Opisthorchiasis, infection with the Southeast Asian liver fluke Opisthorchis viverrini, and liver fluke-associated cholangiocarcinoma cause significant disease burden in Southeast Asia. Northeast Thailand is a particular region where this disease is a public health priority, infecting over 50% of the population in some villages and causing 5000 excess cancer cases per year. People acquire the parasite by eating raw or undercooked fish, a deeply embedded local cultural and culinary tradition. Health education is essential to preventing and controlling the disease, but the environment also plays a major role in enabling and catalyzing transmission between hosts. An emphasis on disease ecology and the environmental determinants of transmission is useful and necessary for public health understanding and for informing and designing future treatment and control interventions. This dissertation takes that approach, investigating each disease host and linkage for the role of the environment in influencing transmission.

Chapter 1 describes and contextualizes liver fluke transmission and why it matters, introducing Lawa Lake and the Lawa Project, which are the background for the context and data examined herein. Chapter 2 presents lab, field, and modeling results related to infection and ecology of the intermediate host Bithynia snails and cyprinid fish. Chapter 3 introduces and presents results from the single-village mathematical model simulating transmission in six village clusters around Lawa Lake. Chapter 4 discusses the role of reservoir hosts (cats and dogs) in the transmission cycle, adds them to the model framework, and simulates the impact of regular praziquantel treatment on long-term infection prevalence. Chapter 5 introduces the rainfall-runoff hydrology model, whose output is incorporated into a metapopulation disease transmission model to connect the six village clusters around Lawa Lake, and the impacts of connectivity and upstream villages are studied and discussed. Chapter 6 concludes with some comments on engineering and public health perspectives, limitations, progress, and future directions for liver fluke and neglected tropical disease control.

Treatment can yield rapid reductions in schistosomiasis infections and morbidity, but sustained control of this water-borne parasitic infection has proven challenging. A better understanding of the epidemiology of schistosomiasis following chemotherapy-based control is urgently needed to inform the design of surveillance systems and interventions in post-control regions. The research presented here documents the reemergence of schistosomiasis in Sichuan Province, China, evaluates surveillance methods for monitoring schistosomiasis-induced morbidity, using ultrasound, and schistosomiasis reemergence, and examines village-level characteristics that may promote schistosomiasis transmission. Research was conducted in a region where praziquantel-based control was ongoing, using a five-year longitudinal study, and in regions where schistosomiasis reemerged five to fifteen years after human infections were controlled, using a cross-sectional survey of 53 villages. Reinfection following treatment was common in endemic regions, and widespread human and bovine infections were documented in the reemerging areas. Two commonly used surveillance methods, surveys for Schistosoma japonicum-infected snails and acute schistosomiasis case reporting greatly underestimated the extent of reemergence. Methods that targeted high-risk human populations had high sensitivity. Village-level characteristics that promoted the distribution of S. japonicum eggs, including the use of human waste as an agricultural fertilizer (night soil) and the density of bovines, predicted human infection status. Infection intensities were low in the reemerging region. Areas where night soil use or bovine ownership are common may be primed for reemergence, providing crucial links in the schistosome life cycle that can promote S. japonicum infections. Interventions and surveillance methods that target populations in high-risk environments may aid in interrupting schistosomiasis transmission and permanently reducing morbidity.

300 million adults and 16 million children in China are now obese. The rapid economic development, urbanization and associated environmental changes occurring in China are thought to be responsible for this growing obesity epidemic. My dissertation research has gradually developed into four interconnected parts which are presented in Chapter 1, 2, 3 and future work. First (Chapter 1), culturally specific food environment survey instruments were developed and used to document the longitudinal changes in food availability in six representative neighborhoods in Kunming via field audits. Second (Chapter 2), to pilot test our integrated methodology, a 12-person cohort was recruited in Kunming, and individual dietary behavior was modeled and topologies were proposed. Third (Chapter 3), to further test our methodology on a larger cohort aiming to examine the relationship between food environment and sugar-sweetened beverage consumption, we worked with Carolina Population Center on their China Beverage Validation Study in urban and rural Shanghai. Lastly (future work), to examine the health impacts of the changing food environment, a 300 adolescent cohort was recruited from two high schools in Kunming, and followed for two years. Their dietary, physical activity, mental, social and physical changes were assessed via traditional research surveys, smartphone-based activity tracking and Internet datamining. Preliminary results on the cohort’s BMIs are presented.

Cyanotoxins, the group of toxic chemicals produced by the blue-green algae or cyanobacteria that can proliferate in fresh and salt-water, cause a range of harmful health effects including skin rashes, flu-like symptoms, nausea, diarrhea, tingling and nerve damage, liver damage, tumors, and death ([1, 2]). Although cyanobacteria are one of the oldest organisms on the planet, anthropogenic development (e.g. dams, water diversions, nutrient rich runoff from intensive agriculture, decreased impervious area from urbanization, etc.) has caused many watersheds to lose substantial water volume, suffer tremendous inputs of nutrients and other organic and inorganic pollutants, increase in temperature and overall become more suitable for the proliferation of harmful blooms of cyanobacteria. Cyanobacteria blooms are now increasingly prevalent in freshwaters as eutrophication becomes ever more common with human stressors, and climate change is likely to only further exacerbate this problem. Public health professionals are dependant upon early and dependable information on the presence, concentration, and location of cyanobacteria blooms in order to inform the public and reduce potential exposure. This research project evaluated the efficacy of remote sensing data to provide this kind of surveillance and early detection for characterizing the presence of toxic algae in freshwater systems. It explored the relevance of specific remote sensing techniques to freshwater cyanobacteria bloom identification. The various remote sensing platforms available for this kind of research vary in cost, swath coverage, spatial scale and spectral resolution. For this study, three different remote imagery platforms were compared in terms of their ability to identify surface blooms and to distinguish gradients in cell density or bloom intensity. This exploration of the application of remote sensing used a hyperspectral airborne sensor with high spatial resolution (SpecTIR), a multispectral satellite image also with high spatial resolution (IKONOS), and a lower spatial resolution multispectral satellite image (Landsat). Water sampling data (algal pigment concentrations, turbidity, transparency, and temperature) from known blue-green algae blooms dominated by microcystis aeruginosa on the Iron Gate and Copco Reservoirs on the Klamath River were used to evaluate and classify these different images.

This research successfully used both satellite and airborne remotely sensed data to visualize where the medium or high density sections of the bloom were located, to quantify the intensity of the bloom in terms of area impacted, and to compare the intensity of the bloom at different dates in time. Remote sensing can provide a synoptic overview of the entire system, making it possible to truly assess relative bloom intensity. Furthermore the results indicate that when given the choice, the investment in higher spectral resolution should be chosen over higher spatial resolution as the former appears to provide more benefits in cyanobacteria detection.