PubMed · 15083158
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David Mabey, Rosanna W Peeling, Andrew Ustianowski, Mark D Perkins. 2004. Diagnostics for the developing world.. https://doi.org/10.1038/nrmicro841
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Infectious diseases are caused by single or successive contacts with pathogens. Nevertheless, contacts with pathogens do not implicate infection. In 1993, Yakovlev et al. proposed a model to study a population of cancer patients with a cured fraction, a well adapted model to describe an infectious disease with a unique infection occasion. Extensions of this model have been proposed in the recent years. We present a mechanistic formulation in the context of infectious diseases with multiple infection occasions. It is a mixture model that enables to study risk factors associated with infection intensity at each infection occasion and factors shortening the delay from exposure to clinical event. Simulations are performed to evaluate the model fitting and two examples are presented for illustration: an analysis of an HIV-1 mother-to-child transmission data set and an analysis of nosocomial urinary tract infections data set.
The Summary of Notifiable Diseases--United States, 2004 contains the official statistics, in tabular and graphic form, for the reported occurrence of nationally notifiable infectious diseases in the United States for 2004. Unless otherwise noted, the data are final totals for 2004 reported as of December 2, 2005. These statistics are collected and compiled from reports sent by state health departments to the National Notifiable Diseases Surveillance System (NNDSS), which is operated by CDC in collaboration with the Council of State and Territorial Epidemiologists (CSTE). The Summary is available at http://www.cdc.gov/mmwr/summary.html. This site also includes publications from previous years.
Remote sensing, referring to the remote study of objects, was originally developed for Earth observation, through the use of sensors on board planes or satellites. Improvements in the use and accessibility of multi-temporal satellite-derived environmental data have, for 30 years, contributed to a growing use in epidemiology. Despite the potential of remote-sensed images and processing techniques for a better knowledge of disease dynamics, an exhaustive analysis of the bibliography shows a generalized use of pre-processed spatial data and low-cost images, resulting in a limited adaptability when addressing biological questions.