Identifying index (source) patient location of SARS transmission in a hospital ward

Abstract

This article presents the application of a probability-concept-based algorithm that can track the source origins of viruses based on the number and location of infected individuals (cases) observed in an enclosed indoor environment. This probability-concept-based prediction uses the convective transfer mechanism of virus-containing airborne aerosols to track inversely the most probable locations of infection sources according to the concentration value measured in certain location(s). A new approach is proposed to convert the number of infection cases to the concentration values of virus particles that can be used as the input for prediction, making the concentration measurement unnecessary for source tracking in a real outbreak of epidemic disease. The source-tracking method is demonstrated and verified by using the SARS infection cases of medical students in a hospital ward outbreak in Hong Kong in 2003. The model successfully predicts the location of the virus origin, i.e., the clinically identified SARS patient's bed in the outbreak. The method shows a good potential for quickly identifying the index patient location during an airborne disease outbreak, as well as confirming the airborne transmission mechanism and dispersion of indoor virus- and bacterium-containing aerosols.

Acknowledgment

Part of the work described in this article was supported by a William Mong Research Fellowship Award to the second author during his stay at the University of Hong Kong.

Haidong Wang, Student Member ASHRAE, is PhD student. Zhiqiang (John) Zhai, DrEng, PhD, Member ASHRAE, is Associate Professor. Yuguo Li, PhD, Fellow ASHRAE, is Professor. Xiang Liu, PhD, Student Member ASHRAE, is Energy Engineer at Nexant Inc.