George Christakos

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BACKGROUND The Hand-Foot-Mouth Disease (HFMD) is the most common infectious disease in China, its total incidence being around 500,000~1,000,000 cases per year. The composite space-time disease variation is the result of underlining attribute mechanisms that could provide clues about the physiologic and demographic determinants of disease transmission and(More)
OBJECTIVE We analysed and mapped the distribution of four reportable sexually transmitted diseases, chlamydial infection/non-gonococcal urethritis (chlamydial infection), gonorrhoea, primary and secondary syphilis (syphilis), and HIV infection, for Wake County, North Carolina, to optimise an intervention. METHODS We used STD surveillance data reported to(More)
JIN-FENG WANG*{, XIN-HU LI{, GEORGE CHRISTAKOS§, YI-LAN LIAO{, TIN ZHANG", XUE GU" and XIAO-YING ZHENG** {Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China {Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361003, China §Department of Geography, San Diego State University,(More)
BACKGROUND This work demonstrates the importance of spatiotemporal stochastic modelling in constructing maps of major epidemics from fragmentary information, assessing population impacts, searching for possible etiologies, and performing comparative analysis of epidemics. METHODS Based on the theory previously published by the authors and incorporating(More)
BACKGROUND This work studies the spatiotemporal evolution of bubonic plague in India during 1896-1906 using stochastic concepts and geographical information science techniques. In the past, most investigations focused on selected cities to conduct different kinds of studies, such as the ecology of rats. No detailed maps existed incorporating the space-time(More)
In geosciences, one often needs to estimate the spatial means of surfaces representing physical attributes. Under certain conditions, this kind of estimation is often performed by a simple summation of a random sample or by some kind of a Kriging (spatial regression) technique. For example, the naive sample mean assumes that the sample is randomly(More)
BACKGROUND Population health attributes (such as disease incidence and prevalence) are often estimated using sentinel hospital records, which are subject to multiple sources of uncertainty. When applied to these health attributes, commonly used biased estimation techniques can lead to false conclusions and ineffective disease intervention and control.(More)
Atmospheric studies often require the generation of high-resolution maps of ozone distribution across space and time. The high natural variability of ozone concentrations and the different levels of accuracy of the algorithms used to generate data from remote sensing instruments introduce major sources of uncertainty in ozone modeling and mapping. These(More)
A meaningful characterization of epidemiologic fields (mortality, incidence rate, etc.) often involves the assessment of their spatiotemporal variation at multiple scales. An adequate analysis should depend on the scale at which the epidemiologic field is considered rather than being limited by the scale at which the data are available. In many studies, for(More)
BACKGROUND Long-term human exposure to ambient pollutants can be an important contributing or etiologic factor of many chronic diseases. Spatiotemporal estimation (mapping) of long-term exposure at residential areas based on field observations recorded in the U.S. Environmental Protection Agency's Air Quality System often suffer from missing data issues due(More)