Retrospective analysis of multi-drug resistant tuberculosis outbreak during a flight using computational fluid dynamics and infection risk assessment

• Published in: Building and environment 2012, Vol.47, p.50-57
• Main Authors: Yin, S., Sze-To, G.N., Chao, Christopher Y.H.
• Format: Article
• Language: English
• Subjects: Air transportation and traffic; Aircraft cabin; Applied sciences; Bacterial diseases; Biological and medical sciences; Computational fluid dynamics; Exact sciences and technology; Ground, air and sea transportation, marine construction; Human bacterial diseases; Infectious diseases; Maximum likelihood estimation; Medical sciences; Multi-drug resistant tuberculosis; Mycobacterium; Outbreaks; Passengers; Retrospective analysis; Risk; Risk assessment; Strength; Tuberculosis; Tuberculosis and atypical mycobacterial infections
• ISSN: 0360-1323; 1873-684X
• DOI: 10.1016/j.buildenv.2011.03.011

Air travel brings convenience to humans but also hastens the global spread of infectious diseases. Not only transporting infectious individuals from one place to another, air travel also provides a chance for infectious diseases transmission during the flight, especially if the disease can be transmitted via the airborne route. A number of documented outbreaks of airborne transmissible diseases were associated with disease transmission during the air travel. This study performed retrospective analysis on an infamous multi-drug resistant Tuberculosis (MDR-TB) outbreak on a commercial flight, where 6 people were infected with the multi-drug resistant disease during the 8.75 h flight. Airflow pattern and the infectious particle dispersion in the aircraft cabin were simulated using computational fluid dynamics (CFD). Infection risks of the passengers under a range of infectious source strength values were then assessed using the dose-response model. Based on the risk data, the infectious source strength of the index case passenger was estimated by likelihood analysis. A concept of mix-ratio was introduced to estimate the impact of human movement and cough behavior on the disease transmission. From the maximum likelihood estimation, the index case passenger may have generated 17.2 millions of viable bacilli/hr during the flight. Spatial pattern of the infection case and the spatial variation of infection risk were reflected in this estimation. The findings of this study provide additional understanding of infectious disease transmission during air travel. The infectious source strength of MDR-TB estimated from this study can be used in further risk assessment on the disease.