Research Interests
My research concerns the control of environmentally-mediated diseases through the quantification of exposures to infectious agents and the study of the social-environmental context behind diseases through the use of epidemiologic methods, spatial analyses, and mathematical modeling.
Notable Recent Research
Disease Ecology: The Impact of the Three Gorges Dam on Poyang Lake Schistosomiasis Snail Populations
In this NIH-funded research, we modeled how changing water levels and weather are associated with changes in snail populations in Poyang Lake downstream of the Three Gorges Dam. Spring snail populations are related to temperature increases after over-wintering, while fall populations are related to the intensity of summer flooding. To the best of our knowledge, this is the first quantitative assessment of the potential impact of the Three Gorges Dam on schistosomisis snail populations.
Seto, E.Y.W., Wu, W., Liu, H., Chen, H., Hubbard, A., Holt, A., Davis, G.M., (2008) Impact of Changing Water Levels and Weather on Oncomelania hupensis hupensis Populations, the Snail Host of Schistosoma japonicum, Downstream of the Three Gorges Dam, EcoHealth, 5: 149-158. doi: 10.1007/s10393-008-0169-x
Seto, E.Y.W., Wu, W., Liu, H.Y., Chen, H.G., Hubbard, A., Holt, A., Davis, G.M., (2008) Schistosomiasis and the Three Gorges Dam: an EcoHealth Perspective, Integrated Management of Coastal and Freshwater Systems, USAID Newsletter, 2(3): 6-10. [link]
Molecular Spatial Epidemiology: Mapping Malaria Reinfection in Uganda
New genotyping methods based on Plasmodium falciparum microsatellite markers enable the distinction between new infection and recrudescence after treatment regimes. Spatial analyses of genetically identified new infection are a powerful new tool for controlling disease re-emergence for malaria elimination programs. Collaborating with researchers from UCSF, we applied spatial clustering algorithms to identify the patterns of post-treatment infection in Uganda.
Clark, T.D., Greenhouse, B., Njama-Meya, D., Nzarubara, B., Maiteki-Sebuguzi, C., Staedke, S.G., Seto, E., Kamya, M.R., Rosenthal, P.J., Dorsey, G., (2008) Factors Determining the Heterogeneity of Malaria Incidence in Children in Kampala, Uganda, The Journal of Infectious Diseases, 198: 393–400. doi: 10.1086/589778
Greenhouse, B., Myrick, A., Dokomajilar, C., Woo, J.M., Carlson, E.J., Rosenthal, P.J., Dorsey, G. (2006) Validation of Microsatellite Markers for Use in Genotyping Polyclonal Plasmodium falciparum Infections, Am. J. Trop. Med. Hyg., 75(5): 836-842.
 Social-Environmental Epidemiology: Spatial Heterogeneity and the role of Connectivity in Schistosoma japonicum infection
In this NIH-funded research, the spatial distribution of water contact and cercarial concentrations were combined to form a cercarial exposure metric, which was found to be positively associated with new S. japonicum infections. Expanding on these findings, we are now conducting field studies of social behaviors, such as personal mobility and person-environment-person interactions which may help sustain and spread infection. Mathematical models developed in collaboration with Case Western University have shown the strong impact that social and hydrological connectivity may play in the spread and persistance of parasitic diseases.
Gurarie, D. and Seto, E.Y.W. (2008) Connectivity Sustains Disease Transmission in Environments with Low Potential for Endemicity: Modeling Schistosomiasis with Hydrologic and Social Connectivities, Journal of the Royal Society Interface, doi:10.1098/rsif.2008.0265.
Seto, E.Y.W., Lee, E.Y., Liang, S., Zhong, B., (2007) Individual and Village-level Study of Water Contact Exposure Patterns and Schistosoma japonicum Reinfection in Mountainous Rural China, Trop Med Intl Health, 12(10):1199-209. doi: 10.1111/j.1365-3156.2007.01903.x
Outbreak Modeling: E. coli 0157:H7 Spinach Outbreak in the United States, 2006.
This is an example of a rapid outbreak assessment for disease control planning using mathematical modeling. Before the outbreak had even ended we had used case data from the CDC to fit a mathematical model of E. coli transmission. Using the model, we found that substantial reductions in incidence would be occur from reduced secondary transmission.
Seto, E.Y.W., Soller, J.A., Colford, J.M. Jr., (2007) Strategies to Reduce Person-to-Person Transmission during Widespread Escherichia coli O157:H7 Outbreak, Emerging Infectious Diseases, 13(6): 860-866. http://www.cdc.gov/EID/content/13/6/860.htm
Funding
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