Stephen Welch

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The FireGrid project aims to harness the potential of advanced forms of computation to support the response to large-scale emergencies (with an initial focus on the response to fires in the built environment). Computational models of physical phenomena are developed, and then deployed and computed on High Performance Computing resources to infer incident(More)
This study reports pediatric surveillance over 3 years for human rhinovirus (HRV) at the District Hospital of Kilifi, coastal Kenya. Nasopharyngeal samples were collected from children presenting at outpatient clinic with no signs of acute respiratory infection, or with signs of upper respiratory tract infection, and from children admitted to the hospital(More)
BACKGROUND Influenza data gaps in sub-Saharan Africa include incidence, case fatality, seasonal patterns, and associations with prevalent disorders. METHODS Nasopharyngeal samples from children aged <12 years who were admitted to Kilifi District Hospital during 2007-2010 with severe or very severe pneumonia and resided in the local demographic(More)
Rift Valley fever virus (RVFV, family Bunyaviridae) is a mosquito-borne pathogen of both livestock and humans, found primarily in Sub-Saharan Africa and the Arabian Peninsula. The viral genome comprises two negative-sense (L and M segments) and one ambisense (S segment) RNAs that encode seven proteins. The S segment encodes the nucleocapsid (N) protein in(More)
FireGrid is a modern concept that aims to leverage a number of modern technologies to aid fire emergency response. In this paper we provide a brief introduction to the FireGrid project. A number of different technologies such as wireless sensor networks, grid-enabled High Performance Computing (HPC) implementation of fire models, and artificial intelligence(More)
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