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      Ventilation of general hospital wards for mitigating infection risks of three kinds of viruses including Middle East respiratory syndrome coronavirus

      1 , 1 , 1 , 1
      Indoor and Built Environment
      SAGE Publications

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          A novel coronavirus associated with severe acute respiratory syndrome.

          A worldwide outbreak of severe acute respiratory syndrome (SARS) has been associated with exposures originating from a single ill health care worker from Guangdong Province, China. We conducted studies to identify the etiologic agent of this outbreak. We received clinical specimens from patients in seven countries and tested them, using virus-isolation techniques, electron-microscopical and histologic studies, and molecular and serologic assays, in an attempt to identify a wide range of potential pathogens. None of the previously described respiratory pathogens were consistently identified. However, a novel coronavirus was isolated from patients who met the case definition of SARS. Cytopathological features were noted in Vero E6 cells inoculated with a throat-swab specimen. Electron-microscopical examination revealed ultrastructural features characteristic of coronaviruses. Immunohistochemical and immunofluorescence staining revealed reactivity with group I coronavirus polyclonal antibodies. Consensus coronavirus primers designed to amplify a fragment of the polymerase gene by reverse transcription-polymerase chain reaction (RT-PCR) were used to obtain a sequence that clearly identified the isolate as a unique coronavirus only distantly related to previously sequenced coronaviruses. With specific diagnostic RT-PCR primers we identified several identical nucleotide sequences in 12 patients from several locations, a finding consistent with a point-source outbreak. Indirect fluorescence antibody tests and enzyme-linked immunosorbent assays made with the new isolate have been used to demonstrate a virus-specific serologic response. This virus may never before have circulated in the U.S. population. A novel coronavirus is associated with this outbreak, and the evidence indicates that this virus has an etiologic role in SARS. Because of the death of Dr. Carlo Urbani, we propose that our first isolate be named the Urbani strain of SARS-associated coronavirus. Copyright 2003 Massachusetts Medical Society
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            The role of particle size in aerosolised pathogen transmission: A review

            Summary Understanding respiratory pathogen transmission is essential for public health measures aimed at reducing pathogen spread. Particle generation and size are key determinant for pathogen carriage, aerosolisation, and transmission. Production of infectious respiratory particles is dependent on the type and frequency of respiratory activity, type and site of infection and pathogen load. Further, relative humidity, particle aggregation and mucus properties influence expelled particle size and subsequent transmission. Review of 26 studies reporting particle sizes generated from breathing, coughing, sneezing and talking showed healthy individuals generate particles between 0.01 and 500 μm, and individuals with infections produce particles between 0.05 and 500 μm. This indicates that expelled particles carrying pathogens do not exclusively disperse by airborne or droplet transmission but avail of both methods simultaneously and current dichotomous infection control precautions should be updated to include measures to contain both modes of aerosolised transmission.
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              Flow dynamics and characterization of a cough.

              Airborne disease transmission has always been a topic of wide interests in various fields for decades. Cough is found to be one of the prime sources of airborne diseases as it has high velocity and large quantity of droplets. To understand and characterize the flow dynamics of a cough can help to control the airborne disease transmission. This study has measured flow dynamics of coughs with human subjects. The flow rate variation of a cough with time can be represented as a combination of gamma-probability-distribution functions. The variables needed to define the gamma-probability-distribution functions can be represented by some medical parameters. A robust multiple linear regression analysis indicated that these medical parameters can be obtained from the physiological details of a person. However, the jet direction and mouth opening area during a cough seemed not related to the physiological parameters of the human subjects. Combining the flow characteristics reported in this study with appropriate virus and droplet distribution information, the infectious source strength by coughing can be evaluated. There is a clear need for the scientific community to accurately predict and control the transmission of airborne diseases. Transportation of airborne viruses is often predicted using Computational Fluid Dynamics (CFD) simulations. CFD simulations are inexpensive but need accurate source boundary conditions for the precise prediction of disease transmission. Cough is found to be the prime source for generating infectious viruses. The present study was designed to develop an accurate source model to define thermo-fluid boundary conditions for a cough. The model can aid in accurately predicting the disease transmission in various indoor environments, such as aircraft cabins, office spaces and hospitals.
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                Author and article information

                Journal
                Indoor and Built Environment
                Indoor and Built Environment
                SAGE Publications
                1420-326X
                1423-0070
                April 12 2017
                April 2017
                February 13 2016
                April 2017
                : 26
                : 4
                : 514-527
                Affiliations
                [1 ]Department of Building Services Engineering, The Hong Kong Polytechnic University, Hong Kong, China
                Article
                10.1177/1420326X16631596
                ea516ca5-a463-434e-8ff3-078a772cd1ce
                © 2017

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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